Advantages of continuous genotype values over genotype classes for GWAS in higher polyploids: a comparative study in hexaploid chrysanthemum.

PubMed

Grandke, Fabian; Singh, Priyanka; Heuven, Henri C M; de Haan, Jorn R; Metzler, Dirk

2016-08-24

Association studies are an essential part of modern plant breeding, but are limited for polyploid crops. The increased number of possible genotype classes complicates the differentiation between them. Available methods are limited with respect to the ploidy level or data producing technologies. While genotype classification is an established noise reduction step in diploids, it gains complexity with increasing ploidy levels. Eventually, the errors produced by misclassifications exceed the benefits of genotype classes. Alternatively, continuous genotype values can be used for association analysis in higher polyploids. We associated continuous genotypes to three different traits and compared the results to the output of the genotype caller SuperMASSA. Linear, Bayesian and partial least squares regression were applied, to determine if the use of continuous genotypes is limited to a specific method. A disease, a flowering and a growth trait with h (2) of 0.51, 0.78 and 0.91 were associated with a hexaploid chrysanthemum genotypes. The data set consisted of 55,825 probes and 228 samples. We were able to detect associating probes using continuous genotypes for multiple traits, using different regression methods. The identified probe sets were overlapping, but not identical between the methods. Baysian regression was the most restrictive method, resulting in ten probes for one trait and none for the others. Linear and partial least squares regression led to numerous associating probes. Association based on genotype classes resulted in similar values, but missed several significant probes. A simulation study was used to successfully validate the number of associating markers. Association of various phenotypic traits with continuous genotypes is successful with both uni- and multivariate regression methods. Genotype calling does not improve the association and shows no advantages in this study. Instead, use of continuous genotypes simplifies the analysis, saves computational time and results more potential markers.

Factors associated with utilization of long-acting and permanent contraceptive methods among women who have decided not to have more children in Gondar city.

PubMed

Zenebe, Chernet Baye; Adefris, Mulat; Yenit, Melaku Kindie; Gelaw, Yalemzewod Assefa

2017-09-06

Despite the fact that long acting family planning methods reduce population growth and improve maternal health, their utilization remains poor. Therefore, this study assessed the prevalence of long acting and permanent family planning method utilization and associated factors among women in reproductive age groups who have decided not to have more children in Gondar city, northwest Ethiopia. An institution based cross-sectional study was conducted from August to October, 2015. Three hundred seventeen women who have decided not to have more children were selected consecutively into the study. A structured and pretested questionnaire was used to collect data. Both bivariate and multi-variable logistic regressions analyses were used to identify factors associated with utilization of long acting and permanent family planning methods. The multi-variable logistic regression analysis was used to investigate factors associated with the utilization of long acting and permanent family planning methods. The Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) was used to show the strength of associations, and variables with a P-value of <0.05 were considered statistically significant. In this study, the overall prevalence of long acting and permanent contraceptive (LAPCM) method utilization was 34.7% (95% CI: 29.5-39.9). According to the multi-variable logistic regression analysis, utilization of long acting and permanent contraceptive methods was significantly associated with women who had secondary school, (AOR: 2279, 95% CI: 1.17, 4.44), college, and above education (AOR: 2.91, 95% CI: 1.36, 6.24), history of previous utilization (AOR: 3.02, 95% CI: 1.69, 5.38), and information about LAPCM (AOR: 8.85, 95% CI: 2.04, 38.41). In this study the prevalence of long acting and permanent family planning method utilization among women who have decided not to have more children was high compared with previous studies conducted elsewhere. Advanced educational status, previous utilization of LAPCM, and information on LAPCM were significantly associated with the utilization of LAPCM. As a result, strengthening behavioral change communication channels to make information accessible is highly recommended.

Demand for long acting contraceptive methods and associated factors among family planning service users, Northwest Ethiopia: a health facility based cross sectional study.

PubMed

Yalew, Saleamlak Adbaru; Zeleke, Berihun Megabiaw; Teferra, Alemayehu Shimeka

2015-02-04

Demand for long acting contraceptive methods is one of the key factors for total fertility rate and reproductive health issues. Increased demand for these methods can decline fertility rate through spacing and limiting family size in turn improving maternal and family health and socioeconomic development of a country. The aim of this study was to assess demand for long acting contraceptives and associated factors among family planning users in Debre-Tabor Town, Northwest Ethiopia. Facility based cross-sectional study was conducted from July to August 2013. Data was collected on 487 current family planning users through face to face interview using structured questionnaire. Study participants were selected by systematic sampling method. Data were entered in to Epi Info and analyzed by using SPSS version 20. Bi-variable and multi-variable regression analyses were done to identify factors associated with demand for long acting contraceptive methods. Odds ratio with 95% CI was used to assess the association between the independent variables and demand for long acting family planning methods. The study showed that, demand for long acting contraceptives was 17%. Only 9.2% of the women were using long acting contraceptive methods (met need). About 7.8% of women were using short acting methods while they actually want to use long acting methods (unmet need). Demand for LACMs was positively associated 3 with being a daily labour (AOR = 3.87, 95% CI = [1.06, 14.20]), being a student (AOR = 2.64, 95% CI = [1.27, 5.47]), no future birth intensions (AOR = 2.17, 95% CI = [1.12, 4.23]), having five or more children (AOR = 1.67, 95% CI = [1.58, 4.83]), deciding together with husbands for using the methods (AOR = 2.73, 95% CI = [1.40, 5.32]) and often having discussion with husband (AOR = 3.89, 95% CI = [1.98, 7.65]). Clients treated poorly by the health care providers during taking the services was negatively associated with demand for LACMs (AOR = 0.42, 95% CI = [0.24, 0.74]). Demand for long acting family planning methods was observed to be lower as compared to other studies. There were also significant proportion of women having unmet need for long acting methods - women using short acting method while actually wanting long acting methods. Therefore, it is necessary to create and increase awareness and advocacy on demand for long acting contraceptive methods considering women and their husbands. Moreover, emphasis should be given to service provision of the methods.

Statistical Selection of Biological Models for Genome-Wide Association Analyses.

PubMed

Bi, Wenjian; Kang, Guolian; Pounds, Stanley B

2018-05-24

Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis of no association without indicating which biological model best explains the observed data. Correctly identifying a specific biological model may improve the scientific interpretation and can be used to more effectively select and design a follow-up validation study. Thus, statistical methodology to identify the correct biological model for a particular genotype-phenotype association can be very useful to investigators. Here, we propose a general statistical method to summarize how accurately each of five biological models (null, additive, dominant, recessive, co-dominant) represents the data observed for each variant in a GWAS study. We show that the new method stringently controls the false discovery rate and asymptotically selects the correct biological model. Simulations of two-stage discovery-validation studies show that the new method has these properties and that its validation power is similar to or exceeds that of simple methods that use the same statistical model for all SNPs. Example analyses of three data sets also highlight these advantages of the new method. An R package is freely available at www.stjuderesearch.org/site/depts/biostats/maew. Copyright © 2018. Published by Elsevier Inc.

An Empirical Study of Applying Associative Method in College English Vocabulary Learning

ERIC Educational Resources Information Center

Zhang, Min

2014-01-01

Vocabulary is the basis of any language learning. To many Chinese non-English majors it is difficult to memorize English words. This paper applied associative method in presenting new words to them. It is found that associative method did receive a better result both in short-term and long-term retention of English words. Compared with the…

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

An efficient empirical Bayes method for genomewide association studies.

PubMed

Wang, Q; Wei, J; Pan, Y; Xu, S

2016-08-01

Linear mixed model (LMM) is one of the most popular methods for genomewide association studies (GWAS). Numerous forms of LMM have been developed; however, there are two major issues in GWAS that have not been fully addressed before. The two issues are (i) the genomic background noise and (ii) low statistical power after Bonferroni correction. We proposed an empirical Bayes (EB) method by assigning each marker effect a normal prior distribution, resulting in shrinkage estimates of marker effects. We found that such a shrinkage approach can selectively shrink marker effects and reduce the noise level to zero for majority of non-associated markers. In the meantime, the EB method allows us to use an 'effective number of tests' to perform Bonferroni correction for multiple tests. Simulation studies for both human and pig data showed that EB method can significantly increase statistical power compared with the widely used exact GWAS methods, such as GEMMA and FaST-LMM-Select. Real data analyses in human breast cancer identified improved detection signals for markers previously known to be associated with breast cancer. We therefore believe that EB method is a valuable tool for identifying the genetic basis of complex traits. © 2015 Blackwell Verlag GmbH.

Missing data imputation and haplotype phase inference for genome-wide association studies

PubMed Central

Browning, Sharon R.

2009-01-01

Imputation of missing data and the use of haplotype-based association tests can improve the power of genome-wide association studies (GWAS). In this article, I review methods for haplotype inference and missing data imputation, and discuss their application to GWAS. I discuss common features of the best algorithms for haplotype phase inference and missing data imputation in large-scale data sets, as well as some important differences between classes of methods, and highlight the methods that provide the highest accuracy and fastest computational performance. PMID:18850115

An Evaluation of Different Target Enrichment Methods in Pooled Sequencing Designs for Complex Disease Association Studies

PubMed Central

Day-Williams, Aaron G.; McLay, Kirsten; Drury, Eleanor; Edkins, Sarah; Coffey, Alison J.; Palotie, Aarno; Zeggini, Eleftheria

2011-01-01

Pooled sequencing can be a cost-effective approach to disease variant discovery, but its applicability in association studies remains unclear. We compare sequence enrichment methods coupled to next-generation sequencing in non-indexed pools of 1, 2, 10, 20 and 50 individuals and assess their ability to discover variants and to estimate their allele frequencies. We find that pooled resequencing is most usefully applied as a variant discovery tool due to limitations in estimating allele frequency with high enough accuracy for association studies, and that in-solution hybrid-capture performs best among the enrichment methods examined regardless of pool size. PMID:22069447

Incident CTS in a large pooled cohort study: associations obtained by a Job Exposure Matrix versus associations obtained from observed exposures.

PubMed

Dale, Ann Marie; Ekenga, Christine C; Buckner-Petty, Skye; Merlino, Linda; Thiese, Matthew S; Bao, Stephen; Meyers, Alysha Rose; Harris-Adamson, Carisa; Kapellusch, Jay; Eisen, Ellen A; Gerr, Fred; Hegmann, Kurt T; Silverstein, Barbara; Garg, Arun; Rempel, David; Zeringue, Angelique; Evanoff, Bradley A

2018-03-29

There is growing use of a job exposure matrix (JEM) to provide exposure estimates in studies of work-related musculoskeletal disorders; few studies have examined the validity of such estimates, nor did compare associations obtained with a JEM with those obtained using other exposures. This study estimated upper extremity exposures using a JEM derived from a publicly available data set (Occupational Network, O*NET), and compared exposure-disease associations for incident carpal tunnel syndrome (CTS) with those obtained using observed physical exposure measures in a large prospective study. 2393 workers from several industries were followed for up to 2.8 years (5.5 person-years). Standard Occupational Classification (SOC) codes were assigned to the job at enrolment. SOC codes linked to physical exposures for forceful hand exertion and repetitive activities were extracted from O*NET. We used multivariable Cox proportional hazards regression models to describe exposure-disease associations for incident CTS for individually observed physical exposures and JEM exposures from O*NET. Both exposure methods found associations between incident CTS and exposures of force and repetition, with evidence of dose-response. Observed associations were similar across the two methods, with somewhat wider CIs for HRs calculated using the JEM method. Exposures estimated using a JEM provided similar exposure-disease associations for CTS when compared with associations obtained using the 'gold standard' method of individual observation. While JEMs have a number of limitations, in some studies they can provide useful exposure estimates in the absence of individual-level observed exposures. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Factors Associated With Contraceptive Method Choice and Initiation in Adolescents and Young Women.

PubMed

Cohen, Rebecca; Sheeder, Jeanelle; Kane, Meghan; Teal, Stephanie B

2017-10-01

The purpose of the study was to identify factors associated with uptake of contraceptive implants or intrauterine devices (IUDs) by adolescents and young women. For this prospective cohort study, we recruited English-speaking female contraceptive initiators aged 14-24 years attending a Title X-supported, youth-focused clinic. Immediately prior to their visits, participants completed surveys assessing demographic and reproductive characteristics and awareness of, interest in, and intent to initiate specific contraceptive methods. Participants also answered questions about their social contacts' contraceptive experiences. Following the visit, participants reported the method initiated and the perceived importance of provider counseling. We used a multivariable regression model to ascertain factors associated with initiation of an IUD, an implant, or a short-acting reversible method. We enrolled 1,048 contraceptive initiators: 277 initiated short-acting methods, 384 IUDs, and 387 implants. High previsit personal acceptability of the method was associated with choosing that method for both implants and IUDs. Knowing someone who uses a specific method and likes it was predictive of personal acceptability of that method (IUD adjusted odds ratio: 10.9, 95% confidence interval: 3.8-31.1; implant adjusted odds ratio: 7.0, 95% confidence interval: 2.3-21.0). However, 10.4% of those initiating IUDs and 14.2% of those initiating implants had never heard of the method before their appointment. Even women with previsit intent to initiate a specific method found importance in contraceptive counseling. Previsit personal acceptability, which was associated with social contacts' experiences, was the strongest predictor of specific method uptake in our study. However, counseling informed the decisions of those with low previsit awareness and supported patients with formed intent. Copyright © 2017 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

PubMed Central

Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

2016-01-01

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks.

PubMed

Zhao, Huiying; Nyholt, Dale R; Yang, Yuanhao; Wang, Jihua; Yang, Yuedong

2017-06-14

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .

Integrated rare variant-based risk gene prioritization in disease case-control sequencing studies.

PubMed

Lin, Jhih-Rong; Zhang, Quanwei; Cai, Ying; Morrow, Bernice E; Zhang, Zhengdong D

2017-12-01

Rare variants of major effect play an important role in human complex diseases and can be discovered by sequencing-based genome-wide association studies. Here, we introduce an integrated approach that combines the rare variant association test with gene network and phenotype information to identify risk genes implicated by rare variants for human complex diseases. Our data integration method follows a 'discovery-driven' strategy without relying on prior knowledge about the disease and thus maintains the unbiased character of genome-wide association studies. Simulations reveal that our method can outperform a widely-used rare variant association test method by 2 to 3 times. In a case study of a small disease cohort, we uncovered putative risk genes and the corresponding rare variants that may act as genetic modifiers of congenital heart disease in 22q11.2 deletion syndrome patients. These variants were missed by a conventional approach that relied on the rare variant association test alone.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

PubMed

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Evaluating the impact of method bias in health behaviour research: a meta-analytic examination of studies utilising the theories of reasoned action and planned behaviour.

PubMed

McDermott, Máirtín S; Sharma, Rajeev

2017-12-01

The methods employed to measure behaviour in research testing the theories of reasoned action/planned behaviour (TRA/TPB) within the context of health behaviours have the potential to significantly bias findings. One bias yet to be examined in that literature is that due to common method variance (CMV). CMV introduces a variance in scores attributable to the method used to measure a construct, rather than the construct it represents. The primary aim of this study was to evaluate the impact of method bias on the associations of health behaviours with TRA/TPB variables. Data were sourced from four meta-analyses (177 studies). The method used to measure behaviour for each effect size was coded for susceptibility to bias. The moderating impact of method type was assessed using meta-regression. Method type significantly moderated the associations of intentions, attitudes and social norms with behaviour, but not that between perceived behavioural control and behaviour. The magnitude of the moderating effect of method type appeared consistent between cross-sectional and prospective studies, but varied across behaviours. The current findings strongly suggest that method bias significantly inflates associations in TRA/TPB research, and poses a potentially serious validity threat to the cumulative findings reported in that field.

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

PubMed

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

Infant carrying methods: Correlates and associated musculoskeletal disorders among nursing mothers in Nigeria.

PubMed

Ojukwu, Chidiebele Petronilla; Anyanwu, Godson Emeka; Anekwu, Emelie Morris; Chukwu, Sylvester Caesar; Fab-Agbo, Chukwubuikem

2017-10-01

Infant carrying is an integral part of the mothering occupation. Paucity of data exists on its correlates and associated musculoskeletal injuries. In this study, factors and musculoskeletal injuries associated with infant carrying were investigated in 227 nursing mothers, using a structured questionnaire. 77.1% utilised the back infant carrying methods (ICM). Maternal comfort was the major factor influencing participants' (37.4%) choices of ICMs. Infant's age (p = .000) and transportation means (p = .045) were significantly associated with ICMs. Low back pain (82.8%) and upper back pain (74.9%) were the most reported musculoskeletal discomforts associated with ICMs, especially among women who utilised back ICM. Back ICM is predominantly used by nursing mothers. Impact statement Infant carrying has been associated with increased energy cost and biomechanical changes. Currently, there is a paucity of data on infant carrying-related musculoskeletal injuries. In this study, investigating factors and musculoskeletal injuries associated with infant carrying, the results showed that back infant carrying method is predominantly used by nursing mothers. Age of the infant and mothers' means of transportation were determinant factors of infant carrying methods. Among the several reported infant carrying-related musculoskeletal disorders, low back and upper back pain were the most prevalent, especially among women who utilised the back infant carrying method. There is need for women's health specialists to introduce appropriate ergonomic training and interventions on infant carrying tasks in order to improve maternal musculoskeletal health during the childbearing years and beyond. Further experimental studies on the effects of various infant carrying methods on the musculoskeletal system are recommended.

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

PubMed Central

Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

2014-01-01

Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212

Dissecting the genetics of complex traits using summary association statistics.

PubMed

Pasaniuc, Bogdan; Price, Alkes L

2017-02-01

During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.

Dissecting the genetics of complex traits using summary association statistics

PubMed Central

Pasaniuc, Bogdan; Price, Alkes L.

2017-01-01

During the past decade, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyze summary association statistics. Here we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases. PMID:27840428

A fast boosting-based screening method for large-scale association study in complex traits with genetic heterogeneity.

PubMed

Wang, Lu-Yong; Fasulo, D

2006-01-01

Genome-wide association study for complex diseases will generate massive amount of single nucleotide polymorphisms (SNPs) data. Univariate statistical test (i.e. Fisher exact test) was used to single out non-associated SNPs. However, the disease-susceptible SNPs may have little marginal effects in population and are unlikely to retain after the univariate tests. Also, model-based methods are impractical for large-scale dataset. Moreover, genetic heterogeneity makes the traditional methods harder to identify the genetic causes of diseases. A more recent random forest method provides a more robust method for screening the SNPs in thousands scale. However, for more large-scale data, i.e., Affymetrix Human Mapping 100K GeneChip data, a faster screening method is required to screening SNPs in whole-genome large scale association analysis with genetic heterogeneity. We propose a boosting-based method for rapid screening in large-scale analysis of complex traits in the presence of genetic heterogeneity. It provides a relatively fast and fairly good tool for screening and limiting the candidate SNPs for further more complex computational modeling task.

Improved score statistics for meta-analysis in single-variant and gene-level association studies.

PubMed

Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo

2018-06-01

Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.

GWASinlps: Nonlocal prior based iterative SNP selection tool for genome-wide association studies.

PubMed

Sanyal, Nilotpal; Lo, Min-Tzu; Kauppi, Karolina; Djurovic, Srdjan; Andreassen, Ole A; Johnson, Valen E; Chen, Chi-Hua

2018-06-19

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using nonlocal priors in an iterative variable selection framework. We develop a variable selection method, named, iterative nonlocal prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations, and concatenates variable selection within that hierarchy. Extensive simulation studies with SNPs having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error, and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype. An R-package for implementing the GWASinlps method is available at https://cran.r-project.org/web/packages/GWASinlps/index.html. Supplementary data are available at Bioinformatics online.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Controlling the joint local false discovery rate is more powerful than meta-analysis methods in joint analysis of summary statistics from multiple genome-wide association studies.

PubMed

Jiang, Wei; Yu, Weichuan

2017-02-15

In genome-wide association studies (GWASs) of common diseases/traits, we often analyze multiple GWASs with the same phenotype together to discover associated genetic variants with higher power. Since it is difficult to access data with detailed individual measurements, summary-statistics-based meta-analysis methods have become popular to jointly analyze datasets from multiple GWASs. In this paper, we propose a novel summary-statistics-based joint analysis method based on controlling the joint local false discovery rate (Jlfdr). We prove that our method is the most powerful summary-statistics-based joint analysis method when controlling the false discovery rate at a certain level. In particular, the Jlfdr-based method achieves higher power than commonly used meta-analysis methods when analyzing heterogeneous datasets from multiple GWASs. Simulation experiments demonstrate the superior power of our method over meta-analysis methods. Also, our method discovers more associations than meta-analysis methods from empirical datasets of four phenotypes. The R-package is available at: http://bioinformatics.ust.hk/Jlfdr.html . eeyu@ust.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Fish intake, cooking practices, and risk of prostate cancer: results from a multi-ethnic case-control study.

PubMed

Joshi, Amit D; John, Esther M; Koo, Jocelyn; Ingles, Sue A; Stern, Mariana C

2012-03-01

Studies conducted to assess the association between fish consumption and prostate cancer (PCA) risk are inconclusive. However, few studies have distinguished between fatty and lean fish, and no studies have considered the role of different cooking practices, which may lead to differential accumulation of chemical carcinogens. In this study, we investigated the association between fish intake and localized and advanced PCA taking into account fish types (lean vs. fatty) and cooking practices. We analyzed data for 1,096 controls, 717 localized and 1,140 advanced cases from the California Collaborative Prostate Cancer Study, a multiethnic, population-based case-control study. We used multivariate conditional logistic regression to estimate odds ratios using nutrient density converted variables of fried fish, tuna, dark fish and white fish consumption. We tested for effect modification by cooking methods (high- vs. low-temperature methods) and levels of doneness. We observed that high white fish intake was associated with increased risk of advanced PCA among men who cooked with high-temperature methods (pan-frying, oven-broiling and grilling) until fish was well done (p (trend) = 0.001). No associations were found among men who cooked fish at low temperature and/or just until done (white fish x cooking method p (interaction) = 0.040). Our results indicate that consideration of fish type (oily vs. lean), specific fish cooking practices and levels of doneness of cooked fish helps elucidate the association between fish intake and PCA risk and suggest that avoiding high-temperature cooking methods for white fish may lower PCA risk.

Application of the stepwise focusing method to optimize the cost-effectiveness of genome-wide association studies with limited research budgets for genotyping and phenotyping.

PubMed

Ohashi, J; Clark, A G

2005-05-01

The recent cataloguing of a large number of SNPs enables us to perform genome-wide association studies for detecting common genetic variants associated with disease. Such studies, however, generally have limited research budgets for genotyping and phenotyping. It is therefore necessary to optimize the study design by determining the most cost-effective numbers of SNPs and individuals to analyze. In this report we applied the stepwise focusing method, with two-stage design, developed by Satagopan et al. (2002) and Saito & Kamatani (2002), to optimize the cost-effectiveness of a genome-wide direct association study using a transmission/disequilibrium test (TDT). The stepwise focusing method consists of two steps: a large number of SNPs are examined in the first focusing step, and then all the SNPs showing a significant P-value are tested again using a larger set of individuals in the second focusing step. In the framework of optimization, the numbers of SNPs and families and the significance levels in the first and second steps were regarded as variables to be considered. Our results showed that the stepwise focusing method achieves a distinct gain of power compared to a conventional method with the same research budget.

Campaign Strategies and Voter Approval of School Referenda: A Mixed Methods Analysis

ERIC Educational Resources Information Center

Johnson, Paul A.; Ingle, William Kyle

2009-01-01

Drawing from state administrative data and surveys of superintendents in Ohio, this mixed methods study examined factors associated with voters' approval of local school levies. Utilizing binomial logistic regression, this study found that new levies and poverty rates were significantly associated with a decrease in the likelihood of passage.…

A psychological study of stress, personality and coping in police personnel.

PubMed

Kaur, Ravneet; Chodagiri, Vamsi K; Reddi, Narasimha K

2013-04-01

There have been few studies focusing on occupational/organizational causes of stress in police. Hardly any studies exist on personality traits and coping methods in this group of individuals. To study the association of personality traits and coping methods to psychological stress in police personnel. This cross-sectional study was conducted among the constables and head constables working in the Police Department, Vizianagram town, Andhra Pradesh. The study sample consisted of 150 police persons. The socio-demographic data was individually collected from them. General Health Questionnaire-28 (GHQ-28) was used for assessing psychological stress, Eysenck's Personality Questionnaire (EPQ) for personality traits, and Coping Checklist-1 (CCL-1) for eliciting coping methods. The statistical analysis was done using SPSS v 10 software. On screening by GHQ-28, 35.33% of the police were found to be having psychological distress. The socio-demographic variables showed no significant association to psychological stress. Personality traits such as neuroticism, psychoticism, and extroversion and coping methods like negative distraction and denial/blame showed statistically significant association (P<0.05) with psychological stress. The most commonly used coping methods across the sample were social support (72.55%), acceptance/redefinition (64.72%), and problem solving (60.46%). As measured by Pearson's correlation coefficient (r), there was evidence of linear association between certain personality traits and coping methods as well. The personality traits and coping methods have significant independent and interactive role in the development of high psychological stress in police persons, thus placing them at a high risk of developing psychiatric disorders.

A comparison of radiographic anatomic axis knee alignment measurements and cross-sectional associations with knee osteoarthritis

PubMed Central

Goulston, L.M.; Sanchez-Santos, M.T.; D'Angelo, S.; Leyland, K.M.; Hart, D.J.; Spector, T.D.; Cooper, C.; Dennison, E.M.; Hunter, D.; Arden, N.K.

2016-01-01

Summary Objective Malalignment is associated with knee osteoarthritis (KOA), however, the optimal anatomic axis (AA) knee alignment measurement on a standard limb radiograph (SLR) is unknown. This study compares one-point (1P) and two-point (2P) AA methods using three knee joint centre locations and examines cross-sectional associations with symptomatic radiographic knee osteoarthritis (SRKOA), radiographic knee osteoarthritis (RKOA) and knee pain. Methods AA alignment was measured six different ways using the KneeMorf software on 1058 SLRs from 584 women in the Chingford Study. Cross-sectional associations with principal outcome SRKOA combined with greatest reproducibility determined the optimal 1P and 2P AA method. Appropriate varus/neutral/valgus alignment categories were established using logistic regression with generalised estimating equation models fitted with restricted cubic spline function. Results The tibial plateau centre displayed greatest reproducibility and associations with SRKOA. As mean 1P and 2P values differed by >2°, new alignment categories were generated for 1P: varus <178°, neutral 178–182°, valgus >182° and for 2P methods: varus <180°, neutral 180–185°, valgus >185°. Varus vs neutral alignment was associated with a near 2-fold increase in SRKOA and RKOA, and valgus vs neutral for RKOA using 2P method. Nonsignificant associations were seen for 1P method for SRKOA, RKOA and knee pain. Conclusions AA alignment was associated with SRKOA and the tibial plateau centre had the strongest association. Differences in AA alignment when 1P vs 2P methods were compared indicated bespoke alignment categories were necessary. Further replication and validation with mechanical axis alignment comparison is required. PMID:26700504

The use of dual or two methods for pregnancy and HIV prevention amongst 18-24-year-olds in a cross-sectional study conducted in South Africa.

PubMed

Seutlwadi, Lebogang; Peltzer, Karl

2013-06-01

The use of dual (for pregnancy and disease prevention) or two methods of contraceptives is recommended for the prevention of unwanted pregnancies and protection against sexually transmitted diseases such as HIV. The study aims to assess the prevalence and explore factors associated with the use of dual or two methods among young people aged 18 to 24 years in South Africa. Factors associated with use of dual or two methods among young people aged 18 to 24 years in South Africa were investigated by individual interviews. The final sample included 1127 males and 1007 females from four provinces (Eastern Cape, Gauteng, KwaZulu-Natal and Mpumalanga) who reported to have ever had sex. The study found among men (18-24 years) 10.4% and among women (18-24 years) 15.4%, current use of dual or two methods was reported. In multivariate analyses, among women, lower poverty, not being unemployed, having concurrent sexual partners and higher sexual intercourse frequency in the past month were associated with use of dual or two methods, while for men, contraceptive methods knowledge, greater relationship control and higher sexual intercourse frequency in the past month were associated with use of dual or two methods. The use of dual or two methods remains low. Innovative ways are needed for the promotion and increased use of dual or two methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Evaluation of the relationship between plasma lipids and abdominal aortic aneurysm: A Mendelian randomization study.

PubMed

Weng, Lu-Chen; Roetker, Nicholas S; Lutsey, Pamela L; Alonso, Alvaro; Guan, Weihua; Pankow, James S; Folsom, Aaron R; Steffen, Lyn M; Pankratz, Nathan; Tang, Weihong

2018-01-01

Studies have reported that higher circulating levels of total cholesterol (TC), low-density lipoprotein (LDL) cholesterol and lower of high-density lipoprotein (HDL) cholesterol may be associated with increased risk of abdominal aortic aneurysm (AAA). Whether dyslipidemia causes AAA is still unclear and is potentially testable using a Mendelian randomization (MR) approach. We investigated the associations between blood lipids and AAA using two-sample MR analysis with SNP-lipids association estimates from a published genome-wide association study of blood lipids (n = 188,577) and SNP-AAA association estimates from European Americans (EAs) of the Atherosclerosis Risk in Communities (ARIC) study (n = 8,793). We used inverse variance weighted (IVW) MR as the primary method and MR-Egger regression and weighted median MR estimation as sensitivity analyses. Over a median of 22.7 years of follow-up, 338 of 8,793 ARIC participants experienced incident clinical AAA. Using the IVW method, we observed positive associations of plasma LDL cholesterol and TC with the risk of AAA (odds ratio (OR) = 1.55, P = 0.02 for LDL cholesterol and OR = 1.61, P = 0.01 for TC per 1 standard deviation of lipid increment). Using the MR-Egger regression and weighted median methods, we were able to validate the association of AAA risk with TC, although the associations were less consistent for LDL cholesterol due to wider confidence intervals. Triglycerides and HDL cholesterol were not associated with AAA in any of the MR methods. Assuming instrumental variable assumptions are satisfied, our finding suggests that higher plasma TC and LDL cholesterol are causally associated with the increased risk of AAA in EAs.

Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies

PubMed Central

Huang, Jim C.; Meek, Christopher; Kadie, Carl; Heckerman, David

2011-01-01

Understanding the role of genetic variation in human diseases remains an important problem to be solved in genomics. An important component of such variation consist of variations at single sites in DNA, or single nucleotide polymorphisms (SNPs). Typically, the problem of associating particular SNPs to phenotypes has been confounded by hidden factors such as the presence of population structure, family structure or cryptic relatedness in the sample of individuals being analyzed. Such confounding factors lead to a large number of spurious associations and missed associations. Various statistical methods have been proposed to account for such confounding factors such as linear mixed-effect models (LMMs) or methods that adjust data based on a principal components analysis (PCA), but these methods either suffer from low power or cease to be tractable for larger numbers of individuals in the sample. Here we present a statistical model for conducting genome-wide association studies (GWAS) that accounts for such confounding factors. Our method scales in runtime quadratic in the number of individuals being studied with only a modest loss in statistical power as compared to LMM-based and PCA-based methods when testing on synthetic data that was generated from a generalized LMM. Applying our method to both real and synthetic human genotype/phenotype data, we demonstrate the ability of our model to correct for confounding factors while requiring significantly less runtime relative to LMMs. We have implemented methods for fitting these models, which are available at http://www.microsoft.com/science. PMID:21765897

Explaining Method Effects Associated with Negatively Worded Items in Trait and State Global and Domain-Specific Self-Esteem Scales

ERIC Educational Resources Information Center

Tomas, Jose M.; Oliver, Amparo; Galiana, Laura; Sancho, Patricia; Lila, Marisol

2013-01-01

Several investigators have interpreted method effects associated with negatively worded items in a substantive way. This research extends those studies in different ways: (a) it establishes the presence of methods effects in further populations and particular scales, and (b) it examines the possible relations between a method factor associated…

A hierarchical and modular approach to the discovery of robust associations in genome-wide association studies from pooled DNA samples

PubMed Central

Sebastiani, Paola; Zhao, Zhenming; Abad-Grau, Maria M; Riva, Alberto; Hartley, Stephen W; Sedgewick, Amanda E; Doria, Alessandro; Montano, Monty; Melista, Efthymia; Terry, Dellara; Perls, Thomas T; Steinberg, Martin H; Baldwin, Clinton T

2008-01-01

Background One of the challenges of the analysis of pooling-based genome wide association studies is to identify authentic associations among potentially thousands of false positive associations. Results We present a hierarchical and modular approach to the analysis of genome wide genotype data that incorporates quality control, linkage disequilibrium, physical distance and gene ontology to identify authentic associations among those found by statistical association tests. The method is developed for the allelic association analysis of pooled DNA samples, but it can be easily generalized to the analysis of individually genotyped samples. We evaluate the approach using data sets from diverse genome wide association studies including fetal hemoglobin levels in sickle cell anemia and a sample of centenarians and show that the approach is highly reproducible and allows for discovery at different levels of synthesis. Conclusion Results from the integration of Bayesian tests and other machine learning techniques with linkage disequilibrium data suggest that we do not need to use too stringent thresholds to reduce the number of false positive associations. This method yields increased power even with relatively small samples. In fact, our evaluation shows that the method can reach almost 70% sensitivity with samples of only 100 subjects. PMID:18194558

Addressing the Learning Outcomes and Assessment Methods Associated with Participation in Student Government Associations: A Qualitative Study of California Community Colleges

ERIC Educational Resources Information Center

Nevin, Miles J.

2017-01-01

This document analysis synthesized student learning outcomes (SLOs) and assessment methods from a sample of 36 student government associations in the California Community College system. Student learning outcomes were grouped according to "governance, ethical and civic behavior", and "experiential learning functions." Using…

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Face-name association learning in early Alzheimer's disease: a comparison of learning methods and their underlying mechanisms.

PubMed

Bier, Nathalie; Van Der Linden, Martial; Gagnon, Lise; Desrosiers, Johanne; Adam, Stephane; Louveaux, Stephanie; Saint-Mleux, Julie

2008-06-01

This study compared the efficacy of five learning methods in the acquisition of face-name associations in early dementia of Alzheimer type (AD). The contribution of error production and implicit memory to the efficacy of each method was also examined. Fifteen participants with early AD and 15 matched controls were exposed to five learning methods: spaced retrieval, vanishing cues, errorless, and two trial-and-error methods, one with explicit and one with implicit memory task instructions. Under each method, participants had to learn a list of five face-name associations, followed by free recall, cued recall and recognition. Delayed recall was also assessed. For AD, results showed that all methods were efficient but there were no significant differences between them. The number of errors produced during the learning phases varied between the five methods but did not influence learning. There were no significant differences between implicit and explicit memory task instructions on test performances. For the control group, there were no differences between the five methods. Finally, no significant correlations were found between the performance of the AD participants in free recall and their cognitive profile, but generally, the best performers had better remaining episodic memory. Also, case study analyses showed that spaced retrieval was the method for which the greatest number of participants (four) obtained results as good as the controls. This study suggests that the five methods are effective for new learning of face-name associations in AD. It appears that early AD patients can learn, even in the context of error production and explicit memory conditions.

Factors Associated with Recruitment and Screening in the Treatment for Adolescents with Depression Study (TADS)

ERIC Educational Resources Information Center

May, Diane E.; Hallin, Mary J.; Kratochvil, Christopher J.; Puumala, Susan E.; Smith, Lynette S.; Reinecke, Mark A.; Silva, Susan G.; Weller, Elizabeth B.; Vitiello, Benedetto; Breland-Noble, Alfiee; March, John S.

2007-01-01

Objective: To examine factors associated with eligibility and randomization and consider the efficiency of recruitment methods. Method: Adolescents, ages 12 to 17 years, were telephone screened (N = 2,804) followed by in-person evaluation (N = 1,088) for the Treatment for Adolescents With Depression Study. Separate logistic regression models,…

Are PCI Service Volumes Associated with 30-Day Mortality? A Population-Based Study from Taiwan.

PubMed

Yu, Tsung-Hsien; Chou, Ying-Yi; Wei, Chung-Jen; Tung, Yu-Chi

2017-11-09

The volume-outcome relationship has been discussed for over 30 years; however, the findings are inconsistent. This might be due to the heterogeneity of service volume definitions and categorization methods. This study takes percutaneous coronary intervention (PCI) as an example to examine whether the service volume was associated with PCI 30-day mortality, given different service volume definitions and categorization methods. A population-based, cross-sectional multilevel study was conducted. Two definitions of physician and hospital volume were used: (1) the cumulative PCI volume in a previous year before each PCI; (2) the cumulative PCI volume within the study period. The volume was further treated in three ways: (1) a categorical variable based on the American Heart Association's recommendation; (2) a semi-data-driven categorical variable based on k-means clustering algorithm; and (3) a data-driven categorical variable based on the Generalized Additive Model. The results showed that, after adjusting the patient-, physician-, and hospital-level covariates, physician volume was associated inversely with PCI 30-day mortality, but hospital volume was not, no matter which definitions and categorization methods of service volume were applied. Physician volume is negatively associated with PCI 30-day mortality, but the results might vary because of definition and categorization method.

Validity of using ad hoc methods to analyze secondary traits in case-control association studies.

PubMed

Yung, Godwin; Lin, Xihong

2016-12-01

Case-control association studies often collect from their subjects information on secondary phenotypes. Reusing the data and studying the association between genes and secondary phenotypes provide an attractive and cost-effective approach that can lead to discovery of new genetic associations. A number of approaches have been proposed, including simple and computationally efficient ad hoc methods that ignore ascertainment or stratify on case-control status. Justification for these approaches relies on the assumption of no covariates and the correct specification of the primary disease model as a logistic model. Both might not be true in practice, for example, in the presence of population stratification or the primary disease model following a probit model. In this paper, we investigate the validity of ad hoc methods in the presence of covariates and possible disease model misspecification. We show that in taking an ad hoc approach, it may be desirable to include covariates that affect the primary disease in the secondary phenotype model, even though these covariates are not necessarily associated with the secondary phenotype. We also show that when the disease is rare, ad hoc methods can lead to severely biased estimation and inference if the true disease model follows a probit model instead of a logistic model. Our results are justified theoretically and via simulations. Applied to real data analysis of genetic associations with cigarette smoking, ad hoc methods collectively identified as highly significant (P<10-5) single nucleotide polymorphisms from over 10 genes, genes that were identified in previous studies of smoking cessation. © 2016 WILEY PERIODICALS, INC.

The association between drinking water turbidity and gastrointestinal illness: a systematic review

PubMed Central

Mann, Andrea G; Tam, Clarence C; Higgins, Craig D; Rodrigues, Laura C

2007-01-01

Background Studies suggest that routine variations in public drinking water turbidity may be associated with endemic gastrointestinal illness. We systematically reviewed the literature on this topic. Methods We searched databases and websites for relevant studies in industrialized countries. Studies investigating the association between temporal variations in drinking water turbidity and incidence of acute gastrointestinal illness were assessed for quality. We reviewed good quality studies for evidence of an association between increased turbidity and gastrointestinal illness. Results We found six relevant good quality studies. Of five studies investigating effluent water turbidity, two found no association. Two studies from Philadelphia reported increased paediatric and elderly hospital use on specific days after increased turbidity. A fifth study reported more telephone health service calls on specific days after peak turbidity. There were differences between studies affecting their comparability, including baseline turbidity and adjustment for seasonal confounders. Conclusion It is likely that an association between turbidity and GI illness exists in some settings or over a certain range of turbidity. A pooled analysis of available data using standard methods would facilitate interpretation. PMID:17888154

Bias Characterization in Probabilistic Genotype Data and Improved Signal Detection with Multiple Imputation

PubMed Central

Palmer, Cameron; Pe’er, Itsik

2016-01-01

Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data. PMID:27310603

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

DISSCO: direct imputation of summary statistics allowing covariates

PubMed Central

Xu, Zheng; Duan, Qing; Yan, Song; Chen, Wei; Li, Mingyao; Lange, Ethan; Li, Yun

2015-01-01

Background: Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates. Methods: We analytically show that in the absence of covariates, correlation among association summary statistics is indeed the same as that among the corresponding genotypes, thus serving as a theoretical justification for the recently proposed methods. We continue to prove that in the presence of covariates, correlation among association summary statistics becomes the partial correlation of the corresponding genotypes controlling for covariates. We therefore develop direct imputation of summary statistics allowing covariates (DISSCO). Results: We consider two real-life scenarios where the correlation and partial correlation likely make practical difference: (i) association studies in admixed populations; (ii) association studies in presence of other confounding covariate(s). Application of DISSCO to real datasets under both scenarios shows at least comparable, if not better, performance compared with existing correlation-based methods, particularly for lower frequency variants. For example, DISSCO can reduce the absolute deviation from the truth by 3.9–15.2% for variants with minor allele frequency <5%. Availability and implementation: http://www.unc.edu/∼yunmli/DISSCO. Contact: yunli@med.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25810429

Prevalence and factors affecting use of long acting and permanent contraceptive methods in Jinka town, Southern Ethiopia: a cross sectional study.

PubMed

Mekonnen, Getachew; Enquselassie, Fikre; Tesfaye, Gezahegn; Semahegn, Agumasie

2014-01-01

In Ethiopia, knowledge of contraceptive methods is high though there is low contraceptive prevalence rate. This study was aimed to assess prevalence and associated factors of long acting and permanent contraceptive methods in Jinka town, southern Ethiopia. Community based cross sectional survey was conducted to assess the prevalence and factors affecting long acting and permanent methods of contraceptives utilization from March to April 2008. Eight hundred child bearing age women were participated in the quantitative study and 32 purposively selected focus group discussants were participated in the qualitative study. Face to face interview was used for data collection. Data were analyzed by SPSS version 13.0 statistical software. Descriptive statistics and logistic regression were computed to analyze the data. The prevalence of long acting and permanent contraceptive method was 7.3%. Three fourth (76.1%) of the women have ever heard about implants and implant 28 (50%) were the most widely used method. Almost two third of women had intention to use long acting and permanent methods. Knowledge of contraceptive and age of women have significant association with the use of long acting and permanent contraceptive methods. The overall prevalence of long acting and permanent contraceptive method was low. Knowledge of contraceptive and age of women have significant association with use of long acting and permanent contraceptive. Extensive health information should be provided.

Comparison of 3 Methods for Identifying Dietary Patterns Associated With Risk of Disease

PubMed Central

DiBello, Julia R.; Kraft, Peter; McGarvey, Stephen T.; Goldberg, Robert; Campos, Hannia

2008-01-01

Reduced rank regression and partial least-squares regression (PLS) are proposed alternatives to principal component analysis (PCA). Using all 3 methods, the authors derived dietary patterns in Costa Rican data collected on 3,574 cases and controls in 1994–2004 and related the resulting patterns to risk of first incident myocardial infarction. Four dietary patterns associated with myocardial infarction were identified. Factor 1, characterized by high intakes of lean chicken, vegetables, fruit, and polyunsaturated oil, was generated by all 3 dietary pattern methods and was associated with a significantly decreased adjusted risk of myocardial infarction (28%–46%, depending on the method used). PCA and PLS also each yielded a pattern associated with a significantly decreased risk of myocardial infarction (31% and 23%, respectively); this pattern was characterized by moderate intake of alcohol and polyunsaturated oil and low intake of high-fat dairy products. The fourth factor derived from PCA was significantly associated with a 38% increased risk of myocardial infarction and was characterized by high intakes of coffee and palm oil. Contrary to previous studies, the authors found PCA and PLS to produce more patterns associated with cardiovascular disease than reduced rank regression. The most effective method for deriving dietary patterns related to disease may vary depending on the study goals. PMID:18945692

A comparison of radiographic anatomic axis knee alignment measurements and cross-sectional associations with knee osteoarthritis.

PubMed

Goulston, L M; Sanchez-Santos, M T; D'Angelo, S; Leyland, K M; Hart, D J; Spector, T D; Cooper, C; Dennison, E M; Hunter, D; Arden, N K

2016-04-01

Malalignment is associated with knee osteoarthritis (KOA), however, the optimal anatomic axis (AA) knee alignment measurement on a standard limb radiograph (SLR) is unknown. This study compares one-point (1P) and two-point (2P) AA methods using three knee joint centre locations and examines cross-sectional associations with symptomatic radiographic knee osteoarthritis (SRKOA), radiographic knee osteoarthritis (RKOA) and knee pain. AA alignment was measured six different ways using the KneeMorf software on 1058 SLRs from 584 women in the Chingford Study. Cross-sectional associations with principal outcome SRKOA combined with greatest reproducibility determined the optimal 1P and 2P AA method. Appropriate varus/neutral/valgus alignment categories were established using logistic regression with generalised estimating equation models fitted with restricted cubic spline function. The tibial plateau centre displayed greatest reproducibility and associations with SRKOA. As mean 1P and 2P values differed by >2°, new alignment categories were generated for 1P: varus <178°, neutral 178-182°, valgus >182° and for 2P methods: varus <180°, neutral 180-185°, valgus >185°. Varus vs neutral alignment was associated with a near 2-fold increase in SRKOA and RKOA, and valgus vs neutral for RKOA using 2P method. Nonsignificant associations were seen for 1P method for SRKOA, RKOA and knee pain. AA alignment was associated with SRKOA and the tibial plateau centre had the strongest association. Differences in AA alignment when 1P vs 2P methods were compared indicated bespoke alignment categories were necessary. Further replication and validation with mechanical axis alignment comparison is required. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Validity of Eye Movement Methods and Indices for Capturing Semantic (Associative) Priming Effects

ERIC Educational Resources Information Center

Odekar, Anshula; Hallowell, Brooke; Kruse, Hans; Moates, Danny; Lee, Chao-Yang

2009-01-01

Purpose: The purpose of this investigation was to evaluate the usefulness of eye movement methods and indices as a tool for studying priming effects by verifying whether eye movement indices capture semantic (associative) priming effects in a visual cross-format (written word to semantically related picture) priming paradigm. Method: In the…

Birthweight, early life body size and adult mammographic density: a review of epidemiologic studies.

PubMed

Yochum, Laura; Tamimi, Rulla M; Hankinson, Susan E

2014-10-01

To evaluate the association between birth weight and early life body size with adult mammographic density in the peer-reviewed literature. A comprehensive literature search was conducted through January, 2014. English language articles that assessed adult mammographic density (MD) in relation to early life body size (≤18 years old), or birthweight were included. Nine studies reported results for early life body size and %MD. Both exposure and outcome were assessed at different ages using multiple methods. In premenopausal women, findings were inconsistent; two studies reported significant, inverse associations, one reported a non-significant, inverse association, and two observed no association. Reasons for these inconsistencies were not obvious. In postmenopausal women, four of five studies supported an inverse association. Two of three studies that adjusted for menopausal status found significant, inverse associations. Birthweight and %MD was evaluated in nine studies. No association was seen in premenopausal women and two of three studies reported positive associations in postmenopausal women. Three of four studies that adjusted for menopausal status found no association. Early life body size and birthweight appear unrelated to %MD in premenopausal women while an inverse association in postmenopausal women is more likely. Although based on limited data, birthweight and %MD appear positively associated in postmenopausal women. Given the small number of studies, the multiple methods of data collection and analysis, other methodologic issues, and lack of consistency in results, additional research is needed to clarify this complex association and develop a better understanding of the underlying biologic mechanisms.

Rare variant association analysis in case-parents studies by allowing for missing parental genotypes.

PubMed

Li, Yumei; Xiang, Yang; Xu, Chao; Shen, Hui; Deng, Hongwen

2018-01-15

The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding "complements" in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association.

Examining Fifth-Grade Students' Level of Associating Some Daily-Life Events with "Changes of State"

ERIC Educational Resources Information Center

Cengiz, Ekrem; Ayvaci, Hakan Sevki

2017-01-01

This study aims to examine fifth grade students' level of associating daily life events with the subject "changes of state" in the science curriculum. Among the qualitative research methods, special case method was used in the study. Seven open-ended questions about the changing states of matter were used for data collection. These…

The relationship of the local food environment with obesity: A systematic review of methods, study quality and results

PubMed Central

Cobb, Laura K; Appel, Lawrence J; Franco, Manuel; Jones-Smith, Jessica C; Nur, Alana; Anderson, Cheryl AM

2015-01-01

Objective To examine the relationship between local food environments and obesity and assess the quality of studies reviewed. Methods Systematic keyword searches identified studies from US and Canada that assessed the relationship of obesity to local food environments. We applied a quality metric based on design, exposure and outcome measurement, and analysis. Results We identified 71 studies representing 65 cohorts. Overall, study quality was low; 60 studies were cross-sectional. Associations between food outlet availability and obesity were predominantly null. Among non-null associations, we saw a trend toward inverse associations between supermarket availability and obesity (22 negative, 4 positive, 67 null) and direct associations between fast food and obesity (29 positive, 6 negative, 71 null) in adults. We saw direct associations between fast food availability and obesity in lower income children (12 positive, 7 null). Indices including multiple food outlets were most consistently associated with obesity in adults (18 expected, 1 not expected, 17 null). Limiting to higher quality studies did not affect results. Conclusions Despite the large number of studies, we found limited evidence for associations between local food environments and obesity. The predominantly null associations should be interpreted cautiously due to the low quality of available studies. PMID:26096983

Overcoming the winner's curse: estimating penetrance parameters from case-control data.

PubMed

Zollner, Sebastian; Pritchard, Jonathan K

2007-04-01

Genomewide association studies are now a widely used approach in the search for loci that affect complex traits. After detection of significant association, estimates of penetrance and allele-frequency parameters for the associated variant indicate the importance of that variant and facilitate the planning of replication studies. However, when these estimates are based on the original data used to detect the variant, the results are affected by an ascertainment bias known as the "winner's curse." The actual genetic effect is typically smaller than its estimate. This overestimation of the genetic effect may cause replication studies to fail because the necessary sample size is underestimated. Here, we present an approach that corrects for the ascertainment bias and generates an estimate of the frequency of a variant and its penetrance parameters. The method produces a point estimate and confidence region for the parameter estimates. We study the performance of this method using simulated data sets and show that it is possible to greatly reduce the bias in the parameter estimates, even when the original association study had low power. The uncertainty of the estimate decreases with increasing sample size, independent of the power of the original test for association. Finally, we show that application of the method to case-control data can improve the design of replication studies considerably.

RESULTS FROM THE 2005 NATIONAL BEACHES STUDY: THE ASSOCIATION BETWEEN RAPIDLY MEASURED INDICATORS OF FECAL CONTAMINATION AND SWIMMING ASSOCIATED GASTROENTERITIS

EPA Science Inventory

In 2003, the US EPA Office of Research and Development conducted studies at two Great Lakes beaches to evaluate the association between novel, rapid methods of measuring fecal contamination and swimming associated health effects. These results were presented at the 2004 Science F...

Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.

PubMed

Pasaniuc, Bogdan; Zaitlen, Noah; Lettre, Guillaume; Chen, Gary K; Tandon, Arti; Kao, W H Linda; Ruczinski, Ingo; Fornage, Myriam; Siscovick, David S; Zhu, Xiaofeng; Larkin, Emma; Lange, Leslie A; Cupples, L Adrienne; Yang, Qiong; Akylbekova, Ermeg L; Musani, Solomon K; Divers, Jasmin; Mychaleckyj, Joe; Li, Mingyao; Papanicolaou, George J; Millikan, Robert C; Ambrosone, Christine B; John, Esther M; Bernstein, Leslie; Zheng, Wei; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Ingles, Sue A; Press, Michael F; Chanock, Stephen J; Deming, Sandra L; Rodriguez-Gil, Jorge L; Palmer, Cameron D; Buxbaum, Sarah; Ekunwe, Lynette; Hirschhorn, Joel N; Henderson, Brian E; Myers, Simon; Haiman, Christopher A; Reich, David; Patterson, Nick; Wilson, James G; Price, Alkes L

2011-04-01

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Associations between heavy-vehicle driver compensation methods, fatigue-related driving behavior, and sleepiness.

PubMed

Thompson, Jason; Stevenson, Mark

2014-01-01

There has been growing recognition that broader economic and organizational factors play a role in creating work environments that facilitate high-risk driving behavior. This study investigates the association between compensation methods for drivers, fatigue-related driving behavior, and sleepiness among Australian heavy-vehicle drivers. Specifically, we hypothesized that piece-rate compensation methods linked to performance outcomes would be associated with greater levels of fatigue-related driving behaviors and sleepiness. We examined data from a random sample of 346 long-haul heavy-vehicle drivers who had not been involved in a crash. A 40-min interview was conducted that elicited information regarding driver demographics, truck characteristics, and compensation arrangements. Specific details about drivers' behavior on their most recent trip including load(s) carried, distances driven, hours driven, rest breaks, and hours of sleep on the previous night were taken. The interview also included a standardized assessment of sleepiness using the Epworth Sleepiness Scale (ESS). A multivariate analysis of covariance demonstrated a significant multivariate effect for compensation methods across the combined, fatigue-related driving behavior dependent variables, F (10, 676)=2.80, p<.01. Between-subject effects demonstrated significant association between compensation methods and 4 of 5 fatigue-related variables under study, including kilometers driven per day, F (2, 340)=7.75, p<.001, hours driven per day, F (2, 341)=2.64, p<.05, total hours worked per week, F (2, 340)=5.27, p<.01, and mean driving time between breaks, F (2, 341)=4.45, p<.05. Post hoc tests revealed that piece-rate compensation methods were associated with higher levels of fatigue-related driving than non-piece-rate methods. Follow-up analysis also revealed higher caffeine and amphetamines use among piece-rate drivers for the purpose of staying awake while driving. Despite this, no association between compensation methods and sleepiness were revealed. RESULTS confirmed that performance-based compensation methods are associated with work practices that may exacerbate driving behaviors associated with fatigue. Despite this finding, however, performance-based compensation methods were not associated with higher levels of sleepiness. This highlights the presence of potential differences in self-selection, operational, or fatigue management practices that may be common to drivers paid under various methods. Implications of these results for safety policy and future safety research within the heavy-vehicle industry are discussed.

Epigenome-wide association studies without the need for cell-type composition.

PubMed

Zou, James; Lippert, Christoph; Heckerman, David; Aryee, Martin; Listgarten, Jennifer

2014-03-01

In epigenome-wide association studies, cell-type composition often differs between cases and controls, yielding associations that simply tag cell type rather than reveal fundamental biology. Current solutions require actual or estimated cell-type composition--information not easily obtainable for many samples of interest. We propose a method, FaST-LMM-EWASher, that automatically corrects for cell-type composition without the need for explicit knowledge of it, and then validate our method by comparison with the state-of-the-art approach. Corresponding software is available from http://www.microsoft.com/science/.

GStream: Improving SNP and CNV Coverage on Genome-Wide Association Studies

PubMed Central

Alonso, Arnald; Marsal, Sara; Tortosa, Raül; Canela-Xandri, Oriol; Julià, Antonio

2013-01-01

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method. PMID:23844243

Association of β-defensin copy number and psoriasis in three cohorts of European origin

PubMed Central

Stuart, Philip E; Hüffmeier, Ulrike; Nair, Rajan P; Palla, Raquel; Tejasvi, Trilokraj; Schalkwijk, Joost; Elder, James T; Reis, Andre; Armour, John AL

2012-01-01

A single previous study has demonstrated significant association of psoriasis with copy number of beta-defensin genes, using DNA from psoriasis cases and controls from Nijmegen and Erlangen. In this study we attempted to replicate that finding in larger new cohorts from Erlangen (N = 2017) and Michigan (N = 5412), using improved methods for beta-defensin copy number determination based on the paralog ratio test (PRT), and enhanced methods of analysis and association testing implemented in the CNVtools resource. We demonstrate that the association with psoriasis found in the discovery sample is maintained after applying improved typing and analysis methods (p = 5.5 × 10−4, OR = 1.25). We also find that the association is replicated in 2616 cases and 2526 controls from Michigan, although at reduced significance (p = 0.014), but not in new samples from Erlangen (1396 cases and 621 controls, p = 0.38). Meta-analysis across all cohorts suggests a nominally significant association (p = 6.6 × 10−3/2 × 10−4) with an effect size (OR = 1.081) much lower than found in the discovery study (OR = 1.32). This reduced effect size and significance on replication is consistent with a genuine but weak association. PMID:22739795

On the Importance of Age-Adjustment Methods in Ecological Studies of Social Determinants of Mortality

PubMed Central

Milyo, Jeffrey; Mellor, Jennifer M

2003-01-01

Objective To illustrate the potential sensitivity of ecological associations between mortality and certain socioeconomic factors to different methods of age-adjustment. Data Sources Secondary analysis employing state-level data from several publicly available sources. Crude and age-adjusted mortality rates for 1990 are obtained from the U.S. Centers for Disease Control. The Gini coefficient for family income and percent of persons below the federal poverty line are from the U.S. Bureau of Labor Statistics. Putnam's (2000) Social Capital Index was downloaded from ; the Social Mistrust Index was calculated from responses to the General Social Survey, following the method described in Kawachi et al. (1997). All other covariates are obtained from the U.S. Census Bureau. Study Design We use least squares regression to estimate the effect of several state-level socioeconomic factors on mortality rates. We examine whether these statistical associations are sensitive to the use of alternative methods of accounting for the different age composition of state populations. Following several previous studies, we present results for the case when only mortality rates are age-adjusted. We contrast these results with those obtained from regressions of crude mortality on age variables. Principal Findings Different age-adjustment methods can cause a change in the sign or statistical significance of the association between mortality and various socioeconomic factors. When age variables are included as regressors, we find no significant association between mortality and either income inequality, minority racial concentration, or social capital. Conclusions Ecological associations between certain socioeconomic factors and mortality may be extremely sensitive to different age-adjustment methods. PMID:14727797

Analyzing Association Mapping in Pedigree-Based GWAS Using a Penalized Multitrait Mixed Model

PubMed Central

Liu, Jin; Yang, Can; Shi, Xingjie; Li, Cong; Huang, Jian; Zhao, Hongyu; Ma, Shuangge

2017-01-01

Genome-wide association studies (GWAS) have led to the identification of many genetic variants associated with complex diseases in the past 10 years. Penalization methods, with significant numerical and statistical advantages, have been extensively adopted in analyzing GWAS. This study has been partly motivated by the analysis of Genetic Analysis Workshop (GAW) 18 data, which have two notable characteristics. First, the subjects are from a small number of pedigrees and hence related. Second, for each subject, multiple correlated traits have been measured. Most of the existing penalization methods assume independence between subjects and traits and can be suboptimal. There are a few methods in the literature based on mixed modeling that can accommodate correlations. However, they cannot fully accommodate the two types of correlations while conducting effective marker selection. In this study, we develop a penalized multitrait mixed modeling approach. It accommodates the two different types of correlations and includes several existing methods as special cases. Effective penalization is adopted for marker selection. Simulation demonstrates its satisfactory performance. The GAW 18 data are analyzed using the proposed method. PMID:27247027

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

A case study of three methods used in detecting bridge deck deterioration associated with spalling.

DOT National Transportation Integrated Search

1973-01-01

The three most widely used current methods for detecting deterioration of concrete bridge decks associated with spalling were compared with a visual inspection of the reinforcing steel and to each other in order to determine the degree of agreement a...

Individual and Environmental Characteristics Associated with Cognitive Development in Down Syndrome: A Longitudinal Study

ERIC Educational Resources Information Center

Couzens, Donna; Haynes, Michele; Cuskelly, Monica

2012-01-01

Background: Associations among cognitive development and intrapersonal and environmental characteristics were investigated for 89 longitudinal study participants with Down syndrome to understand developmental patterns associated with cognitive strengths and weaknesses. Materials and Methods: Subtest scores of the Stanford-Binet IV collected…

Narrative Inquiry as Travel Study Method: Affordances and Constraints

ERIC Educational Resources Information Center

Craig, Cheryl J.; Zou, Yali; Poimbeauf, Rita

2014-01-01

This article maps how narrative inquiry--the use of story to study human experience--has been employed as both method and form to capture cross-cultural learning associated with Western doctoral students' travel study to eastern destinations. While others were the first to employ this method in the travel study domain, we are the first to…

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Dental health of 6-year-old children in Alpes Maritimes, France.

PubMed

Joseph, C; Velley, A M; Pierre, A; Bourgeois, D; Muller-Bolla, M

2011-10-01

To describe the dental health status of 6-year-old children using the ICDAS-II advanced method and to evaluate the association between the known caries risk factors with the cavitated caries lesion (WHO basic method) or with both non-cavitated and cavitated caries lesion caries (ICDAS II). In this cross-sectional study, a questionnaire was used to evaluate oral health and dietary habits of children. A clinical examination and a Cario analysis test (Pierre Fabre Oral care) were performed. Logistic regression analyses were used to assess the association between caries and daily tooth-brushing, dietary habits, visible plaque and salivary factors. There were 341 children (52% female and 6.25+/-0.46 years of age) in this study. Using the ICDAS-II advanced method, 39% of the children were caries-free. This proportion was larger (67.2%) using the WHO method. In multivariate models, visible dental plaque and Streptococcus mutans count were associated with caries experience registered as ICDAS-II codes 1-6 or codes 3-6. The absence of daily tooth-brushing with fluoridated toothpaste was associated only with caries experience ICDAS-II codes 3-6. The use of WHO or ICDAS-II method changed the proportion of caries-free children but not the clinical caries risk factors associated with caries experience.

Methods for meta-analysis of multiple traits using GWAS summary statistics.

PubMed

Ray, Debashree; Boehnke, Michael

2018-03-01

Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.

Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example.

PubMed

Guo, How-Ran

2011-10-20

Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example. A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.

Investigation of Pre-Service English Language Teachers' Cognitive Structures about Some Key Concepts in Approaches and Methods in Language Teaching Course through Word Association Test

ERIC Educational Resources Information Center

Ersanli, Ceylan Yangin

2016-01-01

This study aims to map the cognitive structure of pre-service English language (EL) teachers about three key concepts related to approaches and methods in language teaching so as to discover their learning process and misconceptions. The study involves both qualitative and quantitative data. The researcher administrated a Word Association Test…

Detecting associated single-nucleotide polymorphisms on the X chromosome in case control genome-wide association studies.

PubMed

Chen, Zhongxue; Ng, Hon Keung Tony; Li, Jing; Liu, Qingzhong; Huang, Hanwen

2017-04-01

In the past decade, hundreds of genome-wide association studies have been conducted to detect the significant single-nucleotide polymorphisms that are associated with certain diseases. However, most of the data from the X chromosome were not analyzed and only a few significant associated single-nucleotide polymorphisms from the X chromosome have been identified from genome-wide association studies. This is mainly due to the lack of powerful statistical tests. In this paper, we propose a novel statistical approach that combines the information of single-nucleotide polymorphisms on the X chromosome from both males and females in an efficient way. The proposed approach avoids the need of making strong assumptions about the underlying genetic models. Our proposed statistical test is a robust method that only makes the assumption that the risk allele is the same for both females and males if the single-nucleotide polymorphism is associated with the disease for both genders. Through simulation study and a real data application, we show that the proposed procedure is robust and have excellent performance compared to existing methods. We expect that many more associated single-nucleotide polymorphisms on the X chromosome will be identified if the proposed approach is applied to current available genome-wide association studies data.

A robust and efficient statistical method for genetic association studies using case and control samples from multiple cohorts

PubMed Central

2013-01-01

Background The theoretical basis of genome-wide association studies (GWAS) is statistical inference of linkage disequilibrium (LD) between any polymorphic marker and a putative disease locus. Most methods widely implemented for such analyses are vulnerable to several key demographic factors and deliver a poor statistical power for detecting genuine associations and also a high false positive rate. Here, we present a likelihood-based statistical approach that accounts properly for non-random nature of case–control samples in regard of genotypic distribution at the loci in populations under study and confers flexibility to test for genetic association in presence of different confounding factors such as population structure, non-randomness of samples etc. Results We implemented this novel method together with several popular methods in the literature of GWAS, to re-analyze recently published Parkinson’s disease (PD) case–control samples. The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals. In particular, the new method detected 44 significant SNPs within 25 chromosomal regions of size < 1 Mb but only 6 SNPs in two of these regions were previously detected by the trend test based methods. It discovered two SNPs located 1.18 Mb and 0.18 Mb from the PD candidates, FGF20 and PARK8, without invoking false positive risk. Conclusions We developed a novel likelihood-based method which provides adequate estimation of LD and other population model parameters by using case and control samples, the ease in integration of these samples from multiple genetically divergent populations and thus confers statistically robust and powerful analyses of GWAS. On basis of simulation studies and analysis of real datasets, we demonstrated significant improvement of the new method over the non-parametric trend test, which is the most popularly implemented in the literature of GWAS. PMID:23394771

Psychosocial factors at work, long work hours, and obesity: a systematic review.

PubMed

Solovieva, Svetlana; Lallukka, Tea; Virtanen, Marianna; Viikari-Juntura, Eira

2013-05-01

Associations between psychosocial work environment and excess weight have not been systematically addressed. The aim of this systematic review was to summarize the published evidence for the associations of psychosocial factors at work and long work hours with weight-related outcomes . Methods We conducted a search of Medline and Embase for all original articles published up to September 2012 using predefined keywords. After excluding studies with a definite selection bias, we included 39 articles. About 60% of the studies reported at least one positive association between psychosocial factors at work and a weight-related outcome. However, 76% of the tested associations were found to be non-significant. Furthermore, the associations were rather weak. Studies of higher quality tended to observe associations more often than those of lower quality. Positive associations were found more frequently (i) among women versus men, (ii) in cross-sectional versus longitudinal studies, and (iii) for overweight or obesity versus other outcomes. About 70% of the studies reported positive associations between long work hours and weight-related outcomes. All four studies that evaluated the association between working overtime and weight gain (three longitudinal and one cross-sectional), showed a positive association among men and two of them also observed associations among women. We found evidence for weak associations between psychosocial factors at work and excess weight. Associations were observed between long work hours, working overtime, and weight gain, especially among men. More cohort studies among non-obese baseline participants using appropriate analytical methods based on an elaborated hypothetical model are needed.

A comparison of three apolipoprotein B methods and their associations with incident coronary heart disease risk over a 12-year follow-up period: The Multi-Ethnic Study of Atherosclerosis.

PubMed

Cao, Jing; Steffen, Brian T; Guan, Weihua; Remaley, Alan T; McConnell, Joseph P; Palamalai, Vikram; Tsai, Michael Y

Apolipoprotein B-100 (ApoB) is a well-researched lipoprotein marker used in assessing the risk of coronary heart disease (CHD) development. Despite its continued use at the bedside, ApoB methodologies have not been thoroughly compared and may differentially discriminate CHD risk, resulting in patient misclassification. This study compared 3 ApoB immunoassays and their associations with incident CHD risk over a 12-year follow-up period in the Multi-Ethnic Study of Atherosclerosis. Plasma ApoB concentrations were measured in 4679 participants of Multi-Ethnic Study of Atherosclerosis at baseline, using 3 immunoturbidimetric methods. Roche and Kamiya reagent-based methods were analyzed on a Roche modular P analyzer, and the Diazyme reagent-based method was analyzed on a Siemens Dimension analyzer. Cox proportional analysis estimated ApoB-related risk of incident CHD over a median follow-up period of 12.5 years with adjustments for nonlipid CHD risk factors. ApoB concentrations were examined as continuous variables but were also dichotomized based on clinical designations of borderline (100 mg/dL), high (120 mg/dL), and very high ApoB levels (140 mg/dL). Moderate to strong correlations among ApoB methods were observed (r = 0.79-0.98). ApoB concentrations (per standard deviation) were similarly associated with CHD risk and hazard ratio (95% confidence interval): Roche: 1.16 (1.03-1.30); Kamiya: 1.14 (1.02-1.28); and Diazyme: 1.14 (1.02-1.28). Although all 3 ApoB were similarly associated with risk of incident CHD over the study period regardless of the reagent type, the bias between methods suggests that these reagents are not fungible, and assay harmonization may be warranted. Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.

A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data.

PubMed

Agogo, George O; van der Voet, Hilko; van 't Veer, Pieter; Ferrari, Pietro; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek C

2016-10-13

Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

COMPARISON OF SAMPLING METHODS FOR SEMI-VOLATILE ORGANIC CARBON (SVOC) ASSOCIATED WITH PM 2.5

EPA Science Inventory

This study evaluates the influence of denuder sampling methods and filter collection media on the measurement of semi-volatile organic carbon (SVOC) associated with PM2.5. Two types of collection media, charcoal (activated carbon) and XAD, were used both in diffusion denuders ...

COMPARISON OF SAMPLING METHODS FOR SEMI-VOLATILE ORGANIC CARBON ASSOCIATED WITH PM 2.5

EPA Science Inventory

This study evaluates the influence of denuder sampling methods and filter collection media on the measurement of semi-volatile organic carbon (SVOC) associated with PM2.5. Two types of collection media, charcoal (activated carbon) and XAD, were used both in diffusion denuders ...

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

PubMed Central

Han, Buhm; Kang, Hyun Min; Eskin, Eleazar

2009-01-01

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255

Perceived Risks Associated with Contraceptive Method Use among Men and Women in Ibadan and Kaduna, Nigeria.

PubMed

Schwandt, Hilary M; Skinner, Joanna; Hebert, Luciana E; Saad, Abdulmumin

2015-12-01

Research shows that side effects are often the most common reason for contraceptive non-use in Nigeria; however, research to date has not explored the underlying factors that influence risk and benefit perceptions associated with specific contraceptive methods in Nigeria. A qualitative study design using focus group discussions was used to explore social attitudes and beliefs about family planning methods in Ibadan and Kaduna, Nigeria. A total of 26 focus group discussions were held in 2010 with men and women of reproductive age, disaggregated by city, sex, age, marital status, neighborhood socioeconomic status, and--for women only--family planning experience. A discussion guide was used that included specific questions about the perceived risks and benefits associated with the use of six different family planning methods. A thematic content analytic approach guided the analysis. Participants identified a spectrum of risks encompassing perceived threats to health (both real and fictitious) and social concerns, as well as benefits associated with each method. By exploring Nigerian perspectives on the risks and benefits associated with specific family planning methods, programs aiming to increase contraceptive use in Nigeria can be better equipped to highlight recognized benefits, address specific concerns, and work to dispel misperceptions associated with each family planning method.

Genome-wide association tests of inversions with application to psoriasis

PubMed Central

Ma, Jianzhong; Xiong, Momiao; You, Ming; Lozano, Guillermina; Amos, Christopher I.

2014-01-01

Although inversions have occasionally been found to be associated with disease susceptibility through interrupting a gene or its regulatory region, or by increasing the risk for deleterious secondary rearrangements, no association study has been specifically conducted for risks associated with inversions, mainly because existing approaches to detecting and genotyping inversions do not readily scale to a large number of samples. Based on our recently proposed approach to identifying and genotyping inversions using principal components analysis (PCA), we herein develop a method of detecting association between inversions and disease in a genome-wide fashion. Our method uses genotype data for single nucleotide polymorphisms (SNPs), and is thus cost-efficient and computationally fast. For an inversion polymorphism, local PCA around the inversion region is performed to infer the inversion genotypes of all samples. For many inversions, we found that some of the SNPs inside an inversion region are fixed in the two lineages of different orientations and thus can serve as surrogate markers. Our method can be applied to case-control and quantitative trait association studies to identify inversions that may interrupt a gene or the connection between a gene and its regulatory agents. Our method also offers a new venue to identify inversions that are responsible for disease-causing secondary rearrangements. We illustrated our proposed approach to case-control data for psoriasis and identified novel associations with a few inversion polymorphisms. PMID:24623382

DISSCO: direct imputation of summary statistics allowing covariates.

PubMed

Xu, Zheng; Duan, Qing; Yan, Song; Chen, Wei; Li, Mingyao; Lange, Ethan; Li, Yun

2015-08-01

Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates. We analytically show that in the absence of covariates, correlation among association summary statistics is indeed the same as that among the corresponding genotypes, thus serving as a theoretical justification for the recently proposed methods. We continue to prove that in the presence of covariates, correlation among association summary statistics becomes the partial correlation of the corresponding genotypes controlling for covariates. We therefore develop direct imputation of summary statistics allowing covariates (DISSCO). We consider two real-life scenarios where the correlation and partial correlation likely make practical difference: (i) association studies in admixed populations; (ii) association studies in presence of other confounding covariate(s). Application of DISSCO to real datasets under both scenarios shows at least comparable, if not better, performance compared with existing correlation-based methods, particularly for lower frequency variants. For example, DISSCO can reduce the absolute deviation from the truth by 3.9-15.2% for variants with minor allele frequency <5%. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Implicit treatment of diffusion terms in lower-upper algorithms

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Steinthorsson, E.; Chyu, W. J.

1993-01-01

A method is presented which allows diffusion terms to be treated implicitly in the lower-upper (LU) algorithm (which is a commonly used method for solving 'compressible' Euler and Navier-Stokes equations) so that the algorithm's good stability properties will not be impaired. The new method generalizes the concept of LU factorization from that associated with the sign of eigenvalues to that associated with backward- and forward-difference operators without regard to eigenvalues. The method is verified in a turbulent boundary layer study.

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

A Network-Based Kernel Machine Test for the Identification of Risk Pathways in Genome-Wide Association Studies

PubMed Central

Freytag, Saskia; Manitz, Juliane; Schlather, Martin; Kneib, Thomas; Amos, Christopher I.; Risch, Angela; Chang-Claude, Jenny; Heinrich, Joachim; Bickeböller, Heike

2014-01-01

Biological pathways provide rich information and biological context on the genetic causes of complex diseases. The logistic kernel machine test integrates prior knowledge on pathways in order to analyze data from genome-wide association studies (GWAS). Here, the kernel converts genomic information of two individuals to a quantitative value reflecting their genetic similarity. With the selection of the kernel one implicitly chooses a genetic effect model. Like many other pathway methods, none of the available kernels accounts for topological structure of the pathway or gene-gene interaction types. However, evidence indicates that connectivity and neighborhood of genes are crucial in the context of GWAS, because genes associated with a disease often interact. Thus, we propose a novel kernel that incorporates the topology of pathways and information on interactions. Using simulation studies, we demonstrate that the proposed method maintains the type I error correctly and can be more effective in the identification of pathways associated with a disease than non-network-based methods. We apply our approach to genome-wide association case control data on lung cancer and rheumatoid arthritis. We identify some promising new pathways associated with these diseases, which may improve our current understanding of the genetic mechanisms. PMID:24434848

Predictive Criteria to Study the Pathogenesis of Malaria-Associated ALI/ARDS in Mice

PubMed Central

Ortolan, Luana S.; Sercundes, Michelle K.; Debone, Daniela; Hagen, Stefano C. F.; D' Império Lima, Maria Regina; Alvarez, José M.; Marinho, Claudio R. F.; Epiphanio, Sabrina

2014-01-01

Malaria-associated acute lung injury/acute respiratory distress syndrome (ALI/ARDS) often results in morbidity and mortality. Murine models to study malaria-associated ALI/ARDS have been described; we still lack a method of distinguishing which mice will develop ALI/ARDS before death. This work aimed to characterize malaria-associated ALI/ARDS in a murine model and to demonstrate the first method to predict whether mice are suffering from ALI/ARDS before death. DBA/2 mice infected with Plasmodium berghei ANKA developing ALI/ARDS or hyperparasitemia (HP) were compared using histopathology, PaO2 measurement, pulmonary X-ray, breathing capacity, lung permeability, and serum vascular endothelial growth factor (VEGF) levels according to either the day of death or the suggested predictive criteria. We proposed a model to predict malaria-associated ALI/ARDS using breathing patterns (enhanced pause and frequency respiration) and parasitemia as predictive criteria from mice whose cause of death was known to retrospectively diagnose the sacrificed mice as likely to die of ALI/ARDS as early as 7 days after infection. Using this method, we showed increased VEGF levels and increased lung permeability in mice predicted to die of ALI/ARDS. This proposed method for accurately identifying mice suffering from ALI/ARDS before death will enable the use of this model to study the pathogenesis of this disease. PMID:25276057

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

A measure of association for ordered categorical data in population-based studies

PubMed Central

Nelson, Kerrie P; Edwards, Don

2016-01-01

Ordinal classification scales are commonly used to define a patient’s disease status in screening and diagnostic tests such as mammography. Challenges arise in agreement studies when evaluating the association between many raters’ classifications of patients’ disease or health status when an ordered categorical scale is used. In this paper, we describe a population-based approach and chance-corrected measure of association to evaluate the strength of relationship between multiple raters’ ordinal classifications where any number of raters can be accommodated. In contrast to Shrout and Fleiss’ intraclass correlation coefficient, the proposed measure of association is invariant with respect to changes in disease prevalence. We demonstrate how unique characteristics of individual raters can be explored using random effects. Simulation studies are conducted to demonstrate the properties of the proposed method under varying assumptions. The methods are applied to two large-scale agreement studies of breast cancer screening and prostate cancer severity. PMID:27184590

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution.

PubMed

van Iterson, Maarten; van Zwet, Erik W; Heijmans, Bastiaan T

2017-01-27

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.

How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?

PubMed

Veturi, Yogasudha; Ritchie, Marylyn D

2018-01-01

Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each set. Subsequently, we integrated the GWAS summary statistics derived from the testing set with the weights (or eQTLs) derived from the training set to identify expression-trait associations using (a) TWAS-MP (b) TWAS-SMR (c) eQTL-based GWAS, or (d) standalone GWAS. Finally, we examined the power to detect functionally relevant genes using the different approaches under the considered simulation scenarios. In general, we observed great similarities among TWAS-MP methods although the Bayesian methods resulted in improved power in comparison to LASSO and elastic net as the trait architecture grew more complex while training sample sizes and expression heritability remained small. Finally, we observed high power under causality but very low to moderate power under pleiotropy.

Traffic-Related Air Pollution and Childhood Asthma: Recent Advances and Remaining Gaps in the Exposure Assessment Methods.

PubMed

Khreis, Haneen; Nieuwenhuijsen, Mark J

2017-03-17

Background : Current levels of traffic-related air pollution (TRAP) are associated with the development of childhood asthma, although some inconsistencies and heterogeneity remain. An important part of the uncertainty in studies of TRAP-associated asthma originates from uncertainties in the TRAP exposure assessment and assignment methods. In this work, we aim to systematically review the exposure assessment methods used in the epidemiology of TRAP and childhood asthma, highlight recent advances, remaining research gaps and make suggestions for further research. Methods : We systematically reviewed epidemiological studies published up until 8 September 2016 and available in Embase, Ovid MEDLINE (R), and "Transport database". We included studies which examined the association between children's exposure to TRAP metrics and their risk of "asthma" incidence or lifetime prevalence, from birth to the age of 18 years old. Results : We found 42 studies which examined the associations between TRAP and subsequent childhood asthma incidence or lifetime prevalence, published since 1999. Land-use regression modelling was the most commonly used method and nitrogen dioxide (NO₂) was the most commonly used pollutant in the exposure assessments. Most studies estimated TRAP exposure at the residential address and only a few considered the participants' mobility. TRAP exposure was mostly assessed at the birth year and only a few studies considered different and/or multiple exposure time windows. We recommend that further work is needed including e.g., the use of new exposure metrics such as the composition of particulate matter, oxidative potential and ultra-fine particles, improved modelling e.g., by combining different exposure assessment models, including mobility of the participants, and systematically investigating different exposure time windows. Conclusions : Although our previous meta-analysis found statistically significant associations for various TRAP exposures and subsequent childhood asthma, further refinement of the exposure assessment may improve the risk estimates, and shed light on critical exposure time windows, putative agents, underlying mechanisms and drivers of heterogeneity.

Traffic-Related Air Pollution and Childhood Asthma: Recent Advances and Remaining Gaps in the Exposure Assessment Methods

PubMed Central

Khreis, Haneen; Nieuwenhuijsen, Mark J.

2017-01-01

Background: Current levels of traffic-related air pollution (TRAP) are associated with the development of childhood asthma, although some inconsistencies and heterogeneity remain. An important part of the uncertainty in studies of TRAP-associated asthma originates from uncertainties in the TRAP exposure assessment and assignment methods. In this work, we aim to systematically review the exposure assessment methods used in the epidemiology of TRAP and childhood asthma, highlight recent advances, remaining research gaps and make suggestions for further research. Methods: We systematically reviewed epidemiological studies published up until 8 September 2016 and available in Embase, Ovid MEDLINE (R), and “Transport database”. We included studies which examined the association between children’s exposure to TRAP metrics and their risk of “asthma” incidence or lifetime prevalence, from birth to the age of 18 years old. Results: We found 42 studies which examined the associations between TRAP and subsequent childhood asthma incidence or lifetime prevalence, published since 1999. Land-use regression modelling was the most commonly used method and nitrogen dioxide (NO2) was the most commonly used pollutant in the exposure assessments. Most studies estimated TRAP exposure at the residential address and only a few considered the participants’ mobility. TRAP exposure was mostly assessed at the birth year and only a few studies considered different and/or multiple exposure time windows. We recommend that further work is needed including e.g., the use of new exposure metrics such as the composition of particulate matter, oxidative potential and ultra-fine particles, improved modelling e.g., by combining different exposure assessment models, including mobility of the participants, and systematically investigating different exposure time windows. Conclusions: Although our previous meta-analysis found statistically significant associations for various TRAP exposures and subsequent childhood asthma, further refinement of the exposure assessment may improve the risk estimates, and shed light on critical exposure time windows, putative agents, underlying mechanisms and drivers of heterogeneity. PMID:28304360

Genome-Wide Association Study of Intelligence: Additive Effects of Novel Brain Expressed Genes

ERIC Educational Resources Information Center

Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.

2012-01-01

Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…

Exploring the Changes in Students' Understanding of the Scientific Method Using Word Associations

ERIC Educational Resources Information Center

Gulacar, Ozcan; Sinan, Olcay; Bowman, Charles R.; Yildirim, Yetkin

2015-01-01

A study is presented that explores how students' knowledge structures, as related to the scientific method, compare at different student ages. A word association test comprised of ten total stimulus words, among them "experiment," "science fair," and "hypothesis," is used to probe the students' knowledge structures.…

Perceptions and Practices of Technology Student Association Advisors on Implementation Strategies and Teaching Methods

ERIC Educational Resources Information Center

Haynie, W. J.; DeLuca, V. W.; Matthews, B.

2005-01-01

A study conducted in 1989 surveyed Technology Student Association (TSA) advisors to find their perceptions concerning characteristics of technology education programs with a TSA component and the relationship between participation in co-curricular organizations and the teaching methods used by TSA technology teachers (DeLuca & Haynie, 1991).…

Contraceptive method at first sexual intercourse and subsequent pregnancy risk: findings from a secondary analysis of 16-year-old girls from the RIPPLE and SHARE studies.

PubMed

Parkes, Alison; Wight, Daniel; Henderson, Marion; Stephenson, Judith; Strange, Vicki

2009-01-01

Existing failure rate studies indicate that typical use of oral contraception (OC) results in fewer unplanned pregnancies than condom use, even among teenagers. However, comparative data on pregnancy risk associated with different contraceptive methods are lacking for younger teenagers starting their first sexual relationship. This study examined associations between contraceptive method at first intercourse and subsequent pregnancy in 16-year-old girls. Six thousand three hundred forty-eight female pupils from 51 secondary schools completed a questionnaire at mean age 16 years; 2,501 girls reported sexual intercourse. Logistic regression (N = 1952) was used to model the association of contraceptive method at first intercourse with pregnancy. At first intercourse (median age 15 years) 54% reported using condoms only, 11% dual OC and condoms, 4% OC only, 4% emergency contraception, and 21% no effective method. Method used was associated with a similar method at a most recent intercourse. One in 10 girls reported a pregnancy. When compared to use of condoms only, greater pregnancy risk was found with no effective method (odds ratio [OR] 2.97, 95% confidence interval [CI] 2.12-4.15) or OC only (OR 2.44, 95% CI 1.29-4.60). Pregnancy risk for dual use and emergency contraception did not differ from that for condoms only. Both significant effects were partially attenuated by adjusting for user characteristics and sexual activity. Young teenagers may use OC less efficiently than condoms for pregnancy prevention. The characteristics of those using OC-only confirm vulnerability to unintended pregnancy, and suggest that alternative contraceptive strategies should be considered for these young women.

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

USGS Publications Warehouse

Williams, C.J.; Heglund, P.J.

2009-01-01

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

An improved stereologic method for three-dimensional estimation of particle size distribution from observations in two dimensions and its application.

PubMed

Xu, Yi-Hua; Pitot, Henry C

2003-09-01

Single enzyme-altered hepatocytes; altered hepatic foci (AHF); and nodular lesions have been implicated, respectively in the processes of initiation, promotion, and progression in rodent hepatocarcinogenesis. Qualitative and quantitative analyses of such lesions have been utilized both to identify and to determine the potency of initiating, promoting, and progressor agents in rodent liver. Of a number of possible parameters determined in the study of such lesions, estimation of the number of foci or nodules in the liver is very important. The method of Saltykov has been used for estimating the number of AHF in rat liver. However, in practice, the Saltykov calculation has at least two weak points: (a) the size class range is limited to 12, which in many instances is too narrow to cover the range of AHF data obtained; and (b) under some conditions, the Saltykov equation generates negative values in several size classes, an obvious impossibility in the real world. In order to overcome these limitations in the Saltykov calculations, a study of the particle size distribution in a wide-range, polydispersed sphere system was performed. A stereologic method, termed the 25F Association method, was developed from this study. This method offers 25 association factors that are derived from the frequency of different-sized transections obtained from transecting a spherical particle, thus expanding the size class range to be analyzed up to 25, which is sufficiently wide to encompass all rat AHF found in most cases. This method exhibits greater flexibility, which allows adjustments to be made within the calculation process when NA((k,k)), the net number of transections from the same size spheres, was found to be a negative value, which is not possible in real situations. The reliability of the 25F Association method was tested thoroughly by computer simulation in both monodispersed and polydispersed sphere systems. The test results were compared with the original Saltykov method. We found that the 25F Association method yielded a better estimate of the total number of spheres in the three-dimensional tissue sample as well as the detailed size distribution information. Although the 25F Association method was derived from the study of a polydispersed sphere system, it can be used for continuous size distribution sphere systems. Application of this method to the estimation of parameters of preneoplastic foci in rodent liver is presented as an example of its utility. An application software program, 3D_estimation.exe, which uses the 25F Association method to estimate the number of AHF in rodent liver, has been developed and is now available at the website of this laboratory.

The admixture maximum likelihood test to test for association between rare variants and disease phenotypes.

PubMed

Tyrer, Jonathan P; Guo, Qi; Easton, Douglas F; Pharoah, Paul D P

2013-06-06

The development of genotyping arrays containing hundreds of thousands of rare variants across the genome and advances in high-throughput sequencing technologies have made feasible empirical genetic association studies to search for rare disease susceptibility alleles. As single variant testing is underpowered to detect associations, the development of statistical methods to combine analysis across variants - so-called "burden tests" - is an area of active research interest. We previously developed a method, the admixture maximum likelihood test, to test multiple, common variants for association with a trait of interest. We have extended this method, called the rare admixture maximum likelihood test (RAML), for the analysis of rare variants. In this paper we compare the performance of RAML with six other burden tests designed to test for association of rare variants. We used simulation testing over a range of scenarios to test the power of RAML compared to the other rare variant association testing methods. These scenarios modelled differences in effect variability, the average direction of effect and the proportion of associated variants. We evaluated the power for all the different scenarios. RAML tended to have the greatest power for most scenarios where the proportion of associated variants was small, whereas SKAT-O performed a little better for the scenarios with a higher proportion of associated variants. The RAML method makes no assumptions about the proportion of variants that are associated with the phenotype of interest or the magnitude and direction of their effect. The method is flexible and can be applied to both dichotomous and quantitative traits and allows for the inclusion of covariates in the underlying regression model. The RAML method performed well compared to the other methods over a wide range of scenarios. Generally power was moderate in most of the scenarios, underlying the need for large sample sizes in any form of association testing.

Accounting for genetic and environmental confounds in associations between parent and child characteristics: a systematic review of children-of-twins studies.

PubMed

McAdams, Tom A; Neiderhiser, Jenae M; Rijsdijk, Fruhling V; Narusyte, Jurgita; Lichtenstein, Paul; Eley, Thalia C

2014-07-01

Parental psychopathology, parenting style, and the quality of intrafamilial relationships are all associated with child mental health outcomes. However, most research can say little about the causal pathways underlying these associations. This is because most studies are not genetically informative and are therefore not able to account for the possibility that associations are confounded by gene-environment correlation. That is, biological parents not only provide a rearing environment for their child, but also contribute 50% of their genes. Any associations between parental phenotype and child phenotype are therefore potentially confounded. One technique for disentangling genetic from environmental effects is the children-of-twins (COT) method. This involves using data sets comprising twin parents and their children to distinguish genetic from environmental associations between parent and child phenotypes. The COT technique has grown in popularity in the last decade, and we predict that this surge in popularity will continue. In the present article we explain the COT method for those unfamiliar with its use. We present the logic underlying this approach, discuss strengths and weaknesses, and highlight important methodological considerations for researchers interested in the COT method. We also cover variations on basic COT approaches, including the extended-COT method, capable of distinguishing forms of gene-environment correlation. We then present a systematic review of all the behavioral COT studies published to date. These studies cover such diverse phenotypes as psychosis, substance abuse, internalizing, externalizing, parenting, and marital difficulties. In reviewing this literature, we highlight past applications, identify emergent patterns, and suggest avenues for future research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Method and reporting quality in health professions education research: a systematic review.

PubMed

Cook, David A; Levinson, Anthony J; Garside, Sarah

2011-03-01

Studies evaluating reporting quality in health professions education (HPE) research have demonstrated deficiencies, but none have used comprehensive reporting standards. Additionally, the relationship between study methods and effect size (ES) in HPE research is unknown. This review aimed to evaluate, in a sample of experimental studies of Internet-based instruction, the quality of reporting, the relationship between reporting and methodological quality, and associations between ES and study methods. We conducted a systematic search of databases including MEDLINE, Scopus, CINAHL, EMBASE and ERIC, for articles published during 1990-2008. Studies (in any language) quantifying the effect of Internet-based instruction in HPE compared with no intervention or other instruction were included. Working independently and in duplicate, we coded reporting quality using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement, and coded study methods using a modified Newcastle-Ottawa Scale (m-NOS), the Medical Education Research Study Quality Instrument (MERSQI), and the Best Evidence in Medical Education (BEME) global scale. For reporting quality, articles scored a mean±standard deviation (SD) of 51±25% of STROBE elements for the Introduction, 58±20% for the Methods, 50±18% for the Results and 41±26% for the Discussion sections. We found positive associations (all p<0.0001) between reporting quality and MERSQI (ρ=0.64), m-NOS (ρ=0.57) and BEME (ρ=0.58) scores. We explored associations between study methods and knowledge ES by subtracting each study's ES from the pooled ES for studies using that method and comparing these differences between subgroups. Effect sizes in single-group pretest/post-test studies differed from the pooled estimate more than ESs in two-group studies (p=0.013). No difference was found between other study methods (yes/no: representative sample, comparison group from same community, randomised, allocation concealed, participants blinded, assessor blinded, objective assessment, high follow-up). Information is missing from all sections of reports of HPE experiments. Single-group pre-/post-test studies may overestimate ES compared with two-group designs. Other methodological variations did not bias study results in this sample. © Blackwell Publishing Ltd 2011.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics.

PubMed

Pare, Guillaume; Mao, Shihong; Deng, Wei Q

2016-06-08

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

PubMed Central

Pare, Guillaume; Mao, Shihong; Deng, Wei Q.

2016-01-01

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519

Factors Associated with Objectively Measured Physical Activity and Sedentary Time of 5-6-Year-Old Children in the STEPS Study

ERIC Educational Resources Information Center

Matarma, Tanja; Tammelin, Tuija; Kulmala, Janne; Koski, Pasi; Hurme, Saija; Lagström, Hanna

2017-01-01

Background: The factors associated with preschool-aged children's physical activity (PA) remains unclear. The aim of this cross-sectional study was to examine how different factors were associated with preschool-aged children's objectively measured PA and sedentary time. Methods: The study population was 5-6-year-old children (n = 140) and their…

Paradoxical ventilator associated pneumonia incidences among selective digestive decontamination studies versus other studies of mechanically ventilated patients: benchmarking the evidence base

PubMed Central

2011-01-01

Introduction Selective digestive decontamination (SDD) appears to have a more compelling evidence base than non-antimicrobial methods for the prevention of ventilator associated pneumonia (VAP). However, the striking variability in ventilator associated pneumonia-incidence proportion (VAP-IP) among the SDD studies remains unexplained and a postulated contextual effect remains untested for. Methods Nine reviews were used to source 45 observational (benchmark) groups and 137 component (control and intervention) groups of studies of SDD and studies of three non-antimicrobial methods of VAP prevention. The logit VAP-IP data were summarized by meta-analysis using random effects methods and the associated heterogeneity (tau2) was measured. As group level predictors of logit VAP-IP, the mode of VAP diagnosis, proportion of trauma admissions, the proportion receiving prolonged ventilation and the intervention method under study were examined in meta-regression models containing the benchmark groups together with either the control (models 1 to 3) or intervention (models 4 to 6) groups of the prevention studies. Results The VAP-IP benchmark derived here is 22.1% (95% confidence interval; 95% CI; 19.2 to 25.5; tau2 0.34) whereas the mean VAP-IP of control groups from studies of SDD and of non-antimicrobial methods, is 35.7 (29.7 to 41.8; tau2 0.63) versus 20.4 (17.2 to 24.0; tau2 0.41), respectively (P < 0.001). The disparity between the benchmark groups and the control groups of the SDD studies, which was most apparent for the highest quality studies, could not be explained in the meta-regression models after adjusting for various group level factors. The mean VAP-IP (95% CI) of intervention groups is 16.0 (12.6 to 20.3; tau2 0.59) and 17.1 (14.2 to 20.3; tau2 0.35) for SDD studies versus studies of non-antimicrobial methods, respectively. Conclusions The VAP-IP among the intervention groups within the SDD evidence base is less variable and more similar to the benchmark than among the control groups. These paradoxical observations cannot readily be explained. The interpretation of the SDD evidence base cannot proceed without further consideration of this contextual effect. PMID:21214897

A Systematic Comparison of Linear Regression-Based Statistical Methods to Assess Exposome-Health Associations.

PubMed

Agier, Lydiane; Portengen, Lützen; Chadeau-Hyam, Marc; Basagaña, Xavier; Giorgis-Allemand, Lise; Siroux, Valérie; Robinson, Oliver; Vlaanderen, Jelle; González, Juan R; Nieuwenhuijsen, Mark J; Vineis, Paolo; Vrijheid, Martine; Slama, Rémy; Vermeulen, Roel

2016-12-01

The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.

The Views and Suggestions of Social Studies Teachers about the Implementation of Drama Method

ERIC Educational Resources Information Center

Celikkaya, Tekin

2014-01-01

Associating knowledge with daily life leads to permanent knowledge, which increases students' success in school. Drama is viewed to be one of the most effective methods that serves a purpose, and many researchers have determined that this method must be included at all levels of education. There are not much studies on social studies teachers'…

Implementation in the midst of complexity: Using ethnography to study health care-associated infection prevention and control.

PubMed

Knobloch, Mary Jo; Thomas, Kevin V; Patterson, Erin; Zimbric, Michele L; Musuuza, Jackson; Safdar, Nasia

2017-10-01

Contextual factors associated with health care settings make reducing health care-associated infections (HAIs) a complex task. The aim of this article is to highlight how ethnography can assist in understanding contextual factors that support or hinder the implementation of evidence-based practices for reducing HAIs. We conducted a review of ethnographic studies specifically related to HAI prevention and control in the last 5 years (2012-2017). Twelve studies specific to HAIs and ethnographic methods were found. Researchers used various methods with video-reflexive sessions used in 6 of the 12 studies. Ethnography was used to understand variation in data reporting, identify barriers to adherence, explore patient perceptions of isolation practices and highlight the influence of physical design on infection prevention practices. The term ethnography was used to describe varied research methods. Most studies were conducted outside the United States, and authors indicate insights gained using ethnographic methods (whether observations, interviews, or reflexive video recording) as beneficial to unraveling the complexities of HAI prevention. Ethnography is well-suited for HAI prevention, especially video-reflexive ethnography, for activating patients and clinicians in infection control work. In this era of increasing pressure to reduce HAIs within complex work systems, ethnographic methods can promote understanding of contextual factors and may expedite translation evidence to practice. Published by Elsevier Inc.

Avoid lost discoveries, because of violations of standard assumptions, by using modern robust statistical methods.

PubMed

Wilcox, Rand; Carlson, Mike; Azen, Stan; Clark, Florence

2013-03-01

Recently, there have been major advances in statistical techniques for assessing central tendency and measures of association. The practical utility of modern methods has been documented extensively in the statistics literature, but they remain underused and relatively unknown in clinical trials. Our objective was to address this issue. STUDY DESIGN AND PURPOSE: The first purpose was to review common problems associated with standard methodologies (low power, lack of control over type I errors, and incorrect assessments of the strength of the association). The second purpose was to summarize some modern methods that can be used to circumvent such problems. The third purpose was to illustrate the practical utility of modern robust methods using data from the Well Elderly 2 randomized controlled trial. In multiple instances, robust methods uncovered differences among groups and associations among variables that were not detected by classic techniques. In particular, the results demonstrated that details of the nature and strength of the association were sometimes overlooked when using ordinary least squares regression and Pearson correlation. Modern robust methods can make a practical difference in detecting and describing differences between groups and associations between variables. Such procedures should be applied more frequently when analyzing trial-based data. Copyright © 2013 Elsevier Inc. All rights reserved.

Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application.

PubMed

Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Chen, Zhao; Halonen, Marilyn; Guerra, Stefano

2016-11-14

The study of circulating biomarkers and their association with disease outcomes has become progressively complex due to advances in the measurement of these biomarkers through multiplex technologies. The Least Absolute Shrinkage and Selection Operator (LASSO) is a data analysis method that may be utilized for biomarker selection in these high dimensional data. However, it is unclear which LASSO-type method is preferable when considering data scenarios that may be present in serum biomarker research, such as high correlation between biomarkers, weak associations with the outcome, and sparse number of true signals. The goal of this study was to compare the LASSO to five LASSO-type methods given these scenarios. A simulation study was performed to compare the LASSO, Adaptive LASSO, Elastic Net, Iterated LASSO, Bootstrap-Enhanced LASSO, and Weighted Fusion for the binary logistic regression model. The simulation study was designed to reflect the data structure of the population-based Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD), specifically the sample size (N = 1000 for total population, 500 for sub-analyses), correlation of biomarkers (0.20, 0.50, 0.80), prevalence of overweight (40%) and obese (12%) outcomes, and the association of outcomes with standardized serum biomarker concentrations (log-odds ratio = 0.05-1.75). Each LASSO-type method was then applied to the TESAOD data of 306 overweight, 66 obese, and 463 normal-weight subjects with a panel of 86 serum biomarkers. Based on the simulation study, no method had an overall superior performance. The Weighted Fusion correctly identified more true signals, but incorrectly included more noise variables. The LASSO and Elastic Net correctly identified many true signals and excluded more noise variables. In the application study, biomarkers of overweight and obesity selected by all methods were Adiponectin, Apolipoprotein H, Calcitonin, CD14, Complement 3, C-reactive protein, Ferritin, Growth Hormone, Immunoglobulin M, Interleukin-18, Leptin, Monocyte Chemotactic Protein-1, Myoglobin, Sex Hormone Binding Globulin, Surfactant Protein D, and YKL-40. For the data scenarios examined, choice of optimal LASSO-type method was data structure dependent and should be guided by the research objective. The LASSO-type methods identified biomarkers that have known associations with obesity and obesity related conditions.

A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake

PubMed Central

Agogo, George O.

2017-01-01

Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR). The 24HR intakes are used as response in regression calibration to adjust for bias in the association. For foods not consumed daily, 24HR-reported intakes are usually characterized by excess zeroes, right skewness, and heteroscedasticity posing serious challenge in regression calibration modeling. We proposed a zero-augmented calibration model to adjust for measurement error in reported intake, while handling excess zeroes, skewness, and heteroscedasticity simultaneously without transforming 24HR intake values. We compared the proposed calibration method with the standard method and with methods that ignore measurement error by estimating long-term intake with 24HR and FFQ-reported intakes. The comparison was done in real and simulated datasets. With the 24HR, the mean increase in mercury level per ounce fish intake was about 0.4; with the FFQ intake, the increase was about 1.2. With both calibration methods, the mean increase was about 2.0. Similar trend was observed in the simulation study. In conclusion, the proposed calibration method performs at least as good as the standard method. PMID:27704599

Pilates, Mindfulness and Somatic Education.

PubMed

Caldwell, Karen; Adams, Marianne; Quin, Rebecca; Harrison, Mandy; Greeson, Jeffrey

2013-12-01

The Pilates Method is a form of somatic education with the potential to cultivate mindfulness - a mental quality associated with overall well-being. However, controlled studies are needed to determine whether changes in mindfulness are specific to the Pilates Method or also result from other forms of exercise. This quasi-experimental study compared Pilates Method mat classes and recreational exercise classes on measures of mindfulness and well-being at the beginning, middle and end of a 15 week semester. Total mindfulness scores increased overall for the Pilates Method group but not for the exercise control group, and these increases were directly related to end of semester ratings of self-regulatory self-efficacy, perceived stress and mood. Findings suggest that the Pilates Method specifically enhances mindfulness, and these increases are associated with other measures of wellness. The changes in mindfulness identified in this study support the role of the Pilates Method in the mental well-being of its practitioners and its potential to support dancers' overall well-being.

Pilates, Mindfulness and Somatic Education

PubMed Central

Caldwell, Karen; Quin, Rebecca; Harrison, Mandy; Greeson, Jeffrey

2014-01-01

The Pilates Method is a form of somatic education with the potential to cultivate mindfulness – a mental quality associated with overall well-being. However, controlled studies are needed to determine whether changes in mindfulness are specific to the Pilates Method or also result from other forms of exercise. This quasi-experimental study compared Pilates Method mat classes and recreational exercise classes on measures of mindfulness and well-being at the beginning, middle and end of a 15 week semester. Total mindfulness scores increased overall for the Pilates Method group but not for the exercise control group, and these increases were directly related to end of semester ratings of self-regulatory self-efficacy, perceived stress and mood. Findings suggest that the Pilates Method specifically enhances mindfulness, and these increases are associated with other measures of wellness. The changes in mindfulness identified in this study support the role of the Pilates Method in the mental well-being of its practitioners and its potential to support dancers’ overall well-being. PMID:25328542

Association analysis of multiple traits by an approach of combining P values.

PubMed

Chen, Lili; Wang, Yong; Zhou, Yajing

2018-03-01

Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.

Behavioral Inhibition and Risk for Developing Social Anxiety Disorder: A Meta-Analytic Study

ERIC Educational Resources Information Center

Clauss, Jacqueline A.; Blackford, Jennifer Urbano

2012-01-01

Objective: Behavioral inhibition (BI) has been associated with increased risk for developing social anxiety disorder (SAD); however, the degree of risk associated with BI has yet to be systematically examined and quantified. The goal of the present study was to quantify the association between childhood BI and risk for developing SAD. Method: A…

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

Effects of an Interteaching Probe on Learning and Generalization of American Psychological Association (APA) Style

ERIC Educational Resources Information Center

Slezak, Jonathan M.; Faas, Caitlin

2017-01-01

This study implemented the components of interteaching as a probe to teach American Psychological Association (APA) Style to undergraduate university students in a psychology research methods and statistics course. The interteaching method was compared to the traditional lecture-based approach between two sections of the course with the same…

Self-Esteem and Method Effects Associated with Negatively Worded Items: Investigating Factorial Invariance by Sex

ERIC Educational Resources Information Center

DiStefano, Christine; Motl, Robert W.

2009-01-01

The Rosenberg Self-Esteem scale (RSE) has been widely used in examinations of sex differences in global self-esteem. However, previous examinations of sex differences have not accounted for method effects associated with item wording, which have consistently been reported by researchers using the RSE. Accordingly, this study examined the…

Calcium stone lithoptysis in promary ciliary dyskinesia

EPA Science Inventory

BACKGROUND: An association between lithoptysis and primary ciliary dyskinesia (PCD) has not been previously reported. However, reports of lithoptysis from 2 older patients (>60 yr) prompted a study of this association. METHODS: We performed a prospective study of all PCD patients...

Access to parks and physical activity: an eight country comparison.

PubMed

Schipperijn, Jasper; Cerin, Ester; Adams, Marc A; Reis, Rodrigo; Smith, Graham; Cain, Kelli; Christiansen, Lars B; van Dyck, Delfien; Gidlow, Christopher; Frank, Lawrence D; Mitáš, Josef; Pratt, Michael; Salvo, Deborah; Schofield, Grant; Sallis, James F

2017-10-01

Several systematic reviews have reported mixed associations between access to parks and physical activity, and suggest that this is due to inconsistencies in the study methods or differences across countries. An international study using consistent methods is needed to investigate the association between access to parks and physical activity. The International Physical Activity and Environment Network (IPEN) Adult Study is a multi-country cross-sectional study using a common design and consistent methods. Accelerometer, survey and Geographic Information Systems (GIS) data for 6,181 participants from 12 cities in 8 countries (Belgium, Brazil, Czech Republic, Denmark, Mexico, New Zealand, UK, USA) were used to estimate the strength and shape of associations of 11 measures of park access (1 perceived and 10 GIS-based measures) with accelerometer-based moderate-to-vigorous physical activity (MVPA) and four types of self-reported leisure-time physical activity. Associations were estimated using generalized additive mixed models. More parks within 1 km from participants' homes were associated with greater leisure-time physical activity and accelerometer-measured MVPA. Respondents who lived in the neighborhoods with the most parks did on average 24 minutes more MVPA per week than those living in the neighborhoods with the lowest number of parks. Perceived proximity to a park was positively associated with multiple leisure-time physical activity outcomes. Associations were homogeneous across all cities studied. Living in neighborhoods with many parks could contribute with up to 1/6 of the recommended weekly Having multiple parks nearby was the strongest positive correlate of PA. To increase comparability and validity of park access measures, we recommend that researchers, planners and policy makers use the number of parks within 1 km travel distance of homes as an objective indicator for park access in relation to physical activity.

Safety assessment in pediatric studies.

PubMed

Koren, Gideon; Elzagallaai, Abdelbasset; Etwel, Fatma

2011-01-01

It typically takes many years before an association of a drug with a rare, serious adverse reaction is established. As related to pediatric drug use, evidence is even more erratic, as most drugs are used off labels. To enhance child safety, there is an urgent need to develop robust and rapid methods to identify such associations in as timely a manner as possible. In this chapter, several novel methods, both clinically based pharmacoepidemiological approaches and laboratory-based methods, are described.

A Method for Inferring an Individual’s Genetic Ancestry and Degree of Admixture Associated with Six Major Continental Populations

PubMed Central

Libiger, Ondrej; Schork, Nicholas J.

2013-01-01

The determination of the ancestry and genetic backgrounds of the subjects in genetic and general epidemiology studies is a crucial component in the analysis of relevant outcomes or associations. Although there are many methods for differentiating ancestral subgroups among individuals based on genetic markers only a few of these methods provide actual estimates of the fraction of an individual’s genome that is likely to be associated with different ancestral populations. We propose a method for assigning ancestry that works in stages to refine estimates of ancestral population contributions to individual genomes. The method leverages genotype data in the public domain obtained from individuals with known ancestries. Although we showcase the method in the assessment of ancestral genome proportions leveraging largely continental populations, the strategy can be used for assessing within-continent or more subtle ancestral origins with the appropriate data. PMID:23335941

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Implicit Associations with Popularity in Early Adolescence: An Approach-Avoidance Analysis

ERIC Educational Resources Information Center

Lansu, Tessa A. M.; Cillessen, Antonius H. N.; Karremans, Johan C.

2012-01-01

This study examined 241 early adolescents' implicit and explicit associations with popularity. The peer status and gender of both the targets and the perceivers were considered. Explicit associations with popularity were assessed with sociometric methods. Implicit associations with popularity were assessed with an approach-avoidance task (AAT).…

Using molecular functional networks to manifest connections between obesity and obesity-related diseases

PubMed Central

Yang, Jialiang; Qiu, Jing; Wang, Kejing; Zhu, Lijuan; Fan, Jingjing; Zheng, Deyin; Meng, Xiaodi; Yang, Jiasheng; Peng, Lihong; Fu, Yu; Zhang, Dahan; Peng, Shouneng; Huang, Haiyun; Zhang, Yi

2017-01-01

Obesity is a primary risk factor for many diseases such as certain cancers. In this study, we have developed three algorithms including a random-walk based method OBNet, a shortest-path based method OBsp and a direct-overlap method OBoverlap, to reveal obesity-disease connections at protein-interaction subnetworks corresponding to thousands of biological functions and pathways. Through literature mining, we also curated an obesity-associated disease list, by which we compared the methods. As a result, OBNet outperforms other two methods. OBNet can predict whether a disease is obesity-related based on its associated genes. Meanwhile, OBNet identifies extensive connections between obesity genes and genes associated with a few diseases at various functional modules and pathways. Using breast cancer and Type 2 diabetes as two examples, OBNet identifies meaningful genes that may play key roles in connecting obesity and the two diseases. For example, TGFB1 and VEGFA are inferred to be the top two key genes mediating obesity-breast cancer connection in modules associated with brain development. Finally, the top modules identified by OBNet in breast cancer significantly overlap with modules identified from TCGA breast cancer gene expression study, revealing the power of OBNet in identifying biological processes involved in the disease. PMID:29156709

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.

PubMed

Buu, Anne; Williams, L Keoki; Yang, James J

2018-03-01

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

Argon thermochronology of mineral deposits; a review of analytical methods, formulations, and selected applications

USGS Publications Warehouse

Snee, Lawrence W.

2002-01-01

40Ar/39Ar geochronology is an experimentally robust and versatile method for constraining time and temperature in geologic processes. The argon method is the most broadly applied in mineral-deposit studies. Standard analytical methods and formulations exist, making the fundamentals of the method well defined. A variety of graphical representations exist for evaluating argon data. A broad range of minerals found in mineral deposits, alteration zones, and host rocks commonly is analyzed to provide age, temporal duration, and thermal conditions for mineralization events and processes. All are discussed in this report. The usefulness of and evolution of the applicability of the method are demonstrated in studies of the Panasqueira, Portugal, tin-tungsten deposit; the Cornubian batholith and associated mineral deposits, southwest England; the Red Mountain intrusive system and associated Urad-Henderson molybdenum deposits; and the Eastern Goldfields Province, Western Australia.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

PubMed

Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen

2018-03-01

Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.

Identifying disease polymorphisms from case-control genetic association data.

PubMed

Park, L

2010-12-01

In case-control association studies, it is typical to observe several associated polymorphisms in a gene region. Often the most significantly associated polymorphism is considered to be the disease polymorphism; however, it is not clear whether it is the disease polymorphism or there is more than one disease polymorphism in the gene region. Currently, there is no method that can handle these problems based on the linkage disequilibrium (LD) relationship between polymorphisms. To distinguish real disease polymorphisms from markers in LD, a method that can detect disease polymorphisms in a gene region has been developed. Relying on the LD between polymorphisms in controls, the proposed method utilizes model-based likelihood ratio tests to find disease polymorphisms. This method shows reliable Type I and Type II error rates when sample sizes are large enough, and works better with re-sequenced data. Applying this method to fine mapping using re-sequencing or dense genotyping data would provide important information regarding the genetic architecture of complex traits.

Motivation factors for suicidal behavior and their clinical relevance in admitted psychiatric patients.

PubMed

Hayashi, Naoki; Igarashi, Miyabi; Imai, Atsushi; Yoshizawa, Yuka; Asamura, Kaori; Ishikawa, Yoichi; Tokunaga, Taro; Ishimoto, Kayo; Tatebayashi, Yoshitaka; Harima, Hirohiko; Kumagai, Naoki; Ishii, Hidetoki; Okazaki, Yuji

2017-01-01

Suicidal behavior (SB) is a major, worldwide health concern. To date there is limited understanding of the associated motivational aspects which accompany this self-initiated conduct. To develop a method for identifying motivational features associated with SB by studying admitted psychiatric patients, and to examine their clinical relevance. By performing a factor analytic study using data obtained from a patient sample exhibiting high suicidality and a variety of SB methods, Motivations for SB Scale (MSBS) was constructed to measure the features. Data included assessments of DSM-IV psychiatric and personality disorders, suicide intent, depressive symptomatology, overt aggression, recent life events (RLEs) and methods of SB, collated from structured interviews. Association of identified features with clinical variables was examined by correlation analyses and MANCOVA. Factor analyses elicited a 4-factor solution composed of Interpersonal-testing (IT), Interpersonal-change (IC), Self-renunciation (SR) and Self-sustenance (SS). These factors were classified according to two distinctions, namely interpersonal vs. intra-personal directedness, and the level of assumed influence by SB or the relationship to prevailing emotions. Analyses revealed meaningful links between patient features and clinical variables. Interpersonal-motivations (IT and IC) were associated with overt aggression, low suicidality and RLE discord or conflict, while SR was associated with depression, high suicidality and RLE separation or death. Borderline personality disorder showed association with IC and SS. When self-strangulation was set as a reference SB method, self-cutting and overdose-taking were linked to IT and SS, respectively. The factors extracted in this study largely corresponded to factors from previous studies, implying that they may be useful in a wider clinical context. The association of these features with SB-related factors suggests that they constitute an integral part of the process leading to SB. These results provide a base for further research into clinical strategies for patient management and therapy.

Prioritizing individual genetic variants after kernel machine testing using variable selection.

PubMed

He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

2016-12-01

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

A unified partial likelihood approach for X-chromosome association on time-to-event outcomes.

PubMed

Xu, Wei; Hao, Meiling

2018-02-01

The expression of X-chromosome undergoes three possible biological processes: X-chromosome inactivation (XCI), escape of the X-chromosome inactivation (XCI-E), and skewed X-chromosome inactivation (XCI-S). Although these expressions are included in various predesigned genetic variation chip platforms, the X-chromosome has generally been excluded from the majority of genome-wide association studies analyses; this is most likely due to the lack of a standardized method in handling X-chromosomal genotype data. To analyze the X-linked genetic association for time-to-event outcomes with the actual process unknown, we propose a unified approach of maximizing the partial likelihood over all of the potential biological processes. The proposed method can be used to infer the true biological process and derive unbiased estimates of the genetic association parameters. A partial likelihood ratio test statistic that has been proved asymptotically chi-square distributed can be used to assess the X-chromosome genetic association. Furthermore, if the X-chromosome expression pertains to the XCI-S process, we can infer the correct skewed direction and magnitude of inactivation, which can elucidate significant findings regarding the genetic mechanism. A population-level model and a more general subject-level model have been developed to model the XCI-S process. Finite sample performance of this novel method is examined via extensive simulation studies. An application is illustrated with implementation of the method on a cancer genetic study with survival outcome. © 2017 WILEY PERIODICALS, INC.

Fine-scale patterns of population stratification confound rare variant association tests.

PubMed

O'Connor, Timothy D; Kiezun, Adam; Bamshad, Michael; Rich, Stephen S; Smith, Joshua D; Turner, Emily; Leal, Suzanne M; Akey, Joshua M

2013-01-01

Advances in next-generation sequencing technology have enabled systematic exploration of the contribution of rare variation to Mendelian and complex diseases. Although it is well known that population stratification can generate spurious associations with common alleles, its impact on rare variant association methods remains poorly understood. Here, we performed exhaustive coalescent simulations with demographic parameters calibrated from exome sequence data to evaluate the performance of nine rare variant association methods in the presence of fine-scale population structure. We find that all methods have an inflated spurious association rate for parameter values that are consistent with levels of differentiation typical of European populations. For example, at a nominal significance level of 5%, some test statistics have a spurious association rate as high as 40%. Finally, we empirically assess the impact of population stratification in a large data set of 4,298 European American exomes. Our results have important implications for the design, analysis, and interpretation of rare variant genome-wide association studies.

Evaluation of the Association between Persistent Organic ...

EPA Pesticide Factsheets

Background: Diabetes is a major threat to public health in the United States and worldwide. Understanding the role of environmental chemicals in the development or progression of diabetes is an emerging issue in environmental health.Objective: We assessed the epidemiologic literature for evidence of associations between persistent organic pollutants (POPs) and type 2 diabetes.Methods: Using a PubMed search and reference lists from relevant studies or review articles, we identified 72 epidemiological studies that investigated associations of persistent organic pollutants (POPs) with diabetes. We evaluated these studies for consistency, strengths and weaknesses of study design (including power and statistical methods), clinical diagnosis, exposure assessment, study population characteristics, and identification of data gaps and areas for future research.Conclusions: Heterogeneity of the studies precluded conducting a meta-analysis, but the overall evidence is sufficient for a positive association of some organochlorine POPs with type 2 diabetes. Collectively, these data are not sufficient to establish causality. Initial data mining revealed that the strongest positive correlation of diabetes with POPs occurred with organochlorine compounds, such as trans-nonachlor, dichlorodiphenyldichloroethylene (DDE), polychlorinated biphenyls (PCBs), and dioxins and dioxin-like chemicals. There is less indication of an association between other nonorganochlorine POPs, such as

A hidden two-locus disease association pattern in genome-wide association studies

PubMed Central

2011-01-01

Background Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip. PMID:21569557

Methods of Economic Valuation of The Health Risks Associated with Nanomaterials

NASA Astrophysics Data System (ADS)

Shalhevet, S.; Haruvy, N.

The worldwide market for nanomaterials is growing rapidly, but relatively little is still known about the potential risks associated with these materials. The potential health hazards associated with exposure to nanomaterials may lead in the future to increased health costs as well as increased economic costs to the companies involved, as has happened in the past in the case of asbestos. Therefore, it is important to make an initial estimate of the potential costs associated with these health hazards, and to prepare ahead with appropriate health insurance for individuals and financial insurance for companies. While several studies have examined the environmental and health hazards of different nanomaterials by performing life cycle impact assessments, so far these studies have concentrated on the cost of production, and did not estimate the economic impact of the health hazards. This paper discusses methods of evaluating the economic impact of potential health hazards on the public. The proposed method is based on using life cycle impact assessment studies of nanomaterials to estimate the DALYs (Disability Adjusted Life Years) associated with the increased probability of these health hazards. The economic valuation of DALY's can be carried out based on the income lost and the costs of medical treatment. The total expected increase in cost depends on the increase in the statistical probability of each disease.

Association of meat intake and meat-derived mutagen exposure with the risk of colorectal polyps by histologic type

PubMed Central

Fu, Zhenming; Shrubsole, Martha J.; Smalley, Walter E.; Wu, Huiyun; Chen, Zhi; Shyr, Yu; Ness, Reid M.; Zheng, Wei

2011-01-01

Background The association of meat intake and meat-derived mutagens with colorectal tumor risk remains unclear. We evaluated this hypothesis in a large colonoscopy-based case-control study. Methods Included in the study were 2,543 polyp patients [(1,881 with adenomas, and 622 with hyperplastic polyp (HPP)] and 3,764 polyp-free controls. Surveys obtained information about meat intake by cooking methods and doneness levels plus other suspected or known risk factors for colorectal tumors. Unconditional logistic regression was used to derive odds ratios (ORs) after adjusting for potential confounders. Results High intake of red meat and processed meat (P-trend < 0.05), particularly red meat cooked using high-temperature cooking methods (P-trend ≤ 0.01), was associated with an elevated risk for colorectal polyps. A significant positive association between exposures to meat-derived heterocyclic amines and risk of polyps was found for both adenomas and hyperplastic polyps. Furthermore, the positive association with red-meat intake and heterocyclic amine exposure was stronger for multiple adenomas than single adenoma and serrated than non-serrated adenomas. Conclusion This study supports a role for red meat and meat-derived mutagen exposure in the development of colorectal tumor. PMID:21803984

Intention stability assessed using residual change scores moderates the intention-behaviour association: a prospective cohort study.

PubMed

Rowan, Alicia A; McDermott, Máirtín S; Allen, Mark S

2017-12-01

Intention stability is considered to be one of the key pre-requisites for a strong association between intention and behaviour. It has been claimed, however, that studies examining the moderating impact of intention stability may be invalid, as they have relied on statistically inferior methods. Residual change scores have been suggested as a more appropriate method of measuring change (or lack thereof) in constructs. The aim of the current study, therefore, is to test whether intention stability, calculated using residual change scores, moderates the intention-physical activity behaviour association. A total of 163 participants (124 women, 39 men) completed questionnaires online at three time points separated by 14 day intervals. The moderating impact of intention stability was assessed using multiple linear regression followed up using simple slope analyses to identify the direction of any effect. The interaction of intention and intention stability was found to significantly improve the overall model fit. Intentions had a stronger positive association with behaviour when intentions were more stable than when they were more unstable. However, sensitivity analyses revealed that the association was not robust and reduced to non-significant with the removal of potential multivariate outliers. Future research should use residual change scores as the preferred method of assessing intention stability.

Haplotype-Based Association Analysis via Variance-Components Score Test

PubMed Central

Tzeng, Jung-Ying ; Zhang, Daowen 

2007-01-01

Haplotypes provide a more informative format of polymorphisms for genetic association analysis than do individual single-nucleotide polymorphisms. However, the practical efficacy of haplotype-based association analysis is challenged by a trade-off between the benefits of modeling abundant variation and the cost of the extra degrees of freedom. To reduce the degrees of freedom, several strategies have been considered in the literature. They include (1) clustering evolutionarily close haplotypes, (2) modeling the level of haplotype sharing, and (3) smoothing haplotype effects by introducing a correlation structure for haplotype effects and studying the variance components (VC) for association. Although the first two strategies enjoy a fair extent of power gain, empirical evidence showed that VC methods may exhibit only similar or less power than the standard haplotype regression method, even in cases of many haplotypes. In this study, we report possible reasons that cause the underpowered phenomenon and show how the power of the VC strategy can be improved. We construct a score test based on the restricted maximum likelihood or the marginal likelihood function of the VC and identify its nontypical limiting distribution. Through simulation, we demonstrate the validity of the test and investigate the power performance of the VC approach and that of the standard haplotype regression approach. With suitable choices for the correlation structure, the proposed method can be directly applied to unphased genotypic data. Our method is applicable to a wide-ranging class of models and is computationally efficient and easy to implement. The broad coverage and the fast and easy implementation of this method make the VC strategy an effective tool for haplotype analysis, even in modern genomewide association studies. PMID:17924336

Cytokeratin 8 in Association with sdLDL and ELISA Development

PubMed Central

Ashmaig, Mohmed

2015-01-01

Background: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. Cytokeratins (CKs) which may also be expressed in vascular smooth muscle cells (SMCs) are generally considered to be markers for the differentiation of epithelial cells. Small, dense, low-density lipoprotein (sdLDL) particles, also termed LDL-IV, independently predict risk of CVD. Aims: The aims of this study were to develop an analytical method, apart from ultracentrifugation capable of isolating sdLDL in order to study any associated proteins. Materials and Methods: Using modified gradient gel electrophoresis (GGE), de-identified sdLDL-enriched plasma was used to physically elute and isolate sdLDL particles. To validate the finding, additional plasma from 77 normal and 48 higher risk subjects were used to measure sdLDL particles and CK8. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting method were used to identify the characteristics of proteins associated with sdLDL. An enzyme-linked immunosorbent assay (ELISA) method was developed and validated for the measurement of CK8 in plasma. Results: The validation of the CK8 ELISA method showed good analytical performance. The isolated sdLDL particles were verified with nondenaturing GGE with the apolipoprotein B component confirmed by Western immunoblotting. Confirmed by SDS-PAGE and Western immunoblotting, CK8 was associated with sdLDL. Two-tailed statistical analysis showed that CK8 and sdLDL particles were significantly higher in the high-risk CVD group compared to control group (P < 0.01 and P < 0.01, respectively). Conclusion: This study reports a novel association between CK8 and sdLDL in individuals with CVD who have a predominance of sdLDL. PMID:26713292

Creative Interactive Teaching: Case Method & Other Techniques. Selected Papers of the International Conference on Case Methods Research & Application (16th, Caceres, Spain, 1999).

ERIC Educational Resources Information Center

Klein, Hans E., Ed.

This book presents a selection of papers from the international, interdisciplinary conference of the World Association for Case Method Research & Application. Papers are categorized into seven areas: (1) "International Case Studies" (e.g., event-based entrepreneurship, case studies on consumer complaints, and strategic quality…

OPATs: Omnibus P-value association tests.

PubMed

Chen, Chia-Wei; Yang, Hsin-Chou

2017-07-10

Combining statistical significances (P-values) from a set of single-locus association tests in genome-wide association studies is a proof-of-principle method for identifying disease-associated genomic segments, functional genes and biological pathways. We review P-value combinations for genome-wide association studies and introduce an integrated analysis tool, Omnibus P-value Association Tests (OPATs), which provides popular analysis methods of P-value combinations. The software OPATs programmed in R and R graphical user interface features a user-friendly interface. In addition to analysis modules for data quality control and single-locus association tests, OPATs provides three types of set-based association test: window-, gene- and biopathway-based association tests. P-value combinations with or without threshold and rank truncation are provided. The significance of a set-based association test is evaluated by using resampling procedures. Performance of the set-based association tests in OPATs has been evaluated by simulation studies and real data analyses. These set-based association tests help boost the statistical power, alleviate the multiple-testing problem, reduce the impact of genetic heterogeneity, increase the replication efficiency of association tests and facilitate the interpretation of association signals by streamlining the testing procedures and integrating the genetic effects of multiple variants in genomic regions of biological relevance. In summary, P-value combinations facilitate the identification of marker sets associated with disease susceptibility and uncover missing heritability in association studies, thereby establishing a foundation for the genetic dissection of complex diseases and traits. OPATs provides an easy-to-use and statistically powerful analysis tool for P-value combinations. OPATs, examples, and user guide can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/genetics/association/OPATs.htm. © The Author 2017. Published by Oxford University Press.

Storyline and Associations Pyramid as Methods of Creativity Enhancement: Comparison of Effectiveness in 5-Year-Old Children

ERIC Educational Resources Information Center

Smogorzewska, Joanna

2012-01-01

This article presents the results of a study comparing the originality, the length, the number of neologisms and the syntactic complexity of fairy tales created with "Storyline" and "Associations Pyramid." Both methods were developed to enhance children's language abilities and their creative thinking. One hundred twenty eight 5-year-old children…

Assembly of greek marble inscriptions by isotopic methods.

PubMed

Herz, N; Wenner, D B

1978-03-10

Classical Greek inscriptions cut in marble, whose association as original stelai by archeological methods was debatable, were selected for study. Using traditional geological techniques and determinations of the per mil increments in carbon-13 and oxygen-18, it was determined that fragments could be positively assigned to three stelai, but that fragments from three other stelai had been incorrectly associated.

Association of Cesarean Delivery and Formula Supplementation With the Intestinal Microbiome of 6-Week-Old Infants.

PubMed

Madan, Juliette C; Hoen, Anne G; Lundgren, Sara N; Farzan, Shohreh F; Cottingham, Kathryn L; Morrison, Hilary G; Sogin, Mitchell L; Li, Hongzhe; Moore, Jason H; Karagas, Margaret R

2016-03-01

The intestinal microbiome plays a critical role in infant development, and delivery mode and feeding method (breast milk vs formula) are determinants of its composition. However, the importance of delivery mode beyond the first days of life is unknown, and studies of associations between infant feeding and microbiome composition have been generally limited to comparisons between exclusively breastfed and formula-fed infants, with little consideration given to combination feeding of both breast milk and formula. To examine the associations of delivery mode and feeding method with infant intestinal microbiome composition at approximately 6 weeks of life. Prospective observational study of 102 infants followed up as part of a US pregnancy cohort study. Delivery mode was abstracted from delivery medical records, and feeding method prior to the time of stool collection was ascertained through detailed questionnaires. Stool microbiome composition was characterized using next-generation sequencing of the 16S rRNA gene. There were 102 infants (mean gestational age, 39.7 weeks; range, 37.1-41.9 weeks) included in this study, of whom 70 were delivered vaginally and 32 by cesarean delivery. In the first 6 weeks of life, 70 were exclusively breastfed, 26 received combination feeding, and 6 were exclusively formula fed. We identified independent associations between microbial community composition and both delivery mode (P< .001; Q < .001) and feeding method (P = .01; Q < .001). Differences in microbial community composition between vaginally delivered infants and infants delivered by cesarean birth were equivalent to or significantly larger than those between feeding groups (P = .003). Bacterial communities associated with combination feeding were more similar to those associated with exclusive formula feeding than exclusive breastfeeding (P = .002). We identified 6 individual bacterial genera that were differentially abundant between delivery mode and feeding groups. The infant intestinal microbiome at approximately 6 weeks of age is significantly associated with both delivery mode and feeding method, and the supplementation of breast milk feeding with formula is associated with a microbiome composition that resembles that of infants who are exclusively formula fed. These results may inform feeding choices and shed light on the mechanisms behind the lifelong health consequences of delivery and infant feeding modalities.

Automated and visual scoring methods of cerebral white matter hyperintensities: relation with age and cognitive function.

PubMed

Tiehuis, A M; Vincken, K L; Mali, W P T M; Kappelle, L J; Anbeek, P; Algra, A; Biessels, G J

2008-01-01

A reliable scoring method for ischemic cerebral white matter hyperintensities (WMH) will help to clarify the causes and consequences of these brain lesions. We compared an automated and two visual WMH scoring methods in their relations with age and cognitive function. MRI of the brain was performed on 154 participants of the Utrecht Diabetic Encephalopathy Study. WMH volumes were obtained with an automated segmentation method. Visual rating of deep and periventricular WMH (DWMH and PWMH) was performed with the Scheltens scale and the Rotterdam Scan Study (RSS) scale, respectively. Cognition was assessed with a battery of 11 tests. Within the whole study group, the association with age was most evident for the automated measured WMH volume (beta = 0.43, 95% CI = 0.29-0.57). With regard to cognition, automated measured WMH volume and Scheltens DWMH were significantly associated with information processing speed (beta = -0.22, 95% CI = -0.40 to -0.06; beta = -0.26, 95% CI = -0.42 to -0.10), whereas RSS PWMH were associated with attention and executive function (beta = -0.19, 95% CI = -0.36 to -0.02). Measurements of WMH with an automated quantitative segmentation method are comparable with visual rating scales and highly suitable for use in future studies to assess the relationship between WMH and subtle impairments in cognitive function. (c) 2007 S. Karger AG, Basel.

A systematic review of the association between family meals and adolescent risk outcomes.

PubMed

Goldfarb, Samantha S; Tarver, Will L; Locher, Julie L; Preskitt, Julie; Sen, Bisakha

2015-10-01

To conduct a systematic review of the literature examining the relationship between family meals and adolescent health risk outcomes. We performed a systematic search of original empirical studies published between January 1990 and September 2013. Based on data from selected studies, we conducted logistic regression models to examine the correlates of reporting a protective association between frequent family meals and adolescent outcomes. Of the 254 analyses from 26 selected studies, most reported a significant association between family meals and the adolescent risk outcome-of-interest. However, model analyses which controlled for family connectedness variables, or used advanced empirical methods to account for family-level confounders, were less likely than unadjusted models to report significant relationships. The type of analysis conducted was significantly associated with the likelihood of finding a protective relationship between family meals and the adolescent outcome-of-interest, yet very few studies are using such methods in the literature. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Case-Control Genome-Wide Association Study of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Neale, Benjamin M.; Medland, Sarah; Ripke, Stephan; Anney, Richard J. L.; Asherson, Philip; Buitelaar, Jan; Franke, Barbara; Gill, Michael; Kent, Lindsey; Holmans, Peter; Middleton, Frank; Thapar, Anita; Lesch, Klaus-Peter; Faraone, Stephen V.; Daly, Mark; Nguyen, Thuy Trang; Schafer, Helmut; Steinhausen, Hans-Christoph; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Walitza, Susanne; Freitag, Christine; Meyer, Jobst; Palmason, Haukur; Rothenberger, Aribert; Hawi, Ziarih; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph

2010-01-01

Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. Thus additional genome-wide association studies (GWAS) are needed. Method: We used case-control analyses of 896 cases…

SAW based micro- and acousto-fluidics in biomedicine

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2017-04-01

Protein association starts with random collisions of individual proteins. Multiple collisions and rotational diffusion brings the molecules to a state of orientation. Majority of the protein associations are influenced by electrostatic interactions. To introduce: electrostatic rate enhancement, Brownian dynamics and transient complex theory has been traditionally used. Due to the recent advances in interdisciplinary sciences, an array of molecular assembly methods is being studied. Protein nanostructural assembly and macromolecular crowding are derived from the subsets of biochemistry to study protein-protein interactions and protein self-assembly. This paper tries to investigate the issue of enhancing the protein self-association rate, and bridging the gap between the simulations and experimental results. The methods proposed here include: electrostatic rate enhancement, macromolecular crowing, nanostructural protein assembly, microfluidics based approaches and magnetic force based approaches. Despite the suggestions of several methods, microfluidic and magnetic force based approaches seem to serve the need of protein assembly in a wider scale. Congruence of these approaches may also yield better results. Even though, these methods prove to be conceptually strong, to prevent the disagreement of theory and practice, a wide range of experiments is required. This proposal intends to study theoretical and experimental methods to successfully implement the aforementioned assembly strategies, and conclude with an extensive analysis of experimental data to address practical feasibility.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with prostate cancer and selected the top 100 highly ranked candidate protein complexes. Interestingly, 69 of them were evidenced since at least one of their protein elements are known to be associated with prostate cancer. Our proposed method, including the framework to construct functional similarity protein complex networks and the neighborhood-based algorithm on these networks, could be used for identification of novel disease-protein complex associations.

Psychometric properties of the List of Threatening Experiences--LTE and its association with psychosocial factors and mental disorders according to different scoring methods.

PubMed

Motrico, Emma; Moreno-Küstner, Berta; de Dios Luna, Juan; Torres-González, Francisco; King, Michael; Nazareth, Irwin; Montón-Franco, Carmen; Gilde Gómez-Barragán, María Josefa; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Moreno-Peral, Patricia; Bellón, Juan Ángel

2013-09-25

The List of Threatening Experiences (LTE) questionnaire is frequently used to assess stressful events; however, studies of its psychometric properties are scarce. We examined the LTE's reliability, factorial structure, construct validity and explored the association between LTE scores and psychosocial variables and mental disorders. This study involved interviewing 5442 primary care attendees from Spain. Associations between four different methods of quantifying LTE scores, psychosocial factors, major depression (CIDI), anxiety disorders (PRIME-MD), alcohol misuse and dependence (AUDIT) were measured. The LTE showed high test-retest reliability (Kappa range=0.61-0.87) and low internal consistency (α=0.44). Tetrachoric factorial analysis yielded four factors (spousal and relational problems; employment and financial problems; personal problems; illness and bereavement in close persons). Logistic multilevel regression found a strong association between greater social support and a lower occurrence of stressful events (OR range=0.36-0.79). The association between religious-spiritual beliefs and the LTE, was weaker. The association between mental disorders and LTE scores was greater for depression (OR range=1.64-2.57) than anxiety (OR range=1.35-1.97), though the highest ORs were obtained with alcohol dependence (OR range=2.86-4.80). The ordinal score (ordinal regression) was more sensitive to detect the strength of association with mental disorders. We are unable to distinguish the direction of the association between stressful events, psychosocial factors and mental disorders, due to our cross-sectional design of the study. The LTE is a valid and reliable measure of stress in mental health, and the strength of association with mental disorders depends on the method of quantifying LTE scores. © 2013 Elsevier B.V. All rights reserved.

Validation of an association rule mining-based method to infer associations between medications and problems.

PubMed

Wright, A; McCoy, A; Henkin, S; Flaherty, M; Sittig, D

2013-01-01

In a prior study, we developed methods for automatically identifying associations between medications and problems using association rule mining on a large clinical data warehouse and validated these methods at a single site which used a self-developed electronic health record. To demonstrate the generalizability of these methods by validating them at an external site. We received data on medications and problems for 263,597 patients from the University of Texas Health Science Center at Houston Faculty Practice, an ambulatory practice that uses the Allscripts Enterprise commercial electronic health record product. We then conducted association rule mining to identify associated pairs of medications and problems and characterized these associations with five measures of interestingness: support, confidence, chi-square, interest and conviction and compared the top-ranked pairs to a gold standard. 25,088 medication-problem pairs were identified that exceeded our confidence and support thresholds. An analysis of the top 500 pairs according to each measure of interestingness showed a high degree of accuracy for highly-ranked pairs. The same technique was successfully employed at the University of Texas and accuracy was comparable to our previous results. Top associations included many medications that are highly specific for a particular problem as well as a large number of common, accurate medication-problem pairs that reflect practice patterns.

An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.

PubMed

Kim, Junghi; Bai, Yun; Pan, Wei

2015-12-01

We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods. © 2015 WILEY PERIODICALS, INC.

Comparison between a clinical diagnosis method and the surveillance technique of the Center for Disease Control and Prevention for identification of mechanical ventilator-associated pneumonia.

PubMed

Waltrick, Renata; Possamai, Dimitri Sauter; de Aguiar, Fernanda Perito; Dadam, Micheli; de Souza Filho, Valmir João; Ramos, Lucas Rocker; Laurett, Renata da Silva; Fujiwara, Kênia; Caldeira Filho, Milton; Koenig, Álvaro; Westphal, Glauco Adrieno

2015-01-01

>To evaluate the agreement between a new epidemiological surveillance method of the Center for Disease Control and Prevention and the clinical pulmonary infection score for mechanical ventilator-associated pneumonia detection. This was a prospective cohort study that evaluated patients in the intensive care units of two hospitals who were intubated for more than 48 hours between August 2013 and June 2014. Patients were evaluated daily by physical therapist using the clinical pulmonary infection score. A nurse independently applied the new surveillance method proposed by the Center for Disease Control and Prevention. The diagnostic agreement between the methods was evaluated. A clinical pulmonary infection score of ≥ 7 indicated a clinical diagnosis of mechanical ventilator-associated pneumonia, and the association of a clinical pulmonary infection score ≥ 7 with an isolated semiquantitative culture consisting of ≥ 104 colony-forming units indicated a definitive diagnosis. Of the 801 patients admitted to the intensive care units, 198 required mechanical ventilation. Of these, 168 were intubated for more than 48 hours. A total of 18 (10.7%) cases of mechanical ventilation-associated infectious conditions were identified, 14 (8.3%) of which exhibited possible or probable mechanical ventilator-associated pneumonia, which represented 35% (14/38) of mechanical ventilator-associated pneumonia cases. The Center for Disease Control and Prevention method identified cases of mechanical ventilator-associated pneumonia with a sensitivity of 0.37, specificity of 1.0, positive predictive value of 1.0, and negative predictive value of 0.84. The differences resulted in discrepancies in the mechanical ventilator-associated pneumonia incidence density (CDC, 5.2/1000 days of mechanical ventilation; clinical pulmonary infection score ≥ 7, 13.1/1000 days of mechanical ventilation). The Center for Disease Control and Prevention method failed to detect mechanical ventilator-associated pneumonia cases and may not be satisfactory as a surveillance method.

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.

PubMed

Coull, Brent A; Bobb, Jennifer F; Wellenius, Gregory A; Kioumourtzoglou, Marianthi-Anna; Mittleman, Murray A; Koutrakis, Petros; Godleski, John J

2015-06-01

The United States Environmental Protection Agency (U.S. EPA*) currently regulates individual air pollutants on a pollutant-by-pollutant basis, adjusted for other pollutants and potential confounders. However, the National Academies of Science concluded that a multipollutant regulatory approach that takes into account the joint effects of multiple constituents is likely to be more protective of human health. Unfortunately, the large majority of existing research had focused on health effects of air pollution for one pollutant or for one pollutant with control for the independent effects of a small number of copollutants. Limitations in existing statistical methods are at least partially responsible for this lack of information on joint effects. The goal of this project was to fill this gap by developing flexible statistical methods to estimate the joint effects of multiple pollutants, while allowing for potential nonlinear or nonadditive associations between a given pollutant and the health outcome of interest. We proposed Bayesian kernel machine regression (BKMR) methods as a way to simultaneously achieve the multifaceted goals of variable selection, flexible estimation of the exposure-response relationship, and inference on the strength of the association between individual pollutants and health outcomes in a health effects analysis of mixtures. We first developed a BKMR variable-selection approach, which we call component-wise variable selection, to make estimating such a potentially complex exposure-response function possible by effectively using two types of penalization (or regularization) of the multivariate exposure-response surface. Next we developed an extension of this first variable-selection approach that incorporates knowledge about how pollutants might group together, such as multiple constituents of particulate matter that might represent a common pollution source category. This second grouped, or hierarchical, variable-selection procedure is applicable when groups of highly correlated pollutants are being studied. To investigate the properties of the proposed methods, we conducted three simulation studies designed to evaluate the ability of BKMR to estimate environmental mixtures responsible for health effects under potentially complex but plausible exposure-response relationships. An attractive feature of our simulation studies is that we used actual exposure data rather than simulated values. This real-data simulation approach allowed us to evaluate the performance of BKMR and several other models under realistic joint distributions of multipollutant exposure. The simulation studies compared the two proposed variable-selection approaches (component-wise and hierarchical variable selection) with each other and with existing frequentist treatments of kernel machine regression (KMR). After the simulation studies, we applied the newly developed methods to an epidemiologic data set and to a toxicologic data set. To illustrate the applicability of the proposed methods to human epidemiologic data, we estimated associations between short-term exposures to fine particulate matter constituents and blood pressure in the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) Boston study, a prospective cohort study of elderly subjects. To illustrate the applicability of these methods to animal toxicologic studies, we analyzed data on the associations between both blood pressure and heart rate in canines exposed to a composition of concentrated ambient particles (CAPs) in a study conducted at the Harvard T. H. Chan School of Public Health (the Harvard Chan School; formerly Harvard School of Public Health; Bartoli et al. 2009). We successfully developed the theory and computational tools required to apply the proposed methods to the motivating data sets. Collectively, the three simulation studies showed that component-wise variable selection can identify important pollutants within a mixture as long as the correlations among pollutant concentrations are low to moderate. The hierarchical variable-selection method was more effective in high-dimension, high-correlation settings. Variable selection in existing frequentist KMR models can incur inflated type I error rates, particularly when pollutants are highly correlated. The analyses of the MOBILIZE data yielded evidence of a linear and additive association of black carbon (BC) or Cu exposure with standing diastolic blood pressure (DBP), and a linear association of S exposure with standing systolic blood pressure (SBP). Cu is thought to be a marker of urban road dust associated with traffic; and S is a marker of power plant emissions or regional long-range transported air pollution or both. Therefore, these analyses of the MOBILIZE data set suggest that emissions from these three source categories were most strongly associated with hemodynamic responses in this cohort. In contrast, in the Harvard Chan School canine study, after controlling for an overall effect of CAPs exposure, we did not observe any associations between DBP or SBP and any elemental concentrations. Instead, we observed strong evidence of an association between Mn concentrations and heart rate in that heart rate increased linearly with increasing concentrations of Mn. According to the positive matrix factorization (PMF) source apportionment analyses of the multipollutant data set from the Harvard Chan School Boston Supersite, Mn loads on the two factors that represent the mobile and road dust source categories. The results of the BKMR analyses in both the MOBILIZE and canine studies were similar to those from existing linear mixed model analyses of the same multipollutant data because the effects have linear and additive forms that could also have been detected using standard methods. This work provides several contributions to the KMR literature. First, to our knowledge this is the first time KMR methods have been used to estimate the health effects of multipollutant mixtures. Second, we developed a novel hierarchical variable-selection approach within BKMR that is able to account for the structure of the mixture and systematically handle highly correlated exposures. The analyses of the epidemiologic and toxicologic data on associations between fine particulate matter constituents and blood pressure or heart rate demonstrated associations with constituents that are typically associated with traffic emissions, power plants, and long-range transported pollutants. The simulation studies showed that the BKMR methods proposed here work well for small to moderate data sets; more work is needed to develop computationally fast methods for large data sets. This will be a goal of future work.

Effects of Cesarean delivery and formula supplementation on the intestinal microbiome of six-week old infants

PubMed Central

Madan, Juliette C.; Hoen, Anne G.; Lundgren, Sara N.; Farzan, Shohreh F.; Cottingham, Kathryn L.; Morrison, Hilary G.; Sogin, Mitchell L.; Li, Hongzhe; Moore, Jason H.; Karagas, Margaret R.

2016-01-01

Importance The intestinal microbiome plays a critical role in infant development, and delivery mode and feeding method (breastmilk vs. formula) are determinants of its composition. However, the importance of delivery mode beyond the first days of life is unknown, and studies of associations between infant feeding and microbiome composition have been generally limited to comparisons between exclusively breastfed and formula fed infants, with little consideration given to combination feeding of both breastmilk and formula. Objectives To examine the relative effects of delivery mode and feeding method on infant intestinal microbiome composition at approximately six weeks of life. Design, Setting and Participants Prospective observational study of 102 infants followed as part of a US pregnancy cohort study. Exposures Delivery mode was abstracted from delivery medical records and feeding method prior to the time of stool collection was ascertained through detailed questionnaires. Main Outcomes and Measures Stool microbiome composition was characterized using next-generation sequencing of the 16S rRNA gene. Results We identified independent associations between microbial community composition and both delivery mode and feeding method. Differences in microbial community composition between vaginally and infants delivered by Cesarean section were equivalent to or significantly larger than those between feeding groups. Bacterial communities associated with combination feeding were more similar to those associated with exclusive formula feeding than exclusive breastfeeding. We identified individual bacterial genera that were differentially abundant between delivery mode and feeding groups. Conclusions and Relevance The infant intestinal microbiome at approximately six weeks of age is significantly associated with both delivery mode and feeding method, and the supplementation of breastmilk feeding with formula is associated with a microbiome composition that resembles that of infants who are exclusively formula fed. These results may inform feeding choices and shed light on the mechanisms behind the lifelong health consequences of delivery and infant feeding modalities. PMID:26752321

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

PubMed

Yang, James J; Williams, L Keoki; Buu, Anne

2017-08-24

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

The location of incision in cataract surgery and its impact on induced astigmatism.

PubMed

Hashemi, Hassan; Khabazkhoob, Mehdi; Soroush, Sara; Shariati, Reyhane; Miraftab, Mohammad; Yekta, Abbasali

2016-01-01

The purpose of the present study is a systematic review of previous studies on choosing the best incision site for the correction of astigmatism in cataract surgery and assessing the amount of surgically induced astigmatism (SIA) with each approach. Regardless of astigmatism axis, studies show that using an on-axis incision is associated with favorable results for 0.5-1.0 diopter (D) of astigmatism. In cases with more than 1.0 D astigmatism, paired on-axis incisions can be appreciably efficient in astigmatism correction and cause at least 1.5 D SIA. Considering the amount of SIA, a temporal incision is the best approach when the patient has minimal amounts of corneal astigmatism preoperatively. At higher levels of astigmatism, if no other astigmatism correction method is used simultaneously, the temporal incision is used less frequently; however, since it is associated with the least SIA, it is still the choice site when another correction method is used. The temporal incisions in cataract surgery are associated with little SIA and are appropriate choices for mild preoperative astigmatism. At higher levels of preoperative astigmatism, superior incisions are associated with better results when combined methods are not applied.

Impact of the method of G6PD deficiency assessment on genetic association studies of malaria susceptibility.

PubMed

Johnson, Marla K; Clark, Tamara D; Njama-Meya, Denise; Rosenthal, Philip J; Parikh, Sunil

2009-09-30

Clinical association studies have yielded varied results regarding the impact of glucose-6-phosphate dehydrogenase (G6PD) deficiency upon susceptibility to malaria. Analyses have been complicated by varied methods used to diagnose G6PD deficiency. We compared the association between uncomplicated malaria incidence and G6PD deficiency in a cohort of 601 Ugandan children using two different diagnostic methods, enzyme activity and G6PD genotype (G202A, the predominant East African allele). Although roughly the same percentage of males were identified as deficient using enzyme activity (12%) and genotype (14%), nearly 30% of males who were enzymatically deficient were wild-type at G202A. The number of deficient females was three-fold higher with assessment by genotype (21%) compared to enzyme activity (7%). Heterozygous females accounted for the majority (46/54) of children with a mutant genotype but normal enzyme activity. G6PD deficiency, as determined by G6PD enzyme activity, conferred a 52% (relative risk [RR] 0.48, 95% CI 0.31-0.75) reduced risk of uncomplicated malaria in females. In contrast, when G6PD deficiency was defined based on genotype, the protective association for females was no longer seen (RR = 0.99, 95% CI 0.70-1.39). Notably, restricting the analysis to those females who were both genotypically and enzymatically deficient, the association of deficiency and protection from uncomplicated malaria was again demonstrated in females, but not in males (RR = 0.57, 95% CI 0.37-0.88 for females). This study underscores the impact that the method of identifying G6PD deficient individuals has upon association studies of G6PD deficiency and uncomplicated malaria. We found that G6PD-deficient females were significantly protected against uncomplicated malaria, but this protection was only seen when G6PD deficiency is described using enzyme activity. These observations may help to explain the discrepancy in some published association studies involving G6PD deficiency and uncomplicated malaria.

PICALM gene rs3851179 polymorphism contributes to Alzheimer's disease in an Asian population.

PubMed

Liu, Guiyou; Zhang, Shuyan; Cai, Zhiyou; Ma, Guoda; Zhang, Liangcai; Jiang, Yongshuai; Feng, Rennan; Liao, Mingzhi; Chen, Zugen; Zhao, Bin; Li, Keshen

2013-06-01

PICALM gene rs3851179 polymorphism was reported to an Alzheimer's disease (AD) susceptibility locus in a Caucasian population. However, recent studies reported consistent and inconsistent results in an Asian population. Four studies indicated no association between rs3851179 and AD in a Chinese population and one study reported weak association in a Japanese population. We consider that the failure to replicate the significant association between rs3851179 and AD may be caused by at least two reasons. The first reason may be the genetic heterogeneity in AD among different populations, and the second may be the relatively small sample size compared with large-scale GWAS in Caucasian ancestry. In order to confirm this view, in this research, we first evaluated the genetic heterogeneity of rs3851179 polymorphism in Caucasian and Asian populations. We then investigated rs3851179 polymorphism in an Asian population by a pooled analysis method and a meta-analysis method. We did not observe significant genetic heterogeneity of rs3851179 in the Caucasian and Asian populations. Our results indicate that rs3851179 polymorphism is significantly associated with AD in the Asian population by both pooled analysis and meta-analysis methods. We believe that our findings will be very useful for future genetic studies in AD.

Evidence for association between Disrupted-in-schizophrenia 1 (DISC1) gene polymorphisms and autism in Chinese Han population: a family-based association study

PubMed Central

2011-01-01

Background Disrupted-in-Schizophrenia 1 (DISC1) gene is one of the most promising candidate genes for major mental disorders. In a previous study, a Finnish group demonstrated that DISC1 polymorphisms were associated with autism and Asperger syndrome. However, the results were not replicated in Korean population. To determine whether DISC1 is associated with autism in Chinese Han population, we performed a family-based association study between DISC1 polymorphisms and autism. Methods We genotyped seven tag single nucleotide polymorphisms (SNPs) in DISC1, spanning 338 kb, in 367 autism trios (singleton and their biological parents) including 1,101 individuals. Single SNP association and haplotype association analysis were performed using the family-based association test (FBAT) and Haploview software. Results We found three SNPs showed significant associations with autism (rs4366301: G > C, Z = 2.872, p = 0.004; rs11585959: T > C, Z = 2.199, p = 0.028; rs6668845: A > G, Z = 2.326, p = 0.02). After the Bonferroni correction, SNP rs4366301, which located in the first intron of DISC1, remained significant. When haplotype were constructed with two-markers, three haplotypes displayed significant association with autism. These results were still significant after using the permutation method to obtain empirical p values. Conclusions Our study provided evidence that the DISC1 may be the susceptibility gene of autism. It suggested DISC1 might play a role in the pathogenesis of autism. PMID:21569632

Estimation of the proteomic cancer co-expression sub networks by using association estimators.

PubMed

Erdoğan, Cihat; Kurt, Zeyneb; Diri, Banu

2017-01-01

In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

Estimation of the proteomic cancer co-expression sub networks by using association estimators

PubMed Central

Kurt, Zeyneb; Diri, Banu

2017-01-01

In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators’ performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists. PMID:29145449

Glomerular hyperfiltration and metabolic syndrome: results from the FIrenze-BAgno A Ripoli (FIBAR) Study.

PubMed

Monami, Matteo; Pala, Laura; Bardini, Gianluca; Francesconi, Paolo; Cresci, Barbara; Marchionni, Niccolò; Rotella, Carlo Maria; Mannucci, Edoardo

2009-09-01

Metabolic syndrome (MS) has been associated with microalbuminuria and kidney disease. In the present cohort study, different methods for the estimation of glomerular filtration rate (GFR) on the basis of serum creatinine were compared with respect to their association with MS and their predictive value for incident diabetes mellitus. The present analysis was performed on the cohort of subjects enrolled in the FIBAR study, a screening program for diabetes. GFR was estimated (eGFR) using three different methods: Cockroft-Gault (CG) formula, using actual body weight (CAW), CG formula using ideal body weight (CIW), and Modification of Diet in Renal Disease formula (M). The study was performed on 2,694 nondiabetic subjects, without history of renal insufficiency or serum creatinine at baseline >1.5 mg/dl. Mean follow-up was 27.8 +/- 11.5 months. Elevated eGFR, estimated with different methods, was associated with increased prevalence of most components of MS; however, an association between elevated clearance and MS was observed only when using CAW, which overestimates filtration in obese subjects. During follow-up, 40 new cases of diabetes were recorded (0.5/100 patient*years). After adjusting for age and sex, the HR (with 95% confidence intervals) for diabetes for patients in the highest quintile of eGFR was 1.14 [0.44-2.99], 0.89 [0.31-2.51], and 1.01 [0.42-2.41] for formula CAW, CIW, and M, respectively (all p > 0.7). Elevated eGFR, estimated through methods which do not produce a systematic overestimate in obese subjects, is not associated with the diagnosis of MS, and does not predict diabetes.

Development of a turbomachinery design optimization procedure using a multiple-parameter nonlinear perturbation method

NASA Technical Reports Server (NTRS)

Stahara, S. S.

1984-01-01

An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.

Fusing literature and full network data improves disease similarity computation.

PubMed

Li, Ping; Nie, Yaling; Yu, Jingkai

2016-08-30

Identifying relatedness among diseases could help deepen understanding for the underlying pathogenic mechanisms of diseases, and facilitate drug repositioning projects. A number of methods for computing disease similarity had been developed; however, none of them were designed to utilize information of the entire protein interaction network, using instead only those interactions involving disease causing genes. Most of previously published methods required gene-disease association data, unfortunately, many diseases still have very few or no associated genes, which impeded broad adoption of those methods. In this study, we propose a new method (MedNetSim) for computing disease similarity by integrating medical literature and protein interaction network. MedNetSim consists of a network-based method (NetSim), which employs the entire protein interaction network, and a MEDLINE-based method (MedSim), which computes disease similarity by mining the biomedical literature. Among function-based methods, NetSim achieved the best performance. Its average AUC (area under the receiver operating characteristic curve) reached 95.2 %. MedSim, whose performance was even comparable to some function-based methods, acquired the highest average AUC in all semantic-based methods. Integration of MedSim and NetSim (MedNetSim) further improved the average AUC to 96.4 %. We further studied the effectiveness of different data sources. It was found that quality of protein interaction data was more important than its volume. On the contrary, higher volume of gene-disease association data was more beneficial, even with a lower reliability. Utilizing higher volume of disease-related gene data further improved the average AUC of MedNetSim and NetSim to 97.5 % and 96.7 %, respectively. Integrating biomedical literature and protein interaction network can be an effective way to compute disease similarity. Lacking sufficient disease-related gene data, literature-based methods such as MedSim can be a great addition to function-based algorithms. It may be beneficial to steer more resources torward studying gene-disease associations and improving the quality of protein interaction data. Disease similarities can be computed using the proposed methods at http:// www.digintelli.com:8000/ .

pKWmEB: integration of Kruskal-Wallis test with empirical Bayes under polygenic background control for multi-locus genome-wide association study.

PubMed

Ren, Wen-Long; Wen, Yang-Jun; Dunwell, Jim M; Zhang, Yuan-Ming

2018-03-01

Although nonparametric methods in genome-wide association studies (GWAS) are robust in quantitative trait nucleotide (QTN) detection, the absence of polygenic background control in single-marker association in genome-wide scans results in a high false positive rate. To overcome this issue, we proposed an integrated nonparametric method for multi-locus GWAS. First, a new model transformation was used to whiten the covariance matrix of polygenic matrix K and environmental noise. Using the transferred model, Kruskal-Wallis test along with least angle regression was then used to select all the markers that were potentially associated with the trait. Finally, all the selected markers were placed into multi-locus model, these effects were estimated by empirical Bayes, and all the nonzero effects were further identified by a likelihood ratio test for true QTN detection. This method, named pKWmEB, was validated by a series of Monte Carlo simulation studies. As a result, pKWmEB effectively controlled false positive rate, although a less stringent significance criterion was adopted. More importantly, pKWmEB retained the high power of Kruskal-Wallis test, and provided QTN effect estimates. To further validate pKWmEB, we re-analyzed four flowering time related traits in Arabidopsis thaliana, and detected some previously reported genes that were not identified by the other methods.

Associated Factors of Bone Mineral Density and Osteoporosis in Elderly Males

PubMed Central

Heidari, Behzad; Muhammadi, Abdollah; Javadian, Yahya; Bijani, Ali; Hosseini, Reza; Babaei, Mansour

2016-01-01

Background Low bone mineral density and osteoporosis is prevalent in elderly subjects. This study aimed to determine the associated factors of bone mineral density and osteoporosis in elderly males. Methods All participants of the Amirkola health and ageing project cohort aged 60 years and older entered the study. Bone mineral density at femoral neck and lumbar spine was assessed by the dual energy X-ray absorptiometry (DXA) method. Osteoporosis was diagnosed by the international society for clinical densitometry criteria and the association of bone mineral density and osteoporosis with several clinical, demographic and biochemical parameters. Multiple logistic regression analysis was used to determine independent associations. Results A total of 553 patients were studied and 90 patients (16.2%) had osteoporosis at either femoral neck or lumbar spine. Diabetes, obesity, metabolic syndrome, overweight, and quadriceps muscle strength > 30 kg, metabolic syndrome, abdominal obesity and education level were associated with higher bone mineral density and lower prevalence of osteoporosis, whereas age, anemia, inhaled corticosteroids and fracture history were associated with lower bone mineral density and higher prevalence of osteoporosis (P = 0.001). After adjustment for all covariates, osteoporosis was negatively associated only with diabetes, obesity, overweight, and QMS > 30 kg and positively associated with anemia and fracture history. The association of osteoporosis with other parameters did not reach a statistical level. Conclusions The findings of the study indicate that in elderly males, diabetes, obesity and higher muscle strength was associated with lower prevalence of osteoporosis and anemia, and prior fracture with higher risk of osteoporosis. This issue needs further longitudinal studies. PMID:28835759

Nutritional risk assessment in critically ill cancer patients: systematic review

PubMed Central

Fruchtenicht, Ana Valéria Gonçalves; Poziomyck, Aline Kirjner; Kabke, Geórgia Brum; Loss, Sérgio Henrique; Antoniazzi, Jorge Luiz; Steemburgo, Thais; Moreira, Luis Fernando

2015-01-01

Objective To systematically review the main methods for nutritional risk assessment used in critically ill cancer patients and present the methods that better assess risks and predict relevant clinical outcomes in this group of patients, as well as to discuss the pros and cons of these methods according to the current literature. Methods The study consisted of a systematic review based on analysis of manuscripts retrieved from the PubMed, LILACS and SciELO databases by searching for the key words “nutritional risk assessment”, “critically ill” and “cancer”. Results Only 6 (17.7%) of 34 initially retrieved papers met the inclusion criteria and were selected for the review. The main outcomes of these studies were that resting energy expenditure was associated with undernourishment and overfeeding. The high Patient-Generated Subjective Global Assessment score was significantly associated with low food intake, weight loss and malnutrition. In terms of biochemical markers, higher levels of creatinine, albumin and urea were significantly associated with lower mortality. The worst survival was found for patients with worse Eastern Cooperative Oncologic Group - performance status, high Glasgow Prognostic Score, low albumin, high Patient-Generated Subjective Global Assessment score and high alkaline phosphatase levels. Geriatric Nutritional Risk Index values < 87 were significantly associated with mortality. A high Prognostic Inflammatory and Nutritional Index score was associated with abnormal nutritional status in critically ill cancer patients. Among the reviewed studies that examined weight and body mass index alone, no significant clinical outcome was found. Conclusion None of the methods reviewed helped to define risk among these patients. Therefore, assessment by a combination of weight loss and serum measurements, preferably in combination with other methods using scores such as Eastern Cooperative Oncologic Group - performance status, Glasgow Prognostic Score and Patient-Generated Subjective Global Assessment, is suggested given that their use is simple, feasible and useful in such cases. PMID:26270855

Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

PubMed

Uddin, M B; Chow, C M; Su, S W

2018-03-26

Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

Measurement methods and accuracy in copy number variation: failure to replicate associations of beta-defensin copy number with Crohn's disease.

PubMed

Aldhous, Marian C; Abu Bakar, Suhaili; Prescott, Natalie J; Palla, Raquel; Soo, Kimberley; Mansfield, John C; Mathew, Christopher G; Satsangi, Jack; Armour, John A L

2010-12-15

The copy number variation in beta-defensin genes on human chromosome 8 has been proposed to underlie susceptibility to inflammatory disorders, but presents considerable challenges for accurate typing on the scale required for adequately powered case-control studies. In this work, we have used accurate methods of copy number typing based on the paralogue ratio test (PRT) to assess beta-defensin copy number in more than 1500 UK DNA samples including more than 1000 cases of Crohn's disease. A subset of 625 samples was typed using both PRT-based methods and standard real-time PCR methods, from which direct comparisons highlight potentially serious shortcomings of a real-time PCR assay for typing this variant. Comparing our PRT-based results with two previous studies based only on real-time PCR, we find no evidence to support the reported association of Crohn's disease with either low or high beta-defensin copy number; furthermore, it is noteworthy that there are disagreements between different studies on the observed frequency distribution of copy number states among European controls. We suggest safeguards to be adopted in assessing and reporting the accuracy of copy number measurement, with particular emphasis on integer clustering of results, to avoid reporting of spurious associations in future case-control studies.

Measurement methods and accuracy in copy number variation: failure to replicate associations of beta-defensin copy number with Crohn's disease

PubMed Central

Aldhous, Marian C.; Abu Bakar, Suhaili; Prescott, Natalie J.; Palla, Raquel; Soo, Kimberley; Mansfield, John C.; Mathew, Christopher G.; Satsangi, Jack; Armour, John A.L.

2010-01-01

The copy number variation in beta-defensin genes on human chromosome 8 has been proposed to underlie susceptibility to inflammatory disorders, but presents considerable challenges for accurate typing on the scale required for adequately powered case–control studies. In this work, we have used accurate methods of copy number typing based on the paralogue ratio test (PRT) to assess beta-defensin copy number in more than 1500 UK DNA samples including more than 1000 cases of Crohn's disease. A subset of 625 samples was typed using both PRT-based methods and standard real-time PCR methods, from which direct comparisons highlight potentially serious shortcomings of a real-time PCR assay for typing this variant. Comparing our PRT-based results with two previous studies based only on real-time PCR, we find no evidence to support the reported association of Crohn's disease with either low or high beta-defensin copy number; furthermore, it is noteworthy that there are disagreements between different studies on the observed frequency distribution of copy number states among European controls. We suggest safeguards to be adopted in assessing and reporting the accuracy of copy number measurement, with particular emphasis on integer clustering of results, to avoid reporting of spurious associations in future case–control studies. PMID:20858604

Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types.

PubMed

Cornish, Alex J; Filippis, Ioannis; David, Alessia; Sternberg, Michael J E

2015-09-01

Each cell type found within the human body performs a diverse and unique set of functions, the disruption of which can lead to disease. However, there currently exists no systematic mapping between cell types and the diseases they can cause. In this study, we integrate protein-protein interaction data with high-quality cell-type-specific gene expression data from the FANTOM5 project to build the largest collection of cell-type-specific interactomes created to date. We develop a novel method, called gene set compactness (GSC), that contrasts the relative positions of disease-associated genes across 73 cell-type-specific interactomes to map genes associated with 196 diseases to the cell types they affect. We conduct text-mining of the PubMed database to produce an independent resource of disease-associated cell types, which we use to validate our method. The GSC method successfully identifies known disease-cell-type associations, as well as highlighting associations that warrant further study. This includes mast cells and multiple sclerosis, a cell population currently being targeted in a multiple sclerosis phase 2 clinical trial. Furthermore, we build a cell-type-based diseasome using the cell types identified as manifesting each disease, offering insight into diseases linked through etiology. The data set produced in this study represents the first large-scale mapping of diseases to the cell types in which they are manifested and will therefore be useful in the study of disease systems. Overall, we demonstrate that our approach links disease-associated genes to the phenotypes they produce, a key goal within systems medicine.

Are Prospective Elementary School Teachers' Social Studies Teaching Efficacy Beliefs Related to Their Learning Approaches in a Social Studies Teaching Methods Course?

ERIC Educational Resources Information Center

Dündar, Sahin

2015-01-01

This study aimed to contribute to the growing literature on learning approaches and teacher self-efficacy beliefs by examining associations between prospective elementary school teachers' learning approaches in a social studies teaching methods course and their social studies teaching efficacy beliefs. One hundred ninety-two prospective elementary…

Parents' and Children's Self-Report of Parenting Factors: How Much Do They Agree and Which Is More Strongly Associated with Early Adolescent Alcohol Use?

ERIC Educational Resources Information Center

Pasch, Keryn E.; Stigler, Melissa H.; Perry, Cheryl L.; Komro, Kelli A.

2010-01-01

Objective: The purpose of this study was to determine whether parents' and children's reports of parenting practices were correlated, whether the reports were differentially associated with alcohol use, and which report had the strongest association with alcohol use. Method: We carried out a cross-sectional and longitudinal study in public schools…

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

A method for determining and exploring the distribution of organic matters and hardness salts in natural waters

NASA Astrophysics Data System (ADS)

Sargsyan, Suren

2017-11-01

A question regarding how organic matters in water are associated with hardness salts hasn't been completely studied. For partially clarifying this question, a water fractional separation and investigation method has been recommended. The experiments carried out by the recommended method showed that the dynamics of the distribution of total hardness and permanganate oxidation values in the fractions of frozen and melted water samples coincided completely based on which it has been concluded that organic matters in natural waters are associated with hardness salts and always distributed in this form. All these findings are useful information for the deep study of macro- and microelements in water.

Dietary patterns derived with multiple methods from food diaries and breast cancer risk in the UK Dietary Cohort Consortium

PubMed Central

Pot, Gerda K; Stephen, Alison M; Dahm, Christina C; Key, Timothy J; Cairns, Benjamin J; Burley, Victoria J; Cade, Janet E; Greenwood, Darren C; Keogh, Ruth H; Bhaniani, Amit; McTaggart, Alison; Lentjes, Marleen AH; Mishra, Gita; Brunner, Eric J; Khaw, Kay Tee

2015-01-01

Background/ Objectives In spite of several studies relating dietary patterns to breast cancer risk, evidence so far remains inconsistent. This study aimed to investigate associations of dietary patterns derived with three different methods with breast cancer risk. Subjects/ Methods The Mediterranean Diet Score (MDS), principal components analyses (PCA) and reduced rank regression (RRR) were used to derive dietary patterns in a case-control study of 610 breast cancer cases and 1891 matched controls within 4 UK cohort studies. Dietary intakes were collected prospectively using 4-to 7-day food diaries and resulting food consumption data were grouped into 42 food groups. Conditional logistic regression models were used to estimate odds ratios (ORs) for associations between pattern scores and breast cancer risk adjusting for relevant covariates. A separate model was fitted for post-menopausal women only. Results The MDS was not associated with breast cancer risk (OR comparing 1st tertile with 3rd 1.20 (95% CI 0.92; 1.56)), nor the first PCA-derived dietary pattern, explaining 2.7% of variation of diet and characterized by cheese, crisps and savoury snacks, legumes, nuts and seeds (OR 1.18 (95% CI 0.91; 1.53)). The first RRR-derived pattern, a ‘high-alcohol’ pattern, was associated with a higher risk of breast cancer (OR 1.27; 95% CI 1.00; 1.62), which was most pronounced in post-menopausal women (OR 1.46 (95% CI 1.08; 1.98). Conclusions A ‘high-alcohol’ dietary pattern derived with RRR was associated with an increased breast cancer risk; no evidence of associations of other dietary patterns with breast cancer risk was observed in this study. PMID:25052230

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes, and Cytokine Signaling Genes in Crohn's Disease

PubMed Central

Carbonetto, Peter; Stephens, Matthew

2013-01-01

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn's disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study. PMID:24098138

Covariance Association Test (CVAT) Identifies Genetic Markers Associated with Schizophrenia in Functionally Associated Biological Processes.

PubMed

Rohde, Palle Duun; Demontis, Ditte; Cuyabano, Beatriz Castro Dias; Børglum, Anders D; Sørensen, Peter

2016-08-01

Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single-marker methods have limited power to detect genetic markers with small effects. Instead, aggregating genetic markers based on biological information might increase the power to identify sets of genetic markers of etiological significance. Several set test methods have been proposed: Here we propose a new set test derived from genomic best linear unbiased prediction (GBLUP), the covariance association test (CVAT). We compared the performance of CVAT to other commonly used set tests. The comparison was conducted using a simulated study population having the same genetic parameters as for schizophrenia. We found that CVAT was among the top performers. When extending CVAT to utilize a mixture of SNP effects, we found an increase in power to detect the causal sets. Applying the methods to a Danish schizophrenia case-control data set, we found genomic evidence for association of schizophrenia with vitamin A metabolism and immunological responses, which previously have been implicated with schizophrenia based on experimental and observational studies. Copyright © 2016 by the Genetics Society of America.

Association between women's autonomy and family planning outcome in couples residing in Isfahan

PubMed Central

Kohan, Shahnaz; Talebian, Ferdos; Ehsanpour, Soheila

2014-01-01

Background: One of the important factors in the prediction of family planning outcome is paying attention to women's role in decision making concerning fertility and household affairs. With the improvement of women's status and autonomy, their control over fertility is expected to increase. The present study aimed to investigate the association between women's autonomy and family planning outcome of the couples residing in Isfahan. Materials and Methods: This is cross-sectional study. Two hundred and seventy women of childbearing age, eligible for family planning and residing in Isfahan, were selected through random cluster sampling and they filled a researcher-made questionnaire. Women's autonomy was measured with the questions on their decision-making autonomy concerning household affairs and physical mobility autonomy. The association between women's autonomy and family planning outcome was analyzed through statistical methods. Results: The results showed that the mean of women's decision-making, physical mobility, and general autonomy was 50. Women's autonomy had a direct significant association with the type of contraception method (P = 0.01) and the length of usage of their present contraception method (P = 0.04) as well as where they received family planning services (P = 0.02). Conclusions: Analysis of data revealed women with higher autonomy used a more efficient contraception method and continued their contraception method for a longer time, which leads to improvement of couples’ family planning outcome. Therefore, family planning services should be planned and provided with women's autonomy under consideration. PMID:25400671

Kernelized Locality-Sensitive Hashing for Fast Image Landmark Association

DTIC Science & Technology

2011-03-24

based Simultaneous Localization and Mapping ( SLAM ). The problem, however, is that vision-based navigation techniques can re- quire excessive amounts of...up and optimizing the data association process in vision-based SLAM . Specifically, this work studies the current methods that algorithms use to...required for location identification than that of other methods. This work can then be extended into a vision- SLAM implementation to subsequently

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Metamethod study of qualitative psychotherapy research on clients' experiences: Review and recommendations.

PubMed

Levitt, Heidi M; Pomerville, Andrew; Surace, Francisco I; Grabowski, Lauren M

2017-11-01

A metamethod study is a qualitative meta-analysis focused upon the methods and procedures used in a given research domain. These studies are rare in psychological research. They permit both the documentation of the informal standards within a field of research and recommendations for future work in that area. This paper presents a metamethod analysis of a substantial body of qualitative research that focused on clients' experiences in psychotherapy (109 studies). This review examined the ways that methodological integrity has been established across qualitative research methods. It identified the numbers of participants recruited and the form of data collection used (e.g., semistructured interviews, diaries). As well, it examined the types of checks employed to increase methodological integrity, such as participant counts, saturation, reflexivity techniques, participant feedback, or consensus and auditing processes. Central findings indicated that the researchers quite flexibly integrated procedures associated with one method into studies using other methods in order to strengthen their rigor. It appeared normative to adjust procedures to advance methodological integrity. These findings encourage manuscript reviewers to assess the function of procedures within a study rather than to require researchers to adhere to the set of procedures associated with a method. In addition, when epistemological approaches were mentioned they were overwhelmingly constructivist in nature, despite the increasing use of procedures traditionally associated with objectivist perspectives. It is recommended that future researchers do more to explicitly describe the functions of their procedures so that they are coherently situated within the epistemological approaches in use. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

GRMDA: Graph Regression for MiRNA-Disease Association Prediction

PubMed Central

Chen, Xing; Yang, Jing-Ru; Guan, Na-Na; Li, Jian-Qiang

2018-01-01

Nowadays, as more and more associations between microRNAs (miRNAs) and diseases have been discovered, miRNA has gradually become a hot topic in the biological field. Because of the high consumption of time and money on carrying out biological experiments, computational method which can help scientists choose the most likely associations between miRNAs and diseases for further experimental studies is desperately needed. In this study, we proposed a method of Graph Regression for MiRNA-Disease Association prediction (GRMDA) which combines known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. We used Gaussian interaction profile kernel similarity to supplement the shortage of miRNA functional similarity and disease semantic similarity. Furthermore, the graph regression was synchronously performed in three latent spaces, including association space, miRNA similarity space, and disease similarity space, by using two matrix factorization approaches called Singular Value Decomposition and Partial Least-Squares to extract important related attributes and filter the noise. In the leave-one-out cross validation and five-fold cross validation, GRMDA obtained the AUCs of 0.8272 and 0.8080 ± 0.0024, respectively. Thus, its performance is better than some previous models. In the case study of Lymphoma using the recorded miRNA-disease associations in HMDD V2.0 database, 88% of top 50 predicted miRNAs were verified by experimental literatures. In order to test the performance of GRMDA on new diseases with no known related miRNAs, we took Breast Neoplasms as an example by regarding all the known related miRNAs as unknown ones. We found that 100% of top 50 predicted miRNAs were verified. Moreover, 84% of top 50 predicted miRNAs in case study for Esophageal Neoplasms based on HMDD V1.0 were verified to have known associations. In conclusion, GRMDA is an effective and practical method for miRNA-disease association prediction. PMID:29515453

GRMDA: Graph Regression for MiRNA-Disease Association Prediction.

PubMed

Chen, Xing; Yang, Jing-Ru; Guan, Na-Na; Li, Jian-Qiang

2018-01-01

Nowadays, as more and more associations between microRNAs (miRNAs) and diseases have been discovered, miRNA has gradually become a hot topic in the biological field. Because of the high consumption of time and money on carrying out biological experiments, computational method which can help scientists choose the most likely associations between miRNAs and diseases for further experimental studies is desperately needed. In this study, we proposed a method of Graph Regression for MiRNA-Disease Association prediction (GRMDA) which combines known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. We used Gaussian interaction profile kernel similarity to supplement the shortage of miRNA functional similarity and disease semantic similarity. Furthermore, the graph regression was synchronously performed in three latent spaces, including association space, miRNA similarity space, and disease similarity space, by using two matrix factorization approaches called Singular Value Decomposition and Partial Least-Squares to extract important related attributes and filter the noise. In the leave-one-out cross validation and five-fold cross validation, GRMDA obtained the AUCs of 0.8272 and 0.8080 ± 0.0024, respectively. Thus, its performance is better than some previous models. In the case study of Lymphoma using the recorded miRNA-disease associations in HMDD V2.0 database, 88% of top 50 predicted miRNAs were verified by experimental literatures. In order to test the performance of GRMDA on new diseases with no known related miRNAs, we took Breast Neoplasms as an example by regarding all the known related miRNAs as unknown ones. We found that 100% of top 50 predicted miRNAs were verified. Moreover, 84% of top 50 predicted miRNAs in case study for Esophageal Neoplasms based on HMDD V1.0 were verified to have known associations. In conclusion, GRMDA is an effective and practical method for miRNA-disease association prediction.

A greater number of somatic pain sites is associated with poor mental health in adolescents: a cross-sectional study

PubMed Central

2013-01-01

Background Identifying indicators of poor mental health during adolescence is a significant public health issue. Previous studies which suggested an association between the number of somatic pains and depression have mainly focused on adults or have employed samples with a narrow age range. To date, results from previous studies have been inconsistent regarding the association between somatic pain and academic impairment. Therefore, the main aims of the present study were to 1) investigate the association between the number of somatic pain sites and poor mental health using a community sample of adolescents aged 12 to 18 years and employing a simple method of assessment, and 2) examine the association between the number of somatic pain sites and perceived academic impairment. Methods Data analysis was conducted using a large cross-sectional survey of adolescents in grades 7 to 12. The one-month prevalence rates for three sites of somatic pain including head, neck and shoulders, and abdomen were examined. Poor mental health was evaluated using the General Health Questionnaire, and perceived academic impairment was measured using a self-report questionnaire. Results A total of 18,104 adolescents participated in the survey. A greater number of pain sites was associated with poor mental health, and this association was consistent across age and gender. There was no difference in effect on mental health between any of the pain sites. Although there was an association between the number of somatic pain sites and perceived academic impairment, the results suggested that the association was mediated by poor mental health. Conclusions Simple reporting methods for assessing the number of pain sites may be a feasible indicator of poor mental health in adolescents. Professionals working with adolescents should consider the possibility of poor mental health, especially when students report multiple somatic pains. PMID:23327684

Adaptive Set-Based Methods for Association Testing

PubMed Central

Su, Yu-Chen; Gauderman, W. James; Kiros, Berhane; Lewinger, Juan Pablo

2017-01-01

With a typical sample size of a few thousand subjects, a single genomewide association study (GWAS) using traditional one-SNP-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. While self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly ‘adapt’ to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a LASSO based test. PMID:26707371

Meat intake and meat preparation in relation to risk of postmenopausal breast cancer in the NIH-AARP diet and health study.

PubMed

Kabat, Geoffrey C; Cross, Amanda J; Park, Yikyung; Schatzkin, Arthur; Hollenbeck, Albert R; Rohan, Thomas E; Sinha, Rashmi

2009-05-15

A number of studies have reported that intake of red meat or meat cooked at high temperatures is associated with increased risk of breast cancer, but other studies have shown no association. We assessed the association between meat, meat-cooking methods, and meat-mutagen intake and postmenopausal breast cancer in the NIH-AARP Diet and Health Study cohort of 120,755 postmenopausal women who completed a food frequency questionnaire at baseline (1995-1996) as well as a detailed meat-cooking module within 6 months following baseline. During 8 years of follow-up, 3,818 cases of invasive breast cancer were identified in this cohort. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI). After adjusting for covariates, intake of total meat, red meat, meat cooked at high temperatures, and meat mutagens showed no association with breast cancer risk. This large prospective study with detailed information on meat preparation methods provides no support for a role of meat mutagens in the development of postmenopausal breast cancer. (c) 2008 Wiley-Liss, Inc.

The Association of Cigarette Smoking With Depression and Anxiety: A Systematic Review

PubMed Central

Taylor, Amy E.; Grabski, Meryem; Munafò, Marcus R.

2017-01-01

Background: Many studies report a positive association between smoking and mental illness. However, the literature remains mixed regarding the direction of this association. We therefore conducted a systematic review evaluating the association of smoking and depression and/or anxiety in longitudinal studies. Methods: Studies were identified by searching PubMed, Scopus, and Web of Science and were included if they: (1) used human participants, (2) were longitudinal, (3) reported primary data, (4) had smoking as an exposure and depression and/or anxiety as an outcome, or (5) had depression and/or anxiety as the exposure and smoking as an outcome. Results: Outcomes from 148 studies were categorized into: smoking onset, smoking status, smoking heaviness, tobacco dependence, and smoking trajectory. The results for each category varied substantially, with evidence for positive associations in both directions (smoking to later mental health and mental health to later smoking) as well as null findings. Overall, nearly half the studies reported that baseline depression/anxiety was associated with some type of later smoking behavior, while over a third found evidence that a smoking exposure was associated with later depression/anxiety. However, there were few studies directly supporting a bidirectional model of smoking and anxiety, and very few studies reporting null results. Conclusions: The literature on the prospective association between smoking and depression and anxiety is inconsistent in terms of the direction of association most strongly supported. This suggests the need for future studies that employ different methodologies, such as Mendelian randomization (MR), which will allow us to draw stronger causal inferences. Implications: We systematically reviewed longitudinal studies on the association of different aspects of smoking behavior with depression and anxiety. The results varied considerably, with evidence for smoking both associated with subsequent depression and anxiety, and vice versa. Few studies supported a bidirectional relationship, or reported null results, and no clear patterns by gender, ethnicity, clinical status, length to follow-up, or diagnostic test. Suggesting that despite advantages of longitudinal studies, they cannot alone provide strong evidence of causality. Therefore, future studies investigating this association should employ different methods allowing for stronger causal inferences to be made, such as MR. PMID:27199385

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies

PubMed Central

Zhang, Yu; Liu, Jun S.

2011-01-01

Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online. PMID:22140288

Association between women's autonomy and family planning outcome in couples residing in Isfahan.

PubMed

Kohan, Shahnaz; Talebian, Ferdos; Ehsanpour, Soheila

2014-09-01

One of the important factors in the prediction of family planning outcome is paying attention to women's role in decision making concerning fertility and household affairs. With the improvement of women's status and autonomy, their control over fertility is expected to increase. The present study aimed to investigate the association between women's autonomy and family planning outcome of the couples residing in Isfahan. This is cross-sectional study. Two hundred and seventy women of childbearing age, eligible for family planning and residing in Isfahan, were selected through random cluster sampling and they filled a researcher-made questionnaire. Women's autonomy was measured with the questions on their decision-making autonomy concerning household affairs and physical mobility autonomy. The association between women's autonomy and family planning outcome was analyzed through statistical methods. The results showed that the mean of women's decision-making, physical mobility, and general autonomy was 50. Women's autonomy had a direct significant association with the type of contraception method (P = 0.01) and the length of usage of their present contraception method (P = 0.04) as well as where they received family planning services (P = 0.02). Analysis of data revealed women with higher autonomy used a more efficient contraception method and continued their contraception method for a longer time, which leads to improvement of couples' family planning outcome. Therefore, family planning services should be planned and provided with women's autonomy under consideration.

Cross-sectional analysis of health-related quality of life and elements of yoga practice.

PubMed

Birdee, Gurjeet S; Ayala, Sujata G; Wallston, Kenneth A

2017-01-31

Mind-body practices such as yoga have been studied for their generally positive effects on health-related quality of life (HRQOL). The association between how a person practices yoga and the person's HRQOL is not known. Yoga practitioners were sent invitations to participate in an online survey via email. Yoga characteristics, HRQOL, and other sociodemographics were collected. Analyses of data from 309 consenting responders evaluated associations between yoga practice characteristics (use of yoga tools, length of practice, location, method, etc.) and the 10-item PROMIS Global Health scale for both physical and mental health components. Multivariable regression models demonstrated higher mental health scores were associated with regular meditation practice, higher income, and the method of practicing in a community group class (versus one-on-one). Higher physical health scores were associated with length of lifetime practice, teacher status, Krishnamacharya yoga style, and practicing in a yoga school/studio (versus at home). Meditation practice in yoga is positively associated with mental health. Length of lifetime yoga practice was significantly associated with better physical health, suggesting yoga has a potential cumulative benefit over time. Different locations and methods of practice may be associated with varying effects on health outcomes. Comparative cross-sectional and longitudinal studies on the variations in yoga practice are needed to further characterize health benefits of yoga.

Assessing the Probability that a Finding Is Genuine for Large-Scale Genetic Association Studies

PubMed Central

Kuo, Chia-Ling; Vsevolozhskaya, Olga A.; Zaykin, Dmitri V.

2015-01-01

Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity of P-values and the automated way they are, as a rule, produced by software packages. Attempts to design simple ways to convert an association P-value into the probability that a finding is spurious have been met with difficulties. The False Positive Report Probability (FPRP) method has gained increasing popularity. However, FPRP is not designed to estimate the probability for a particular finding, because it is defined for an entire region of hypothetical findings with P-values at least as small as the one observed for that finding. Here we propose a method that lets researchers extract probability that a finding is spurious directly from a P-value. Considering the counterpart of that probability, we term this method POFIG: the Probability that a Finding is Genuine. Our approach shares FPRP's simplicity, but gives a valid probability that a finding is spurious given a P-value. In addition to straightforward interpretation, POFIG has desirable statistical properties. The POFIG average across a set of tentative associations provides an estimated proportion of false discoveries in that set. POFIGs are easily combined across studies and are immune to multiple testing and selection bias. We illustrate an application of POFIG method via analysis of GWAS associations with Crohn's disease. PMID:25955023

Assessing the Probability that a Finding Is Genuine for Large-Scale Genetic Association Studies.

PubMed

Kuo, Chia-Ling; Vsevolozhskaya, Olga A; Zaykin, Dmitri V

2015-01-01

Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity of P-values and the automated way they are, as a rule, produced by software packages. Attempts to design simple ways to convert an association P-value into the probability that a finding is spurious have been met with difficulties. The False Positive Report Probability (FPRP) method has gained increasing popularity. However, FPRP is not designed to estimate the probability for a particular finding, because it is defined for an entire region of hypothetical findings with P-values at least as small as the one observed for that finding. Here we propose a method that lets researchers extract probability that a finding is spurious directly from a P-value. Considering the counterpart of that probability, we term this method POFIG: the Probability that a Finding is Genuine. Our approach shares FPRP's simplicity, but gives a valid probability that a finding is spurious given a P-value. In addition to straightforward interpretation, POFIG has desirable statistical properties. The POFIG average across a set of tentative associations provides an estimated proportion of false discoveries in that set. POFIGs are easily combined across studies and are immune to multiple testing and selection bias. We illustrate an application of POFIG method via analysis of GWAS associations with Crohn's disease.

Thai Adolescent Survivors 1 Year after the 2004 Tsunami: A Mixed Methods Study

ERIC Educational Resources Information Center

Tuicomepee, Arunya; Romano, John L.

2008-01-01

This study examined the impact of the 2004 Asian tsunami on 400 Thai adolescents 1 year after the disaster. Quantitative analyses showed that youth behavior problems were positively associated with tsunami experiences and negatively associated with positive family functioning. Tsunami exposure, school connectedness, religious beliefs and…

Chronic Health Conditions and Student Performance at School

ERIC Educational Resources Information Center

Taras, Howard; Potts-Datema, William

2005-01-01

To review the state of research on the association between common chronic health conditions and academic outcomes, the authors reviewed published studies investigating the association of school attendance, cognitive ability, and achievement with a number of chronic diseases. Tables with brief descriptions of each study's research methods and…

Distinct ADHD Symptom Clusters Differentially Associated with Personality Traits

ERIC Educational Resources Information Center

McKinney, Ashley A.; Canu, Will H.; Schneider, H. G.

2013-01-01

Objective: ADHD has been linked to various constructs, yet there is a lack of focus on how its symptom clusters differentially associate with personality, which this study addresses. Method: The current study examines the relationship between impulsive and inattentive ADHD traits and personality, indexed by the Revised NEO Personality Inventory…

Prospective Associations between Dietary Patterns and Cognitive Performance during Adolescence

ERIC Educational Resources Information Center

Nyaradi, Anett; Foster, Jonathan K.; Hickling, Siobhan; Li, Jianghong; Ambrosini, Gina L.; Jacques, Angela; Oddy, Wendy H.

2014-01-01

Background: The aim of the study was to investigate prospective associations between dietary patterns and cognitive performance during adolescence. Methods: Participants were sourced from the Western Australian Pregnancy Cohort (Raine) Study that includes 2868 children born between 1989 and 1992 in Perth, Western Australia. When the children were…

Molecular methods for diagnosis of odontogenic infections.

PubMed

Flynn, Thomas R; Paster, Bruce J; Stokes, Lauren N; Susarla, Srinivas M; Shanti, Rabie M

2012-08-01

Historically, the identification of microorganisms has been limited to species that could be cultured in the microbiology laboratory. The purpose of the present study was to apply molecular techniques to identify microorganisms in orofacial odontogenic infections (OIs). Specimens were obtained from subjects with clinical evidence of OI. To identify the microorganisms involved, 16S rRNA sequencing methods were used on clinical specimens. The name and number of the clones of each species identified and the combinations of species present were recorded for each subject. Descriptive statistics were computed for the study variables. Specimens of pus or wound fluid were obtained from 9 subjects. A mean of 7.4 ± 3.7 (standard deviation) species per case were identified. The predominant species detected in the present study that have previously been associated with OIs were Fusobacterium spp, Parvimonas micra, Porphyromonas endodontalis, and Prevotella oris. The predominant species detected in our study that have not been previously associated with OIs were Dialister pneumosintes and Eubacterium brachy. Unculturable phylotypes accounted for 24% of the species identified in our study. All species detected were obligate or facultative anaerobes. Streptococci were not detected. Molecular methods have enabled us to detect previously cultivated and not-yet-cultivated species in OIs; these methods could change our understanding of the pathogenic flora of orofacial OIs. Copyright © 2012 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Methicillin-resistant Staphylococcus aureus in HIV patients: risk factors associated with colonization and/or infection and methods for characterization of isolates - a systematic review.

PubMed

Ferreira, Dennis de Carvalho; Silva, Glaucilene Rodrigues da; Cavalcante, Fernanda Sampaio; Carmo, Flavia Lima do; Fernandes, Leonardo Alexandre; Moreira, Suelen; Passos, Mauro Romero Leal; Colombo, Ana Paula Vieira; Santos, Katia Regina Netto dos

2014-11-01

Staphylococcus aureus is an important cause of infections and HIV-infected individuals are frequently susceptible to this pathogen. The aim of this study was to perform a systematic review to identify both the risk factors associated with colonization/infection by methicillin-resistant S. aureus in HIV patients and the methods used for characterization of isolates. An electronic search of articles published between January 2001 and December 2013 was first conducted. Among 116 studies categorized as being at a quality level of A, B or C, only 9 studies were considered to have high methodological quality (level A). The majority of these studies were retrospective (4/9 studies). The risk factors associated with colonization/infection by S. aureus were use of antimicrobials (4/9 studies), previous hospitalization (4/9 studies) and low CD4+ T lymphocyte counts (<200 cells/μl) (3/9 studies). Culture in mannitol salt agar (3/9 studies) and the latex agglutination test (5/9 studies) were the main methods used for bacterial phenotypic identification. Genotypic profiles were accessed by pulsed-field gel electrophoresis (6/9 studies) and USA300 was the most prevalent lineage (5/9 studies). Most isolates were resistant to erythromycin (3/9 studies) and susceptible to vancomycin (4/9 studies). Ultimately, use of antimicrobials and previous hospitalization were the main risk factors for colonization/infection by methicillin-resistant S. aureus in HIV-infected individuals. However, the numbers of evaluated patients, the exclusion and inclusion criteria and the characterization of the S. aureus isolates were not uniform, which made it difficult to establish the characteristics associated with HIV patients who are colonized/infected by S. aureus.

Adolescents: Contraceptive Knowledge and Use, a Brazilian Study

PubMed Central

Correia, Divanise S.; Pontes, Ana C. P.; Cavalcante, Jairo C.; Egito, E. Sócrates T.; Maia, Eulália M.C.

2009-01-01

The purpose of this study was to identify the knowledge and use of contraceptive methods by female adolescent students. The study was cross-sectional and quantitative, using a semi-structured questionnaire that was administered to 12- to 19-year-old female students in Maceió, Brazil. A representative and randomized sample was calculated, taking into account the number of hospital admissions for curettage. This study was approved by the Human Research Ethics Committee, and Epi InfoTM software was used for data and result evaluation using the mean and chi-square statistical test. Our results show that the majority of students know of some contraceptive methods (95.5%), with the barrier/hormonal methods being the most mentioned (72.4%). Abortion and aborting drugs were inaccurately described as contraceptives, and 37.9% of the sexually active girls did not make use of any method. The barrier methods were the most used (35.85%). A significant association was found in the total sample (2,592) between pregnancy and the use of any contraceptive method. This association was not found, however, in the group having an active sexual life (559). The study points to a knowledge of contraceptive methods, especially by teenagers who have already been pregnant, but contraceptives were not adequately used. The low use of chemical methods of contraception brings the risk of pregnancy. Since abortion and aborting drugs were incorrectly cited as contraceptive methods, this implies a nonpreventive attitude towards pregnancy. PMID:19151897

Chemical screening method for the rapid identification of microbial sources of marine invertebrate-associated metabolites.

PubMed

Berrue, Fabrice; Withers, Sydnor T; Haltli, Brad; Withers, Jo; Kerr, Russell G

2011-03-21

Marine invertebrates have proven to be a rich source of secondary metabolites. The growing recognition that marine microorganisms associated with invertebrate hosts are involved in the biosynthesis of secondary metabolites offers new alternatives for the discovery and development of marine natural products. However, the discovery of microorganisms producing secondary metabolites previously attributed to an invertebrate host poses a significant challenge. This study describes an efficient chemical screening method utilizing a 96-well plate-based bacterial cultivation strategy to identify and isolate microbial producers of marine invertebrate-associated metabolites.

Carbohydrate Intake Exhibited a Positive Association with the Risk of Metabolic Syndrome in Both Semi-Quantitative Food Frequency Questionnaires and 24-Hour Recall in Women.

PubMed

Ahn, Jaeouk; Kim, Nam Soo; Lee, Byung Kook; Park, Sunmin

2017-09-01

We compared the usual nutrient intake in both the semi-quantitative food frequency questionnaire (SQFFQ) and 24-hour recall methods and determined the association between metabolic syndrome (MetS) risk and nutrient intake calculated by both methods in Korea National Health and Nutrition Examination Survey (KNHANES; 2012-2014) data. Adjusted odds ratios for MetS were calculated according to the intake of macronutrients, measured by the 2 methods in 10,286 adults, while controlling for covariates associated with MetS. Fat and carbohydrate intake (energy percent) calculated by 24-hour recall and SQFFQ was significantly different between the MetS and non-MetS groups, particularly in women. The differences in other nutrient intakes determined by both methods were mainly non-significant. The correlation coefficients between the 2 methods were about 0.4 for most nutrients except total vitamin A and iron (Fe). Energy intake according to gender and MetS presence was similar between the 2 methods. Carbohydrate intake exhibited a positive association with the MetS risk, while fat intake showed a negative association in both methods. The association exhibited a gender interaction with carbohydrate and fat intake calculated by 24-hour recall: women exhibited a significant association. However, for the SQFFQ a gender interaction was evident only for carbohydrate intake. In diet quality index of SQFFQ the adequacy of vegetables and total fat intake was higher in the non-MetS than the MetS. In conclusion, the MetS prevalence exhibited a positive association with carbohydrate intake only in women, as assessed by 24-hour recall and SQFFQ. The SQFFQ can be used to assess the association between usual food intake and MetS risk in large population studies. © 2017 The Korean Academy of Medical Sciences.

A Unified Framework for Association Analysis with Multiple Related Phenotypes

PubMed Central

Stephens, Matthew

2013-01-01

We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737

Poisson Approximation-Based Score Test for Detecting Association of Rare Variants.

PubMed

Fang, Hongyan; Zhang, Hong; Yang, Yaning

2016-07-01

Genome-wide association study (GWAS) has achieved great success in identifying genetic variants, but the nature of GWAS has determined its inherent limitations. Under the common disease rare variants (CDRV) hypothesis, the traditional association analysis methods commonly used in GWAS for common variants do not have enough power for detecting rare variants with a limited sample size. As a solution to this problem, pooling rare variants by their functions provides an efficient way for identifying susceptible genes. Rare variant typically have low frequencies of minor alleles, and the distribution of the total number of minor alleles of the rare variants can be approximated by a Poisson distribution. Based on this fact, we propose a new test method, the Poisson Approximation-based Score Test (PAST), for association analysis of rare variants. Two testing methods, namely, ePAST and mPAST, are proposed based on different strategies of pooling rare variants. Simulation results and application to the CRESCENDO cohort data show that our methods are more powerful than the existing methods. © 2016 John Wiley & Sons Ltd/University College London.

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

Association of SNP rs1867277 in FOXE1 Gene and Cleft Lip with or without Cleft Palate in a Han Chinese Population.

PubMed

Xie, Liang; Deng, Ying; Yuan, Yumei; Tan, Xiong; Liu, Lijun; Li, Nana; Deng, Changfei; Liu, Hanmin; Dai, Li

2018-04-01

The genetic factors causing cleft lip with or without cleft palate (CL ± P) are still unclear. The SNPs in FOXE1 gene were associated with CL ± P. However, the results have been inconsistent. We explored the associations of four SNPs in FOXE1 gene and CL ± P by a family based study. 128 children with CL ± P and their parents were recruited. rs3758249 and rs1867277 were genotyped by high-resolution melting curve (HRM) method, whereas rs1443434 and rs907577 were genotyped by Sequenom MassARRAY® method. The software PLINK, FBAT and FAMHAP were used for analyzing data. rs1867277 was associated with CL ± P (P m = 0.0395). The patients were divided into two subgroups, individuals with cleft lip only and persons with cleft lip and palate. There were no associations in subgroup analyses. We confirmed the association of FOXE1 gene and CL ± P by a family based study. For the first time, rs1867277 was significantly associated with CL ± P.

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

PubMed

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

Introductory guide to the statistics of molecular genetics.

PubMed

Eley, Thalia C; Rijsdijk, Frühling

2005-10-01

This introductory guide presents the main two analytical approaches used by molecular geneticists: linkage and association. Traditional linkage and association methods are described, along with more recent advances in methodologies such as those using a variance components approach. New methods are being developed all the time but the core principles of linkage and association remain the same. The basis of linkage is the transmission of a marker along with a disease within families, whereas association is based on the comparison of marker frequencies in case and control groups. It is becoming increasingly clear that effect sizes of individual markers on diseases and traits are likely to be very small. As such, much greater power is needed, and correspondingly greater sample sizes. Although non-replication is still a problem, molecular genetic studies in some areas such as attention deficit/hyperactivity disorder (ADHD) are starting to show greater convergence. Epidemiologists and other researchers with large well-characterized samples will be well placed to use these methods. Inter-disciplinary studies can then ask far more interesting questions such as those relating to developmental, multivariate and gene-environment interaction hypotheses.

Performance of human fecal anaerobe-associated PCR-based assays in a multi-laboratory method evaluation study

EPA Science Inventory

A number of PCR-based methods for detecting human fecal material in environmental waters have been developed over the past decade, but these methods have rarely received independent comparative testing. Here, we evaluated ten of these methods (BacH, BacHum-UCD, B. thetaiotaomic...

Evaluation of a modified method to measure total starch in animal feeds

USDA-ARS?s Scientific Manuscript database

The AOAC method 996.11 has been recognized as an accurate, repeatable, and efficient method to measure total starch in animal feeds. However, analyzing starch using the AOAC method can be expensive and associated with technical challenges. The objective of this study was to determine if an alternati...

Lifestyle Factors and Visible Skin Aging in a Population of Japanese Elders

PubMed Central

Asakura, Keiko; Nishiwaki, Yuji; Milojevic, Ai; Michikawa, Takehiro; Kikuchi, Yuriko; Nakano, Makiko; Iwasawa, Satoko; Hillebrand, Greg; Miyamoto, Kukizo; Ono, Masaji; Kinjo, Yoshihide; Akiba, Suminori; Takebayashi, Toru

2009-01-01

Background The number of studies that use objective and quantitative methods to evaluate facial skin aging in elderly people is extremely limited, especially in Japan. Therefore, in this cross-sectional study we attempted to characterize the condition of facial skin (hyperpigmentation, pores, texture, and wrinkling) in Japanese adults aged 65 years or older by using objective and quantitative imaging methods. In addition, we aimed to identify lifestyle factors significantly associated with these visible signs of aging. Methods The study subjects were 802 community-dwelling Japanese men and women aged at least 65 years and living in the town of Kurabuchi (Takasaki City, Gunma Prefecture, Japan), a mountain community with a population of approximately 4800. The facial skin condition of subjects was assessed quantitatively using a standardized facial imaging system and subsequent computer image analysis. Lifestyle information was collected using a structured questionnaire. The association between skin condition and lifestyle factors was examined using multivariable regression analysis. Results Among women, the mean values for facial texture, hyperpigmentation, and pores were generally lower than those among age-matched men. There was no significant difference between sexes in the severity of facial wrinkling. Older age was associated with worse skin condition among women only. After adjusting for age, smoking status and topical sun protection were significantly associated with skin condition among both men and women. Conclusions Our study revealed significant differences between sexes in the severity of hyperpigmentation, texture, and pores, but not wrinkling. Smoking status and topical sun protection were significantly associated with signs of visible skin aging in this study population. PMID:19700917

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

PubMed

Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

The Brain-Derived Neurotrophic Factor Val66Met Polymorphism, Delivery Method, Birth Weight, and Night Sleep Duration as Determinants of Obesity in Vietnamese Children of Primary School Age.

PubMed

Tuyet, Le Thi; Nhung, Bui Thi; Dao, Duong Thi Anh; Hanh, Nguyen Thi Hong; Tuyen, Le Danh; Binh, Tran Quang; Thuc, Vu Thi Minh

2017-10-01

Obesity is a complex disease that involves both environmental and genetic factors in its pathogenesis. Several studies have identified multiple obesity-associated loci in many populations. However, their contribution to obesity in the Vietnamese population is not fully described, especially in children. The study aimed to investigate the association of obesity with Val66Met polymorphism in brain-derived neurotrophic factor (BDNF) gene, delivery method, birth weight, and lifestyle factors in Vietnamese primary school children. A case-control study was conducted on 559 children aged 6-11 years (278 obese cases and 281 normal controls). The obesity of the children was classified using both criteria of International Obesity Task Force (IOTF, 2000) and World Health Organization (WHO, 2007). Lifestyle factors, birth delivery, and birth weight of the children were self-reported by parents. The BDNF genotype was analyzed using the polymerase chain reaction-restriction fragment length polymorphism method. Association was evaluated by multivariate logistic regression and cross-validated by the Bayesian model averaging method. The most significantly independent factors for obesity were delivery method (cesarean section vs. vaginal delivery, β = 0.56, p = 0.007), birth weight (>3500 to <4000 g vs. 2500-3500 g, β = 0.52, p = 0.035; ≥4000 g vs. 2500-3500 g, β = 1.06, p = 0.015), night sleep duration (<8 h/day vs. ≥8 h/day, β = 0.99, p < 0.0001), and BDNF Val66Met polymorphism (AA and GG vs. AG, β = 0.38, p = 0.039). The study suggested the significant association of delivery method, birth weight, night sleep duration, and BDNF Val66Met polymorphism, with obesity in Vietnamese primary school children.

Signatures of polygenic adaptation associated with climate across the range of a threatened fish species with high genetic connectivity.

PubMed

Harrisson, Katherine A; Amish, Stephen J; Pavlova, Alexandra; Narum, Shawn R; Telonis-Scott, Marina; Rourke, Meaghan L; Lyon, Jarod; Tonkin, Zeb; Gilligan, Dean M; Ingram, Brett A; Lintermans, Mark; Gan, Han Ming; Austin, Christopher M; Luikart, Gordon; Sunnucks, Paul

2017-11-01

Adaptive differences across species' ranges can have important implications for population persistence and conservation management decisions. Despite advances in genomic technologies, detecting adaptive variation in natural populations remains challenging. Key challenges in gene-environment association studies involve distinguishing the effects of drift from those of selection and identifying subtle signatures of polygenic adaptation. We used paired-end restriction site-associated DNA sequencing data (6,605 biallelic single nucleotide polymorphisms; SNPs) to examine population structure and test for signatures of adaptation across the geographic range of an iconic Australian endemic freshwater fish species, the Murray cod Maccullochella peelii. Two univariate gene-association methods identified 61 genomic regions associated with climate variation. We also tested for subtle signatures of polygenic adaptation using a multivariate method (redundancy analysis; RDA). The RDA analysis suggested that climate (temperature- and precipitation-related variables) and geography had similar magnitudes of effect in shaping the distribution of SNP genotypes across the sampled range of Murray cod. Although there was poor agreement among the candidate SNPs identified by the univariate methods, the top 5% of SNPs contributing to significant RDA axes included 67% of the SNPs identified by univariate methods. We discuss the potential implications of our findings for the management of Murray cod and other species generally, particularly in relation to informing conservation actions such as translocations to improve evolutionary resilience of natural populations. Our results highlight the value of using a combination of different approaches, including polygenic methods, when testing for signatures of adaptation in landscape genomic studies. © 2017 John Wiley & Sons Ltd.

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise.

PubMed

Rosenheim, Jay A; Gratton, Claudio

2017-01-31

Ecoinformatics, as defined in this review, is the use of preexisting data sets to address questions in ecology. We provide the first review of ecoinformatics methods in agricultural entomology. Ecoinformatics methods have been used to address the full range of questions studied by agricultural entomologists, enabled by the special opportunities associated with data sets, nearly all of which have been observational, that are larger and more diverse and that embrace larger spatial and temporal scales than most experimental studies do. We argue that ecoinformatics research methods and traditional, experimental research methods have strengths and weaknesses that are largely complementary. We address the important interpretational challenges associated with observational data sets, highlight common pitfalls, and propose some best practices for researchers using these methods. Ecoinformatics methods hold great promise as a vehicle for capitalizing on the explosion of data emanating from farmers, researchers, and the public, as novel sampling and sensing techniques are developed and digital data sharing becomes more widespread.

Water Quality Management Studies. Postimpoundment Study of R.E. ’Bob’ Woodruff Lake, Alabama River, Alabama.

DTIC Science & Technology

1984-08-01

8 3. Water-quality, sediment, and biological parameters, associated units, EPA STORET codes, container type, 0 preservative and methods used for...Section III.B). Water samples were collected and preserved according to * _ approved EPA (1974) or American Public Health Association (APHA) (1975...procedures. Water-quality parameters tested, associated units, EPA STORET codes, test procedures, and preservation tech- niques used throughout the

Association between School Policies and Built Environment, and Youth's Participation in Various Types of Physical Activities

ERIC Educational Resources Information Center

Ward, Stephanie; Bélanger, Mathieu; Donovan, Denise; Caissie, Isabelle; Goguen, Julie; Vanasse, Allain

2015-01-01

Background: School environmental characteristics may be associated with youth's participation in different types of physical activities (PAs). This study aimed to identify which school policies and built environmental characteristics were associated with participation in organized, nonorganized, individual, and group-based activities. Methods:…

The Association of Attention Deficit Hyperactivity Disorder with Socioeconomic Disadvantage: Alternative Explanations and Evidence

ERIC Educational Resources Information Center

Russell, Ginny; Ford, Tamsin; Rosenberg, Rachel; Kelly, Susan

2014-01-01

Background: Studies throughout Northern Europe, the United States and Australia have found an association between childhood attention deficit hyperactivity disorder (ADHD) and family socioeconomic disadvantage. We report further evidence for the association and review potential causal pathways that might explain the link. Methods: Secondary…

Statistical testing and power analysis for brain-wide association study.

PubMed

Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

2018-04-05

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

Family-based association study of 5-HT(2A) receptor T102C polymorphism and suicidal behavior in Ashkenazi inpatient adolescents.

PubMed

Zalsman, Gil; Frisch, Amos; Baruch-Movshovits, Ruth; Sher, Leo; Michaelovsky, Elena; King, Robert A; Fischel, Tsvi; Hermesh, Haggai; Goldberg, Pablo; Gorlyn, Marianne; Misgav, Sagit; Apter, Alan; Tyano, Sam; Weizman, Abraham

2005-01-01

Suicidal behavior runs in families and is partially genetically determined. Since greater serotonin 5-HT(2A) receptor binding has been reported in postmortem brain and platelets of suicide victims, the 5-HT(2A) receptor gene polymorphism T102C became one of the candidate sites in the study of suicide and impulsive-aggressive traits. However, studies that examined the association of this polymorphism with suicidality have contradictory results. This study used a family-based method and one homogenous ethnic group to overcome ethnic stratification in order to test this association. Thirty families of inpatient adolescents from Jewish Ashkenazi origin, with a recent suicide attempt, were genotyped. All subjects were interviewed for clinical diagnosis, depressive and impulsive-aggressive traits and demographic data. Allele frequencies were assessed using the Haplotype Relative Risk method for trios. No difference was found in allelic distribution between transmitted and non-transmitted alleles. There was no significant association of genotype with any of the clinical traits These preliminary results suggest that the 5-HT(2A) T102C polymorphism is unlikely to be associated with suicidal behavior and related traits in adolescent suicide attempters.

Generalizing Terwilliger's likelihood approach: a new score statistic to test for genetic association.

PubMed

el Galta, Rachid; Uitte de Willige, Shirley; de Visser, Marieke C H; Helmer, Quinta; Hsu, Li; Houwing-Duistermaat, Jeanine J

2007-09-24

In this paper, we propose a one degree of freedom test for association between a candidate gene and a binary trait. This method is a generalization of Terwilliger's likelihood ratio statistic and is especially powerful for the situation of one associated haplotype. As an alternative to the likelihood ratio statistic, we derive a score statistic, which has a tractable expression. For haplotype analysis, we assume that phase is known. By means of a simulation study, we compare the performance of the score statistic to Pearson's chi-square statistic and the likelihood ratio statistic proposed by Terwilliger. We illustrate the method on three candidate genes studied in the Leiden Thrombophilia Study. We conclude that the statistic follows a chi square distribution under the null hypothesis and that the score statistic is more powerful than Terwilliger's likelihood ratio statistic when the associated haplotype has frequency between 0.1 and 0.4 and has a small impact on the studied disorder. With regard to Pearson's chi-square statistic, the score statistic has more power when the associated haplotype has frequency above 0.2 and the number of variants is above five.

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

The Effect of PNPLA3 on Fibrosis Progression and Development of Hepatocellular Carcinoma: A Meta-analysis

PubMed Central

Singal, Amit G.; Manjunath, Hema; Yopp, Adam C.; Beg, Muhammad S.; Marrero, Jorge A.; Gopal, Purva; Waljee, Akbar K.

2017-01-01

OBJECTIVES The PNPLA3 rs738409 single-nucleotide polymorphism is known to promote nonalcoholic steatohepatitis (NASH), but its association with fibrosis severity and hepatocellular carcinoma (HCC) risk is less well-defined. The objectives of this study were to determine the association between PNPLA3 and liver fibrosis severity, HCC risk, and HCC prognosis among patients with liver disease. METHODS We performed a systematic literature review using the Medline, PubMed, Scopus, and Embase databases through May 2013 and a manual search of national meeting abstracts from 2010 to 2012. Two investigators independently extracted data on patient populations, study methods, and results using standardized forms. Pooled odds ratios (ORs), according to PNPLA3 genotype, were calculated using the DerSimonian and Laird method for a random effects model. RESULTS Among 24 studies, with 9,915 patients, PNPLA3 was associated with fibrosis severity (OR 1.32, 95 % confidence interval (CI) 1.20–1.45), with a consistent increased risk across liver disease etiologies. Among nine studies, with 2,937 patients, PNPLA3 was associated with increased risk of HCC in patients with cirrhosis (OR 1.40, 95 % CI 1.12–1.75). On subgroup analysis, increased risk of HCC was demonstrated in patients with NASH or alcohol-related cirrhosis (OR 1.67, 95 % CI 1.27–2.21) but not in those with other etiologies of cirrhosis (OR 1.33, 95 % CI 0.96–1.82). Three studies, with 463 patients, do not support an association between PNPLA3 and HCC prognosis but are limited by heterogeneous outcome measures. For all outcomes, most studies were conducted in homogenous Caucasian populations, and studies among racially diverse cohorts are needed. CONCLUSIONS PNPLA3 is associated with an increased risk of advanced fibrosis among patients with a variety of liver diseases and is an independent risk factor for HCC among patients with nonalcoholic steatohepatitis or alcohol-related cirrhosis. PMID:24445574

Paradoxical Acinetobacter-associated ventilator-associated pneumonia incidence rates within prevention studies using respiratory tract applications of topical polymyxin: benchmarking the evidence base.

PubMed

Hurley, J C

2018-04-10

Regimens containing topical polymyxin appear to be more effective in preventing ventilator-associated pneumonia (VAP) than other methods. To benchmark the incidence rates of Acinetobacter-associated VAP (AAVAP) within component (control and intervention) groups from concurrent controlled studies of polymyxin compared with studies of various VAP prevention methods other than polymyxin (non-polymyxin studies). An AAVAP benchmark was derived using data from 77 observational groups without any VAP prevention method under study. Data from 41 non-polymyxin studies provided additional points of reference. The benchmarking was undertaken by meta-regression using generalized estimating equation methods. Within 20 studies of topical polymyxin, the mean AAVAP was 4.6% [95% confidence interval (CI) 3.0-6.9] and 3.7% (95% CI 2.0-5.3) for control and intervention groups, respectively. In contrast, the AAVAP benchmark was 1.5% (95% CI 1.2-2.0). In the AAVAP meta-regression model, group origin from a trauma intensive care unit (+0.55; +0.16 to +0.94, P = 0.006) or membership of a polymyxin control group (+0.64; +0.21 to +1.31, P = 0.023), but not membership of a polymyxin intervention group (+0.24; -0.37 to +0.84, P = 0.45), were significant positive correlates. The mean incidence of AAVAP within the control groups of studies of topical polymyxin is more than double the benchmark, whereas the incidence rates within the groups of non-polymyxin studies and, paradoxically, polymyxin intervention groups are more similar to the benchmark. These incidence rates, which are paradoxical in the context of an apparent effect against VAP within controlled trials of topical polymyxin-based interventions, force a re-appraisal. Copyright © 2018 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies

PubMed Central

Howie, Bryan N.; Donnelly, Peter; Marchini, Jonathan

2009-01-01

Genotype imputation methods are now being widely used in the analysis of genome-wide association studies. Most imputation analyses to date have used the HapMap as a reference dataset, but new reference panels (such as controls genotyped on multiple SNP chips and densely typed samples from the 1,000 Genomes Project) will soon allow a broader range of SNPs to be imputed with higher accuracy, thereby increasing power. We describe a genotype imputation method (IMPUTE version 2) that is designed to address the challenges presented by these new datasets. The main innovation of our approach is a flexible modelling framework that increases accuracy and combines information across multiple reference panels while remaining computationally feasible. We find that IMPUTE v2 attains higher accuracy than other methods when the HapMap provides the sole reference panel, but that the size of the panel constrains the improvements that can be made. We also find that imputation accuracy can be greatly enhanced by expanding the reference panel to contain thousands of chromosomes and that IMPUTE v2 outperforms other methods in this setting at both rare and common SNPs, with overall error rates that are 15%–20% lower than those of the closest competing method. One particularly challenging aspect of next-generation association studies is to integrate information across multiple reference panels genotyped on different sets of SNPs; we show that our approach to this problem has practical advantages over other suggested solutions. PMID:19543373

FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm

PubMed Central

Tuo, Shouheng; Zhang, Junying; Yuan, Xiguo; Zhang, Yuanyuan; Liu, Zhaowen

2016-01-01

Motivation Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS). Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models. Method In this study, two scoring functions (Bayesian network based K2-score and Gini-score) are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA) is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models. Results We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE) which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR), specificity (SPC), positive predictive value (PPV) and accuracy (ACC). Our method has identified two SNPs (rs3775652 and rs10511467) that may be also associated with disease in AMD dataset. PMID:27014873

Protein determination by microchip capillary electrophoresis using an asymmetric squarylium dye: noncovalent labeling and nonequilibrium measurement of association constants.

PubMed

Sloat, Amy L; Roper, Michael G; Lin, Xiuli; Ferrance, Jerome P; Landers, James P; Colyer, Christa L

2008-08-01

In response to a growing interest in the use of smaller, faster microchip (mu-chip) methods for the separation of proteins, advancements are proposed that employ the asymmetric squarylium dye Red-1c as a noncovalent label in mu-chip CE separations. This work compares on-column and precolumn labeling methods for the proteins BSA, beta-lactoglobulin B (beta-LB), and alpha-lactalbumin (alpha-LA). Nonequilibrium CE of equilibrium mixtures (NECEEM) represents an efficient method to determine equilibrium parameters associated with the formation of intermolecular complexes, such as those formed between the dye and proteins in this work, and it allows for the use of weak affinity probes in protein quantitation. In particular, nonequilibrium methods employing both mu-chip and conventional CE systems were implemented to determine association constants governing the formation of noncovalent complexes of the red luminescent squarylium dye Red-1c with BSA and beta-LB. By our mu-chip NECEEM method, the association constants K(assoc) for beta-LB and BSA complexes with Red-1c were found to be 3.53 x 10(3) and 1.65 x 10(5) M(-1), respectively, whereas association constants found by our conventional CE-LIF NECEEM method for these same protein-dye systems were some ten times higher. Despite discrepancies between the two methods, both confirmed the preferential interaction of Red-1c with BSA. In addition, the effect of protein concentration on measured association constant was assessed by conventional CE methods. Although a small decrease in K(assoc) was observed with the increase in protein concentration, our studies indicate that absolute protein concentration may affect the equilibrium determination less than the relative concentration of protein-to-dye.

Validation of cooking methods using shell eggs inoculated with Salmonella serotypes Enteritidis and Heidelberg.

PubMed

Davis, A L; Curtis, P A; Conner, D E; McKee, S R; Kerth, L K

2008-08-01

Salmonella enterica serotype Enteritidis has long been associated with eggs, and more recently, Salmonella enterica serotype Heidelberg has also become associated with eggs. This study was undertaken to determine whether Salmonella Enteritidis and Salmonella Heidelberg are effectively eliminated from eggs by various cooking methods. Seven cooking methods were chosen--hard and soft cooked, scrambled, over easy, sunny-side up, poached, and free poached--and a pan insert and the free-flowing method were used. Shell eggs, purchased from a grocery store, were inoculated with Salmonella and cooked. The cooked eggs were analyzed by USDA-approved methods for Salmonella recovery. Findings indicated that existing cooking methods for the hard-cooked, soft-cooked, and poaching methods were safe. However, the same was not true for the current sunny-side-up, over-easy, and scrambled egg cooking methods.

On Narrative Method, Biography and Narrative Unities in the Study of Teaching.

ERIC Educational Resources Information Center

Connelly, F. Michael; Clandinin, D. Jean

This paper outlines a narrative method for the study of teaching which has as its principle feature the reconstruction of classroom meaning in terms of narrative unities in the lives of classroom participants. This purpose is achieved by comparatively outlining similarities and differences with closely associated lines of work. This study of…

Learning and Study Strategies of Students with Traumatic Brain Injury: A Mixed Method Study

ERIC Educational Resources Information Center

Bush, Erin; Hux, Karen; Zickefoose, Samantha; Simanek, Gina; Holmberg, Michelle; Henderson, Ambyr

2011-01-01

The purpose of this research was to explore the perceptions of four college students with severe traumatic brain injury and people associated with them regarding the use of learning skills and study strategies. The researchers employed a concurrent mixed method design using descriptive quantitative data as well as qualitative multiple case study…

Sex education and contraceptive use at coital debut in the United States: results from Cycle 6 of the National Survey of Family Growth.

PubMed

Isley, Michelle M; Edelman, Alison; Kaneshiro, Bliss; Peters, Dawn; Nichols, Mark D; Jensen, Jeffrey T

2010-09-01

The study was conducted to characterize the relationship between formal sex education and the use and type of contraceptive method used at coital debut among female adolescents. This study employed a cross-sectional, nationally representative database (2002 National Survey of Family Growth). Contraceptive use and type used were compared among sex education groups [abstinence only (AO), birth control methods only (MO) and comprehensive (AM)]. Analyses also evaluated the association between demographic, socioeconomic, behavioral variables and sex education. Multiple logistic regression with adjustment for sampling design was used to measure associations of interest. Of 1150 adolescent females aged 15-19 years, 91% reported formal sex education (AO 20.4%, MO 4.9%, AM 65.1%). The overall use of contraception at coitarche did not differ between groups. Compared to the AO and AM groups, the proportion who used a reliable method in the MO group (37%) was significantly higher (p=.03) (vs. 15.8% and 14.8%, respectively). Data from the 2002 NSFG do not support an association between type of formal sex education and contraceptive use at coitarche but do support an association between abstinence-only messaging and decreased reliable contraceptive method use at coitarche. Copyright 2010 Elsevier Inc. All rights reserved.

Feasibility Study of Using Infrared Radiation Heating as a Sustainable Tomato Peeling Method

USDA-ARS?s Scientific Manuscript database

The yye peeling technique is putting both environmental and economic pressure on California tomato processing industry due to its associated salinity issues and wastewater disposal problems. This study is aimed at developing alternative peeling methods with reduced or no caustic usage to produce hi...

Domestic Violence Assessments in the Child Advocacy Center

ERIC Educational Resources Information Center

Thackeray, Jonathan D.; Scribano, Philip V.; Rhoda, Dale

2010-01-01

Objective: This study was designed to identify the frequency, methods, and practices of universal assessments for domestic violence (DV) within child advocacy centers (CACs) and determine which factors are associated with CACs that conduct universal DV assessments. Methods: The study design was a cross-sectional, web-based survey distributed to…

Pesticide exposure and liver cancer: a review

PubMed Central

VoPham, Trang; Bertrand, Kimberly A.; Hart, Jaime E.; Laden, Francine; Brooks, Maria M.; Yuan, Jian-Min; Talbott, Evelyn O.; Ruddell, Darren; Chang, Chung-Chou H.; Weissfeld, Joel L.

2017-01-01

Purpose To review the epidemiologic literature examining pesticide exposure and liver cancer incidence. Methods A search of the MEDLINE and Embase databases was conducted in October 2015. Eligibility criteria included examining hepatocellular carcinoma (HCC) or primary liver cancer, pesticides as an exposure of interest, and individual-level incidence. The review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results Forty-eight papers were assessed for eligibility and 15 studies were included in the review. The majority of studies were conducted in China and Egypt (n=8), used a case-control design (n=14), and examined HCC (n=14). Most studies showed no association between self-reported and/or occupational exposure to pesticides and liver cancer risk. Six studies demonstrated statistically significant positive associations, including three biomarker-based studies (two using pre-diagnostic sera) that reported higher serum levels of dichlorodiphenyltrichloroethane (DDT) were associated with increased HCC risk. Studies indirectly measuring pesticide exposure using self-reported exposure, occupation, job-exposure matrices, or geographic residence demonstrated inconsistent results. These studies were limited by exposure assessment methods, lack of confounder information, minimal case confirmation, selection bias, and/or over-adjustment. Conclusions There is mixed evidence suggesting a possible association between specific pesticides and HCC risk, with the strongest evidence observed in biomarker-based studies. In particular, organochlorine pesticides, including DDT, may increase HCC risk. Future research should focus on improved pesticide exposure assessment methods, potentially incorporating multiple approaches including biomonitoring while considering the chemicals of interest, historical exposure to address latency periods, and examining specific chemicals and exposure pathways. PMID:28194594

Accuracy and differential bias in copy number measurement of CCL3L1 in association studies with three auto-immune disorders.

PubMed

Carpenter, Danielle; Walker, Susan; Prescott, Natalie; Schalkwijk, Joost; Armour, John Al

2011-08-18

Copy number variation (CNV) contributes to the variation observed between individuals and can influence human disease progression, but the accurate measurement of individual copy numbers is technically challenging. In the work presented here we describe a modification to a previously described paralogue ratio test (PRT) method for genotyping the CCL3L1/CCL4L1 copy variable region, which we use to ascertain CCL3L1/CCL4L1 copy number in 1581 European samples. As the products of CCL3L1 and CCL4L1 potentially play a role in autoimmunity we performed case control association studies with Crohn's disease, rheumatoid arthritis and psoriasis clinical cohorts. We evaluate the PRT methodology used, paying particular attention to accuracy and precision, and highlight the problems of differential bias in copy number measurements. Our PRT methods for measuring copy number were of sufficient precision to detect very slight but systematic differential bias between results from case and control DNA samples in one study. We find no evidence for an association between CCL3L1 copy number and Crohn's disease, rheumatoid arthritis or psoriasis. Differential bias of this small magnitude, but applied systematically across large numbers of samples, would create a serious risk of false positive associations in copy number, if measured using methods of lower precision, or methods relying on single uncorroborated measurements. In this study the small differential bias detected by PRT in one sample set was resolved by a simple pre-treatment by restriction enzyme digestion.

Accuracy and differential bias in copy number measurement of CCL3L1 in association studies with three auto-immune disorders

PubMed Central

2011-01-01

Background Copy number variation (CNV) contributes to the variation observed between individuals and can influence human disease progression, but the accurate measurement of individual copy numbers is technically challenging. In the work presented here we describe a modification to a previously described paralogue ratio test (PRT) method for genotyping the CCL3L1/CCL4L1 copy variable region, which we use to ascertain CCL3L1/CCL4L1 copy number in 1581 European samples. As the products of CCL3L1 and CCL4L1 potentially play a role in autoimmunity we performed case control association studies with Crohn's disease, rheumatoid arthritis and psoriasis clinical cohorts. Results We evaluate the PRT methodology used, paying particular attention to accuracy and precision, and highlight the problems of differential bias in copy number measurements. Our PRT methods for measuring copy number were of sufficient precision to detect very slight but systematic differential bias between results from case and control DNA samples in one study. We find no evidence for an association between CCL3L1 copy number and Crohn's disease, rheumatoid arthritis or psoriasis. Conclusions Differential bias of this small magnitude, but applied systematically across large numbers of samples, would create a serious risk of false positive associations in copy number, if measured using methods of lower precision, or methods relying on single uncorroborated measurements. In this study the small differential bias detected by PRT in one sample set was resolved by a simple pre-treatment by restriction enzyme digestion. PMID:21851606

Association between the accessibility to lethal methods and method-specific suicide rates: An ecological study in Taiwan.

PubMed

Lin, Jin-Jia; Lu, Tsung-Hsueh

2006-07-01

To examine the association between availability of lethal methods of suicide and method-specific suicide rates at the city/ county level in Taiwan. Age-adjusted and age-specific suicide rates of 23 cities/counties in Taiwan for the years 1999 to 2003 were calculated. Partial correlation coefficients were used to examine cross-sectional associations between independent variables, i.e., proportion of agricultural population and proportion of households living on the sixth floor or above, and suicide rates by different methods (poisoning by solids/liquids, jumping, and hanging) after adjusting for unemployment rates and prevalence of depression. The partial correlation coefficient was 0.77 (p < .001) for proportion of agricultural population with solids/liquids poisoning suicide rates. It was 0.73 (p < .001) for the proportion of households living on the sixth floor or above with suicide rates by jumping. Correlations between hanging suicide rates and proportion of agricultural population or between hanging suicide rates and proportion of households living on the sixth floor or above were not significant. The results showed strong positive associations between access to lethal methods and method-specific suicide rates. Controlling the availability of pesticides and fencing high buildings or installing window guards may be effective measures for suicide prevention.

A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors.

PubMed

Zhao, Huaqing; Rebbeck, Timothy R; Mitra, Nandita

2009-12-01

Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors. 2009 Wiley-Liss, Inc.

Testing for genetic association taking into account phenotypic information of relatives.

PubMed

Uh, Hae-Won; Wijk, Henk Jan van der; Houwing-Duistermaat, Jeanine J

2009-12-15

We investigated efficient case-control association analysis using family data. The outcome of interest was coronary heart disease. We employed existing and new methods that take into account the correlations among related individuals to obtain the proper type I error rates. The methods considered for autosomal single-nucleotide polymorphisms were: 1) generalized estimating equations-based methods, 2) variance-modified Cochran-Armitage (MCA) trend test incorporating kinship coefficients, and 3) genotypic modified quasi-likelihood score test. Additionally, for X-linked single-nucleotide polymorphisms we proposed a two-degrees-of-freedom test. Performance of these methods was tested using Framingham Heart Study 500 k array data.

Obesity and Associated Adverse Health Outcomes Among U.S. Military Members and Veterans: Findings from the Millennium Cohort Study

DTIC Science & Technology

2016-06-27

Obesity and Associated Adverse Health Outcomes Among US Military Members and Veterans: Findings from the Millennium Cohort Study Toni Rush1,2,3...Cynthia A. LeardMann3, and Nancy F. Crum-Cianflone1,3,4 Objective: To assess the prevalence of obesity and associated health outcomes among US service...members and veterans. Methods: Data from three survey cycles (2001–2008) of the Millennium Cohort Study were used to examine the prevalence of obesity

The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland.

PubMed

Latkin, Carl A; Edwards, Catie; Davey-Rothwell, Melissa A; Tobin, Karin E

2017-10-01

Social desirability response bias may lead to inaccurate self-reports and erroneous study conclusions. The present study examined the relationship between social desirability response bias and self-reports of mental health, substance use, and social network factors among a community sample of inner-city substance users. The study was conducted in a sample of 591 opiate and cocaine users in Baltimore, Maryland from 2009 to 2013. Modified items from the Marlowe-Crowne Social Desirability Scale were included in the survey, which was conducted face-to-face and using Audio Computer Self Administering Interview (ACASI) methods. There were highly statistically significant differences in levels of social desirability response bias by levels of depressive symptoms, drug use stigma, physical health status, recent opiate and cocaine use, Alcohol Use Disorders Identification Test (AUDIT) scores, and size of social networks. There were no associations between health service utilization measures and social desirability bias. In multiple logistic regression models, even after including the Center for Epidemiologic Studies Depression Scale (CES-D) as a measure of depressive symptomology, social desirability bias was associated with recent drug use and drug user stigma. Social desirability bias was not associated with enrollment in prior research studies. These findings suggest that social desirability bias is associated with key health measures and that the associations are not primarily due to depressive symptoms. Methods are needed to reduce social desirability bias. Such methods may include the wording and prefacing of questions, clearly defining the role of "study participant," and assessing and addressing motivations for socially desirable responses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

PubMed Central

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

Novel Loci Associated with PR Interval in a Genome-Wide Association Study of Ten African American Cohorts

PubMed Central

Butler, Anne M.; Yin, Xiaoyan; Evans, Daniel S.; Nalls, Michael A.; Smith, Erin N.; Tanaka, Toshiko; Li, Guo; Buxbaum, Sarah G.; Whitsel, Eric A.; Alonso, Alvaro; Arking, Dan E.; Benjamin, Emelia J.; Berenson, Gerald S.; Bis, Josh C.; Chen, Wei; Deo, Rajat; Ellinor, Patrick T.; Heckbert, Susan R.; Heiss, Gerardo; Hsueh, Wen-Chi; Keating, Brendan J.; Kerr, Kathleen F.; Li, Yun; Limacher, Marian C.; Liu, Yongmei; Lubitz, Steven A.; Marciante, Kristin D.; Mehra, Reena; Meng, Yan A.; Newman, Anne B.; Newton-Cheh, Christopher; North, Kari E.; Palmer, Cameron D.; Psaty, Bruce M.; Quibrera, P. Miguel; Redline, Susan; Reiner, Alex P.; Rotter, Jerome I.; Schnabel, Renate B.; Schork, Nicholas J.; Singleton, Andrew B.; Smith, J. Gustav; Soliman, Elsayed Z.; Srinivasan, Sathanur R.; Zhang, Zhu-ming; Zonderman, Alan B.; Ferrucci, Luigi; Murray, Sarah S.; Evans, Michele K.; Sotoodehnia, Nona; Magnani, Jared W.; Avery, Christy L.

2013-01-01

Background The PR interval (PR) as measured by the resting, standard 12-lead electrocardiogram (ECG) reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at nine loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans. Methods and Results We present results from the largest genome-wide association study to date of PR in 13,415 adults of African descent from ten cohorts. We tested for association between PR (ms) and approximately 2.8 million genotyped and imputed single nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (lambda range: 0.9–1.1), although not after genomic control correction was applied to the overall meta-analysis (lambda: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0×10−8), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained two additional independent secondary signals influencing PR (P<5.0×10−8). Conclusions This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European and Asian descent. PMID:23139255

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Human MAIT-cell responses to Escherichia coli: activation, cytokine production, proliferation, and cytotoxicity.

PubMed

Dias, Joana; Sobkowiak, Michał J; Sandberg, Johan K; Leeansyah, Edwin

2016-07-01

Mucosa-associated invariant T cells are a large and relatively recently described innate-like antimicrobial T-cell subset in humans. These cells recognize riboflavin metabolites from a range of microbes presented by evolutionarily conserved major histocompatibility complex, class I-related molecules. Given the innate-like characteristics of mucosa-associated invariant T cells and the novel type of antigens they recognize, new methodology must be developed and existing methods refined to allow comprehensive studies of their role in human immune defense against microbial infection. In this study, we established protocols to examine a range of mucosa-associated invariant T-cell functions as they respond to antigen produced by Escherichia coli These improved and dose- and time-optimized experimental protocols allow detailed studies of MR1-dependent mucosa-associated invariant T-cell responses to Escherichia coli pulsed antigen-presenting cells, as assessed by expression of activation markers and cytokines, by proliferation, and by induction of apoptosis and death in major histocompatibility complex, class I-related-expressing target cells. The novel and optimized protocols establish a framework of methods and open new possibilities to study mucosa-associated invariant T-cell immunobiology, using Escherichia coli as a model antigen. Furthermore, we propose that these robust experimental systems can also be adapted to study mucosa-associated invariant T-cell responses to other microbes and types of antigen-presenting cells. © The Author(s).

Higher Weight, Lower Education: A Longitudinal Association between Adolescents' Body Mass Index and Their Subsequent Educational Achievement Level?

ERIC Educational Resources Information Center

Larsen, Junilla K.; Kleinjan, Marloes; Engels, Rutger C. M. E.; Fisher, Jennifer O.; Hermans, Roel

2014-01-01

Background: The purpose of this study was to examine the association between adolescents' body mass index (BMI) z-scores and their subsequent level of schooling, extending previous longitudinal research by using objectively measured weight and height data. Methods: A longitudinal study with 3 study waves (1-year intervals) involving 1248 Dutch…

Measuring diet cost at the individual level: a comparison of three methods.

PubMed

Monsivais, P; Perrigue, M M; Adams, S L; Drewnowski, A

2013-11-01

Household-level food spending data are not suitable for population-based studies of the economics of nutrition. This study compared three methods of deriving diet cost at the individual level. Adult men and women (n=164) completed 4-day diet diaries and a food frequency questionnaire (FFQ). Food expenditures over 4 weeks and supermarket prices for 384 foods were obtained. Diet costs (US$/day) were estimated using: (1) diet diaries and expenditures; (2) diet diaries and supermarket prices; and (3) FFQs and supermarket prices. Agreement between the three methods was assessed on the basis of Pearson correlations and limits of agreement. Income-related differences in diet costs were estimated using general linear models. Diet diaries yielded mean (s.d.) diet costs of $10.04 (4.27) based on Method 1 and $8.28 (2.32) based on Method 2. FFQs yielded mean diet costs of $7.66 (2.72) based on Method 3. Correlations between energy intakes and costs were highest for Method 3 (r(2)=0.66), lower for Method 2 (r(2)=0.24) and lowest for Method 1 (r(2)=0.06). Cost estimates were significantly associated with household incomes. The weak association between food expenditures and food intake using Method 1 makes it least suitable for diet and health research. However, merging supermarket food prices with standard dietary assessment tools can provide estimates of individual diet cost that are more closely associated with food consumed. The derivation of individual diet cost can provide insights into some of the economic determinants of food choice, diet quality and health.

Stability-based validation of dietary patterns obtained by cluster analysis.

PubMed

Sauvageot, Nicolas; Schritz, Anna; Leite, Sonia; Alkerwi, Ala'a; Stranges, Saverio; Zannad, Faiez; Streel, Sylvie; Hoge, Axelle; Donneau, Anne-Françoise; Albert, Adelin; Guillaume, Michèle

2017-01-14

Cluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have an influence on the results. Therefore, there is a need of an objective methodology helping researchers in their decisions during cluster analysis. The objective of this study was to use such a methodology based on stability of clustering solutions to select the most appropriate clustering method and number of clusters for describing dietary patterns in the NESCAV study (Nutrition, Environment and Cardiovascular Health), a large population-based cross-sectional study in the Greater Region (N = 2298). Clustering solutions were obtained with K-means, K-medians and Ward's method and a number of clusters varying from 2 to 6. Their stability was assessed with three indices: adjusted Rand index, Cramer's V and misclassification rate. The most stable solution was obtained with K-means method and a number of clusters equal to 3. The "Convenient" cluster characterized by the consumption of convenient foods was the most prevalent with 46% of the population having this dietary behaviour. In addition, a "Prudent" and a "Non-Prudent" patterns associated respectively with healthy and non-healthy dietary habits were adopted by 25% and 29% of the population. The "Convenient" and "Non-Prudent" clusters were associated with higher cardiovascular risk whereas the "Prudent" pattern was associated with a decreased cardiovascular risk. Associations with others factors showed that the choice of a specific dietary pattern is part of a wider lifestyle profile. This study is of interest for both researchers and public health professionals. From a methodological standpoint, we showed that using stability of clustering solutions could help researchers in their choices. From a public health perspective, this study showed the need of targeted health promotion campaigns describing the benefits of healthy dietary patterns.

Associations of Truancy, Perceived School Performance, and Mental Health with Alcohol Consumption among Adolescents

ERIC Educational Resources Information Center

Holtes, Muriel; Bannink, Rienke; Joosten-van Zwanenburg, Evelien; van As, Els; Raat, Hein; Broeren, Suzanne

2015-01-01

Background: This study examined associations of truancy, perceived school performance, and mental health with adolescents' week, weekend, and binge drinking. Methods: A cross-sectional study was conducted among 1167 secondary school students of Dutch ethnicity (mean age, 15.9 years, SD?=?0.69). Alcohol consumption, truancy, perceived school…

Typologies of Childhood Exposure to Violence: Associations with College Student Mental Health

ERIC Educational Resources Information Center

Miller-Graff, Laura E.; Howell, Kathryn H.; Martinez-Torteya, Cecilia; Hunter, Erin C.

2015-01-01

Objective: This study examined typologies of childhood violence exposure (CVE) and the associations of profiles with current demographic characteristics and mental health in emerging adulthood. Participants: The study evaluated a sample of college students from 2 US geographic regions (Midwest, n = 195; Southeast, n = 200). Methods: An online…

Controls on architecture of Argentine limestone and associated strata in northeastern Kansas. A firstcut method for evaluating limestone aggregate durability using spectral scintillometry

DOT National Transportation Integrated Search

2006-10-01

Missourian strata were studied in eastern Kansas to evaluate the build-and-fill controls on strata deposited in association with high-amplitude glacioeustatic sea-level fluctuations. Results from this study show that creation of relief in high-freque...

Evidence for Shared Genetic Risk between ADHD Symptoms and Reduced Mathematics Ability: A Twin Study

ERIC Educational Resources Information Center

Greven, Corina U.; Kovas, Yulia; Willcutt, Erik G.; Petrill, Stephen A.; Plomin, Robert

2013-01-01

Background: Attention-deficit/hyperactivity disorder (ADHD) symptoms and mathematics ability are associated, but little is known about the genetic and environmental influences underlying this association. Methods: Data came from more than 6,000 twelve-year-old twin pairs from the UK population-representative Twins Early Development Study. Parents…

Sociocognitive Factors and Perceived Consequences Associated with Alternative Forms of Alcohol Use

ERIC Educational Resources Information Center

Braitman, Abby L.; Linden-Carmichael, Ashley N.; Stamates, Amy L.; Lau-Barraco, Cathy

2017-01-01

Objective: Popular media have highly publicized alternative forms of alcohol use (e.g., eyeballing, inhaling alcohol vapor) among college students as a growing concern, possibly associated with severe health risks. Formative research indicates rarity of use. Participants and Methods: College students (Study 1: n = 411; Study 2: n = 687) completed…

Genome-Wide Association Study of Receptive Language Ability of 12-Year-Olds

ERIC Educational Resources Information Center

Harlaar, Nicole; Meaburn, Emma L.; Hayiou-Thomas, Marianna E.; Davis, Oliver S. P.; Docherty, Sophia; Hanscombe, Ken B.; Haworth, Claire M. A.; Price, Thomas S.; Trzaskowski, Maciej; Dale, Philip S.; Plomin, Robert

2014-01-01

Purpose: Researchers have previously shown that individual differences in measures of receptive language ability at age 12 are highly heritable. In the current study, the authors attempted to identify some of the genes responsible for the heritability of receptive language ability using a "genome-wide association" approach. Method: The…

Hyperactive-Impulsive Symptoms Associated with Self-Reported Sleep Quality in Nonmedicated Adults with ADHD

ERIC Educational Resources Information Center

Mahajan, Neha; Hong, Nuong; Wigal, Timothy L.; Gehricke, Jean-G.

2010-01-01

Objective: Individuals with ADHD often report sleep problems. Though most studies on ADHD and sleep examined children or nonclinically diagnosed adults, the present study specifically examines nonmedicated adults with ADHD to determine whether inattentive and hyperactive-impulsive symptoms are associated with sleep problems. Method: A total of 22…

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Spatial data analysis for exploration of regional scale geothermal resources

NASA Astrophysics Data System (ADS)

Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

2013-10-01

Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

Design and analysis of multiple diseases genome-wide association studies without controls.

PubMed

Chen, Zhongxue; Huang, Hanwen; Ng, Hon Keung Tony

2012-11-15

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls. Copyright © 2012 Elsevier B.V. All rights reserved.

Incorporating Functional Genomic Information in Genetic Association Studies Using an Empirical Bayes Approach.

PubMed

Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2016-04-01

There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses.

PubMed

Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick

2016-01-05

Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Factors associated with law enforcement-related use-of-force injury.

PubMed

Castillo, Edward M; Prabhakar, Nitin; Luu, Bethi

2012-05-01

Use-of-force (UOF) techniques are used by law enforcement to gain control of noncompliant subjects. The purpose of this study was to assess factors associated with subject and deputy injuries during law enforcement UOF. This is a retrospective study of nonlethal UOF events from January to June 2009 by a single law enforcement agency serving a population of 3 million. A standard data collection tool, which included basic demographic data, the type of force used, subject response, and if there were any injuries to the subject or deputies involved, was used by deputies for each UOF event. Descriptive statistics were used to describe the specific subject and incident details. Univariate and multivariate analysis was used to identify factors potentially associated with subject and deputy injuries. There were 1174 UOF incidents recorded during the study period. A total of 282 incidents (24%) involved no physical force, 135 (11.5%) involved less lethal methods, 620 (52.8%) involved other physical restraint methods, and 137 (11.7%) involved both less lethal and other physical methods. Factors with the largest independent associations with subject injury were physical resistance by the subject (odds ratio [OR], 2.65; 95% confidence interval [CI], 1.49-4.74) and force used to prevent a violent felony (OR, 2.15; 95% CI, 1.24-3.71). When the subject had a weapon (OR, 4.15; 95% CI, 1.53-11.23) and physical resistance by the subject (OR, 4.15; 95% CI, 1.24-13.94) had the largest associations with deputy injury. This study identifies situational characteristics potentially associated with subject and deputy injuries during UOF events. Copyright © 2012 Elsevier Inc. All rights reserved.

Associations of learning style with cultural values and demographics in nursing students in Iran and Malaysia

PubMed Central

Abdollahimohammad, Abdolghani; Ja’afar, Rogayah

2015-01-01

Purpose: The goal of the current study was to identify associations between the learning style of nursing students and their cultural values and demographic characteristics. Methods: A non-probability purposive sampling method was used to gather data from two populations. All 156 participants were female, Muslim, and full-time degree students. Data were collected from April to June 2010 using two reliable and validated questionnaires: the Learning Style Scales and the Values Survey Module 2008 (VSM 08). A simple linear regression was run for each predictor before conducting multiple linear regression analysis. The forward selection method was used for variable selection. P-values ≤0.05 and ≤0.1 were considered to indicate significance and marginal significance, respectively. Moreover, multi-group confirmatory factor analysis was performed to determine the invariance of the Farsi and English versions of the VSM 08. Results: The perceptive learning style was found to have a significant negative relationship with the power distance and monumentalism indices of the VSM 08. Moreover, a significant negative association was observed between the solitary learning style and the power distance index. However, no significant association was found between the analytic, competitive, and imaginative learning styles and cultural values (P>0.05). Likewise, no significant associations were observed between learning style, including the perceptive, solitary, analytic, competitive, and imaginative learning styles, and year of study or age (P>0.05). Conclusion: Students who reported low values on the power distance and monumentalism indices are more likely to prefer perceptive and solitary learning styles. Within each group of students in our study sample from the same school the year of study and age did not show any significant associations with learning style. PMID:26268831

Study methods, recruitment, socio-demographic findings and demographic representativeness in the OPPERA study

PubMed Central

Slade, Gary D.; Bair, Eric; By, Kunthel; Mulkey, Flora; Baraian, Cristina; Rothwell, Rebecca; Reynolds, Maria; Miller, Vanessa; Gonzalez, Yoly; Gordon, Sharon; Ribeiro-Dasilva, Margarete; Lim, Pei Feng; Greenspan, Joel D; Dubner, Ron; Fillingim, Roger B; Diatchenko, Luda; Maixner, William; Dampier, Dawn; Knott, Charles; Ohrbach, Richard

2011-01-01

This paper describes methods used in the project “Orofacial Pain Prospective Evaluation and Risk Assessment” (OPPERA) and evaluates socio-demographic characteristics associated with temporomandibular disorders (TMD) in the OPPERA case-control study. Representativeness was investigated by comparing socio-demographic profiles of OPPERA participants with population census profiles of counties near study sites and by comparing age- and gender-associations with TMD in OPPERA and the 2007-09 US National Health Interview Survey. Volunteers aged 18-44 years were recruited at four US study sites: 3,263 people without TMD were enrolled into the prospective cohort study; 1,633 of them were selected as controls for the baseline case-control study. Cases were 185 volunteers with examiner-classified TMD. Distributions of some demographic characteristics among OPPERA participants differed from census profiles, although there was less difference in socio-economic profiles. Odds of TMD was associated with greater age in this 18-44 year range; females had three times the odds of TMD as males; and relative to non-Hispanic-Whites, other racial groups had one-fifth the odds of TMD. Age- and gender-associations with chronic TMD were strikingly similar to associations observed in the US population. Assessments of representativeness in this demographically diverse group of community volunteers suggest that OPPERA case-control findings have good internal validity. PMID:22074749

[Construction of haplotype and haplotype block based on tag single nucleotide polymorphisms and their applications in association studies].

PubMed

Gu, Ming-liang; Chu, Jia-you

2007-12-01

Human genome has structures of haplotype and haplotype block which provide valuable information on human evolutionary history and may lead to the development of more efficient strategies to identify genetic variants that increase susceptibility to complex diseases. Haplotype block can be divided into discrete blocks of limited haplotype diversity. In each block, a small fraction of ptag SNPsq can be used to distinguish a large fraction of the haplotypes. These tag SNPs can be potentially useful for construction of haplotype and haplotype block, and association studies in complex diseases. There are two general classes of methods to construct haplotype and haplotype blocks based on genotypes on large pedigrees and statistical algorithms respectively. The author evaluate several construction methods to assess the power of different association tests with a variety of disease models and block-partitioning criteria. The advantages, limitations and applications of each method and the application in the association studies are discussed equitably. With the completion of the HapMap and development of statistical algorithms for addressing haplotype reconstruction, ideas of construction of haplotype based on combination of mathematics, physics, and computer science etc will have profound impacts on population genetics, location and cloning for susceptible genes in complex diseases, and related domain with life science etc.

Confounding by season in ecologic studies of seasonal exposures and outcomes: examples from estimates of mortality due to influenza.

PubMed

Jackson, Michael L

2009-10-01

Many health outcomes exhibit seasonal variation in incidence, including accidents, suicides, and infections. For seasonal outcomes it can be difficult to distinguish the causal roles played by factors that also vary seasonally, such as weather, air pollution, and pathogen circulation. Various approaches to estimating the association between a seasonal exposure and a seasonal outcome in ecologic studies are reviewed, using studies of influenza-related mortality as an example. Because mortality rates vary seasonally and circulation of other respiratory viruses peaks during influenza season, it is a challenge to estimate which winter deaths were caused by influenza. Results of studies that estimated the contribution of influenza to all-cause mortality using different methods on the same data are compared. Methods for estimating associations between season exposures and outcomes vary greatly in their advantages, disadvantages, and assumptions. Even when applied to identical data, different methods can give greatly different results for the expected contribution of influenza to all-cause mortality. When the association between exposures and outcomes that vary seasonally is estimated, models must be selected carefully, keeping in mind the assumptions inherent in each model.

Bayesian Scalar-on-Image Regression with Application to Association Between Intracranial DTI and Cognitive Outcomes

PubMed Central

Huang, Lei; Goldsmith, Jeff; Reiss, Philip T.; Reich, Daniel S.; Crainiceanu, Ciprian M.

2013-01-01

Diffusion tensor imaging (DTI) measures water diffusion within white matter, allowing for in vivo quantification of brain pathways. These pathways often subserve specific functions, and impairment of those functions is often associated with imaging abnormalities. As a method for predicting clinical disability from DTI images, we propose a hierarchical Bayesian “scalar-on-image” regression procedure. Our procedure introduces a latent binary map that estimates the locations of predictive voxels and penalizes the magnitude of effect sizes in these voxels, thereby resolving the ill-posed nature of the problem. By inducing a spatial prior structure, the procedure yields a sparse association map that also maintains spatial continuity of predictive regions. The method is demonstrated on a simulation study and on a study of association between fractional anisotropy and cognitive disability in a cross-sectional sample of 135 multiple sclerosis patients. PMID:23792220

Hypertension and arterial stiffness in heart transplantation patients

PubMed Central

de Souza-Neto, João David; de Oliveira, Ítalo Martins; Lima-Rocha, Hermano Alexandre; Oliveira-Lima, José Wellington; Bacal, Fernando

2016-01-01

OBJECTIVES: Post-transplantation hypertension is prevalent and is associated with increased cardiovascular morbidity and subsequent graft dysfunction. The present study aimed to identify the factors associated with arterial stiffness as measured by the ambulatory arterial stiffness index. METHODS: The current study used a prospective, observational, analytical design to evaluate a group of adult heart transplantation patients. Arterial stiffness was obtained by monitoring ambulatory blood pressure and using the ambulatory arterial stiffness index as the surrogate outcome. Multivariate logistic regression analyses were performed to control confounding. RESULTS: In a group of 85 adult heart transplantation patients, hypertension was independently associated with arterial stiffness (OR 4.98, CI 95% 1.06-23.4) as well as systolic and diastolic blood pressure averages and nighttime descent. CONCLUSIONS: Measurement of ambulatory arterial stiffness index is a new, non-invasive method that is easy to perform, may contribute to better defining arterial stiffness prognosis and is associated with hypertension. PMID:27652829

Dynamics of contraceptive use in India: apprehension versus future intention among non-users and traditional method users.

PubMed

Rai, Rajesh Kumar; Unisa, Sayeed

2013-06-01

This study examines the reasons for not using any method of contraception as well as reasons for not using modern methods of contraception, and factors associated with the future intention to use different types of contraceptives in India and its selected states, namely Uttar Pradesh, Assam and West Bengal. Data from the third wave of District Level Household and Facility Survey, 2007-08 were used. Bivariate as well as logistic regression analyses were performed to fulfill the study objective. Postpartum amenorrhea and breastfeeding practices were reported as the foremost causes for not using any method of contraception. Opposition to use, health concerns and fear of side effects were reported to be major hurdles in the way of using modern methods of contraception. Results from logistic regression suggest considerable variation in explaining the factors associated with future intention to use contraceptives. Promotion of health education addressing the advantages of contraceptive methods and eliminating apprehension about the use of these methods through effective communication by community level workers is the need of the hour. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive Set-Based Methods for Association Testing.

PubMed

Su, Yu-Chen; Gauderman, William James; Berhane, Kiros; Lewinger, Juan Pablo

2016-02-01

With a typical sample size of a few thousand subjects, a single genome-wide association study (GWAS) using traditional one single nucleotide polymorphism (SNP)-at-a-time methods can only detect genetic variants conferring a sizable effect on disease risk. Set-based methods, which analyze sets of SNPs jointly, can detect variants with smaller effects acting within a gene, a pathway, or other biologically relevant sets. Although self-contained set-based methods (those that test sets of variants without regard to variants not in the set) are generally more powerful than competitive set-based approaches (those that rely on comparison of variants in the set of interest with variants not in the set), there is no consensus as to which self-contained methods are best. In particular, several self-contained set tests have been proposed to directly or indirectly "adapt" to the a priori unknown proportion and distribution of effects of the truly associated SNPs in the set, which is a major determinant of their power. A popular adaptive set-based test is the adaptive rank truncated product (ARTP), which seeks the set of SNPs that yields the best-combined evidence of association. We compared the standard ARTP, several ARTP variations we introduced, and other adaptive methods in a comprehensive simulation study to evaluate their performance. We used permutations to assess significance for all the methods and thus provide a level playing field for comparison. We found the standard ARTP test to have the highest power across our simulations followed closely by the global model of random effects (GMRE) and a least absolute shrinkage and selection operator (LASSO)-based test. © 2015 WILEY PERIODICALS, INC.

More physically active and leaner adolescents have higher energy intake.

PubMed

Cuenca-García, Magdalena; Ortega, Francisco B; Ruiz, Jonatan R; Labayen, Idoia; Moreno, Luis A; Patterson, Emma; Vicente-Rodríguez, Germán; González-Gross, Marcela; Marcos, Ascensión; Polito, Angela; Manios, Yannis; Beghin, Laurent; Huybrechts, Inge; Wästlund, Acki; Hurtig-Wennlöf, Anita; Hagströmer, Maria; Molnár, Dénes; Widhalm, Kurt; Kafatos, Anthony; De Henauw, Stefaan; Castillo, Manuel J; Gutin, Bernard; Sjöström, Michael

2014-01-01

To test whether youths who engage in vigorous physical activity are more likely to have lean bodies while ingesting relatively large amounts of energy. For this purpose, we studied the associations of both physical activity and adiposity with energy intake in adolescents. The study subjects were adolescents who participated in 1 of 2 cross-sectional studies, the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study (n = 1450; mean age, 14.6 years) or the European Youth Heart Study (EYHS; n = 321; mean age, 15.6 years). Physical activity was measured by accelerometry, and energy intake was measured by 24-hour recall. In the HELENA study, body composition was assessed by 2 or more of the following methods: skinfold thickness, bioelectrical impedance analysis, plus dual-energy X-ray absorptiometry or air-displacement plethysmography in a subsample. In the EYHS, body composition was assessed by skinfold thickness. Fat mass was inversely associated with energy intake in both studies and using 4 different measurement methods (P ≤ .006). Overall, fat-free mass was positively associated with energy intake in both studies, yet the results were not consistent across measurement methods in the HELENA study. Vigorous physical activity in the HELENA study (P < .05) and moderate physical activity in the EYHS (P < .01) were positively associated with energy intake. Overall, results remained unchanged after adjustment for potential confounding factors, after mutual adjustment among the main exposures (physical activity and fat mass), and after the elimination of obese subjects, who might tend to underreport energy intake, from the analyses. Our data are consistent with the hypothesis that more physically active and leaner adolescents have higher energy intake than less active adolescents with larger amounts of fat mass. Copyright © 2014 Mosby, Inc. All rights reserved.

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

Practicing Accounting Profession Criterial Skills in the Classroom: A Study of Collaborative Testing and the Impact on Final Exam Scores

ERIC Educational Resources Information Center

VanderLaan, Ski R.

2010-01-01

This mixed methods study (Creswell, 2008) was designed to test the influence of collaborative testing on learning using a quasi-experimental approach. This study used a modified embedded mixed method design in which the qualitative and quantitative data, associated with the secondary questions, provided a supportive role in a study based primarily…

Diversity and evolutionary origins of fungi associated with seeds of a neotropical pioneer tree: a case study for analysing fungal environmental samples.

PubMed

U'ren, Jana M; Dalling, James W; Gallery, Rachel E; Maddison, David R; Davis, E Christine; Gibson, Cara M; Arnold, A Elizabeth

2009-04-01

Fungi associated with seeds of tropical trees pervasively affect seed survival and germination, and thus are an important, but understudied, component of forest ecology. Here, we examine the diversity and evolutionary origins of fungi isolated from seeds of an important pioneer tree (Cecropia insignis, Cecropiaceae) following burial in soil for five months in a tropical moist forest in Panama. Our approach, which relied on molecular sequence data because most isolates did not sporulate in culture, provides an opportunity to evaluate several methods currently used to analyse environmental samples of fungi. First, intra- and interspecific divergence were estimated for the nu-rITS and 5.8S gene for four genera of Ascomycota that are commonly recovered from seeds. Using these values we estimated species boundaries for 527 isolates, showing that seed-associated fungi are highly diverse, horizontally transmitted, and genotypically congruent with some foliar endophytes from the same site. We then examined methods for inferring the taxonomic placement and phylogenetic relationships of these fungi, evaluating the effects of manual versus automated alignment, model selection, and inference methods, as well as the quality of BLAST-based identification using GenBank. We found that common methods such as neighbor-joining and Bayesian inference differ in their sensitivity to alignment methods; analyses of particular fungal genera differ in their sensitivity to alignments; and numerous and sometimes intricate disparities exist between BLAST-based versus phylogeny-based identification methods. Lastly, we used our most robust methods to infer phylogenetic relationships of seed-associated fungi in four focal genera, and reconstructed ancestral states to generate preliminary hypotheses regarding the evolutionary origins of this guild. Our results illustrate the dynamic evolutionary relationships among endophytic fungi, pathogens, and seed-associated fungi, and the apparent evolutionary distinctiveness of saprotrophs. Our study also elucidates the diversity, taxonomy, and ecology of an important group of plant-associated fungi and highlights some of the advantages and challenges inherent in the use of ITS data for environmental sampling of fungi.

Attitudes of adolescent girls towards contraceptive methods.

PubMed

Shah, Chinmay; Solanki, Vipul; Mehta, H B

2011-01-01

There has been a growing interest in patterns of contraceptive use among adolescents, due, in particular, to the social relevance attached to pregnancy in this age group. Therefore, the objective of the study was to investigate factors associated with the use of contraceptive methods among female adolescent students. A cross-sectional study was conducted, by means of selfapplied questionnaires, among 500 adolescent girls ranging from 15to 19 years of age. Prevalence with respect to the knowledge of contraceptive methods, condom use, and AIDS was calculated. Among the 500 students who participated in study only one was sexually active .The factors associated with knowledge lack and misconception are less discussion at home or at school or college level. There were many negative beliefs like impotence after condom use, weakness after sterilization, fear of becoming obese as reasons for choosing different contraceptive methods. These results confirm the there is a need for reproductive health education in school and college as well as robust research to determine the contraceptive needs of adolescents.

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method

PubMed Central

Rietveld, Cornelius A.; Esko, Tõnu; Davies, Gail; Pers, Tune H.; Turley, Patrick; Benyamin, Beben; Chabris, Christopher F.; Emilsson, Valur; Johnson, Andrew D.; Lee, James J.; de Leeuw, Christiaan; Marioni, Riccardo E.; Medland, Sarah E.; Miller, Michael B.; Rostapshova, Olga; van der Lee, Sven J.; Vinkhuyzen, Anna A. E.; Amin, Najaf; Conley, Dalton; Derringer, Jaime; van Duijn, Cornelia M.; Fehrmann, Rudolf; Franke, Lude; Glaeser, Edward L.; Hansell, Narelle K.; Hayward, Caroline; Iacono, William G.; Ibrahim-Verbaas, Carla; Jaddoe, Vincent; Karjalainen, Juha; Laibson, David; Lichtenstein, Paul; Liewald, David C.; Magnusson, Patrik K. E.; Martin, Nicholas G.; McGue, Matt; McMahon, George; Pedersen, Nancy L.; Pinker, Steven; Porteous, David J.; Posthuma, Danielle; Rivadeneira, Fernando; Smith, Blair H.; Starr, John M.; Tiemeier, Henning; Timpson, Nicholas J.; Trzaskowski, Maciej; Uitterlinden, André G.; Verhulst, Frank C.; Ward, Mary E.; Wright, Margaret J.; Davey Smith, George; Deary, Ian J.; Johannesson, Magnus; Plomin, Robert; Visscher, Peter M.; Benjamin, Daniel J.; Koellinger, Philipp D.

2014-01-01

We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory. PMID:25201988

Training Synesthetic Letter-color Associations by Reading in Color

PubMed Central

Colizoli, Olympia; Murre, Jaap M. J.; Rouw, Romke

2014-01-01

Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure. PMID:24638033

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: a review.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2009-04-01

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.

A power set-based statistical selection procedure to locate susceptible rare variants associated with complex traits with sequencing data.

PubMed

Sun, Hokeun; Wang, Shuang

2014-08-15

Existing association methods for rare variants from sequencing data have focused on aggregating variants in a gene or a genetic region because of the fact that analysing individual rare variants is underpowered. However, these existing rare variant detection methods are not able to identify which rare variants in a gene or a genetic region of all variants are associated with the complex diseases or traits. Once phenotypic associations of a gene or a genetic region are identified, the natural next step in the association study with sequencing data is to locate the susceptible rare variants within the gene or the genetic region. In this article, we propose a power set-based statistical selection procedure that is able to identify the locations of the potentially susceptible rare variants within a disease-related gene or a genetic region. The selection performance of the proposed selection procedure was evaluated through simulation studies, where we demonstrated the feasibility and superior power over several comparable existing methods. In particular, the proposed method is able to handle the mixed effects when both risk and protective variants are present in a gene or a genetic region. The proposed selection procedure was also applied to the sequence data on the ANGPTL gene family from the Dallas Heart Study to identify potentially susceptible rare variants within the trait-related genes. An R package 'rvsel' can be downloaded from http://www.columbia.edu/∼sw2206/ and http://statsun.pusan.ac.kr. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

PubMed Central

Liu, Xiaolei; Huang, Meng; Fan, Bin; Buckler, Edward S.; Zhang, Zhiwu

2016-01-01

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days. PMID:26828793

50 CFR 218.171 - Permissible methods of taking.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 50 Wildlife and Fisheries 10 2013-10-01 2013-10-01 false Permissible methods of taking. 218.171 Section 218.171 Wildlife and Fisheries NATIONAL MARINE FISHERIES SERVICE, NATIONAL OCEANIC AND ATMOSPHERIC... Complex and the Associated Proposed Extensions Study Area § 218.171 Permissible methods of taking. (a...

An Examination of Secondary Wind Instrument Methods Courses

ERIC Educational Resources Information Center

Wagoner, Cynthia L.; Juchniewicz, Jay

2017-01-01

The purpose of this study was to investigate current secondary woodwind, brass, and combined wind instrument methods courses for preservice music teachers across the United States. Two-hundred eleven (N = 211) wind methods course instructors from National Association of Schools of Music-accredited institutions completed an online survey that…

Incorporating Formative Assessment and Science Content into Elementary Science Methods--A Case Study

ERIC Educational Resources Information Center

Brower, Derek John

2012-01-01

Just as elementary students enter the science classroom with prior knowledge and experiences, so do preservice elementary teachers who enter the science methods classroom. Elementary science methods instructors recognize the challenges associated with preparing teachers for the science classroom. Two of these challenges include overcoming limited…

Utilization of Positive and Negative Controls to Examine Comorbid Associations in Observational Database Studies.

PubMed

Desai, Jigar R; Hyde, Craig L; Kabadi, Shaum; St Louis, Matthew; Bonato, Vinicius; Katrina Loomis, A; Galaznik, Aaron; Berger, Marc L

2017-03-01

Opportunities to leverage observational data for precision medicine research are hampered by underlying sources of bias and paucity of methods to handle resulting uncertainty. We outline an approach to account for bias in identifying comorbid associations between 2 rare genetic disorders and type 2 diabetes (T2D) by applying a positive and negative control disease paradigm. Association between 10 common and 2 rare genetic disorders [Hereditary Fructose Intolerance (HFI) and α-1 antitrypsin deficiency] and T2D was compared with the association between T2D and 7 negative control diseases with no established relationship with T2D in 4 observational databases. Negative controls were used to estimate how much bias and variance existed in datasets when no effect should be observed. Unadjusted association for common and rare genetic disorders and T2D was positive and variable in magnitude and distribution in all 4 databases. However, association between negative controls and T2D was 200% greater than expected indicating the magnitude and confidence intervals for comorbid associations are sensitive to systematic bias. A meta-analysis using this method demonstrated a significant association between HFI and T2D but not for α-1 antitrypsin deficiency. For observational studies, when covariate data are limited or ambiguous, positive and negative controls provide a method to account for the broadest level of systematic bias, heterogeneity, and uncertainty. This provides greater confidence in assessing associations between diseases and comorbidities. Using this approach we were able to demonstrate an association between HFI and T2D. Leveraging real-world databases is a promising approach to identify and corroborate potential targets for precision medicine therapies.

THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES

PubMed Central

Song, Chi; Min, Xiaoyi; Zhang, Heping

2016-01-01

The chromosome copy number variation (CNV) is the deviation of genomic regions from their normal copy number states, which may associate with many human diseases. Current genetic studies usually collect hundreds to thousands of samples to study the association between CNV and diseases. CNVs can be called by detecting the change-points in mean for sequences of array-based intensity measurements. Although multiple samples are of interest, the majority of the available CNV calling methods are single sample based. Only a few multiple sample methods have been proposed using scan statistics that are computationally intensive and designed toward either common or rare change-points detection. In this paper, we propose a novel multiple sample method by adaptively combining the scan statistic of the screening and ranking algorithm (SaRa), which is computationally efficient and is able to detect both common and rare change-points. We prove that asymptotically this method can find the true change-points with almost certainty and show in theory that multiple sample methods are superior to single sample methods when shared change-points are of interest. Additionally, we report extensive simulation studies to examine the performance of our proposed method. Finally, using our proposed method as well as two competing approaches, we attempt to detect CNVs in the data from the Primary Open-Angle Glaucoma Genes and Environment study, and conclude that our method is faster and requires less information while our ability to detect the CNVs is comparable or better. PMID:28090239

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

A 2-step penalized regression method for family-based next-generation sequencing association studies.

PubMed

Ding, Xiuhua; Su, Shaoyong; Nandakumar, Kannabiran; Wang, Xiaoling; Fardo, David W

2014-01-01

Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.

Mendelian randomization study of height and risk of colorectal cancer

PubMed Central

Thrift, Aaron P; Gong, Jian; Peters, Ulrike; Chang-Claude, Jenny; Rudolph, Anja; Slattery, Martha L; Chan, Andrew T; Esko, Tonu; Wood, Andrew R; Yang, Jian; Vedantam, Sailaja; Gustafsson, Stefan; Pers, Tune H; Baron, John A; Bezieau, Stéphane; Küry, Sébastien; Ogino, Shuji; Berndt, Sonja I; Casey, Graham; Haile, Robert W; Du, Mengmeng; Harrison, Tabitha A; Thornquist, Mark; Duggan, David J; Le Marchand, Loic; Lemire, Mathieu; Lindor, Noralane M; Seminara, Daniela; Song, Mingyang; Thibodeau, Stephen N; Cotterchio, Michelle; Win, Aung Ko; Jenkins, Mark A; Hopper, John L; Ulrich, Cornelia M; Potter, John D; Newcomb, Polly A; Schoen, Robert E; Hoffmeister, Michael; Brenner, Hermann; White, Emily; Hsu, Li; Campbell, Peter T

2015-01-01

Background: For men and women, taller height is associated with increased risk of all cancers combined. For colorectal cancer (CRC), it is unclear whether the differential association of height by sex is real or is due to confounding or bias inherent in observational studies. We performed a Mendelian randomization study to examine the association between height and CRC risk. Methods: To minimize confounding and bias, we derived a weighted genetic risk score predicting height (using 696 genetic variants associated with height) in 10 226 CRC cases and 10 286 controls. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for associations between height, genetically predicted height and CRC. Results: Using conventional methods, increased height (per 10-cm increment) was associated with increased CRC risk (OR = 1.08, 95% CI = 1.02–1.15). In sex-specific analyses, height was associated with CRC risk for women (OR = 1.15, 95% CI = 1.05–1.26), but not men (OR = 0.98, 95% CI = 0.92–1.05). Consistent with these results, carrying greater numbers of (weighted) height-increasing alleles (per 1-unit increase) was associated with higher CRC risk for women and men combined (OR = 1.07, 95% CI = 1.01–1.14) and for women (OR = 1.09, 95% CI = 1.01–1.19). There was weaker evidence of an association for men (OR = 1.05, 95% CI = 0.96–1.15). Conclusion: We provide evidence for a causal association between height and CRC for women. The CRC-height association for men remains unclear and warrants further investigation in other large studies. PMID:25997436

A novel risk assessment method for landfill slope failure: Case study application for Bhalswa Dumpsite, India.

PubMed

Jahanfar, Ali; Amirmojahedi, Mohsen; Gharabaghi, Bahram; Dubey, Brajesh; McBean, Edward; Kumar, Dinesh

2017-03-01

Rapid population growth of major urban centres in many developing countries has created massive landfills with extraordinary heights and steep side-slopes, which are frequently surrounded by illegal low-income residential settlements developed too close to landfills. These extraordinary landfills are facing high risks of catastrophic failure with potentially large numbers of fatalities. This study presents a novel method for risk assessment of landfill slope failure, using probabilistic analysis of potential failure scenarios and associated fatalities. The conceptual framework of the method includes selecting appropriate statistical distributions for the municipal solid waste (MSW) material shear strength and rheological properties for potential failure scenario analysis. The MSW material properties for a given scenario is then used to analyse the probability of slope failure and the resulting run-out length to calculate the potential risk of fatalities. In comparison with existing methods, which are solely based on the probability of slope failure, this method provides a more accurate estimate of the risk of fatalities associated with a given landfill slope failure. The application of the new risk assessment method is demonstrated with a case study for a landfill located within a heavily populated area of New Delhi, India.

Effect of oil and dry roasting of peanuts at various temperatures and times on survival of Salmonella and Enterococcus faecium

USDA-ARS?s Scientific Manuscript database

A number of outbreaks of salmonellosis since 2006 associated with the consumption of Salmonella-contaminated peanut butter have increased concerns about this food and the associated processing methods. Laboratory studies were conducted to determine the level of Salmonella reduction associated with o...

Associate Residency Training Directors in Psychiatry: Demographics, Professional Activities, and Job Satisfaction

ERIC Educational Resources Information Center

Arbuckle, Melissa R.; DeGolia, Sallie G.; Esposito, Karin; Miller, Deborah A.; Weinberg, Michael; Brenner, Adam M.

2012-01-01

Objective: The purpose of this study was to characterize associate training director (ATD) positions in psychiatry. Method: An on-line survey was e-mailed in 2009 to all ATDs identified through the American Association of Directors of Psychiatric Residency Training (AADPRT). Survey questions elicited information regarding demographics,…

The association between vitamin B12, albuminuria and reduced kidney function: an observational cohort study

USDA-ARS?s Scientific Manuscript database

Background: Variants in CUBN, the gene encoding cubilin, a proximal tubular transport protein, have been associated with albuminuria and vitamin B12 (B12) deficiency. We hypothesized that low levels of B12 would be associated with albuminuria in a population-based cohort. Methods: We analyzed parti...

Association between body weight and composition and plasma 25 hydroxyvitamin D level in the diabetes prevention program

USDA-ARS?s Scientific Manuscript database

Objective: We examined associations between body weight and plasma 25-hydroxyvitamin D concentration (25OHD) in prediabetes and sought to estimate the impact of adiposity on these associations. Methods: The study was conducted in the placebo (n = 1082) and intensive lifestyle (n = 1079) groups of ...

Associations between Smoking and Extreme Dieting among Adolescents

ERIC Educational Resources Information Center

Seo, Dong-Chul; Jiang, Nan

2009-01-01

This study examined the association between cigarette smoking and dieting behaviors and trends in that association among US adolescents in grades 9-12 between 1999 and 2007. Youth Risk Behavior Survey datasets were analyzed using the multivariable logistic regression method. The sample size of each survey year ranged from 13,554 to 15,273 with…

Associations between Maternal Attention-Deficit/Hyperactivity Disorder Symptoms and Parenting

ERIC Educational Resources Information Center

Chronis-Tuscano, Andrea; Raggi, Veronica L.; Clarke, Tana L.; Rooney, Mary E.; Diaz, Yamalis; Pian, Jessica

2008-01-01

Mothers of children with attention-deficit/hyperactivity disorder (ADHD) are at increased risk for an ADHD diagnosis themselves, which is likely associated with impairments in parenting. The present study utilized a multi-method assessment of maternal ADHD and parenting to examine the extent to which maternal ADHD symptoms are associated with…

Associations between owner personality and psychological status and the prevalence of canine behavior problems

PubMed Central

Dodman, Nicholas H.; Brown, Dorothy C.

2018-01-01

Behavioral problems are a major source of poor welfare and premature mortality in companion dogs. Previous studies have demonstrated associations between owners’ personality and psychological status and the prevalence and/or severity of their dogs’ behavior problems. However, the mechanisms responsible for these associations are currently unknown. Other studies have detected links between the tendency of dogs to display behavior problems and their owners’ use of aversive or confrontational training methods. This raises the possibility that the effects of owner personality and psychological status on dog behavior are mediated via their influence on the owner’s choice of training methods. We investigated this hypothesis in a self-selected, convenience sample of 1564 current dog owners using an online battery of questionnaires designed to measure, respectively, owner personality, depression, emotion regulation, use of aversive/confrontational training methods, and owner-reported dog behavior. Multivariate linear and logistic regression analyses identified modest, positive associations between owners’ use of aversive/confrontational training methods and the prevalence/severity of the following dog behavior problems: owner-directed aggression, stranger-directed aggression, separation problems, chasing, persistent barking, and house-soiling (urination and defecation when left alone). The regression models also detected modest associations between owners’ low scores on four of the ‘Big Five’ personality dimensions (Agreeableness, Emotional Stability, Extraversion & Conscientiousness) and their dogs’ tendency to display higher rates of owner-directed aggression, stranger-directed fear, and/or urination when left alone. The study found only weak evidence to support the hypothesis that these relationships between owner personality and dog behavior were mediated via the owners’ use of punitive training methods, but it did detect a more than five-fold increase in the use of aversive/confrontational training techniques among men with moderate depression. Further research is needed to clarify the causal relationship between owner personality and psychological status and the behavioral problems of companion dogs. PMID:29444154

Associations between owner personality and psychological status and the prevalence of canine behavior problems.

PubMed

Dodman, Nicholas H; Brown, Dorothy C; Serpell, James A

2018-01-01

Behavioral problems are a major source of poor welfare and premature mortality in companion dogs. Previous studies have demonstrated associations between owners' personality and psychological status and the prevalence and/or severity of their dogs' behavior problems. However, the mechanisms responsible for these associations are currently unknown. Other studies have detected links between the tendency of dogs to display behavior problems and their owners' use of aversive or confrontational training methods. This raises the possibility that the effects of owner personality and psychological status on dog behavior are mediated via their influence on the owner's choice of training methods. We investigated this hypothesis in a self-selected, convenience sample of 1564 current dog owners using an online battery of questionnaires designed to measure, respectively, owner personality, depression, emotion regulation, use of aversive/confrontational training methods, and owner-reported dog behavior. Multivariate linear and logistic regression analyses identified modest, positive associations between owners' use of aversive/confrontational training methods and the prevalence/severity of the following dog behavior problems: owner-directed aggression, stranger-directed aggression, separation problems, chasing, persistent barking, and house-soiling (urination and defecation when left alone). The regression models also detected modest associations between owners' low scores on four of the 'Big Five' personality dimensions (Agreeableness, Emotional Stability, Extraversion & Conscientiousness) and their dogs' tendency to display higher rates of owner-directed aggression, stranger-directed fear, and/or urination when left alone. The study found only weak evidence to support the hypothesis that these relationships between owner personality and dog behavior were mediated via the owners' use of punitive training methods, but it did detect a more than five-fold increase in the use of aversive/confrontational training techniques among men with moderate depression. Further research is needed to clarify the causal relationship between owner personality and psychological status and the behavioral problems of companion dogs.

Exposure of the surgeon's hands to radiation during hand surgery procedures.

PubMed

Żyluk, Andrzej; Puchalski, Piotr; Szlosser, Zbigniew; Dec, Paweł; Chrąchol, Joanna

2014-01-01

The objective of the study was to assess the time of exposure of the surgeon's hands to radiation and calculate of the equivalent dose absorbed during surgery of hand and wrist fractures with C-arm fluoroscope guidance. The necessary data specified by the objective of the study were acquired from operations of 287 patients with fractures of fingers, metacarpals, wrist bones and distal radius. 218 operations (78%) were percutaneous procedures and 60 (22%) were performed by open method. Data on the time of exposure and dose of radiation were acquired from the display of the fluoroscope, where they were automatically generated. These data were assigned to the individual patient, type of fracture, method of surgery and the operating surgeon. Fixations of distal radial fractures required longer times of radiation exposure (mean 61 sec.) than fractures of the wrist/metacarpals and fingers (38 and 32 sec., respectively), which was associated with absorption of significantly higher equivalent doses. Fixations of distal radial fractures by open method were associated with statistically significantly higher equivalent doses (0.41 mSv) than percutaneous procedures (0.3 mSv). Fixations of wrist and metacarpal bone fractures by open method were associated with lower equivalent doses (0.34 mSv) than percutaneous procedures (0.37 mSv),but the difference was not significant. Fixations of finger fractures by open method were associated with lower equivalent doses (0.13 mSv) than percutaneous procedures (0.24 mSv), the difference being statistically non-significant. Statistically significant differences in exposure time and equivalent doses were noted between 4 surgeons participating in the study, but no definitive relationship was found between these parameters and surgeons' employment time. 1. Hand surgery procedures under fluoroscopic guidance are associated with mild exposure of the surgeons' hands to radiation. 2. The equivalent dose was related to the type of fracture, operative technique and - to some degree - to the time of employment of the surgeon.

Population assessment of tropical tuna based on their associative behavior around floating objects.

PubMed

Capello, M; Deneubourg, J L; Robert, M; Holland, K N; Schaefer, K M; Dagorn, L

2016-11-03

Estimating the abundance of pelagic fish species is a challenging task, due to their vast and remote habitat. Despite the development of satellite, archival and acoustic tagging techniques that allow the tracking of marine animals in their natural environments, these technologies have so far been underutilized in developing abundance estimations. We developed a new method for estimating the abundance of tropical tuna that employs these technologies and exploits the aggregative behavior of tuna around floating objects (FADs). We provided estimates of abundance indices based on a simulated set of tagged fish and studied the sensitivity of our method to different association dynamics, FAD numbers, population sizes and heterogeneities of the FAD-array. Taking the case study of yellowfin tuna (Thunnus albacares) acoustically-tagged in Hawaii, we implemented our approach on field data and derived for the first time the ratio between the associated and the total population. With more extensive and long-term monitoring of FAD-associated tunas and good estimates of the numbers of fish at FADs, our method could provide fisheries-independent estimates of populations of tropical tuna. The same approach can be applied to obtain population assessments for any marine and terrestrial species that display associative behavior and from which behavioral data have been acquired using acoustic, archival or satellite tags.

Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

PubMed Central

Calle, M. Luz; Rothman, Nathaniel; Urrea, Víctor; Kogevinas, Manolis; Petrus, Sandra; Chanock, Stephen J.; Tardón, Adonina; García-Closas, Montserrat; González-Neira, Anna; Vellalta, Gemma; Carrato, Alfredo; Navarro, Arcadi; Lorente-Galdós, Belén; Silverman, Debra T.; Real, Francisco X.; Wu, Xifeng; Malats, Núria

2013-01-01

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk. PMID:24391818

Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

PubMed

Suratanee, Apichat; Plaimas, Kitiporn

2017-01-01

The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.

Benefit Finding in Maternal Caregivers of Pediatric Cancer Survivors: A Mixed Methods Approach.

PubMed

Willard, Victoria W; Hostetter, Sarah A; Hutchinson, Katherine C; Bonner, Melanie J; Hardy, Kristina K

2016-09-01

Benefit finding has been described as the identification of positive effects resulting from otherwise stressful experiences. In this mixed methods study, we examined the relations between qualitative themes related to benefit finding and quantitative measures of psychosocial adjustment and coping as reported by maternal caregivers of survivors of pediatric cancer. Female caregivers of survivors of pediatric cancer (n = 40) completed a qualitative questionnaire about their experiences caring for their child, along with several quantitative measures. Qualitative questionnaires were coded for salient themes, including social support and personal growth. Correlation matrices evaluated associations between qualitative themes and quantitative measures of stress and coping. Identified benefits included social support and personal growth, as well as child-specific benefits. Total benefits reported were significantly positively correlated with availability of emotional resources. Coping methods were also associated, with accepting responsibility associated with fewer identified benefits. Despite the stress of their child's illness, many female caregivers of survivors of pediatric cancer reported finding benefits associated with their experience. Benefit finding in this sample was associated with better adjustment. © 2016 by Association of Pediatric Hematology/Oncology Nurses.

Breastfeeding in African Americans May Not Depend on Sleep Arrangement: A Mixed-Methods Study

PubMed Central

Kadakia, Ashaini; Joyner, Brandi; Tender, Jennifer; Oden, Rosalind; Moon, Rachel Y.

2015-01-01

Background Despite high bedsharing rates, breastfeeding rates are low among African Americans. Objective Describe the association between breastfeeding and bedsharing; elucidate barriers to breastfeeding in African Americans. Methods African American mothers with infants <6 months were recruited for this cross-sectional, mixed-methods study and completed an infant care practices survey. A subgroup participated in focus groups or individual interviews. Results A total of 412 completed the survey; 83 participated in a focus group or interview. Lower socioeconomic status mothers were more likely to breastfeed exclusively or at all if they bedshared (P = .02 and P = .01, respectively). Bedsharing was not associated with breastfeeding among higher socioeconomic status mothers. Breast pain, lack of support, and maternal skepticism about breastfeeding benefits were barriers; the latter was a recurrent theme among nonbreastfeeding mothers. Conclusions While bedsharing is associated with breastfeeding in lower socioeconomic groups, it is not in higher socioeconomic African American groups. Skepticism about breastfeeding benefits may contribute to low breastfeeding rates in African Americans. PMID:25139664

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

An association of platelet indices with blood pressure in Beijing adults: Applying quadratic inference function for a longitudinal study.

PubMed

Yang, Kun; Tao, Lixin; Mahara, Gehendra; Yan, Yan; Cao, Kai; Liu, Xiangtong; Chen, Sipeng; Xu, Qin; Liu, Long; Wang, Chao; Huang, Fangfang; Zhang, Jie; Yan, Aoshuang; Ping, Zhao; Guo, Xiuhua

2016-09-01

The quadratic inference function (QIF) method becomes more acceptable for correlated data because of its advantages over generalized estimating equations (GEE). This study aimed to evaluate the relationship between platelet indices and blood pressure using QIF method, which has not been studied extensively in real data settings.A population-based longitudinal study was conducted in Beijing from 2007 to 2012, and the median of follow-up was 6 years. A total of 6515 cases, who were aged between 20 and 65 years at baseline and underwent routine physical examinations every year from 3 Beijing hospitals were enrolled to explore the association between platelet indices and blood pressure by QIF method. The original continuous platelet indices were categorized into 4 levels (Q1-Q4) using the 3 quartiles of P25, P50, and P75 as a critical value. GEE was performed to make a comparison with QIF.After adjusting for age, usage of drugs, and other confounding factors, mean platelet volume was negatively associated with diastolic blood pressure (DBP) (Equation is included in full-text article.)in males and positively linked with systolic blood pressure (SBP) (Equation is included in full-text article.). Platelet distribution width was negatively associated with SBP (Equation is included in full-text article.). Blood platelet count was associated with DBP (Equation is included in full-text article.)in males.Adults in Beijing with prolonged exposure to extreme value of platelet indices have elevated risk for future hypertension and evidence suggesting using some platelet indices for early diagnosis of high blood pressure was provided.

Genome-wide association study of telomere length among South Asians identifies a second RTEL1 association signal

PubMed Central

Zhang, Chenan; Chen, Lin S; Gao, Jianjun; Roy, Shantanu; Shinkle, Justin; Sabarinathan, Mekala; Tong, Lin; Ahmed, Alauddin; Islam, Tariqul; Rakibuz-Zaman, Muhammad; Sarwar, Golam; Shahriar, Hasan; Rahman, Mahfuzar; Yunus, Mohammad; Jasmine, Farzana; Kibriya, Muhammad G; Ahsan, Habibul; Pierce, Brandon L

2018-01-01

Background Leucocyte telomere length (TL) is a potential biomarker of ageing and risk for age-related disease. Leucocyte TL is heritable and shows substantial differences by race/ethnicity. Recent genome-wide association studies (GWAS) report ~10 loci harbouring SNPs associated with leucocyte TL, but these studies focus primarily on populations of European ancestry. Objective This study aims to enhance our understanding of genetic determinants of TL across populations. Methods We performed a GWAS of TL using data on 5075 Bangladeshi adults. We measured TL using one of two technologies (qPCR or a Luminex-based method) and used standardised variables as TL phenotypes. Results Our results replicate previously reported associations in the TERC and TERT regions (P=2.2×10−8 and P=6.4×10−6, respectively). We observed a novel association signal in the RTEL1 gene (intronic SNP rs2297439; P=2.82×10−7) that is independent of previously reported TL-associated SNPs in this region. The minor allele for rs2297439 is common in South Asian populations (≥0.25) but at lower frequencies in other populations (eg, 0.07 in Northern Europeans). Among the eight other previously reported association signals, all were directionally consistent with our study, but only rs8105767 (ZNF208) was nominally significant (P=0.003). SNP-based heritability estimates were as high as 44% when analysing close relatives but much lower when analysing distant relatives only. Conclusions In this first GWAS of TL in a South Asian population, we replicate some, but not all, of the loci reported in prior GWAS of individuals of European ancestry, and we identify a novel second association signal at the RTEL1 locus. PMID:29151059

Talk as a Metacognitive Strategy during the Information Search Process of Adolescents

ERIC Educational Resources Information Center

Bowler, Leanne

2010-01-01

Introduction: This paper describes a metacognitive strategy related to the social dimension of the information search process of adolescents. Method: A case study that used naturalistic methods to explore the metacognitive thinking nd associated emotions of ten adolescents. The study was framed by Kuhlthau's Information Search Process model and…

City Governments and Aging in Place: Community Design, Transportation and Housing Innovation Adoption

ERIC Educational Resources Information Center

Lehning, Amanda J.

2012-01-01

Purpose of the study: To examine the characteristics associated with city government adoption of community design, housing, and transportation innovations that could benefit older adults. Design and methods: A mixed-methods study with quantitative data collected via online surveys from 62 city planners combined with qualitative data collected via…

Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies

PubMed Central

Chen, Guanjie; Yuan, Ao; Zhou, Jie; Bentley, Amy R.; Adeyemo, Adebowale; Rotimi, Charles N.

2012-01-01

Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size. PMID:22837643

Mixed methods research in mental health nursing.

PubMed

Kettles, A M; Creswell, J W; Zhang, W

2011-08-01

Mixed methods research is becoming more widely used in order to answer research questions and to investigate research problems in mental health and psychiatric nursing. However, two separate literature searches, one in Scotland and one in the USA, revealed that few mental health nursing studies identified mixed methods research in their titles. Many studies used the term 'embedded' but few studies identified in the literature were mixed methods embedded studies. The history, philosophical underpinnings, definition, types of mixed methods research and associated pragmatism are discussed, as well as the need for mixed methods research. Examples of mental health nursing mixed methods research are used to illustrate the different types of mixed methods: convergent parallel, embedded, explanatory and exploratory in their sequential and concurrent combinations. Implementing mixed methods research is also discussed briefly and the problem of identifying mixed methods research in mental and psychiatric nursing are discussed with some possible solutions to the problem proposed. © 2011 Blackwell Publishing.

Measuring diet cost at the individual level: a comparison of three methods

PubMed Central

Monsivais, P; Perrigue, M M; Adams, S L; Drewnowski, A

2013-01-01

Background/objectives: Household-level food spending data are not suitable for population-based studies of the economics of nutrition. This study compared three methods of deriving diet cost at the individual level. Subjects/methods: Adult men and women (n=164) completed 4-day diet diaries and a food frequency questionnaire (FFQ). Food expenditures over 4 weeks and supermarket prices for 384 foods were obtained. Diet costs (US$/day) were estimated using: (1) diet diaries and expenditures; (2) diet diaries and supermarket prices; and (3) FFQs and supermarket prices. Agreement between the three methods was assessed on the basis of Pearson correlations and limits of agreement. Income-related differences in diet costs were estimated using general linear models. Results: Diet diaries yielded mean (s.d.) diet costs of $10.04 (4.27) based on Method 1 and $8.28 (2.32) based on Method 2. FFQs yielded mean diet costs of $7.66 (2.72) based on Method 3. Correlations between energy intakes and costs were highest for Method 3 (r2=0.66), lower for Method 2 (r2=0.24) and lowest for Method 1 (r2=0.06). Cost estimates were significantly associated with household incomes. Conclusion: The weak association between food expenditures and food intake using Method 1 makes it least suitable for diet and health research. However, merging supermarket food prices with standard dietary assessment tools can provide estimates of individual diet cost that are more closely associated with food consumed. The derivation of individual diet cost can provide insights into some of the economic determinants of food choice, diet quality and health. PMID:24045791

Exploring the Changes in Students' Understanding of the Scientific Method Using Word Associations

NASA Astrophysics Data System (ADS)

Gulacar, Ozcan; Sinan, Olcay; Bowman, Charles R.; Yildirim, Yetkin

2015-10-01

A study is presented that explores how students' knowledge structures, as related to the scientific method, compare at different student ages. A word association test comprised of ten total stimulus words, among them experiment, science fair, and hypothesis, is used to probe the students' knowledge structures. Students from grades four, five, and eight, as well as first-year college students were tested to reveal their knowledge structures relating to the scientific method. Younger students were found to have a naïve view of the science process with little understanding of how science relates to the real world. However, students' conceptions about the scientific process appear to be malleable, with science fairs a potentially strong influencer. The strength of associations between words is observed to change from grade to grade, with younger students placing science fair near the center of their knowledge structure regarding the scientific method, whereas older students conceptualize the scientific method around experiment.

Evaluation Of Odors Associated With Land Application Of Biosolids

EPA Science Inventory

An odor study was performed at a biosolids application demonstration site using several different gas collection devices and analytical methods to determine changes in air concentration of several organic and inorganic compounds associated with biosolids application over various ...

Methods to predict seasonal high water table (SHGWT) : final report.

DOT National Transportation Integrated Search

2017-04-03

The research study was sectioned into 5 separate tasks. Task 1 included defining the seasonal high ground water table (SHGWT); describing : methods and techniques used to determine SHGWTs; identify problems associated with estimating SHGWT conditions...

Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.

PubMed

Dudbridge, Frank; Koeleman, Bobby P C

2004-09-01

Large exploratory studies, including candidate-gene-association testing, genomewide linkage-disequilibrium scans, and array-expression experiments, are becoming increasingly common. A serious problem for such studies is that statistical power is compromised by the need to control the false-positive rate for a large family of tests. Because multiple true associations are anticipated, methods have been proposed that combine evidence from the most significant tests, as a more powerful alternative to individually adjusted tests. The practical application of these methods is currently limited by a reliance on permutation testing to account for the correlated nature of single-nucleotide polymorphism (SNP)-association data. On a genomewide scale, this is both very time-consuming and impractical for repeated explorations with standard marker panels. Here, we alleviate these problems by fitting analytic distributions to the empirical distribution of combined evidence. We fit extreme-value distributions for fixed lengths of combined evidence and a beta distribution for the most significant length. An initial phase of permutation sampling is required to fit these distributions, but it can be completed more quickly than a simple permutation test and need be done only once for each panel of tests, after which the fitted parameters give a reusable calibration of the panel. Our approach is also a more efficient alternative to a standard permutation test. We demonstrate the accuracy of our approach and compare its efficiency with that of permutation tests on genomewide SNP data released by the International HapMap Consortium. The estimation of analytic distributions for combined evidence will allow these powerful methods to be applied more widely in large exploratory studies.

Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents.

PubMed

Huybrechts, Inge; Lioret, Sandrine; Mouratidou, Theodora; Gunter, Marc J; Manios, Yannis; Kersting, Mathilde; Gottrand, Frederic; Kafatos, Anthony; De Henauw, Stefaan; Cuenca-García, Magdalena; Widhalm, Kurt; Gonzales-Gross, Marcela; Molnar, Denes; Moreno, Luis A; McNaughton, Sarah A

2017-01-01

This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12-17 years) and Australia (2007 National Children's Nutrition and Physical Activity Survey, including 1498 adolescents, 12-16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled 'energy dense, high fat, low fibre') explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet-obesity associations, to prevent reverse causality.

[What do we know about participation in cultural activities and health?].

PubMed

Knudtsen, Margunn Skjei; Holmen, Jostein; Håpnes, Odd

2005-12-15

Knowledge of the association between health status and lifestyle factors, such as food habits, smoking and physical activity, is abundant. Other lifestyle factors, such as participation in cultural activities, have attained less attention. The article is based on studies of the literature. Reference lists in key articles have been used as well as references given by research colleagues. The survey shows an association between participation in cultural activities, cultural experiences and health status, also when measured by differing methods. Further population studies, longitudinal studies and controlled studies are needed in order to expand our knowledge of the relationship between participation in cultural activities and health status. There is a need for multidisciplinary cooperation and increased use of combined quantitative and qualitative methods.

Comparison of wildfire smoke estimation methods and associations with cardiopulmonary-related hospital admissions.

PubMed

Gan, Ryan W; Ford, Bonne; Lassman, William; Pfister, Gabriele; Vaidyanathan, Ambarish; Fischer, Emily; Volckens, John; Pierce, Jeffrey R; Magzamen, Sheryl

2017-03-01

Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM 2.5 ) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM 2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM 2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM 2.5 . A 10 μg/m 3 increase in GWR smoke PM 2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019-1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM 2.5 exposure method: a 10 μg/m 3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026-1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931-1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM 2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W; Collins, Ryan L; Wejse, Christian; Sirugo, Giorgio; Williams, Scott M; Moore, Jason H

2013-01-01

Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies. PMID:23396514

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

PubMed Central

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-01-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0. PMID:27892471

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies.

PubMed

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-28

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

NASA Astrophysics Data System (ADS)

Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

2016-11-01

The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

FARVATX: FAmily-based Rare Variant Association Test for X-linked genes

PubMed Central

Choi, Sungkyoung; Lee, Sungyoung; Qiao, Dandi; Hardin, Megan; Cho, Michael H.; Silverman, Edwin K; Park, Taesung; Won, Sungho

2016-01-01

Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease (COPD). Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods. PMID:27325607

FARVATX: Family-Based Rare Variant Association Test for X-Linked Genes.

PubMed

Choi, Sungkyoung; Lee, Sungyoung; Qiao, Dandi; Hardin, Megan; Cho, Michael H; Silverman, Edwin K; Park, Taesung; Won, Sungho

2016-09-01

Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods. © 2016 WILEY PERIODICALS, INC.

Personal use of hair dyes and the risk of bladder cancer: results of a meta-analysis.

PubMed Central

Huncharek, Michael; Kupelnick, Bruce

2005-01-01

OBJECTIVE: This study examined the methodology of observational studies that explored an association between personal use of hair dye products and the risk of bladder cancer. METHODS: Data were pooled from epidemiological studies using a general variance-based meta-analytic method that employed confidence intervals. The outcome of interest was a summary relative risk (RRs) reflecting the risk of bladder cancer development associated with use of hair dye products vs. non-use. Sensitivity analyses were performed to explain any observed statistical heterogeneity and to explore the influence of specific study characteristics of the summary estimate of effect. RESULTS: Initially combining homogenous data from six case-control and one cohort study yielded a non-significant RR of 1.01 (0.92, 1.11), suggesting no association between hair dye use and bladder cancer development. Sensitivity analyses examining the influence of hair dye type, color, and study design on this suspected association showed that uncontrolled confounding and design limitations contributed to a spurious non-significant summary RR. The sensitivity analyses yielded statistically significant RRs ranging from 1.22 (1.11, 1.51) to 1.50 (1.30, 1.98), indicating that personal use of hair dye products increases bladder cancer risk by 22% to 50% vs. non-use. CONCLUSION: The available epidemiological data suggest an association between personal use of hair dye products and increased risk of bladder cancer. PMID:15736329

Investigation of 2‐stage meta‐analysis methods for joint longitudinal and time‐to‐event data through simulation and real data application

PubMed Central

Tudur Smith, Catrin; Gueyffier, François; Kolamunnage‐Dona, Ruwanthi

2017-01-01

Background Joint modelling of longitudinal and time‐to‐event data is often preferred over separate longitudinal or time‐to‐event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time‐to‐event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta‐analysis of joint model estimates from multiple studies. Methods We propose a 2‐stage method for meta‐analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta‐analyses of separate longitudinal or time‐to‐event models. A simulation study is conducted to contrast separate versus joint analyses over a range of scenarios. Results Using the real dataset, similar results were obtained by using the separate and joint analyses. However, the simulation study indicated a benefit of use of joint rather than separate methods in a meta‐analytic setting where association exists between the longitudinal and time‐to‐event outcomes. Conclusions Where evidence of association between longitudinal and time‐to‐event outcomes exists, results from joint models over standalone analyses should be pooled in 2‐stage meta‐analyses. PMID:29250814

Association between central auditory processing mechanism and cardiac autonomic regulation

PubMed Central

2014-01-01

Background This study was conducted to describe the association between central auditory processing mechanism and the cardiac autonomic regulation. Methods It was researched papers on the topic addressed in this study considering the following data bases: Medline, Pubmed, Lilacs, Scopus and Cochrane. The key words were: “auditory stimulation, heart rate, autonomic nervous system and P300”. Results The findings in the literature demonstrated that auditory stimulation influences the autonomic nervous system and has been used in conjunction with other methods. It is considered a promising step in the investigation of therapeutic procedures for rehabilitation and quality of life of several pathologies. Conclusion The association between auditory stimulation and the level of the cardiac autonomic nervous system has received significant contributions in relation to musical stimuli. PMID:24834128

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Type of contraception method used at last intercourse and associations with health risk behaviors among US adolescents

PubMed Central

Cavazos-Rehg, Patricia A.; Krauss, Melissa J.; Spitznagel, Edward L.; Schootman, Mario; Peipert, Jeffrey F.; Cottler, Linda B.; Bierut, Laura Jean

2010-01-01

Background This study was conducted to examine associations with contraception methods used at last sexual intercourse among US adolescents. Study design Data consisted of sexually active adolescents (9th–12th grade, weighted n = 24,638) from 1999–2007 Youth Risk Behavior Surveillance System (YRBSS). We performed multinomial multivariable logistic regression analyses with condom users at last sexual intercourse as the reference group. Results Males who used alcohol, cigarettes, marijuana, and cocaine were more likely to use no method/unsure of method (OR = 2.4 CI: 1.7–3.4) or rely on withdrawal (OR = 2.6 CI: 1.5–4.3). Females with six or more sexual partners were more likely to rely on withdrawal (OR: 2.9 CI: 2.1–3.9) or contraception methods that offer no STI protection (i.e., birth control pills, OR: 1.9 CI: 1.4–2.5, and depot medroxyprogesterone acetate [DMPA, marketed as Depo Provera], OR: 2.6 CI: 1.6–4.2). Earlier age of sexual debut was also associated with nonuse. Conclusion Prevention efforts should focus on at-risk adolescents including substance-using males, females with six or more sexual partners, and those who initiate sexual intercourse at an early age. PMID:21074019

Quantification of protein interaction kinetics in a micro droplet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, L. L.; College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044; Wang, S. P., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the averagemore » SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.« less

Quantification of protein interaction kinetics in a micro droplet

NASA Astrophysics Data System (ADS)

Yin, L. L.; Wang, S. P.; Shan, X. N.; Zhang, S. T.; Tao, N. J.

2015-11-01

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.

Cleaning Hospital Room Surfaces to Prevent Health Care-Associated Infections: A Technical Brief.

PubMed

Han, Jennifer H; Sullivan, Nancy; Leas, Brian F; Pegues, David A; Kaczmarek, Janice L; Umscheid, Craig A

2015-10-20

The cleaning of hard surfaces in hospital rooms is critical for reducing health care-associated infections. This review describes the evidence examining current methods of cleaning, disinfecting, and monitoring cleanliness of patient rooms, as well as contextual factors that may affect implementation and effectiveness. Key informants were interviewed, and a systematic search for publications since 1990 was done with the use of several bibliographic and gray literature resources. Studies examining surface contamination, colonization, or infection with Clostridium difficile, methicillin-resistant Staphylococcus aureus, or vancomycin-resistant enterococci were included. Eighty studies were identified-76 primary studies and 4 systematic reviews. Forty-nine studies examined cleaning methods, 14 evaluated monitoring strategies, and 17 addressed challenges or facilitators to implementation. Only 5 studies were randomized, controlled trials, and surface contamination was the most commonly assessed outcome. Comparative effectiveness studies of disinfecting methods and monitoring strategies were uncommon. Future research should evaluate and compare newly emerging strategies, such as self-disinfecting coatings for disinfecting and adenosine triphosphate and ultraviolet/fluorescent surface markers for monitoring. Studies should also assess patient-centered outcomes, such as infection, when possible. Other challenges include identifying high-touch surfaces that confer the greatest risk for pathogen transmission; developing standard thresholds for defining cleanliness; and using methods to adjust for confounders, such as hand hygiene, when examining the effect of disinfecting methods.

Cleaning Hospital Room Surfaces to Prevent Health Care–Associated Infections

PubMed Central

Han, Jennifer H.; Sullivan, Nancy; Leas, Brian F.; Pegues, David A.; Kaczmarek, Janice L.; Umscheid, Craig A.

2015-01-01

The cleaning of hard surfaces in hospital rooms is critical for reducing health care–associated infections. This review describes the evidence examining current methods of cleaning, disinfecting, and monitoring cleanliness of patient rooms, as well as contextual factors that may affect implementation and effectiveness. Key informants were interviewed, and a systematic search for publications since 1990 was done with the use of several bibliographic and gray literature resources. Studies examining surface contamination, colonization, or infection with Clostridium difficile, methicillin-resistant Staphylococcus aureus, or vancomycinresistant enterococci were included. Eighty studies were identified—76 primary studies and 4 systematic reviews. Forty-nine studies examined cleaning methods, 14 evaluated monitoring strategies, and 17 addressed challenges or facilitators to implementation. Only 5 studies were randomized, controlled trials, and surface contamination was the most commonly assessed outcome. Comparative effectiveness studies of disinfecting methods and monitoring strategies were uncommon. Future research should evaluate and compare newly emerging strategies, such as self-disinfecting coatings for disinfecting and adenosine triphosphate and ultraviolet/fluorescent surface markers for monitoring. Studies should also assess patient-centered outcomes, such as infection, when possible. Other challenges include identifying high-touch surfaces that confer the greatest risk for pathogen transmission; developing standard thresholds for defining cleanliness; and using methods to adjust for confounders, such as hand hygiene, when examining the effect of disinfecting methods. PMID:26258903

Psychological Abuse between Parents: Associations with Child Maltreatment from a Population-Based Sample

ERIC Educational Resources Information Center

Chang, Jen Jen; Theodore, Adrea D.; Martin, Sandra L.; Runyan, Desmond K.

2008-01-01

Objective: This study examined the association between partner psychological abuse and child maltreatment perpetration. Methods: This cross-sectional study examined a population-based sample of mothers with children aged 0-17 years in North and South Carolina (n = 1,149). Mothers were asked about the occurrence of potentially neglectful or abusive…

Concurrent-Chains Schedules as a Method to Study Choice between Alcohol-Associated Conditioned Reinforcers

ERIC Educational Resources Information Center

Jimenez-Gomez, Corina; Shahan, Timothy A.

2012-01-01

An extensive body of research using concurrent-chains schedules of reinforcement has shown that choice for one of two differentially valued food-associated stimuli is dependent upon the overall temporal context in which those stimuli are embedded. The present experiments examined whether the concurrent chains procedure was useful for the study of…

The Association between Maltreatment and Obesity among Preschool Children

ERIC Educational Resources Information Center

Whitaker, Robert C.; Phillips, Shannon M.; Orzol, Sean M.; Burdette, Hillary L.

2007-01-01

Objective: To determine whether child maltreatment is associated with obesity in preschool children. Methods: Data were obtained from the Fragile Families and Child Wellbeing Study, a birth cohort study of 4898 children born between 1998 and 2000 in 20 large US cities. At 3 years of age, 2412 of these children had their height and weight measured,…

Analysis of Influential Factors Associated with the Smoking Behavior of Aboriginal Schoolchildren in Remote Taiwanese Mountainous Areas

ERIC Educational Resources Information Center

Huang, Hsiao-Ling; Hsu, Chih-Cheng; Peng, Wu-Der; Yen, Yea-Yin; Chen, Ted; Hu, Chih-Yang; Shi, Hon-Yi; Lee, Chien-Hung; Chen, Fu-Li; Lin, Pi-Li

2012-01-01

Background: A disparity in smoking behavior exists between the general and minority populations residing in Taiwan's mountainous areas. This study analyzed individual and environmental factors associated with children's smoking behavior in these areas of Taiwan. Methods: In this school-based study, data on smoking behavior and related factors for…

Use of travel cost models in planning: A case study

Treesearch

Allan Marsinko; William T. Zawacki; J. Michael Bowker

2002-01-01

This article examines the use of the travel cost, method in tourism-related decision making in the area of nonconsumptive wildlife-associated recreation. A travel cost model of nonconsumptive wildlife-associated recreation, developed by Zawacki, Maninko, and Bowker, is used as a case study for this analysis. The travel cost model estimates the demand for the activity...

Parental and Adolescent Perceptions of Neighborhood Safety Related to Adolescents' Physical Activity in Their Neighborhood

ERIC Educational Resources Information Center

Esteban-Cornejo, Irene; Carlson, Jordan A.; Conway, Terry L.; Cain, Kelli L.; Saelens, Brian E.; Frank, Lawrence D.; Glanz, Karen; Roman, Caterina G.; Sallis, James F.

2016-01-01

Purpose: The purpose of this study was to examine the association between adolescent and parental perceptions of neighborhood safety and adolescents' physical activity in multiple locations and to investigate the moderating effect of sex within this association. Method: This cross-sectional study was conducted with 928 adolescents aged 12 to 16…

The Association between Changes in Health Status and Nursing Home Resident Quality of Life

ERIC Educational Resources Information Center

Degenholtz, Howard B.; Rosen, Jules; Castle, Nicholas; Mittal, Vikas; Liu, Darren

2008-01-01

Purpose: Previous research on nursing home resident quality of life (QOL) has mainly been cross-sectional. This study examined the association between changes in QOL and changes in resident clinical factors. Design and Methods: A longitudinal study of resident QOL was conducted in two nursing homes. Self-report interviews using a multidimensional…

Is Tobacco Use Associated with Academic Failure among Government School Students in Urban India?

ERIC Educational Resources Information Center

Dhavan, Poonam; Stigler, Melissa H.; Perry, Cheryl L.; Arora, Monika; Reddy, K. Srinath

2010-01-01

Background: Not much is known about the academic correlates of tobacco use among students in developing countries. This study investigated associations between multiple forms of tobacco use, psychosocial risk factors, and academic failure among 10- to 16-year-old government school students in Delhi and Chennai, India. Methods: This study was a…

Dimensions of Manic Symptoms in Youth: Psychosocial Impairment and Cognitive Performance in the IMAGEN Sample

ERIC Educational Resources Information Center

Stringaris, Argyris; Castellanos-Ryan, Natalie; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun L.; Bromberg, Uli; Büchel, Christian; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Juergen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Itterman, Bernd; Lawrence, Claire; Nees, Frauke; Paillere-Martinot, Marie-Laure; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Smolka, Michael N.; Schumann, Gunter; Goodman, Robert; Conrod, Patricia

2014-01-01

Background: It has been reported that mania may be associated with superior cognitive performance. In this study, we test the hypothesis that manic symptoms in youth separate along two correlated dimensions and that a symptom constellation of high energy and cheerfulness is associated with superior cognitive performance. Method: We studied 1755…

Measuring Tree Seedlings and Associated Understory Vegetation in Pennsylvania's Forests

Treesearch

William H. McWilliams; Todd W. Bowersox; Patrick H. Brose; Daniel A. Devlin; James C. Finley; Kurt W. Gottschalk; Steve Horsley; Susan L. King; Brian M. LaPoint; Tonya W. Lister; Larry H. McCormick; Gary W. Miller; Charles T. Scott; Harry Steele; Kim C. Steiner; Susan L. Stout; James A. Westfall; Robert L. White

2005-01-01

The Northeastern Research Station's Forest Inventory and Analysis (NE-FIA) unit is conducting the Pennsylvania Regeneration Study (PRS) to evaluate composition and abundance of tree seedlings and associated vegetation. Sampling methods for the PRS were tested and developed in a pilot study to determine the appropriate number of 2-m microplots needed to capture...

Adjusting survival time estimates to account for treatment switching in randomized controlled trials--an economic evaluation context: methods, limitations, and recommendations.

PubMed

Latimer, Nicholas R; Abrams, Keith R; Lambert, Paul C; Crowther, Michael J; Wailoo, Allan J; Morden, James P; Akehurst, Ron L; Campbell, Michael J

2014-04-01

Treatment switching commonly occurs in clinical trials of novel interventions in the advanced or metastatic cancer setting. However, methods to adjust for switching have been used inconsistently and potentially inappropriately in health technology assessments (HTAs). We present recommendations on the use of methods to adjust survival estimates in the presence of treatment switching in the context of economic evaluations. We provide background on the treatment switching issue and summarize methods used to adjust for it in HTAs. We discuss the assumptions and limitations associated with adjustment methods and draw on results of a simulation study to make recommendations on their use. We demonstrate that methods used to adjust for treatment switching have important limitations and often produce bias in realistic scenarios. We present an analysis framework that aims to increase the probability that suitable adjustment methods can be identified on a case-by-case basis. We recommend that the characteristics of clinical trials, and the treatment switching mechanism observed within them, should be considered alongside the key assumptions of the adjustment methods. Key assumptions include the "no unmeasured confounders" assumption associated with the inverse probability of censoring weights (IPCW) method and the "common treatment effect" assumption associated with the rank preserving structural failure time model (RPSFTM). The limitations associated with switching adjustment methods such as the RPSFTM and IPCW mean that they are appropriate in different scenarios. In some scenarios, both methods may be prone to bias; "2-stage" methods should be considered, and intention-to-treat analyses may sometimes produce the least bias. The data requirements of adjustment methods also have important implications for clinical trialists.

Sacral orientation revisited.

PubMed

Peleg, Smadar; Dar, Gali; Steinberg, Nili; Peled, Nathan; Hershkovitz, Israel; Masharawi, Youssef

2007-07-01

A descriptive study of the sacral anatomic orientation (SAO) and its association with pelvic incidence (PI). To introduce the concept of SAO, establish a method for measuring it, and evaluate its association with pelvic orientation. Pelvic orientation (PO) is considered a key factor in spinal shape and balance. Sacral slope (SS), PI, and pelvic tilt (PT) are the most frequently used parameters for evaluating PO. Nevertheless, the association between the anatomic orientation of the sacrum and these parameters has never been established. The aim of the present study is to define the anatomic orientation of the sacrum, to establish a reliable method for measuring it, and to examine its association with PI. SAO was defined as the angle created between the intersection of a line running parallel to the superior endplate surface of the sacrum and a line running between the anterior superior iliac spine (ASIS) and the anterior-superior edge of the symphysis pubis. Methods for measuring SAO and PI on both skeletal populations and living individuals are described. The study was carried out on 424 skeletons (articulated pelves) using a three-dimensional digitizer and on 20 adult individuals using CT three-dimensional images (volume-rendering method). Reliability (intratester and intertester) was assessed using intraclass correlation test. A regression analysis was carried out to evaluate the association between the two measurements. The mean SAO and PI in the human skeletal population were found to be 48.46 degrees +/- 10.17 degrees and 54.08 degrees +/- 12.64 degrees , respectively and of the living individuals (CT) 52.76 degrees +/- 10.31 degrees and 57.14 degrees +/- 13.08 degrees , respectively. SAO and PI measurements were highly correlated (r = -0.824, and r = -0.828, P < 0.001 for skeletal material and living individuals, respectively). PI can be predicted via SAO, i.e., PI = [-0.971 x SAO] + 101.16 degrees . The newly suggested parameter (SAO) may be an important tool in defining the sagittal shape of the spine and understanding its association with spinal diseases.

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations

PubMed Central

Majumdar, Arunabha; Haldar, Tanushree; Bhattacharya, Sourabh; Witte, John S.

2018-01-01

Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy). For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes) that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC) technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package ‘CPBayes’ implementing the proposed method. PMID:29432419

Antifungal susceptibility testing of Malassezia yeast: comparison of two different methodologies.

PubMed

Rojas, Florencia D; Córdoba, Susana B; de Los Ángeles Sosa, María; Zalazar, Laura C; Fernández, Mariana S; Cattana, María E; Alegre, Liliana R; Carrillo-Muñoz, Alfonso J; Giusiano, Gustavo E

2017-02-01

All Malassezia species are lipophilic; thus, modifications are required in susceptibility testing methods to ensure their growth. Antifungal susceptibility of Malassezia species using agar and broth dilution methods has been studied. Currently, few tests using disc diffusion methods are being performed. The aim was to evaluate the in vitro susceptibility of Malassezia yeast against antifungal agents using broth microdilution and disc diffusion methods, then to compare both methodologies. Fifty Malassezia isolates were studied. Microdilution method was performed as described in reference document and agar diffusion test was performed using antifungal tablets and discs. To support growth, culture media were supplemented. To correlate methods, linear regression analysis and categorical agreement was determined. The strongest linear association was observed for fluconazole and miconazole. The highest agreement between both methods was observed for itraconazole and voriconazole and the lowest for amphotericin B and fluconazole. Although modifications made to disc diffusion method allowed to obtain susceptibility data for Malassezia yeast, variables cannot be associated through a linear correlation model, indicating that inhibition zone values cannot predict MIC value. According to the results, disc diffusion assay may not represent an alternative to determine antifungal susceptibility of Malassezia yeast. © 2016 Blackwell Verlag GmbH.

Single Nucleotide Polymorphism (SNP)-Strings: An Alternative Method for Assessing Genetic Associations

PubMed Central

Goodin, Douglas S.; Khankhanian, Pouya

2014-01-01

Background Genome-wide association studies (GWAS) identify disease-associations for single-nucleotide-polymorphisms (SNPs) from scattered genomic-locations. However, SNPs frequently reside on several different SNP-haplotypes, only some of which may be disease-associated. This circumstance lowers the observed odds-ratio for disease-association. Methodology/Principal Findings Here we develop a method to identify the two SNP-haplotypes, which combine to produce each person’s SNP-genotype over specified chromosomal segments. Two multiple sclerosis (MS)-associated genetic regions were modeled; DRB1 (a Class II molecule of the major histocompatibility complex) and MMEL1 (an endopeptidase that degrades both neuropeptides and β-amyloid). For each locus, we considered sets of eleven adjacent SNPs, surrounding the putative disease-associated gene and spanning ∼200 kb of DNA. The SNP-information was converted into an ordered-set of eleven-numbers (subject-vectors) based on whether a person had zero, one, or two copies of particular SNP-variant at each sequential SNP-location. SNP-strings were defined as those ordered-combinations of eleven-numbers (0 or 1), representing a haplotype, two of which combined to form the observed subject-vector. Subject-vectors were resolved using probabilistic methods. In both regions, only a small number of SNP-strings were present. We compared our method to the SHAPEIT-2 phasing-algorithm. When the SNP-information spanning 200 kb was used, SHAPEIT-2 was inaccurate. When the SHAPEIT-2 window was increased to 2,000 kb, the concordance between the two methods, in both of these eleven-SNP regions, was over 99%, suggesting that, in these regions, both methods were quite accurate. Nevertheless, correspondence was not uniformly high over the entire DNA-span but, rather, was characterized by alternating peaks and valleys of concordance. Moreover, in the valleys of poor-correspondence, SHAPEIT-2 was also inconsistent with itself, suggesting that the SNP-string method is more accurate across the entire region. Conclusions/Significance Accurate haplotype identification will enhance the detection of genetic-associations. The SNP-string method provides a simple means to accomplish this and can be extended to cover larger genomic regions, thereby improving a GWAS’s power, even for those published previously. PMID:24727690

Systematic review of suicide in economic recession

PubMed Central

Oyesanya, Mayowa; Lopez-Morinigo, Javier; Dutta, Rina

2015-01-01

AIM: To provide a systematic update of the evidence concerning the relationship between economic recession and suicide. METHODS: A keyword search of Ovid Medline, Embase, Embase Classic, PsycINFO and PsycARTICLES was performed to identify studies that had investigated the association between economic recession and suicide. RESULTS: Thirty-eight studies met predetermined selection criteria and 31 of them found a positive association between economic recession and increased suicide rates. Two studies reported a negative association, two articles failed to find such an association, and three studies were inconclusive. CONCLUSION: Economic recession periods appear to increase overall suicide rates, although further research is warranted in this area, particularly in low income countries. PMID:26110126

The effects of particulate air pollution on daily deaths: a multi-city case crossover analysis

PubMed Central

Schwartz, J

2004-01-01

Background: Numerous studies have reported that day-to-day changes in particulate air pollution are associated with day-to-day changes in deaths. Recently, several reports have indicated that the software used to control for season and weather in some of these studies had deficiencies. Aims: To investigate the use of the case-crossover design as an alternative. Methods: This approach compares the exposure of each case to their exposure on a nearby day, when they did not die. Hence it controls for seasonal patterns and for all slowly varying covariates (age, smoking, etc) by matching rather than complex modelling. A key feature is that temperature can also be controlled by matching. This approach was applied to a study of 14 US cities. Weather and day of the week were controlled for in the regression. Results: A 10 µg/m3 increase in PM10 was associated with a 0.36% increase in daily deaths from internal causes (95% CI 0.22% to 0.50%). Results were little changed if, instead of symmetrical sampling of control days the time stratified method was applied, when control days were matched on temperature, or when more lags of winter time temperatures were used. Similar results were found using a Poisson regression, but the case-crossover method has the advantage of simplicity in modelling, and of combining matched strata across multiple locations in a single stage analysis. Conclusions: Despite the considerable differences in analytical design, the previously reported associations of particles with mortality persisted in this study. The association appeared quite linear. Case-crossover designs represent an attractive method to control for season and weather by matching. PMID:15550600

Promoting Engagement With a Digital Health Intervention (HeLP-Diabetes) Using Email and Text Message Prompts: Mixed-Methods Study

PubMed Central

Modrow, Kerstin; Hamilton, Fiona; Pal, Kingshuk; Ross, Jamie

2017-01-01

Background Engagement with digital health interventions (DHIs) may be regarded as a prerequisite for the intervention to achieve positive health or behavior change outcomes. One method employed to promote engagement is the use of prompts such as emails and text messages. However, little is known about the characteristics of prompts that promote engagement. This study explored the association between the content and delivery mode of prompts and the users’ engagement with HeLP-Diabetes (Healthy Living for People with type 2 Diabetes), a DHI that aimed to promote self-management in adults with type 2 diabetes. Objective The objective of this study was to identify the characteristics of prompts, specifically the content and delivery mode, which were associated with increased engagement. Methods This was a mixed-methods study. Email and text message prompts were sent to the registered users of HeLP-Diabetes. Use of the intervention was recorded and examined to identify which email and text message prompts were associated with subsequent visits to the DHI. Characteristics of prompts that were identified as particularly effective or ineffective were explored through think-aloud interviews with the participants. Results Of a total of 39 email prompts, 49% (19/39) prompts showed a significant association with subsequent visits to the DHI. However, none of the text message prompts were associated with subsequent visits to the DHI. Furthermore, think-aloud interviews were carried out with 6 experienced participants with type 2 diabetes. The findings suggest that these participants preferred email prompts that were clear, relatively short, and empowering; used nondirective advice; included health professional references; were visually appealing; and contained news and updates. Conclusions The findings of this study contribute to the existing evidence supporting the role of email prompts in promoting and maintaining engagement with DHIs. This study described the content of prompts that may be engaging. However, the results should be interpreted with caution, as prompts may be context-specific interventions and the results may not be generalizable across other DHIs or other types of interventions targeting self-management of type 2 diabetes. PMID:28829328

Method of Continuous Variations: Applications of Job Plots to the Study of Molecular Associations in Organometallic Chemistry[**

PubMed Central

Renny, Joseph S.; Tomasevich, Laura L.; Tallmadge, Evan H.; Collum, David B.

2014-01-01

Applications of the method of continuous variations—MCV or the Method of Job—to problems of interest to organometallic chemists are described. MCV provides qualitative and quantitative insights into the stoichiometries underlying association of m molecules of A and n molecules of B to form AmBn. Applications to complex ensembles probe associations that form metal clusters and aggregates. Job plots in which reaction rates are monitored provide relative stoichiometries in rate-limiting transition structures. In a specialized variant, ligand- or solvent-dependent reaction rates are dissected into contributions in both the ground states and transition states, which affords insights into the full reaction coordinate from a single Job plot. Gaps in the literature are identified and critiqued. PMID:24166797

Complex Demands on Teaching Require Innovation: Case Method & Other Techniques. Selected Papers of the International Conference on Case Method Research & Application (17th, Budapest, Hungary, July 2-5, 2000).

ERIC Educational Resources Information Center

Klein, Hans E., Ed.

This book presents a selection of papers from the annual, international, interdisciplinary conference of the World Association for Case Method Research & Application. Papers are categorized into six areas: (1) "Case Studies and Research" (e.g., subjectivity as a source of insight in case study research, evolution of a teaching case,…

Thermal detection thresholds in 5-year-old preterm born children; IQ does matter.

PubMed

de Graaf, Joke; Valkenburg, Abraham J; Tibboel, Dick; van Dijk, Monique

2012-07-01

Experiencing pain at newborn age may have consequences on one's somatosensory perception later in life. Children's perception for cold and warm stimuli may be determined with the Thermal Sensory Analyzer (TSA) device by two different methods. This pilot study in 5-year-old children born preterm aimed at establishing whether the TSA method of limits, which is dependent of reaction time, and the method of levels, which is independent of reaction time, would yield different cold and warm detection thresholds. The second aim was to establish possible associations between intellectual ability and the detection thresholds obtained with either method. A convenience sample was drawn from the participants in an ongoing 5-year follow-up study of a randomized controlled trial on effects of morphine during mechanical ventilation. Thresholds were assessed using both methods and statistically compared. Possible associations between the child's intelligence quotient (IQ) and threshold levels were analyzed. The method of levels yielded more sensitive thresholds than did the method of limits, i.e. mean (SD) cold detection thresholds: 30.3 (1.4) versus 28.4 (1.7) (Cohen'sd=1.2, P=0.001) and warm detection thresholds; 33.9 (1.9) versus 35.6 (2.1) (Cohen's d=0.8, P=0.04). IQ was statistically significantly associated only with the detection thresholds obtained with the method of limits (cold: r=0.64, warm: r=-0.52). The TSA method of levels, is to be preferred over the method of limits in 5-year-old preterm born children, as it establishes more sensitive detection thresholds and is independent of IQ. Copyright © 2011 Elsevier Ltd. All rights reserved.

Surveillance versus clinical adjudication: differences persist with new ventilator-associated event definition.

PubMed

McMullen, Kathleen M; Boyer, Anthony F; Schoenberg, Noah; Babcock, Hilary M; Micek, Scott T; Kollef, Marin H

2015-06-01

The National Healthcare Safety Network (NHSN) has recently supported efforts to shift surveillance away from ventilator-associated pneumonia to ventilator-associated events (VAEs) to decrease subjectivity in surveillance and minimize concerns over clinical correlation. The goals of this study were to compare the results of an automated surveillance strategy using the new VAE definition with a prospectively performed clinical application of the definition. All patients ventilated for ≥2 days in a medical and surgical intensive care unit were evaluated by 2 methods: retrospective surveillance using an automated algorithm combined with manual chart review after the NHSN's VAE methodology and prospective surveillance by pulmonary physicians in collaboration with the clinical team administering care to the patient at the bedside. Overall, a similar number of events were called by each method (69 vs 67). Of the 1,209 patients, 56 were determined to have VAEs by both methods (κ = .81, P = .04). There were 24 patients considered to be a VAE by only 1 of the methods. Most discrepancies were the result of clinical disagreement with the NHSN's VAE methodology. There was good agreement between the study teams. Awareness of the limitations of the surveillance definition for VAE can help infection prevention personnel in discussions with critical care partners about optimal use of these data. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their Application

PubMed Central

Cantor, Rita M.; Lange, Kenneth; Sinsheimer, Janet S.

2010-01-01

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the GWAS provide preliminary genetic information that is available for additional analysis by statistical procedures that accumulate evidence, and that these secondary analyses are very likely to provide valuable information that will help prioritize the strongest constellations of results. We review and discuss three analytic methods to combine preliminary GWAS statistics to identify genes, alleles, and pathways for deeper investigations. Meta-analysis seeks to pool information from multiple GWAS to increase the chances of finding true positives among the false positives and provides a way to combine associations across GWAS, even when the original data are unavailable. Testing for epistasis within a single GWAS study can identify the stronger results that are revealed when genes interact. Pathway analysis of GWAS results is used to prioritize genes and pathways within a biological context. Following a GWAS, association results can be assigned to pathways and tested in aggregate with computational tools and pathway databases. Reviews of published methods with recommendations for their application are provided within the framework for each approach. PMID:20074509

Factors associated with sterilization use among women leaving a U.S. jail: a mixed methods study.

PubMed

Ramaswamy, Megha; Kelly, Patricia J

2014-07-31

Despite the high rates of reported sterilization use among women who have spent time in correctional facilities, little is known about the context in which women in this population choose this option. The objective of our study was to use both quantitative and qualitative methods to understand factors associated with sterilization use among women leaving a U.S. jail. We administered a cross-sectional survey with 102 jailed women who were participating in a study about contraceptive use after release from jail, and then conducted semi-structured interviews with 29 of those women after their release from jail. We used logistic regression and analytic induction to assess factors associated with self-reported sterilization use. In our cross-sectional survey, one-third of our sample reported a history of sterilization use. Controlling for age and past pregnancies, the only factor associated with sterilization use was physical abuse history before age 16. In semi-structured interviews, we found that women's primary motivation for sterilization was the desire to limit childbearing permanently, in some cases where other contraceptive methods had failed them. The decision for sterilization was generally supported by family, partners, and providers. Many women who opted for sterilization expressed financial concern about supporting children and/or reported family histories of sterilization. The decision to use the permanent method of sterilization as a contraceptive method is a complex one. Results from this study suggest that while explicit coercion may not be a factor in women's choice for sterilization, interpersonal relationship histories, negative experiences with contraceptives, and structural constraints, such as financial concerns and ongoing criminal justice involvement, seem to influence sterilization use among the vulnerable group of women with criminal justice histories. Public health programs that connect women to reproductive health services should acknowledge constraints on contraceptive decision-making in vulnerable populations.

Describing Elementary Certification Methods across the Elementary Music Career Cycle

ERIC Educational Resources Information Center

Svec, Christina L.

2017-01-01

The purpose of the study was to describe elementary music method choice and certification method choice overall and across the elementary music career cycle. Participants (N = 254) were categorized as Level I or Elementary Division in a southwestern music education association database. The questionnaire included 25 four-point Likert-type items…

The Keyword Method and Children's Vocabulary Learning: An Interaction with Vocabulary Knowledge.

ERIC Educational Resources Information Center

McGivern, Julie E.; Levin, Joel R.

A study explored a potential aptitude-by-treatment interaction associated with the keyword method of vocabulary acquisition. This method is a two-stage mnemonic process whereby an unfamiliar term is first transformed into a familiar concrete stimulus and then a thematic relationship is created between the transformed stimulus and the information…

Rosenberg's Self-Esteem Scale: Two Factors or Method Effects.

ERIC Educational Resources Information Center

Tomas, Jose M.; Oliver, Amparo

1999-01-01

Results of a study with 640 Spanish high school students suggest the existence of a global self-esteem factor underlying responses to Rosenberg's (M. Rosenberg, 1965) Self-Esteem Scale, although the inclusion of method effects is needed to achieve a good model fit. Method effects are associated with item wording. (SLD)

The Use of Quantitative and Qualitative Methods in the Analysis of Academic Achievement among Undergraduates in Jamaica

ERIC Educational Resources Information Center

McLaren, Ingrid Ann Marie

2012-01-01

This paper describes a study which uses quantitative and qualitative methods in determining the relationship between academic, institutional and psychological variables and degree performance for a sample of Jamaican undergraduate students. Quantitative methods, traditionally associated with the positivist paradigm, and involving the counting and…

Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

PubMed

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm.

PubMed

Tuo, Shouheng; Zhang, Junying; Yuan, Xiguo; Zhang, Yuanyuan; Liu, Zhaowen

2016-01-01

Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS). Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models. In this study, two scoring functions (Bayesian network based K2-score and Gini-score) are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA) is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models. We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE) which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR), specificity (SPC), positive predictive value (PPV) and accuracy (ACC). Our method has identified two SNPs (rs3775652 and rs10511467) that may be also associated with disease in AMD dataset.

Airway stent complications: the role of follow-up bronchoscopy as a surveillance method

PubMed Central

Labaki, Wassim; Yu, Diana H.; Salwen, Benjamin; Gilbert, Christopher; Schneider, Andrea L. C.; Ortiz, Ricardo; Feller-Kopman, David; Arias, Sixto; Yarmus, Lonny

2017-01-01

Background Airway stenting has become an integral part of the therapeutic endoscopic management of obstructive benign and malignant central airway diseases. Despite increased use of airway stents and frequent stent-associated complications, no clear guidelines for surveillance and maintenance exist. This study aim is to elucidate predictive factors associated with development of stent complications, as well as an optimal surveillance period for follow-up bronchoscopy for early detection and possible prevention of stent-associated complications. Methods Retrospective cohort study of all patients who underwent airway stent placements at our institution from April 2010 to December 2013 for benign and malignant airway diseases. Metallic, silicone (straight, Y stent, T-tube) and hybrid stents were included in the study. Stent complications were analyzed at the time of follow-up bronchoscopy performed four to six weeks after initial stent placement or earlier if patients became symptomatic. Results The study included 134 patients of which 147 stents were placed. Follow-up bronchoscopy was performed in 94 patients. Symptomatic status at the time of follow-up bronchoscopy was not associated with stent complications [odds ratio (OR) =1.88; 95% CI: 0.79–4.45; P=0.15]. Patient age, sex, indication for stent placement, and stent location, were not associated with development of complications (all P>0.05). Compared to all other stents, hybrid stents were more likely to migrate (OR =6.60; 95% CI: 2.16–20.2; P=0.001) or obstruct by secretions (OR =2.53; 95% CI: 1.10–5.84; P=0.03). There were no complications associated with surveillance bronchoscopy. Conclusions Surveillance bronchoscopy within 4 to 6 weeks of stent placement may be useful for early detection of complications and their subsequent management, regardless of symptomatic status and indication for stent placement. Prospective multicenter studies are needed to compare optimal surveillance methods and the impact on patient mortality, morbidity and healthcare costs. PMID:29268534

Animal food intake and cooking methods in relation to endometrial cancer risk in Shanghai

PubMed Central

Xu, W-H; Dai, Q; Xiang, Y-B; Zhao, G-M; Zheng, W; Gao, Y-T; Ruan, Z-X; Cheng, J-R; Shu, X-O

2006-01-01

We evaluated animal food intake and cooking methods in relation to endometrial cancer risk in a population-based case–control study in Shanghai, China. A validated food frequency questionnaire was used to collect the usual dietary habits of 1204 cases and 1212 controls aged 30–69 years between 1997 and 2003. Statistical analyses were based on an unconditional logistic regression model adjusting for potential confounders. High intake of meat and fish was associated with an increased risk of endometrial cancer, with adjusted odds ratios for the highest vs the lowest quartile groups being 1.7 (95% confidence interval: 1.3–2.2) and 2.4 (1.8–3.1), respectively. The elevated risk was observed for all types of meat and fish intake. Intake of eggs and milk was not related to risk. Cooking methods and doneness levels for meat and fish were not associated with risk, nor did they modify the association with meat and fish consumption. Our study suggests that animal food consumption may play an important role in the aetiology of endometrial cancer, but cooking methods have minimal influence on risk among Chinese women. PMID:17060930

School-Level Factors Associated with Increased Fruit and Vegetable Consumption among Students in California Middle and High Schools

ERIC Educational Resources Information Center

Gosliner, Wendi

2014-01-01

Background: This study assessed associations between selective school-level factors and students' consumption of fruits and vegetables at school. Better understanding of school factors associated with increased produce consumption is especially important, as students are served more produce items at school. Methods: This cross-sectional study…

State-Level School Competitive Food and Beverage Laws Are Associated with Children's Weight Status

ERIC Educational Resources Information Center

Hennessy, Erin; Oh, April; Agurs-Collins, Tanya; Chriqui, Jamie F.; Mâsse, Louise C.; Moser, Richard P.; Perna, Frank

2014-01-01

Background: This study attempted to determine whether state laws regulating low nutrient, high energy-dense foods and beverages sold outside of the reimbursable school meals program (referred to as "competitive foods") are associated with children's weight status. Methods: We use the Classification of Laws Associated with School…

Association between Experiencing Relational Bullying and Adolescent Health-Related Quality of Life

ERIC Educational Resources Information Center

Chester, Kayleigh L.; Spencer, Neil H.; Whiting, Lisa; Brooks, Fiona M.

2017-01-01

Background: Bullying is a public health concern for the school-aged population, however, the health outcomes associated with the subtype of relational bullying are less understood. The purpose of this study was to examine the association between relational bullying and health-related quality of life (HRQL) among young people. Methods: This study…

How Depressive Levels Are Related to the Adults' Experiences of Lower-Limb Amputation: A Mixed Methods Pilot Study

ERIC Educational Resources Information Center

Senra, Hugo

2013-01-01

The current pilot study aims to explore whether different adults' experiences of lower-limb amputation could be associated with different levels of depression. To achieve these study objectives, a convergent parallel mixed methods design was used in a convenience sample of 42 adult amputees (mean age of 61 years; SD = 13.5). All of them had…

A Mixed Methods Study of the Effects of a Modified High School Calendar on Student Achievement and Teacher Perceptions

ERIC Educational Resources Information Center

Watrous, Lorena Harper

2011-01-01

The purpose of this mixed-methods explanatory case study was to determine the impact of a reduced school calendar on student achievement for students in grades 9 through 12 in two rural school districts in Virginia and to explore meanings associated with this change. The study focused on two research questions: how does student performance during…

Prenatal and Perinatal Risk Factors in a Twin Study of Autism Spectrum Disorders

PubMed Central

Froehlich-Santino, Wendy; Tobon, Amalia Londono; Cleveland, Sue; Torres, Andrea; Phillips, Jennifer; Cohen, Brianne; Torigoe, Tiffany; Miller, Janet; Fedele, Angie; Collins, Jack; Smith, Karen; Lotspeich, Linda; Croen, Lisa A.; Ozonoff, Sally; Lajonchere, Clara; Grether, Judith K.; O’Hara, Ruth; Hallmayer, Joachim

2014-01-01

Introduction Multiple studies associate prenatal and perinatal complications with increased risks for autism spectrum disorders (ASDs). The objectives of this study were to utilize a twin study design to 1) Investigate whether shared gestational and perinatal factors increase concordance for ASDs in twins, 2) Determine whether individual neonatal factors are associated with the presence of ASDs in twins, and 3) Explore whether associated factors may influence males and females differently. Methods Data from medical records and parent response questionnaires from 194 twin pairs, in which at least one twin had an ASD, were analyzed. Results Shared factors including parental age, prenatal use of medications, uterine bleeding, and prematurity did not increase concordance risks for ASDs in twins. Among the individual factors, respiratory distress demonstrated the strongest association with increased risk for ASDs in the group as a whole (OR 2.11, 95% CI 1.27–3.51). Furthermore, respiratory distress (OR 2.29, 95% CI 1.12–4.67) and other markers of hypoxia (OR 1.99, 95% CI 1.04–3.80) were associated with increased risks for ASDs in males, while jaundice was associated with an increased risk for ASDs in females (OR 2.94, 95% CI 1.28–6.74). Conclusions Perinatal factors associated with respiratory distress and other markers of hypoxia appear to increase risk for autism in a subgroup of twins. Future studies examining potential gender differences and additional prenatal, perinatal and postnatal environmental factors are required for elucidating the etiology of ASDs and suggesting new methods for treatment and prevention. PMID:24726638

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression.

PubMed

Malki, Karim; Tosto, Maria Grazia; Mouriño-Talín, Héctor; Rodríguez-Lorenzo, Sabela; Pain, Oliver; Jumhaboy, Irfan; Liu, Tina; Parpas, Panos; Newman, Stuart; Malykh, Artem; Carboni, Lucia; Uher, Rudolf; McGuffin, Peter; Schalkwyk, Leonard C; Bryson, Kevin; Herbster, Mark

2017-04-01

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Cooking Methods for Red Meats and Risk of Type 2 Diabetes: A Prospective Study of U.S. Women.

PubMed

Liu, Gang; Zong, Geng; Hu, Frank B; Willett, Walter C; Eisenberg, David M; Sun, Qi

2017-08-01

This study examined different cooking methods for red meats in relation to type 2 diabetes (T2D) risk among U.S. women who consumed red meats regularly (≥2 servings/week). We monitored 59,033 women (1986-2012) aged 30-55 years and free of diabetes, cardiovascular disease, and cancer at baseline when information on frequency of different cooking methods for red meats, including broiling, barbequing, roasting, pan-frying, and stewing/boiling, was collected. During 1.24 million person-years of follow-up, we documented 6,206 incident cases of T2D. After multivariate adjustment including red meat cooking methods, total red meat and processed red meat intake were both associated with a monotonically increased T2D risk (both P trend <0.05). After multivariate adjustment including total red meat intake, a higher frequency of broiling, barbequing, and roasting red meats was each independently associated with a higher T2D risk. When comparing ≥2 times/week with <1 time/month, the hazard ratios (HRs) and 95% CI of T2D were 1.29 (1.19, 1.40; P trend <0.001) for broiling, 1.23 (1.11, 1.38; P trend <0.001) for barbequing, and 1.11 (1.01, 1.23; P trend = 0.14) for roasting. In contrast, the frequency of stewing/boiling red meats was not associated with T2D risk, and an inverse association was observed for pan-frying frequency and T2D risk. The results remained similar after cooking methods were further mutually adjusted. Independent of total red meat consumption, high-temperature and/or open-flame cooking methods for red meats, especially broiling and barbequing, may further increase diabetes risk among regular meat eaters. © 2017 by the American Diabetes Association.

[Contraceptive use among adolescents at public schools in Brazil].

PubMed

de Almeida, Maria da Conceição Chagas; de Aquino, Estela Maria Leão; Gaffikin, Lynne; Magnani, Robert J

2003-10-01

There has been a growing interest in patterns of contraceptive use among adolescents, due, in particular, to the social relevance attached to pregnancy in this age group. Therefore, the objective of the study was to investigate factors associated with the use of contraceptive methods among female and male adolescent students. A cross-sectional study was conducted, by means of self-applied questionnaires, among 4,774 students ranging from 11 to 19 years of age. Prevalence with respect to the use of contraceptive methods during the first experience of sexual intercourse as well as the most recent one was calculated both separately, that is, for each of these events, and in conjunction as a measure of consistent use. Logistic regression was carried out for simultaneous analysis of factors associated with the use of contraceptive methods and in order to calculate adjusted measures. Among the 1,664 students who reported being sexually active, the factors positively associated with the consistent use of contraceptive methods among male students included a) postponing their first experience of sexual intercourse and interaction with a stable partner, b) the family as a potential supplier of contraceptive methods, and c) access to health services. On the other hand, among female students factors positively associated with the consistent use of contraceptive methods included a) recent sexual initiation, and b) having a father as their source of information regarding sexuality, contraception and STD/AIDS prevention. Pregnancy was reported by 6.4% of the boys and 18.1% of the girls, its absence was associated with the consistent use of contraceptives by them (the girls) (Odds Ratio=3.83; 2.06-7.15). The results confirm the complexity of determining contraceptive behavior among adolescents and therefore reinforce the need to include multi-dimensional aspects of this theme in order to ensure the efficacy of sex education programs.

Neural Correlates of Biased Responses: The Negative Method Effect in the Rosenberg Self-Esteem Scale Is Associated with Right Amygdala Volume.

PubMed

Wang, Yinan; Kong, Feng; Huang, Lijie; Liu, Jia

2016-10-01

Self-esteem is a widely studied construct in psychology that is typically measured by the Rosenberg Self-Esteem Scale (RSES). However, a series of cross-sectional and longitudinal studies have suggested that a simple and widely used unidimensional factor model does not provide an adequate explanation of RSES responses due to method effects. To identify the neural correlates of the method effect, we sought to determine whether and how method effects were associated with the RSES and investigate the neural basis of these effects. Two hundred and eighty Chinese college students (130 males; mean age = 22.64 years) completed the RSES and underwent magnetic resonance imaging (MRI). Behaviorally, method effects were linked to both positively and negatively worded items in the RSES. Neurally, the right amygdala volume negatively correlated with the negative method factor, while the hippocampal volume positively correlated with the general self-esteem factor in the RSES. The neural dissociation between the general self-esteem factor and negative method factor suggests that there are different neural mechanisms underlying them. The amygdala is involved in modulating negative affectivity; therefore, the current study sheds light on the nature of method effects that are related to self-report with a mix of positively and negatively worded items. © 2015 Wiley Periodicals, Inc.

Comprehensive Assessment of the Psychological Burden for Students in Physical Education Classes in Chinese Universities.

PubMed

Wei, Xuemei; Liu, Zhen

2018-05-15

BACKGROUND Physical education (PE) is part of the curriculum in Chinese universities. The psychological burden, or anxiety levels, for students in PE classes, can result from several factors, including teaching content, teaching environment, and the organization of the teaching methods. The aim of this study was to assess the psychological burden on students in PE classes in Chinese universities. MATERIAL AND METHODS The study included 400 students (200 men and 200 women) from a Chinese university, who participated in PE classes. The distribution of the levels of psychological burden associated with PE was assessed using subjective measurements and a fuzzy comprehensive evaluation method that to provide an integrated framework combining the results of judgments made at multiple stages of the evaluation process. RESULTS Of the 400 study participants who attended PE classes, 61.5% of male students and 47.5% of female students coped well or very well when dealing with the perceived psychological burden; 33.5% of male students and 42.5% of female students reported a medium level of psychological burden. Few students reported a high level of psychological burden associated with PE classes. The average psychological burden in female students was greater than for male students who participated in PE classes. CONCLUSIONS The combination of subjective measurement of the psychological burden associated with PE classes by university students in China, combined with a fuzzy comprehensive evaluation method showed that female university students might require more support than male students to overcome any psychological burden associated with PE classes.

Analysis of Risk Factors for Postoperative Morbidity in Perforated Peptic Ulcer

PubMed Central

Kim, Jae-Myung; Jeong, Sang-Ho; Park, Soon-Tae; Choi, Sang-Kyung; Hong, Soon-Chan; Jung, Eun-Jung; Ju, Young-Tae; Jeong, Chi-Young; Ha, Woo-Song

2012-01-01

Purpose Emergency operations for perforated peptic ulcer are associated with a high incidence of postoperative complications. While several studies have investigated the impact of perioperative risk factors and underlying diseases on the postoperative morbidity after abdominal surgery, only a few have analyzed their role in perforated peptic ulcer disease. The purpose of this study was to determine any possible associations between postoperative morbidity and comorbid disease or perioperative risk factors in perforated peptic ulcer. Materials and Methods In total, 142 consecutive patients, who underwent surgery for perforated peptic ulcer, at a single institution, between January 2005 and October 2010 were included in this study. The clinical data concerning the patient characteristics, operative methods, and complications were collected retrospectively. Results The postoperative morbidity rate associated with perforated peptic ulcer operations was 36.6% (52/142). Univariate analysis revealed that a long operating time, the open surgical method, age (≥60), sex (female), high American Society of Anesthesiologists (ASA) score and presence of preoperative shock were significant perioperative risk factors for postoperative morbidity. Significant comorbid risk factors included hypertension, diabetes mellitus and pulmonary disease. Multivariate analysis revealed a long operating time, the open surgical method, high ASA score and the presence of preoperative shock were all independent risk factors for the postoperative morbidity in perforated peptic ulcer. Conclusions A high ASA score, preoperative shock, open surgery and long operating time of more than 150 minutes are high risk factors for morbidity. However, there is no association between postoperative morbidity and comorbid disease in patients with a perforated peptic ulcer. PMID:22500261

Whole genome survey of coding SNPs reveals a reproducible pathway determinant of Parkinson disease

PubMed Central

Srinivasan, Balaji S; Doostzadeh, Jaleh; Absalan, Farnaz; Mohandessi, Sharareh; Jalili, Roxana; Bigdeli, Saharnaz; Wang, Justin; Mahadevan, Jaydev; Lee, Caroline LG; Davis, Ronald W; William Langston, J; Ronaghi, Mostafa

2009-01-01

It is quickly becoming apparent that situating human variation in a pathway context is crucial to understanding its phenotypic significance. Toward this end, we have developed a general method for finding pathways associated with traits that control for pathway size. We have applied this method to a new whole genome survey of coding SNP variation in 187 patients afflicted with Parkinson disease (PD) and 187 controls. We show that our dataset provides an independent replication of the axon guidance association recently reported by Lesnick et al. [PLoS Genet 2007;3:e98], and also indicates that variation in the ubiquitin-mediated proteolysis and T-cell receptor signaling pathways may predict PD susceptibility. Given this result, it is reasonable to hypothesize that pathway associations are more replicable than individual SNP associations in whole genome association studies. However, this hypothesis is complicated by a detailed comparison of our dataset to the second recent PD association study by Fung et al. [Lancet Neurol 2006;5:911–916]. Surprisingly, we find that the axon guidance pathway does not rank at the very top of the Fung dataset after controlling for pathway size. More generally, in comparing the studies, we find that SNP frequencies replicate well despite technologically different assays, but that both SNP and pathway associations are globally uncorrelated across studies. We thus have a situation in which an association between axon guidance pathway variation and PD has been found in 2 out of 3 studies. We conclude by relating this seeming inconsistency to the molecular heterogeneity of PD, and suggest future analyses that may resolve such discrepancies. PMID:18853455

Association of Short-term Bleeding and Cramping Patterns with Long-Acting Reversible Contraceptive Method Satisfaction

PubMed Central

Diedrich, Justin T.; Desai, Sanyukta; Zhao, Qiuhong; Secura, Gina; Madden, Tessa; Peipert, Jeffrey F.

2014-01-01

Objectives To examine the short-term (3 and 6-month), self-reported bleeding and cramping patterns with intrauterine devices (IUDs) and the contraceptive implant, and the association of these symptoms with method satisfaction. Study Design We analyzed 3 and 6-month survey data from IUD and implant users in the Contraceptive CHOICE Project, a prospective cohort study. Participants who received a long-acting reversible contraceptive (LARC) method (levonorgestrel intrauterine system (LNG-IUS), copper IUD, or the etonogestrel implant) and completed their 3- and 6-month surveys were included. Univariable and multivariable analyses were performed to examine the association of bleeding and cramping patterns with short-term satisfaction. Results Our analytic sample included 5,011 CHOICE participants: 3001 LNG-IUS users, 826 copper IUD users, and 1184 implant users. At 3 months, over 65% of LNG-IUS and implant users reported no change or decreased cramping, while 63% of copper IUD users reported increased menstrual cramping. Lighter bleeding was reported by 67% of LNG-IUS users, 58% of implant users, and 8% of copper IUD users. Satisfaction of all LARC methods was high (≥90%) and significantly higher than non-LARC methods (p<0.001). LARC users with increased menstrual cramping (HR 0.96, 95% CI 0.92 – 0.99), heavier bleeding (HR 0.91, 95% CI 0.87 – 0.96), and increased bleeding frequency (HR 0.92, 95% CI 0.89 – 0.96) were less likely to report being very satisfied at 6 months. Conclusion Regardless of the LARC method, satisfaction at 3 and 6 months is very high. Changes in self-reported bleeding and cramping are associated with short-term LARC satisfaction. PMID:25046805

Does the prediction of breast cancer improve using a combination of mammographic density measures compared to individual measures alone?

NASA Astrophysics Data System (ADS)

Wong Sik Hee, Joseph Ryan; Harkness, Elaine F.; Gadde, Soujanya; Lim, Yit Y.; Maxwell, Anthony J.; Evans, D. Gareth; Howell, Anthony; Astley, Susan M.

2017-03-01

High mammographic density is associated with an increased risk of breast cancer, however whether the association is stronger when there is agreement across measures is unclear. This study investigates whether a combination of density measures is a better predictor of breast cancer risk than individual methods alone. Women recruited to the Predicting Risk of Cancer At Screening (PROCAS) study and with mammographic density assessed using three different methods were included (n=33,304). Density was assessed visually using Visual Analogue Scales (VAS) and by two fully automated methods, Quantra and Volpara. Percentage breast density was divided into (high, medium and low) and combinations of measures were used to further categorise individuals (e.g. `all high'). A total of 667 breast cancers were identified and logistic regression was used to determine the relationship between breast density and breast cancer risk. In total, 44% of individuals were in the same tertile for all three measures, 8.6% were in non-adjacent (high and low) or mixed categories (high, medium and low). For individual methods the strongest association with breast cancer risk was for medium and high tertiles of VAS with odds ratios (OR) adjusted for age and BMI of 1.63 (95% CI 1.31-2.03) and 2.33 (1.87-2.90) respectively. For the combination of density methods the strongest association was for `all high' (OR 2.42, 1.77-3.31) followed by "two high" (OR 1.90, 1.35-3.31) and "two medium" (OR 1.88, 1.40-2.52). Combining density measures did not affect the magnitude of risk compared to using individual methods.

One-year contraceptive continuation and pregnancy in adolescent girls and women initiating hormonal contraceptives.

PubMed

Raine, Tina R; Foster-Rosales, Anne; Upadhyay, Ushma D; Boyer, Cherrie B; Brown, Beth A; Sokoloff, Abby; Harper, Cynthia C

2011-02-01

To assess contraceptive discontinuation, switching, factors associated with method discontinuation, and pregnancy among women initiating hormonal contraceptives. This was a 12-month longitudinal cohort study of adolescent girls and women (n=1,387) aged 15 to 24 years attending public family planning clinics who did not desire pregnancy for at least 1 year and selected to initiate the patch, ring, depot medroxyprogesterone acetate, or pills. Participants completed follow-up assessments at 3, 6, and 12 months after baseline. Life table analysis was used to estimate survival rates for contraceptive continuation. Cox proportional hazards models were used to estimate factors associated with method discontinuation. The continuation rate (per 100 person-years) at 12 months was low for all methods; however, it was lowest for patch and depot medroxyprogesterone acetate initiators, 10.9 and 12.1 per 100 person years, respectively (P≤.003); continuation among ring initiators was comparable to pill initiators, 29.4 and 32.7 per 100 person-years, respectively (P=.06). Discontinuation was independently associated with method initiated and younger age. The only factors associated with lower risk of discontinuation were greater intent to use the method and being in school or working. The pregnancy rate (per 100 person-years) was highest for patch and ring initiators (30.1 and 30.5) and comparable for pill and depot medroxyprogesterone acetate initiators (16.5 and 16.1; P<.001). The patch and the ring may not be better options than the pill or depot medroxyprogesterone acetate for women at high risk for unintended pregnancy. This study highlights the need for counseling interventions to improve contraceptive continuation, education about longer-acting methods, and developing new contraceptives that women may be more likely to continue. II.

Constructing Social Networks From Secondary Storage With Bulk Analysis Tools

DTIC Science & Technology

2016-06-01

that classic measures of centrality are effective for identifying important nodes and close associates, and that further study of modularity classes...which ground truth was determined by interviews with the owners, and which can be used for future study in this area. Two objectives motivated this thesis...tifying important nodes and close associates, and that further study of modularity classes may be a promising method of partitioning complex components

Exploring the Ecological Association Between Crime and Medical Marijuana Dispensaries

PubMed Central

Kepple, Nancy J.; Freisthler, Bridget

2012-01-01

Objective: Routine activities theory purports that crime occurs in places with a suitable target, motivated offender, and lack of guardianship. Medical marijuana dispensaries may be places that satisfy these conditions, but this has not yet been studied. The current study examined whether the density of medical marijuana dispensaries is associated with crime. Method: An ecological, cross-sectional design was used to explore the spatial relationship between density of medical marijuana dispensaries and two types of crime rates (violent crime and property crime) in 95 census tracts in Sacramento, CA, during 2009. Spatial error regression methods were used to determine associations between crime rates and density of medical marijuana dispensaries, controlling for neighborhood characteristics associated with routine activities. Results: Violent and property crime rates were positively associated with percentage of commercially zoned areas, percentage of one-person households, and unemployment rate. Higher violent crime rates were associated with concentrated disadvantage. Property crime rates were positively associated with the percentage of population 15–24 years of age. Density of medical marijuana dispensaries was not associated with violent or property crime rates. Conclusions: Consistent with previous work, variables measuring routine activities at the ecological level were related to crime. There were no observed cross-sectional associations between the density of medical marijuana dispensaries and either violent or property crime rates in this study. These results suggest that the density of medical marijuana dispensaries may not be associated with crime rates or that other factors, such as measures dispensaries take to reduce crime (i.e., doormen, video cameras), may increase guardianship such that it deters possible motivated offenders. PMID:22630790

SECURE BASE SCRIPT CONTENT EXPLAINS THE ASSOCIATION BETWEEN ATTACHMENT AVOIDANCE AND EMOTION-RELATED CONSTRUCTS IN PARENTS OF YOUNG CHILDREN.

PubMed

Borelli, Jessica L; Burkhart, Margaret L; Rasmussen, Hannah F; Brody, Robin; Sbarra, David A

2017-03-01

The secure base script (SBS) framework is one method of assessing implicit internal working models of attachment; recently, researchers have applied this method to analyze narratives regarding relationship experiences. This study examines the associations between attachment avoidance and SBS content when parents recall a positive moment of connection between themselves and their children (relational savoring) as well as their association with parental emotion and reflective functioning (RF). Using a sample of parents (N = 155, 92% female) of young children (53% boys, M age = 12.76 months), we found that parental attachment avoidance is inversely associated with SBS content during relational savoring, and that SBS content is an indirect effect explaining the association between attachment avoidance and postsavoring (positive and negative) emotion as well as avoidance and poststressor RF. Findings have implications for understanding attachment and parenting. © 2017 Michigan Association for Infant Mental Health.

Principles of cophylogenetic maps

NASA Astrophysics Data System (ADS)

Charleston, Michael A.

Cophylogeny is the study of the relationships between phylogenies of ecologically related groups (taxa, geographical areas, genes etc.), where one, the "host" phylogeny, is independent and the other, the "associate" phylogeny, is hypothesized to be dependent to some degree on the host. Given two such phylogenies our aim is to estimate the past associations between the host and associate taxa. This chapter describes cophylogeny and discusses some of its basic pri nciples. The necessary properties of any cophylogenetic method are described. Charleston [5] created a graph which contains all the potential solutions to a given cophylogenetic problem. The vertices of this graph are associations, either observed or hypothetical, between "host" and associated taxonomic units, and the arcs correspond to the associate phylogeny. A new and more general method of constructing the Jungle is presented, which will correctly account for reticulate host and/or parasite phylogenies. Keywords: cophylogeny, coevolution, gene tree/species tree, host/parasite coevolution, host switch, horizontal transfer, biogeography.

Identification of TNIP1 Polymorphisms by High Resolution Melting Analysis with Unlabelled Probe: Association with Systemic Lupus Erythematosus

PubMed Central

Zhang, Jie; Chen, Yuewen; Shao, Yong; Wu, Qi; Guan, Ming; Zhang, Wei; Wan, Jun; Yu, Bo

2012-01-01

Background. TNFα-induced protein 3 (TNFAIP3) interacting with protein 1 (TNIP1) acts as a negative regulator of NF-κB and plays an important role in maintaining the homeostasis of immune system. A recent genome-wide association study (GWAS) showed that the polymorphism of TNIP1 was associated with the disease risk of SLE in Caucasian. In this study, we investigated whether the association of TNIP1 with SLE was replicated in Chinese population. Methods. The association of TNIP1 SNP rs7708392 (G/C) was determined by high resolution melting (HRM) analysis with unlabeled probe in 285 SLE patients and 336 healthy controls. Results. A new SNP rs79937737 located on 5 bp upstream of rs7708392 was discovered during the HRM analysis. No association of rs7708392 or rs79937737 with the disease risk of SLE was found. Furthermore, rs7708392 and rs79937737 were in weak linkage disequilibrium (LD). Hypotypes analysis of the two SNPs also showed no association with SLE in Chinese population. Conclusions. High resolution melting analysis with unlabeled probes proves to be a powerful and efficient genotyping method for identifying and screening SNPs. No association of rs7708392 or rs79937737 with the disease risk of SLE was observed in Chinese population. PMID:22852072

A prediction method for broadband shock associated noise from supersonic rectangualr jets

NASA Technical Reports Server (NTRS)

Tam, Christopher K. W.; Reddy, N. N.

1993-01-01

Braodband shock associated noise is an important aircraft noise component of the proposed high-speed civil transport (HSCT) at take-offs and landings. For noise certification purpose one would, therefore, like to be able to predict as accurately as possible the intensity, directivity and spectral content of this noise component. The purpose of this work is to develop a semi-empirical prediction method for the broadband shock associated noise from supersonic rectangular jets. The complexity and quality of the noise prediction method are to be similar to those for circular jets. In this paper only the broadband shock associated noise of jets issued from rectangular nozzles with straight side walls is considered. Since many current aircraft propulsion systems have nozzle aspect ratios (at nozzle exit) in the range of 1 to 4, the present study has been confined to nozzles with aspect ratio less than 6. In developing the prediction method the essential physics of the problem are taken into consideration. Since the braodband shock associated noise generation mechanism is the same whether the jet is circular or round the present prediction method in a number of ways is quite similar to that for axisymmetric jets. Comparisons between predictions and measurements for jets with aspect ratio up to 6 will be reported. Efforts will be concentrated on the fly-over plane. However, side line angles and other directions will also be included.

Survey and Method for Determination of Trajectory Predictor Requirements

NASA Technical Reports Server (NTRS)

Rentas, Tamika L.; Green, Steven M.; Cate, Karen Tung

2009-01-01

A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

A supervised learning rule for classification of spatiotemporal spike patterns.

PubMed

Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

2016-08-01

This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

The association between the environmental endocrine disruptor bisphenol A and polycystic ovary syndrome: a systematic review and meta-analysis.

PubMed

Hu, Ying; Wen, Shu; Yuan, Dongzhi; Peng, Le; Zeng, Rujun; Yang, Zhilan; Liu, Qi; Xu, Liangzhi; Kang, Deying

2018-05-01

To investigate the association between bisphenol A (BPA) and polycystic ovary syndrome (PCOS). A systematic review and meta-analysis using STATA software for observational studies. Nine studies involving 493 PCOS patients and 440 controls were included in this review. The meta-analysis demonstrated that PCOS patients had significantly higher BPA levels compared with control groups (standardized mean difference (SMD): 2.437, 95% confidence interval (CI): (1.265, 3.609), p < .001). For studies of serum samples detected by enzyme-linked immunosorbent assay (ELISA), subgroup analyses according to ethnicity, body mass index (BMI), sample size, detection method (high-performance liquid chromatography (HPLC) and ELISA), PCOS-to-control ratio and study quality displayed that high BPA levels were significantly associated with Caucasian PCOS patients (SMD: 0.615, 95% CI: (0.308, 0.922), p < .001), high BMI (SMD: 0.512, 95% CI: (0.180, 0.843), p = .002), high quality (SMD: 0.624, 95% CI: (0.391, 0.856), p < .001), and high HOMA-IR (SMD: 0.467, 95% CI: (0.121, 0.813), p = .008). Serum BPA may be positively associated with women with PCOS and BPA might be involved in the insulin-resistance and hyperandrogenism of PCOS. More evidence from high quality studies, advanced detection methods, and larger cohorts for observational trials are needed to further confirm the association between BPA and PCOS.

High resolution melting curve assay for detecting rs12979860 IL28B polymorphisms involved in response of Iranian patients to chronic hepatitis C treatment.

PubMed

Fateh, Abolfazl; Aghasadeghi, Mohammad Reza; Keyvani, Hossein; Mollaie, Hamid Reza; Yari, Shamsi; Hadizade Tasbiti, Ali Reza; Ghazanfari, Morteza; Monavari, Seyed Hamid Reza

2015-01-01

A recent genome-wide association study (GWAS) on patients with chronic hepatitis C (CHC) treated with peginterferon and ribavirin (pegIFN-α/RBV) identified a single nucleotide polymorphism (SNP) on chromosome 19 (rs12979860) which was strongly associated with a sustained virological response (SVR). The aim of this study was twofold: to study the relationship between IL28B rs12979860 and sustained virological response (SVR) to pegIFN-α/RVB therapy among CHC patients and to detect the rs12979860 polymorphism by high resolution melting curve (HRM) assay as a simple, fast, sensitive, and inexpensive method. The study examined outcomes in 100 patients with chronic hepatitis C in 2 provinces of Iran from December 2011 to June 2013. Two methods were applied to detect IL28B polymorphisms: PCR-sequencing as a gold standard method and HRM as a simple, fast, sensitive, and inexpensive method. The frequencies of IL28B rs12979860 CC, CT, and TT alleles in chronic hepatitis C genotype 1a patients were 10% (10/100), 35% (35/100), and 6% (6/100) and in genotype 3a were 13% (13/100), 31% (31/100), and 5% (5/100), respectively. In genotype 3a infected patients, rs12979860 (CC and CT alleles) and in genotype 1a infected patients (CC allele) were significantly associated with a sustained virological response (SVR). The SVR rates for CC, CT and TT (IL28B rs12979860) were 18%, 34% and 4%, respectively. Multiple logistic regression analysis identified two independent factors that were significantly associated with SVR: IL-28B genotype (rs 12979860 CC vs TT and CT; odds ratio [ORs], 7.86 and 4.084, respectively), and HCV subtype 1a (OR, 7.46). In the present study, an association between SVR rates and IL28B polymorphisms was observed. The HRM assay described herein is rapid, inexpensive, sensitive and accurate for detecting rs12979860 alleles in CHC patients. This method can be readily adopted by any molecular diagnostic laboratory with HRM capability and will be clinically beneficial in predicting treatment response in HCV genotype 1 and 3 infected patients. In addition, it was demonstrated that CC and CT alleles in HCV-3a and the CC allele in HCV-1a were significantly associated with response to pegIFN-α/RBV treatment. The present results may help identify subjects for whom the therapy might be successful.

The Biomarkers of Exposure and Effect in Agriculture (BEEA) Study: Rationale, design, methods, and participant characteristics

EPA Science Inventory

Agricultural exposures including pesticides, endotoxin, and allergens have been associated with risk of various cancers and other chronic diseases, although the biological mechanisms underlying these associations are generally unclear. To facilitate future molecular epidemiologic...

AN OBJECTIVE CLIMATOLOGY OF CAROLINA COASTAL FRONTS

EPA Science Inventory

This study describes a simple objective method to identify cases of coastal frontogenesis offshore of the Carolinas and to characterize the sensible weather associated with frontal passage at measurement sites near the coast. The identification method, based on surface hourly d...

Lack of association between NAT2 polymorphism and prostate cancer risk: a meta-analysis and trial sequential analysis

PubMed Central

Tang, Jingyuan; Xu, Lingyan; Xu, Haoxiang; Li, Ran; Han, Peng; Yang, Haiwei

2017-01-01

Previous studies have investigated the association between NAT2 polymorphism and the risk of prostate cancer (PCa). However, the findings from these studies remained inconsistent. Hence, we performed a meta-analysis to provide a more reliable conclusion about such associations. In the present meta-analysis, 13 independent case-control studies were included with a total of 14,469 PCa patients and 10,689 controls. All relevant studies published were searched in the databates PubMed, EMBASE, and Web of Science, till March 1st, 2017. We used the pooled odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of the association between NAT2*4 allele and susceptibility to PCa. Subgroup analysis was carried out by ethnicity, source of controls and genotyping method. What's more, we also performed trial sequential analysis (TSA) to reduce the risk of type I error and evaluate whether the evidence of the results was firm. Firstly, our results indicated that NAT2*4 allele was not associated with PCa susceptibility (OR = 1.00, 95% CI= 0.95–1.05; P = 0.100). However, after excluding two studies for its heterogeneity and publication bias, no significant relationship was also detected between NAT2*4 allele and the increased risk of PCa, in fixed-effect model (OR = 0.99, 95% CI= 0.94–1.04; P = 0.451). Meanwhile, no significant increased risk of PCa was found in the subgroup analyses by ethnicity, source of controls and genotyping method. Moreover, TSA demonstrated that such association was confirmed in the present study. Therefore, this meta-analysis suggested that no significant association between NAT2 polymorphism and the risk of PCa was found. PMID:28915684

Nonlinear association criterion, nonlinear Granger causality and related issues with applications to neuroimage studies.

PubMed

Tao, Chenyang; Feng, Jianfeng

2016-03-15

Quantifying associations in neuroscience (and many other scientific disciplines) is often challenged by high-dimensionality, nonlinearity and noisy observations. Many classic methods have either poor power or poor scalability on data sets of the same or different scales such as genetical, physiological and image data. Based on the framework of reproducing kernel Hilbert spaces we proposed a new nonlinear association criteria (NAC) with an efficient numerical algorithm and p-value approximation scheme. We also presented mathematical justification that links the proposed method to related methods such as kernel generalized variance, kernel canonical correlation analysis and Hilbert-Schmidt independence criteria. NAC allows the detection of association between arbitrary input domain as long as a characteristic kernel is defined. A MATLAB package was provided to facilitate applications. Extensive simulation examples and four real world neuroscience examples including functional MRI causality, Calcium imaging and imaging genetic studies on autism [Brain, 138(5):13821393 (2015)] and alcohol addiction [PNAS, 112(30):E4085-E4093 (2015)] are used to benchmark NAC. It demonstrates the superior performance over the existing procedures we tested and also yields biologically significant results for the real world examples. NAC beats its linear counterparts when nonlinearity is presented in the data. It also shows more robustness against different experimental setups compared with its nonlinear counterparts. In this work we presented a new and robust statistical approach NAC for measuring associations. It could serve as an interesting alternative to the existing methods for datasets where nonlinearity and other confounding factors are present. Copyright © 2016 Elsevier B.V. All rights reserved.

A powerful approach for association analysis incorporating imprinting effects

PubMed Central

Xia, Fan; Zhou, Ji-Yuan; Fung, Wing Kam

2011-01-01

Motivation: For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants. Results: In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy–Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset. Contact: wingfung@hku.hk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21798962

A powerful approach for association analysis incorporating imprinting effects.

PubMed

Xia, Fan; Zhou, Ji-Yuan; Fung, Wing Kam

2011-09-15

For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants. In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy-Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset. wingfung@hku.hk Supplementary data are available at Bioinformatics online.

Pathway-Based Genome-Wide Association Studies for Two Meat Production Traits in Simmental Cattle.

PubMed

Fan, Huizhong; Wu, Yang; Zhou, Xiaojing; Xia, Jiangwei; Zhang, Wengang; Song, Yuxin; Liu, Fei; Chen, Yan; Zhang, Lupei; Gao, Xue; Gao, Huijiang; Li, Junya

2015-12-17

Most single nucleotide polymorphisms (SNPs) detected by genome-wide association studies (GWAS), explain only a small fraction of phenotypic variation. Pathway-based GWAS were proposed to improve the proportion of genes for some human complex traits that could be explained by enriching a mass of SNPs within genetic groups. However, few attempts have been made to describe the quantitative traits in domestic animals. In this study, we used a dataset with approximately 7,700,000 SNPs from 807 Simmental cattle and analyzed live weight and longissimus muscle area using a modified pathway-based GWAS method to orthogonalise the highly linked SNPs within each gene using principal component analysis (PCA). As a result, of the 262 biological pathways of cattle collected from the KEGG database, the gamma aminobutyric acid (GABA)ergic synapse pathway and the non-alcoholic fatty liver disease (NAFLD) pathway were significantly associated with the two traits analyzed. The GABAergic synapse pathway was biologically applicable to the traits analyzed because of its roles in feed intake and weight gain. The proposed method had high statistical power and a low false discovery rate, compared to those of the smallest P-value and SNP set enrichment analysis methods.

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer’s disease risk

PubMed Central

Caffo, Brian S.; Crainiceanu, Ciprian M.; Verduzco, Guillermo; Joel, Suresh; Mostofsky, Stewart H.; Bassett, Susan Spear; Pekar, James J.

2010-01-01

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer’s disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer’s disease risk under a verbal paired associates task. We found a indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, that was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles. PMID:20227508

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk.

PubMed

Caffo, Brian S; Crainiceanu, Ciprian M; Verduzco, Guillermo; Joel, Suresh; Mostofsky, Stewart H; Bassett, Susan Spear; Pekar, James J

2010-07-01

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer's disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found an indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, which was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles. Copyright (c) 2010 Elsevier Inc. All rights reserved.

A Follow-Up Study of Mortality, Health Conditions and Associated Disabilities of People with Intellectual Disabilities in a Swedish County

ERIC Educational Resources Information Center

Gustavson, K.-H.; Umb-Carlsson, O.; Sonnander, K.

2005-01-01

Background: In the planning of services and health care for individuals with intellectual disability (ID), information is needed on the special requirements for habilitation and medical service and associated disabilities. Material and Methods: An unselected consecutive series of 82 adult persons with ID was studied. The medical examination…

Changes Observed in Views of Nature of Science during a Historically Based Unit

ERIC Educational Resources Information Center

Rudge, David Wÿss; Cassidy, David Paul; Fulford, Janice Marie; Howe, Eric Michael

2014-01-01

Numerous empirical studies have provided evidence of the effectiveness of an explicit and reflective approach to the learning of issues associated with the nature of science (NOS) (c.f. Abd-El-Khalick and Lederman in "J Res Sci Teach" 37(10):1057-1095, 2000). This essay reports the results of a mixed-methods association study involving…

Evaluating the Workload of On-Call Psychiatry Residents: Which Activities Are Associated with Sleep Loss?

ERIC Educational Resources Information Center

Cooke, Brian K.; Cooke, Erinn O.; Sharfstein, Steven S.

2012-01-01

Objective: The purpose of this study was to review the workload inventory of on-call psychiatry residents and to evaluate which activities were associated with reductions in on-call sleep. Method: A prospective cohort study was conducted, following 20 psychiatry residents at a 231-bed psychiatry hospital, from July 1, 2008 through June 30, 2009.…

Reader Reaction On the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty

PubMed Central

Wu, Baolin; Guan, Weihua

2015-01-01

Summary Acar and Sun (2013, Biometrics, 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model. PMID:25351417

Reader reaction on the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty.

PubMed

Wu, Baolin; Guan, Weihua

2015-06-01

Acar and Sun (2013, Biometrics 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model. © 2014, The International Biometric Society.

Effectively Identifying eQTLs from Multiple Tissues by Combining Mixed Model and Meta-analytic Approaches

PubMed Central

Choi, Ted; Eskin, Eleazar

2013-01-01

Gene expression data, in conjunction with information on genetic variants, have enabled studies to identify expression quantitative trait loci (eQTLs) or polymorphic locations in the genome that are associated with expression levels. Moreover, recent technological developments and cost decreases have further enabled studies to collect expression data in multiple tissues. One advantage of multiple tissue datasets is that studies can combine results from different tissues to identify eQTLs more accurately than examining each tissue separately. The idea of aggregating results of multiple tissues is closely related to the idea of meta-analysis which aggregates results of multiple genome-wide association studies to improve the power to detect associations. In principle, meta-analysis methods can be used to combine results from multiple tissues. However, eQTLs may have effects in only a single tissue, in all tissues, or in a subset of tissues with possibly different effect sizes. This heterogeneity in terms of effects across multiple tissues presents a key challenge to detect eQTLs. In this paper, we develop a framework that leverages two popular meta-analysis methods that address effect size heterogeneity to detect eQTLs across multiple tissues. We show by using simulations and multiple tissue data from mouse that our approach detects many eQTLs undetected by traditional eQTL methods. Additionally, our method provides an interpretation framework that accurately predicts whether an eQTL has an effect in a particular tissue. PMID:23785294

Association between Chewing Side Preference and Dental Caries among Deciduous, Mixed and Permanent Dentition

PubMed Central

Sharma, Reena; Kashyap, Nilotpol; Prajapati, Deepesh; Kappadi, Damodar; Wadhwa, Saakshe; Gandotra, Shina; Yadav, Poonam

2016-01-01

Introduction Chewing Side Preference (CSP) is said to occur when mastication is recognized exclusively/consistently or predominantly on the same side of the jaw. It can be assessed by using the direct method - visual observation and indirect methods by electric programs, such as cinematography, kinetography and computerized electromyography. Aim The present study was aimed at evaluating the prevalence of CSP in deciduous, mixed and permanent dentitions and relating its association with dental caries. Materials and Methods In a cross-sectional observational study, 240 school going children aged 3 to 18years were randomly allocated to three experimental groups according to the deciduous dentition, mixed dentition and permanent dentition period. The existence of a CSP was determined using a direct method by asking the children to chew on a piece of gum (trident sugarless). The Mann Whitney U-test was used to compare the CSP and also among the boys and girls. The Spearman’s Correlation Coefficient was used to correlate CSP and dental caries among the three study groups and also among the groups. Results CSP was observed in 69%, 83% and 76% of children with primary, mixed and permanent dentition respectively (p>0.05). There was no statistically significant association between the presence of CSP and dental caries among the three study groups. Conclusion There was a weak or no correlation between gender and distribution of CSP and between presence of CSP and dental caries. PMID:27790569

Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report.

PubMed

Kim, Dong Wook; Kim, Hwiyoung; Nam, Woong; Kim, Hyung Jun; Cha, In-Ho

2018-04-23

The aim of this study was to build and validate five types of machine learning models that can predict the occurrence of BRONJ associated with dental extraction in patients taking bisphosphonates for the management of osteoporosis. A retrospective review of the medical records was conducted to obtain cases and controls for the study. Total 125 patients consisting of 41 cases and 84 controls were selected for the study. Five machine learning prediction algorithms including multivariable logistic regression model, decision tree, support vector machine, artificial neural network, and random forest were implemented. The outputs of these models were compared with each other and also with conventional methods, such as serum CTX level. Area under the receiver operating characteristic (ROC) curve (AUC) was used to compare the results. The performance of machine learning models was significantly superior to conventional statistical methods and single predictors. The random forest model yielded the best performance (AUC = 0.973), followed by artificial neural network (AUC = 0.915), support vector machine (AUC = 0.882), logistic regression (AUC = 0.844), decision tree (AUC = 0.821), drug holiday alone (AUC = 0.810), and CTX level alone (AUC = 0.630). Machine learning methods showed superior performance in predicting BRONJ associated with dental extraction compared to conventional statistical methods using drug holiday and serum CTX level. Machine learning can thus be applied in a wide range of clinical studies. Copyright © 2017. Published by Elsevier Inc.

A Bayesian Method for Evaluating and Discovering Disease Loci Associations

PubMed Central

Jiang, Xia; Barmada, M. Michael; Cooper, Gregory F.; Becich, Michael J.

2011-01-01

Background A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. PMID:21853025

Perceived discrimination, humiliation, and mental health: a mixed-methods study among Haitian migrants in the Dominican Republic.

PubMed

Keys, Hunter M; Kaiser, Bonnie N; Foster, Jennifer W; Burgos Minaya, Rosa Y; Kohrt, Brandon A

2015-01-01

Many Haitian migrants live and work as undocumented laborers in the Dominican Republic. This study examines the legacy of anti-Haitian discrimination in the Dominican Republic and association of discrimination with mental health among Haitian migrants. This study used mixed methods to generate hypotheses for associations between discrimination and mental health of Haitian migrants in the Dominican Republic. In-depth interviews were conducted with 21 Haitian and 18 Dominican community members and clinicians. One hundred and twenty-seven Haitian migrants participated in a pilot cross-sectional community survey. Instruments included culturally adapted Kreyòl versions of the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) and a locally developed function impairment scale. Haitian migrants described humiliation (imilyasyon) as a reason for mental distress and barrier to health care. Dominicans reported that discrimination (discriminación) was not a current social problem and attributed negative social interactions to sociocultural, behavioral, and biological differences between Dominicans and Haitians. These qualitative findings were supported in the quantitative analyses. Perceived discrimination was significantly associated with depression severity and functional impairment. Perceived mistreatment by Dominicans was associated with a 6.6-point increase in BDI score (90% confidence interval [CI]: 3.29, 9.9). Knowing someone who was interrogated or deported was associated with a 3.4-point increase in BAI score (90% CI: 0.22, 6.64). Both qualitative and quantitative methods suggest that perceived discrimination and the experience of humiliation contribute to Haitian migrant mental ill-health and limit access to health care. Future research should evaluate these associations and identify intervention pathways for both improved treatment access and reduction of discrimination-related health risk factors.

Real-Time Tracking of Knee Adduction Moment in Patients with Knee Osteoarthritis

PubMed Central

Kang, Sang Hoon; Lee, Song Joo; Zhang, Li-Qun

2014-01-01

Background The external knee adduction moment (EKAM) is closely associated with the presence, progression, and severity of knee osteoarthritis (OA). However, there is a lack of convenient and practical method to estimate and track in real-time the EKAM of patients with knee OA for clinical evaluation and gait training, especially outside of gait laboratories. New Method A real-time EKAM estimation method was developed and applied to track and investigate the EKAM and other knee moments during stepping on an elliptical trainer in both healthy subjects and a patient with knee OA. Results Substantial changes were observed in the EKAM and other knee moments during stepping in the patient with knee OA. Comparison with Existing Method(s) This is the first study to develop and test feasibility of real-time tracking method of the EKAM on patients with knee OA using 3-D inverse dynamics. Conclusions The study provides us an accurate and practical method to evaluate in real-time the critical EKAM associated with knee OA, which is expected to help us to diagnose and evaluate patients with knee OA and provide the patients with real-time EKAM feedback rehabilitation training. PMID:24361759

Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918

A Mixed-Method Study to Determine the Benefits of Periconceptional Folic Acid Supplementation and Effects of Folic Acid Deficiency in Mothers on Birth Outcomes.

PubMed

Murthy, Gudlavalleti Venkata S; Kolli, Sunanda Reddy; Neogi, Sutapa B; Singh, Samiksha; Allagh, Komal Preet; John, Neena; N, Srinivas; Ramani, Sudha; Shamanna, B R; Doyle, Pat; Kinra, Sanjay; Ness, Andy; Pallepogula, Dinesh Raj; Pant, Hira B; Babbar, Smiksha; Reddy, Raghunath; Singh, Rachna

2016-06-23

Evidence from high income countries shows mothers who are supplemented with folic acid in their periconceptional period and early pregnancy have significantly reduced adverse outcomes like birth defects. However, in India there is a paucity of data on association of birth defects and folic acid supplementation. We identified a few important questions to be answered using separate scientific methods and then planned to triangulate the information. In this paper, we describe the protocol of our study that aims to determine the association of folic acid and pregnancy outcomes like neural tube defects (NTDs) and orofacial clefts (OFCs). We decided to fill the gaps in knowledge from India to determine public health consequences of folic acid deficiency and factors influencing dietary and periconceptional consumption of folic acid. The proposed study will be carried out in five stages and will examine the questions related to folic acid deficiency across selected locations in South and North India. The study will be carried out over a period of 4 years through the hierarchical evidence-based approach. At first a systematic review was conducted to pool the current birth prevalence of NTDs and orofacial clefts OFCs in India. To investigate the population prevalence, we plan to use the key informant method to determine prevalence of NTDs and OFCs. To determine the normal serum estimates of folic acid, iron, and vitamin B12 among Indian women (15-35 years), we will conduct a population-based, cross-sectional study. We will further strengthen the evidence of association between OFCs and folic acid by conducting a hospital-based, case-control study across three locations of India. Lastly, using qualitative methods we will understand community and health workers perspective on factors that decide the intake of folic acid supplements. This study will provide evidence on the community prevalence of birth defects and prevalence folic acid and vitamin B12 deficiency in the community. The case-control study will help understand the association of folic acid deficiency with OFCs. The results from this study are intended to strengthen the evidence base in childhood disability for planning and policy initiatives.

Aphid Species and Population Dynamics Associated with Strawberry.

PubMed

Bernardi, D; Araujo, E S; Zawadneak, M A C; Botton, M; Mogor, A F; Garcia, M S

2013-12-01

Aphids are among the major pests associated with strawberries in Southern Brasil. In this study, we identified the main species that occur in strawberry fields in the states of Paraná and Rio Grande do Sul, Brasil. We also compared the effectiveness of different sampling methods and studied the population dynamics of aphid species during two strawberry crop cycles in the municipality of Pinhais, state of Paraná, Brasil. Chaetosiphon fragaefolii (Cockerell) and Aphis forbesi Weed were the main species associated with strawberry. The method of hit plant and the Möericke trap showed equal effectiveness to capture wingless and winged insects. The peak population of aphids in the state of Paraná occurred from September to November. This information can help producers to implement strategies to monitor and control the major aphid species that occur in strawberry culture.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

PubMed

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Acceptability of an existing, female-controlled contraceptive method that could potentially protect against HIV: a comparison of diaphragm users and other method users.

PubMed

Bird, Sheryl Thorburn; Harvey, S Marie; Maher, Julie E; Beckman, Linda J

2004-01-01

The diaphragm, an internal barrier contraceptive device, is a candidate for a female-controlled method for preventing human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs). This study's objective was to examine how women who use the diaphragm differ from women using the pill and/or condoms with respect to factors hypothesized to influence the acceptability of contraceptive methods. Our goal was to increase understanding of who finds the diaphragm acceptable and why. We conducted a cross-sectional telephone survey with selected female members of a managed care organization. For this analysis, we limited the sample to 585 women currently using the diaphragm (n = 196), pill (n = 200), condoms (n = 132), or pill and condoms (n = 57). We conducted bivariate analyses and multinomial logistic regression analyses to assess the associations between selected characteristics and diaphragm use. Diaphragm use was significantly associated with several variables. Of particular interest, placing less importance on hormonal method characteristics was significantly associated with diaphragm use (versus use of the pill, condoms, or both). Placing more importance on barrier method attributes was significantly associated with diaphragm use (versus pill use, alone or with condoms). In addition, lower condom use self-efficacy was significantly associated with diaphragm use (versus condom use, alone or with pill). Lack of motivation to avoid HIV/STIs was significantly associated with using the diaphragm versus condoms (only). These results have important implications for future research, interventions, counseling strategies for providers, and product development. Our findings suggest that if the diaphragm protects against HIV, it could be a desirable option for some women.

A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations.

PubMed

Xiao, Qiu; Luo, Jiawei; Liang, Cheng; Cai, Jie; Ding, Pingjian

2017-09-01

MicroRNAs (miRNAs) play crucial roles in post-transcriptional regulations and various cellular processes. The identification of disease-related miRNAs provides great insights into the underlying pathogenesis of diseases at a system level. However, most existing computational approaches are biased towards known miRNA-disease associations, which is inappropriate for those new diseases or miRNAs without any known association information. In this study, we propose a new method with graph regularized non-negative matrix factorization in heterogeneous omics data, called GRNMF, to discover potential associations between miRNAs and diseases, especially for new diseases and miRNAs or those diseases and miRNAs with sparse known associations. First, we integrate the disease semantic information and miRNA functional information to estimate disease similarity and miRNA similarity, respectively. Considering that there is no available interaction observed for new diseases or miRNAs, a preprocessing step is developed to construct the interaction score profiles that will assist in prediction. Next, a graph regularized non-negative matrix factorization framework is utilized to simultaneously identify potential associations for all diseases. The results indicated that our proposed method can effectively prioritize disease-associated miRNAs with higher accuracy compared with other recent approaches. Moreover, case studies also demonstrated the effectiveness of GRNMF to infer unknown miRNA-disease associations for those novel diseases and miRNAs. The code of GRNMF is freely available at https://github.com/XIAO-HN/GRNMF/. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Identification of causal genes for complex traits

PubMed Central

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-01-01

Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484

Identification of causal genes for complex traits.

PubMed

Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar

2015-06-15

Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Fast and robust group-wise eQTL mapping using sparse graphical models.

PubMed

Cheng, Wei; Shi, Yu; Zhang, Xiang; Wang, Wei

2015-01-16

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways. We introduce a new approach to identify novel group-wise associations between sets of SNPs and sets of genes. Such associations are captured by hidden variables connecting SNPs and genes. Our model is a linear-Gaussian model and uses two types of hidden variables. One captures the set associations between SNPs and genes, and the other captures confounders. We develop an efficient optimization procedure which makes this approach suitable for large scale studies. Extensive experimental evaluations on both simulated and real datasets demonstrate that the proposed methods can effectively capture both individual and group-wise signals that cannot be identified by the state-of-the-art eQTL mapping methods. Considering group-wise associations significantly improves the accuracy of eQTL mapping, and the successful multi-layer regression model opens a new approach to understand how multiple SNPs interact with each other to jointly affect the expression level of a group of genes.

Teaching Methods Associated with Student Progress in General Education Courses. IDEA Research Report #9

ERIC Educational Resources Information Center

Benton, Stephen L.; Li, Dan

2015-01-01

This study examined which teaching methods are most highly correlated with student progress on relevant course objectives in first- and second-year (lower-level) general education courses. We specifically sought to identify teaching methods that distinguish progress made by students taking a general education course from that made by students…

Ethical Principles Associated with the Publication of Research in ASHA's Scholarly Journals: Importance and Adequacy of Coverage

ERIC Educational Resources Information Center

Ingham, Janis C.; Minifie, Fred D.; Horner, Jennifer; Robey, Randall R.; Lansing, Charissa; McCartney, James H.; Slater, Sarah C.; Moss, Sharon E.

2011-01-01

Purpose: The purpose of this 2-part study was to determine the importance of specific topics relating to publication ethics and adequacy of the American Speech-Language-Hearing Association's (ASHA's) policies regarding these topics. Method: A 56-item Web-based survey was sent to (a) ASHA journal editors, associate editors, and members of the…

Evaluation Plan for the Computerized Adaptive Vocational Aptitude Battery

DTIC Science & Technology

1982-05-15

Educational and Psychological Tests published by the American Psychological Association, the American Educational Research Association, and the National...Psychometric Society Meetings, May 1981. References 71 American Psychological Association. Standards for educational and psychological tests . Washington, D.C...Methods Program, Dept. of Psychology , Uni- versity of Minnesota, MN, September, 1981. Koch, W.R. & Reckase, M.D. A live tailored testing comparison study

Behavior Correlates of Post-Stroke Disability Using Data Mining and Infographics

PubMed Central

Yoon, Sunmoo; Gutierrez, Jose

2015-01-01

Purpose Disability is a potential risk for stroke survivors. This study aims to identify disability risk factors associated with stroke and their relative importance and relationships from a national behavioral risk factor dataset. Methods Data of post-stroke individuals in the U.S (n=19,603) including 397 variables were extracted from a publically available national dataset and analyzed. Data mining algorithms including C4.5 and linear regression with M5s methods were applied to build association models for post-stroke disability using Weka software. The relative importance and relationship of 70 variables associated with disability were presented in infographics for clinicians to understand easily. Results Fifty-five percent of post-stroke patients experience disability. Exercise, employment and satisfaction of life were relatively important factors associated with disability among stroke patients. Modifiable behavior factors strongly associated with disability include exercise (OR: 0.46, P<0.01) and good rest (OR 0.37, P<0.01). Conclusions Data mining is promising to discover factors associated with post-stroke disability from a large population dataset. The findings can be potentially valuable for establishing the priorities for clinicians and researchers and for stroke patient education. The methods may generalize to other health conditions. PMID:26835413

City Governments and Aging in Place: Community Design, Transportation and Housing Innovation Adoption

PubMed Central

Lehning, Amanda J.

2012-01-01

Purpose of the study: To examine the characteristics associated with city government adoption of community design, housing, and transportation innovations that could benefit older adults. Design and methods: A mixed-methods study with quantitative data collected via online surveys from 62 city planners combined with qualitative data collected via telephone interviews with a subsample of 18 survey respondents. Results: Results indicate that advocacy is an effective strategy to encourage city government adoption of these innovations. Percent of the population with a disability was positively associated, whereas percent of the population aged 65 and older was not associated or negatively associated, with innovation adoption in the regression models. Qualitative interviews suggest that younger individuals with disabilities are more active in local advocacy efforts. Implications: Results suggest that successful advocacy strategies for local government adoption include facilitating the involvement of older residents, targeting key decision makers within government, emphasizing the financial benefits to the city, and focusing on cities whose aging residents are vulnerable to disease and disability. PMID:21900505

Methods for associating or dissociating guest materials with a metal organic framework, systems for associating or dissociating guest materials within a series of metal organic frameworks, thermal energy transfer assemblies, and methods for transferring thermal energy

DOEpatents

McGrail, B. Peter; Brown, Daryl R.; Thallapally, Praveen K.

2016-08-02

Methods for releasing associated guest materials from a metal organic framework are provided. Methods for associating guest materials with a metal organic framework are also provided. Methods are provided for selectively associating or dissociating guest materials with a metal organic framework. Systems for associating or dissociating guest materials within a series of metal organic frameworks are provided. Thermal energy transfer assemblies are provided. Methods for transferring thermal energy are also provided.

Methods for associating or dissociating guest materials with a metal organic framework, systems for associating or dissociating guest materials within a series of metal organic frameworks, thermal energy transfer assemblies, and methods for transferring thermal energy

DOEpatents

McGrail, B. Peter; Brown, Daryl R.; Thallapally, Praveen K.

2014-08-05

Methods for releasing associated guest materials from a metal organic framework are provided. Methods for associating guest materials with a metal organic framework are also provided. Methods are provided for selectively associating or dissociating guest materials with a metal organic framework. Systems for associating or dissociating guest materials within a series of metal organic frameworks are provided. Thermal energy transfer assemblies are provided. Methods for transferring thermal energy are also provided.

Associations of physical activity, fitness, and body composition with heart rate variability–based indicators of stress and recovery on workdays: a cross-sectional study

PubMed Central

2014-01-01

Background The purpose of this study was to investigate how physical activity (PA), cardiorespiratory fitness (CRF), and body composition are associated with heart rate variability (HRV)-based indicators of stress and recovery on workdays. Additionally, we evaluated the association of objectively measured stress with self-reported burnout symptoms. Methods Participants of this cross-sectional study were 81 healthy males (age range 26–40 y). Stress and recovery on workdays were measured objectively based on HRV recordings. CRF and anthropometry were assessed in laboratory conditions. The level of PA was based on a detailed PA interview (MET index [MET-h/d]) and self-reported activity class. Results PA, CRF, and body composition were significantly associated with levels of stress and recovery on workdays. MET index (P < 0.001), activity class (P = 0.001), and CRF (P = 0.019) were negatively associated with stress during working hours whereas body fat percentage (P = 0.005) was positively associated. Overall, 27.5% of the variance of total stress on workdays (P = 0.001) was accounted for by PA, CRF, and body composition. Body fat percentage and body mass index were negatively associated with night-time recovery whereas CRF was positively associated. Objective work stress was associated (P = 0.003) with subjective burnout symptoms. Conclusions PA, CRF, and body composition are associated with HRV-based stress and recovery levels, which needs to be taken into account in the measurement, prevention, and treatment of work-related stress. The HRV-based method used to determine work-related stress and recovery was associated with self-reported burnout symptoms, but more research on the clinical importance of the methodology is needed. PMID:24742265

Properties of permutation-based gene tests and controlling type 1 error using a summary statistic based gene test

PubMed Central

2013-01-01

Background The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these associations, numerous statistical methods have been devoted to them. However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective and those methods currently implemented are often permutation-based. Results One property of some permutation-based tests is that their power varies as a function of whether significant markers are in regions of linkage disequilibrium (LD) or not, which we show from a theoretical perspective. We therefore develop two methods for quantifying the degree of association between a genomic region and outcome, both of whose power does not vary as a function of LD structure. One method uses dimension reduction to “filter” redundant information when significant LD exists in the region, while the other, called the summary-statistic test, controls for LD by scaling marker Z-statistics using knowledge of the correlation matrix of markers. An advantage of this latter test is that it does not require the original data, but only their Z-statistics from univariate regressions and an estimate of the correlation structure of markers, and we show how to modify the test to protect the type 1 error rate when the correlation structure of markers is misspecified. We apply these methods to sequence data of oral cleft and compare our results to previously proposed gene tests, in particular permutation-based ones. We evaluate the versatility of the modification of the summary-statistic test since the specification of correlation structure between markers can be inaccurate. Conclusion We find a significant association in the sequence data between the 8q24 region and oral cleft using our dimension reduction approach and a borderline significant association using the summary-statistic based approach. We also implement the summary-statistic test using Z-statistics from an already-published GWAS of Chronic Obstructive Pulmonary Disorder (COPD) and correlation structure obtained from HapMap. We experiment with the modification of this test because the correlation structure is assumed imperfectly known. PMID:24199751

Properties of permutation-based gene tests and controlling type 1 error using a summary statistic based gene test.

PubMed

Swanson, David M; Blacker, Deborah; Alchawa, Taofik; Ludwig, Kerstin U; Mangold, Elisabeth; Lange, Christoph

2013-11-07

The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these associations, numerous statistical methods have been devoted to them. However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective and those methods currently implemented are often permutation-based. One property of some permutation-based tests is that their power varies as a function of whether significant markers are in regions of linkage disequilibrium (LD) or not, which we show from a theoretical perspective. We therefore develop two methods for quantifying the degree of association between a genomic region and outcome, both of whose power does not vary as a function of LD structure. One method uses dimension reduction to "filter" redundant information when significant LD exists in the region, while the other, called the summary-statistic test, controls for LD by scaling marker Z-statistics using knowledge of the correlation matrix of markers. An advantage of this latter test is that it does not require the original data, but only their Z-statistics from univariate regressions and an estimate of the correlation structure of markers, and we show how to modify the test to protect the type 1 error rate when the correlation structure of markers is misspecified. We apply these methods to sequence data of oral cleft and compare our results to previously proposed gene tests, in particular permutation-based ones. We evaluate the versatility of the modification of the summary-statistic test since the specification of correlation structure between markers can be inaccurate. We find a significant association in the sequence data between the 8q24 region and oral cleft using our dimension reduction approach and a borderline significant association using the summary-statistic based approach. We also implement the summary-statistic test using Z-statistics from an already-published GWAS of Chronic Obstructive Pulmonary Disorder (COPD) and correlation structure obtained from HapMap. We experiment with the modification of this test because the correlation structure is assumed imperfectly known.

Association between social factors and performance during Functional Capacity Evaluations: a systematic review.

PubMed

Ansuategui Echeita, Jone; van Holland, Berry J; Gross, Douglas P; Kool, Jan; Oesch, Peter; Trippolini, Maurizio A; Reneman, Michiel F

2018-03-09

Determine the association of different social factors with Functional Capacity Evaluation (FCE) performance in adults. A systematic literature search was performed in MEDLINE, CINAHL, and PsycINFO electronic databases. Studies were eligible if they studied social factor's association with the performance of adults undergoing FCE. Studies were assessed on methodological quality and quality of evidence. The review was performed using best-evidence synthesis methods. Thirteen studies were eligible and 11 social factors were studied. Considerable heterogeneity regarding measurements, populations, and methods existed among the studies. High quality of evidence was found for the association of FCE performance with the country of FCE and examiner's fear behavior; moderate quality of evidence with previous job salary; and low or very low quality of evidence with compensation status, litigation status, type of instruction, time of day (workday), primary or mother language, and ethnicity. Other social factors were not studied. Evidence for associations of various social factors with FCE performance was found, but robust conclusions about the strength of the associations cannot be made. Quality of evidence ranged from high to very low. Further research on social factors, also within a biopsychosocial context, is necessary to provide a better understanding of FCE performance. Implications for Rehabilitation Research on Functional Capacity Evaluation (FCE) performance and its association with biopsychosocial factors have scarcely addressed the impact of social factors, limiting full understanding of FCE results. The social factors, healthcare (examiner's fear behavior and type of instruction), personal or cultural systems (country of FCE, primary or mother language, and ethnicity), workplace system (previous job salary, time of day (workday)), and legislative and insurance system (compensation and litigation status), have a bearing in FCE performance. Better understanding of factors associating with functional capacity provide insights in FCE, allowing clinicians to improve the evaluations and interpretations of the assessment and better design the rehabilitation program. Better understanding of factors that influence FCE performance, and of unstudied factors, will allow researchers guidance to further investigate the construct of functional capacity.

Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing

PubMed Central

Hua, Xing; Zeller, Georg; Sunagawa, Shinichi; Voigt, Anita Y.; Hercog, Rajna; Goedert, James J.; Shi, Jianxin; Bork, Peer; Sinha, Rashmi

2016-01-01

Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect associations that are reproducible and significant after correction for multiple testing. PMID:27171425

Does Categorization Method Matter in Exploring Volume-Outcome Relation? A Multiple Categorization Methods Comparison in Coronary Artery Bypass Graft Surgery Surgical Site Infection.

PubMed

Yu, Tsung-Hsien; Tung, Yu-Chi; Chung, Kuo-Piao

2015-08-01

Volume-infection relation studies have been published for high-risk surgical procedures, although the conclusions remain controversial. Inconsistent results may be caused by inconsistent categorization methods, the definitions of service volume, and different statistical approaches. The purpose of this study was to examine whether a relation exists between provider volume and coronary artery bypass graft (CABG) surgical site infection (SSI) using different categorization methods. A population-based cross-sectional multi-level study was conducted. A total of 10,405 patients who received CABG surgery between 2006 and 2008 in Taiwan were recruited. The outcome of interest was surgical site infection for CABG surgery. The associations among several patient, surgeon, and hospital characteristics was examined. The definition of surgeons' and hospitals' service volume was the cumulative CABG service volumes in the previous year for each CABG operation and categorized by three types of approaches: Continuous, quartile, and k-means clustering. The results of multi-level mixed effects modeling showed that hospital volume had no association with SSI. Although the relation between surgeon volume and surgical site infection was negative, it was inconsistent among the different categorization methods. Categorization of service volume is an important issue in volume-infection study. The findings of the current study suggest that different categorization methods might influence the relation between volume and SSI. The selection of an optimal cutoff point should be taken into account for future research.

Acupuncture and chiropractic care for chronic pain in an integrated health plan: a mixed methods study

PubMed Central

2011-01-01

Background Substantial recent research examines the efficacy of many types of complementary and alternative (CAM) therapies. However, outcomes associated with the "real-world" use of CAM has been largely overlooked, despite calls for CAM therapies to be studied in the manner in which they are practiced. Americans seek CAM treatments far more often for chronic musculoskeletal pain (CMP) than for any other condition. Among CAM treatments for CMP, acupuncture and chiropractic (A/C) care are among those with the highest acceptance by physician groups and the best evidence to support their use. Further, recent alarming increases in delivery of opioid treatment and surgical interventions for chronic pain--despite their high costs, potential adverse effects, and modest efficacy--suggests the need to evaluate real world outcomes associated with promising non-pharmacological/non-surgical CAM treatments for CMP, which are often well accepted by patients and increasingly used in the community. Methods/Design This multi-phase, mixed methods study will: (1) conduct a retrospective study using information from electronic medical records (EMRs) of a large HMO to identify unique clusters of patients with CMP (e.g., those with differing demographics, histories of pain condition, use of allopathic and CAM health services, and comorbidity profiles) that may be associated with different propensities for A/C utilization and/or differential outcomes associated with such care; (2) use qualitative interviews to explore allopathic providers' recommendations for A/C and patients' decisions to pursue and retain CAM care; and (3) prospectively evaluate health services/costs and broader clinical and functional outcomes associated with the receipt of A/C relative to carefully matched comparison participants receiving traditional CMP services. Sensitivity analyses will compare methods relying solely on EMR-derived data versus analyses supplementing EMR data with conventionally collected patient and clinician data. Discussion Successful completion of these aggregate aims will provide an evaluation of outcomes associated with the real-world use of A/C services. The trio of retrospective, qualitative, and prospective study will also provide a clearer understanding of the decision-making processes behind the use of A/C for CMP and a transportable methodology that can be applied to other health care settings, CAM treatments, and clinical populations. Trial registration ClinicalTrials.gov: NCT01345409 PMID:22118061

A scoping review on determinants of unmet need for family planning among women of reproductive age in low and middle income countries.

PubMed

Wulifan, Joseph K; Brenner, Stephan; Jahn, Albrecht; De Allegri, Manuela

2016-01-15

Poor access and low contraceptive prevalence are common to many Low- and Middle-Income Countries (LMICs). Unmet need for family planning (FP), defined as the proportion of women wishing to limit or postpone child birth, but not using contraception, has been central to reproductive health efforts for decades and still remains relevant for most policy makers and FP programs in LMICs. There is still a lag in contraceptive uptake across regions resulting in high unmet need due to various socioeconomic and cultural factors. In this mixed method scoping review we analyzed quantitative, qualitative and mixed method studies to summarize those factors influencing unmet need among women in LMICs. We conducted our scoping review by employing mixed method approach. We included studies applying quantitative and qualitative methods retrieved from online data bases (PubMed, JSTOR, and Google Scholar). We also reviewed the indexes of journals specific to the field of reproductive health by using a set of keywords related to unmet contraception need, and non-contraception use in LMICs. We retrieved 283 articles and retained 34 articles meeting our inclusion criteria. Of these, 26 were quantitative studies and 8 qualitative studies. We found unmet need for FP to range between 20 % and 58% in most studies. Woman's age was negatively associated with total unmet need for FP, meaning as women get older the unmet need for FP decreases. The number of children was found to be a positively associated determinant for a woman's total unmet need. Also, woman's level of education was negatively associated--as a woman's education improves, her total unmet need decreases. Frequently reported reasons for non-contraception use were opposition from husband or husbands fear of infidelity, as well as woman's fear of side effects or other health concerns related to contraceptive methods. Factors associated with unmet need for FP and non-contraception use were common across different LMIC settings. This suggests that women in LMICs face similar barriers to FP and that it is still necessary for reproductive health programs to identify FP interventions that more specifically tackle unmet need.

Power System Transient Stability Based on Data Mining Theory

NASA Astrophysics Data System (ADS)

Cui, Zhen; Shi, Jia; Wu, Runsheng; Lu, Dan; Cui, Mingde

2018-01-01

In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.

The Occupational Role of Women in Military Service: Validation of Occupation and Prevalence of Exposures in the Millennium Cohort Study

DTIC Science & Technology

2007-08-01

These and other studies investigating exposures associated with morbidity and reproductive health outcomes (Hourani & Hilton 2000; Kang et al. 2000...epidemiologic studies. Objectively ascertained exposure data are often not available. Consequently , researchers must rely on self-reported data to assess...associations between exposures and adverse health outcomes . Both assessment methods are limited in scope and inferential capabilities and may lead to

Evaluating the efficacy of a centrifugation-flotation method for extracting Ascaris ova from soil.

PubMed

Cranston, Imogen; Teoh, Penelope J; Baker, Sarah M; Sengupta, Mita E; Ensink, Jeroen H J

2016-07-01

Soil transmitted helminths (STH) continue to be associated with high burdens of disease, with an estimated 1.45 billion people infected with STH globally. The promotion and construction of latrines is considered the first barrier to prevent transmission of STH. The absence of a reliable method to extract STH ova from soil makes it challenging to examine whether the use of latrines may or may not have an effect on environmental contamination with ova. The present study evaluated the recovery rate of a method developed to extract STH ova from soil. The adapted centrifugation and flotation technique was applied to 15 soil types, which were seeded with Ascaris suum ova. Soil type, soil moisture content, soil texture and organic matter content were assessed for each soil sample. The average ova recovery rate was 28.2%, with the recovery rate of the method decreasing with increasing soil moisture content, particle size and organic matter content. The association between recovery rate and organic matter content was statistically significant. The present study identified a low recovery rate for an adapted centrifugation-flotation method, although this was similar to the recovery rate demonstrated by other methods developed for soil. Soil organic matter content was significantly associated with ova recovery rates. © The Author 2016. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Determinants of long acting and permanent contraceptive methods utilization among married women of reproductive age groups in western Ethiopia: a cross-sectional study.

PubMed

Melka, Alemu Sufa; Tekelab, Tesfalidet; Wirtu, Desalegn

2015-01-01

In Ethiopia information on the level of utilization of the long term and permanent contraceptive methods and associated factorsis lacking. The aim of this study was to understand the determinant factors of long acting and permanent contraceptive methods use among married women of reproductive age in Western Ethiopia. A community based cross-sectional study design was employed. Multi stage sampling was used to select 1003 study participants. Data was collected from April 10 to April 25,2014 using a pre- tested structured questionnaire. The data were entered using Epi-info version 3.5.1 and exported to SPSS version 20 for analysis. Multivariate logistic regression analysis was done to identify predictors of long acting and permanent contraceptive methods at 95% CL. Use of long acting and permanent contraceptive methods in this study was found to be 20%. Survey results showed a significant positive association between utilization of long acting and permanent contraceptive methods and women's education (AOR=1.72, 95%CI=1.02-3.05), women's occupation (AOR=2.01, 95% CI=1.11-3.58), number of live children (AOR=2.42, 95% CI: 1.46-4.02), joint fertility related decision (AOR=6.11, 95% CI: 2.29-16.30), having radio/TV (AOR=2.31, 95% CI: 1.40-3.80), and discussion with health care provider about long acting and permanent contraceptive methods (AOR=13.72, 95% CI: 8.37-22.47). Efforts need to be aimed at women empowerment, health education, and encouraging open discussion of family planning by couples.

"Stand by Me": A Mixed Methods Study of a Collegiate Marching Band Members' Intragroup Beliefs throughout a Performance Season

ERIC Educational Resources Information Center

Matthews, Wendy K.

2017-01-01

The purpose of this mixed methods study was to investigate intragroup beliefs regarding participation in a National Collegiate Athletic Association (NCAA) Division II marching band throughout the university's American football season. Fifty-three undergraduates from an urban midwestern university elected one of two options: (1) focus group only or…

Effects of time and rainfall on PCR success using DNA extracted from deer fecal pellets

Treesearch

Todd J. Brinkman; Michael K. Schwartz; David K. Person; Kristine L. Pilgrim; Kris J. Hundertmark

2009-01-01

Non-invasive wildlife research using DNA from feces has become increasingly popular. Recent studies have attempted to solve problems associated with recovering DNA from feces by investigating the influence of factors such as season, diet, collection method, preservation method, extraction protocol, and time. To our knowledge, studies of this nature have not addressed...

Association of 25-hydroxy Vitamin D levels with indexes of general and abdominal obesity in Iranian adolescents: The CASPIAN-III study

PubMed Central

Jari, Mohsen; Qorbani, Mostafa; Moafi, Mohammad; Motlagh, Mohammad Esmaeil; Keikha, Mojtaba; Ardalan, Gelayol; Kelishadi, Roya

2015-01-01

Background: This study aimed to determine the association of serum 25-hydroxy Vitamin D (25(OH)D) levels with measures of general and abdominal obesity in Iranian adolescents. Materials and Methods: This nationwide cross-sectional study was conducted among 1090 students, aged 10-18 years, living in 27 provinces in Iran. Serum concentration of 25(OH)D was analyzed quantitatively by direct competitive immunoassay chemiluminescence method. Body mass index (BMI) and waist-to-height ratio (WHtR) were considered as measures of generalized and abdominal obesity, respectively. Results: Study participants consisted of 1090 adolescents (51.9% boy and 67.1% urban residents) with mean age, BMI, and waist circumference of 14.7 (2.6) years, 19.3 (4.2) kg/m2, and 67.82 (12.23) cm, respectively. The median serum 25(OH)D was 13.0 ng/mL (interquartile range: 20.6). Overall, 40% of participants were Vitamin D deficient, and 39% were Vitamin D insufficient. Serum 25(OH)D level was not associated with BMI and WHtR. Conclusion: We did not document any significant association between serum 25(OH)D level and anthropometric measures in adolescents. This finding may be because of considerably high prevalence of hypovitaminosis D in the study population. PMID:25983762

The association between drinking water turbidity and gastrointestinal illness: a systematic review.

PubMed

Mann, Andrea G; Tam, Clarence C; Higgins, Craig D; Rodrigues, Laura C

2007-09-21

Studies suggest that routine variations in public drinking water turbidity may be associated with endemic gastrointestinal illness. We systematically reviewed the literature on this topic. We searched databases and websites for relevant studies in industrialized countries. Studies investigating the association between temporal variations in drinking water turbidity and incidence of acute gastrointestinal illness were assessed for quality. We reviewed good quality studies for evidence of an association between increased turbidity and gastrointestinal illness. We found six relevant good quality studies. Of five studies investigating effluent water turbidity, two found no association. Two studies from Philadelphia reported increased paediatric and elderly hospital use on specific days after increased turbidity. A fifth study reported more telephone health service calls on specific days after peak turbidity. There were differences between studies affecting their comparability, including baseline turbidity and adjustment for seasonal confounders. It is likely that an association between turbidity and GI illness exists in some settings or over a certain range of turbidity. A pooled analysis of available data using standard methods would facilitate interpretation.

Variance Component Selection With Applications to Microbiome Taxonomic Data.

PubMed

Zhai, Jing; Kim, Juhyun; Knox, Kenneth S; Twigg, Homer L; Zhou, Hua; Zhou, Jin J

2018-01-01

High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator) penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV) infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.

Childhood cancer incidence in relation to sunlight exposure

PubMed Central

Musselman, J R B; Spector, L G

2011-01-01

Background: There is increasing interest in the possible association between cancer incidence and vitamin D through its role as a regulator of cell growth and differentiation. Epidemiological studies in adults and one paediatric study suggest an inverse association between sunlight exposure and cancer incidence. Methods: We carried out an ecological study using childhood cancer registry data and two population-level surrogates of sunlight exposure, (1) latitude of the registry city or population centroid of the registry nation and (2) annual solar radiation. All models were adjusted for nation-level socioeconomic status using socioeconomic indicators. Results: Latitude and radiation were significantly associated with cancer incidence, and the direction of association was consistent between the surrogates. Findings were not consistent across tumour types. Conclusion: Our ecological study offers some evidence to support an association between sunlight exposure and risk of childhood cancer. PMID:21102587

Mining gene link information for survival pathway hunting.

PubMed

Jing, Gao-Jian; Zhang, Zirui; Wang, Hong-Qiang; Zheng, Hong-Mei

2015-08-01

This study proposes a gene link-based method for survival time-related pathway hunting. In this method, the authors incorporate gene link information to estimate how a pathway is associated with cancer patient's survival time. Specifically, a gene link-based Cox proportional hazard model (Link-Cox) is established, in which two linked genes are considered together to represent a link variable and the association of the link with survival time is assessed using Cox proportional hazard model. On the basis of the Link-Cox model, the authors formulate a new statistic for measuring the association of a pathway with survival time of cancer patients, referred to as pathway survival score (PSS), by summarising survival significance over all the gene links in the pathway, and devise a permutation test to test the significance of an observed PSS. To evaluate the proposed method, the authors applied it to simulation data and two publicly available real-world gene expression data sets. Extensive comparisons with previous methods show the effectiveness and efficiency of the proposed method for survival pathway hunting.

High red and processed meat consumption is associated with non-alcoholic fatty liver disease and insulin resistance.

PubMed

Zelber-Sagi, Shira; Ivancovsky-Wajcman, Dana; Fliss Isakov, Naomi; Webb, Muriel; Orenstein, Dana; Shibolet, Oren; Kariv, Revital

2018-06-01

High red and processed meat consumption is related to type 2 diabetes. In addition, cooking meat at high temperatures for a long duration forms heterocyclic amines (HCAs), which are related to oxidative stress. However, the association between meat consumption and non-alcoholic fatty liver disease (NAFLD) is yet to be thoroughly tested. Therefore, we aimed to test the association of meat type and cooking method with NAFLD and insulin resistance (IR). This was a cross-sectional study in individuals who were 40-70 years old and underwent screening colonoscopy between 2013 and 2015 in a single center in Israel. NAFLD and IR were evaluated by ultrasonography and homeostasis model assessment. Meat type and cooking method were measured by a food frequency questionnaire (FFQ) and a detailed meat questionnaire. Unhealthy cooking methods were considered as frying and grilling to a level of well done and very well done. Dietary HCA intake was calculated. A total of 789 individuals had a valid FFQ and 357 had a valid meat questionnaire. High consumption of total meat (portions/day above the median) (odds ratio [OR] 1.49; 95% CI 1.05-2.13; p = 0.028; OR 1.63; 1.12-2.37; p = 0.011), red and/or processed meat (OR1.47; 95% CI 1.04-2.09; p = 0.031; OR1.55; 1.07-2.23; p = 0.020) was independently associated with higher odds of NAFLD and IR, respectively, when adjusted for: body mass index, physical activity, smoking, alcohol, energy, saturated fat and cholesterol intake. High intake of meat cooked using unhealthy methods (OR1.92; 95% CI 1.12-3.30; p = 0.018) and HCAs (OR2.22; 95% CI 1.28-3.86; p = 0.005) were independently associated with higher odds of IR. High consumption of red and/or processed meat is associated with both NAFLD and IR. High HCA intake is associated with IR. If confirmed in prospective studies, limiting the consumption of unhealthy meat types and improving preparation methods may be considered as part of NAFLD lifestyle treatment. High red and processed meat consumption is related to several diseases. In addition, cooking meat at high temperatures for a long duration forms heterocyclic amines, which have harmful health effects. Non-alcoholic fatty liver disease is a significant public health burden and its formation is strongly related to insulin resistance. In this study, both were found to be more frequent in people who consume relatively high quantities of red and processed meat. In addition, a high intake of heterocyclic amines was associated with insulin resistance. Copyright © 2018 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Demand for long acting and permanent contraceptive methods and associated factors among married women of reproductive age group in Debre Markos Town, North West Ethiopia.

PubMed

Bulto, Gizachew Abdissa; Zewdie, Tatek Abate; Beyen, Teresa Kisi

2014-03-13

Ethiopia is the second most populous country in sub Saharan Africa with high total fertility rate, and high maternal and child mortality rates. In sub Saharan African countries, including Ethiopia, even though studies show that demand for contraception is high, the practice is low. Particularly, in Ethiopia, despite the fact that practices on long acting and permanent methods are believed to be low, there are limited evidences on the real magnitude of demand for the methods. To assess demand for long acting and permanent contraceptive methods and associated factors among married women of reproductive age group in Debre Markos town, Amhara Regional State, North West Ethiopia, A community based cross sectional study was conducted, from April 08-19, 2012. Systematic sampling technique was used to select 523 study participants. Pre tested structured Amharic version questionnaire was used to collect the data through interview. Both bivariate and multiple logistic regressions were used to identify associated factors. Among 519 respondents, 323 (62.2%) were using modern family planning (FP) methods in which 101 (19.5%) were using long acting and permanent contraceptive methods (LAPMs). Among all respondents, 171 (32.9%) had unmet need for LAPMs. The total demand for LAPMs was 272 (52.4%) of which 37.1% were satisfied and 62.9% unsatisfied demand. Being in the older age group (40-44 years) [AOR = 2.8; 95% CI:1.12, 9.55], having no desire for more child [AOR = 20.37; 95% CI:9.28, 44.72], desire to have a child after 2 years [AOR = 6.4; 95%CI:3.04,13.47], not ever heard of modern FP [AOR = 5.73; 95% CI:1.26, 25.91], not ever using of modern FP [AOR = 1.89; 95% CI:1.01, 3.55] and having no spousal discussion in the last six month [AOR = 1.642, 95% CI: 1.049, 2.57) were some of the factors significantly associated with demand for LAPMs. Demand and unmet need for LAPMs were high in the study area. Therefore raising awareness of the community, counseling/discussion about the methods with all clients, encouraging spousal involvement are fundamental areas of intervention. Moreover, increasing the availability and accessibility of LAPMs is required to meet the unmet needs.

An epigenome-wide association meta-analysis of prenatal maternal stress in neonates: A model approach for replication

PubMed Central

Rijlaarsdam, Jolien; Pappa, Irene; Walton, Esther; Bakermans-Kranenburg, Marian J.; Mileva-Seitz, Viara R.; Rippe, Ralph C.A.; Roza, Sabine J.; Jaddoe, Vincent W.V.; Verhulst, Frank C.; Felix, Janine F.; Cecil, Charlotte A.M.; Relton, Caroline L.; Gaunt, Tom R.; McArdle, Wendy; Mill, Jonathan; Barker, Edward D.; Tiemeier, Henning; van IJzendoorn, Marinus H.

2016-01-01

ABSTRACT Prenatal maternal stress exposure has been associated with neonatal differential DNA methylation. However, the available evidence in humans is largely based on candidate gene methylation studies, where only a few CpG sites were evaluated. The aim of this study was to examine the association between prenatal exposure to maternal stress and offspring genome-wide cord blood methylation using different methods. First, we conducted a meta-analysis and follow-up pathway analyses. Second, we used novel region discovery methods [i.e., differentially methylated regions (DMRs) analyses]. To this end, we used data from two independent population-based studies, the Generation R Study (n = 912) and the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 828), to (i) measure genome-wide DNA methylation in cord blood and (ii) extract a prenatal maternal stress composite. The meta-analysis (ntotal = 1,740) revealed no epigenome-wide (meta P <1.00e-07) associations of prenatal maternal stress exposure with neonatal differential DNA methylation. Follow-up analyses of the top hits derived from our epigenome-wide meta-analysis (meta P <1.00e-04) indicated an over-representation of the methyltransferase activity pathway. We identified no Bonferroni-corrected (P <1.00e-06) DMRs associated with prenatal maternal stress exposure. Combining data from two independent population-based samples in an epigenome-wide meta-analysis, the current study indicates that there are no large effects of prenatal maternal stress exposure on neonatal DNA methylation. Such replication efforts are essential in the search for robust associations, whether derived from candidate gene methylation or epigenome-wide studies. PMID:26889969

Ambiguous taxa: Effects on the characterization and interpretation of invertebrate assemblages

USGS Publications Warehouse

Cuffney, T.F.; Bilger, Michael D.; Haigler, A.M.

2007-01-01

Damaged and immature specimens often result in macroinvertebrate data that contain ambiguous parent-child pairs (i.e., abundances associated with multiple related levels of the taxonomic hierarchy such as Baetis pluto and the associated ambiguous parent Baetis sp.). The choice of method used to resolve ambiguous parent-child pairs may have a very large effect on the characterization of invertebrate assemblages and the interpretation of responses to environmental change because very large proportions of taxa richness (73-78%) and abundance (79-91%) can be associated with ambiguous parents. To address this issue, we examined 16 variations of 4 basic methods for resolving ambiguous taxa: RPKC (remove parent, keep child), MCWP (merge child with parent), RPMC (remove parent or merge child with parent depending on their abundances), and DPAC (distribute parents among children). The choice of method strongly affected assemblage structure, assemblage characteristics (e.g., metrics), and the ability to detect responses along environmental (urbanization) gradients. All methods except MCWP produced acceptable results when used consistently within a study. However, the assemblage characteristics (e.g., values of assemblage metrics) differed widely depending on the method used, and data should not be combined unless the methods used to resolve ambiguous taxa are well documented and are known to be comparable. The suitability of the methods was evaluated and compared on the basis of 13 criteria that considered conservation of taxa richness and abundance, consistency among samples, methods, and studies, and effects on the interpretation of the data. Methods RPMC and DPAC had the highest suitability scores regardless of whether ambiguous taxa were resolved for each sample separately or for a group of samples. Method MCWP gave consistently poor results. Methods MCWP and DPAC approximate the use of family-level identifications and operational taxonomic units (OTU), respectively. Our results suggest that restricting identifications to the family level is not a good method of resolving ambiguous taxa, whereas generating OTUs works well provided that documentation issues are addressed. ?? 2007 by The North American Benthological Society.

Laboratory and Self-Report Methods to Assess Reappraisal and Distraction in Youth.

PubMed

Bettis, Alexandra H; Henry, Lauren; Prussien, Kemar V; Vreeland, Allison; Smith, Michele; Adery, Laura H; Compas, Bruce E

2018-06-07

Coping and emotion regulation are central features of risk and resilience in childhood and adolescence, but research on these constructs has relied on different methods of assessment. The current study aimed to bridge the gap between questionnaire and experimental methods of measuring secondary control coping strategies, specifically distraction and cognitive reappraisal, and examine associations with symptoms of anxiety and depression in youth. A community sample of 70 youth (ages 9-15) completed a novel experimental coping and emotion regulation paradigm and self-report measures of coping and emotion regulation and symptoms. Findings indicate that use of distraction and reappraisal during the laboratory paradigm was associated with lower levels of negative emotion during the task. Youth emotion ratings while implementing distraction, but not reappraisal, during the laboratory task were associated with youth self-reported use of secondary control coping in response to family stress. Youth symptoms of anxiety and depression were also significantly positively associated with negative emotion ratings during the laboratory task, and both laboratory task and self-reported coping and emotion regulation accounted for significant variance in symptoms in youth. Both questionnaire and laboratory methods to assess coping and emotion regulation in youth are important for understanding these processes as possible mechanisms of risk and resilience and continued integration of these methods is a priority for future research.

The CREATE Method Does Not Result in Greater Gains in Critical Thinking than a More Traditional Method of Analyzing the Primary Literature †

PubMed Central

Segura-Totten, Miriam; Dalman, Nancy E.

2013-01-01

Analysis of the primary literature in the undergraduate curriculum is associated with gains in student learning. In particular, the CREATE (Consider, Read, Elucidate hypotheses, Analyze and interpret the data, and Think of the next Experiment) method is associated with an increase in student critical thinking skills. We adapted the CREATE method within a required cell biology class and compared the learning gains of students using CREATE to those of students involved in less structured literature discussions. We found that while both sets of students had gains in critical thinking, students who used the CREATE method did not show significant improvement over students engaged in a more traditional method for dissecting the literature. Students also reported similar learning gains for both literature discussion methods. Our study suggests that, at least in our educational context, the CREATE method does not lead to higher learning gains than a less structured way of reading primary literature. PMID:24358379

Addressing the NASM health and safety standard through curricular changes in a brass methods course: an outcome study.

PubMed

Laursen, Amy; Chesky, Kris

2014-09-01

The National Association of Schools of Music (NASM) recently ratified a new health and safety standard requiring schools of music to inform students about health concerns related to music. While organizations such as the Performing Arts Medicine Association have developed advisories, the exact implementation is the prerogative of the institution. One possible approach is to embed health education activities into existing methods courses that are routinely offered to music education majors. This may influence student awareness, knowledge, and the perception of competency and responsibility for addressing health risks associated with learning and performing musical instruments. Unfortunately, there are no known lesson plans or curriculum guides for supporting such activities. Therefore, the purpose of this study is to (1) develop course objectives and content that can be applied to a preexisting brass methods course, (2) implement course objectives into a semester-long brass methods course, and (3) test the effectiveness of this intervention on students' awareness, knowledge, perception of competency, and responsibly of health risks that are related to learning and performing brass instruments. Results showcase the potential for modifying methods courses without compromising the other objectives of the course. Additionally, students' awareness, knowledge, perception of competency, and responsibility were positively influenced as measured by changes in pre to post responses to survey group questions.

Combining land use information and small stream sampling with PCR-based methods for better characterization of diffuse sources of human fecal pollution.

PubMed

Peed, Lindsay A; Nietch, Christopher T; Kelty, Catherine A; Meckes, Mark; Mooney, Thomas; Sivaganesan, Mano; Shanks, Orin C

2011-07-01

Diffuse sources of human fecal pollution allow for the direct discharge of waste into receiving waters with minimal or no treatment. Traditional culture-based methods are commonly used to characterize fecal pollution in ambient waters, however these methods do not discern between human and other animal sources of fecal pollution making it difficult to identify diffuse pollution sources. Human-associated quantitative real-time PCR (qPCR) methods in combination with low-order headwatershed sampling, precipitation information, and high-resolution geographic information system land use data can be useful for identifying diffuse source of human fecal pollution in receiving waters. To test this assertion, this study monitored nine headwatersheds over a two-year period potentially impacted by faulty septic systems and leaky sanitary sewer lines. Human fecal pollution was measured using three different human-associated qPCR methods and a positive significant correlation was seen between abundance of human-associated genetic markers and septic systems following wet weather events. In contrast, a negative correlation was observed with sanitary sewer line densities suggesting septic systems are the predominant diffuse source of human fecal pollution in the study area. These results demonstrate the advantages of combining water sampling, climate information, land-use computer-based modeling, and molecular biology disciplines to better characterize diffuse sources of human fecal pollution in environmental waters.

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption.

PubMed

Hartwig, Fernando Pires; Davey Smith, George; Bowden, Jack

2017-12-01

Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions. Here, a new method - the mode-based estimate (MBE) - is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk. The MBE presented less bias and lower type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared with the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia. The MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in sensitivity analyses. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

Analytic thinking reduces belief in conspiracy theories.

PubMed

Swami, Viren; Voracek, Martin; Stieger, Stefan; Tran, Ulrich S; Furnham, Adrian

2014-12-01

Belief in conspiracy theories has been associated with a range of negative health, civic, and social outcomes, requiring reliable methods of reducing such belief. Thinking dispositions have been highlighted as one possible factor associated with belief in conspiracy theories, but actual relationships have only been infrequently studied. In Study 1, we examined associations between belief in conspiracy theories and a range of measures of thinking dispositions in a British sample (N=990). Results indicated that a stronger belief in conspiracy theories was significantly associated with lower analytic thinking and open-mindedness and greater intuitive thinking. In Studies 2-4, we examined the causational role played by analytic thinking in relation to conspiracist ideation. In Study 2 (N=112), we showed that a verbal fluency task that elicited analytic thinking reduced belief in conspiracy theories. In Study 3 (N=189), we found that an alternative method of eliciting analytic thinking, which related to cognitive disfluency, was effective at reducing conspiracist ideation in a student sample. In Study 4, we replicated the results of Study 3 among a general population sample (N=140) in relation to generic conspiracist ideation and belief in conspiracy theories about the July 7, 2005, bombings in London. Our results highlight the potential utility of supporting attempts to promote analytic thinking as a means of countering the widespread acceptance of conspiracy theories. Copyright © 2014 Elsevier B.V. All rights reserved.

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses.

PubMed

Zaneveld, Jesse R R; Thurber, Rebecca L V

2014-01-01

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

PubMed Central

RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG

2015-01-01

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

Exposure to family planning messages and modern contraceptive use among men in urban Kenya, Nigeria, and Senegal: a cross-sectional study.

PubMed

Okigbo, Chinelo C; Speizer, Ilene S; Corroon, Meghan; Gueye, Abdou

2015-07-22

Family planning (FP) researchers and policy makers have often overlooked the importance of involving men in couples' fertility choices and contraception, despite the fact that male involvement is a vital factor in sexual and reproductive health programming. This study aimed to assess whether men's exposure to FP demand-generation activities is associated with their reported use of modern contraceptive methods. We used evaluation data from the Measurement, Learning & Evaluation project for the Urban Reproductive Health Initiative (URHI) in select cities of three African countries (Kenya, Nigeria, and Senegal) collected in 2012/2013. A two-stage cluster sampling design was used to select a representative sample of men in the study sites. The sample for this study includes men aged 15-59 years who had no missing data on any of the key variables: 696 men in Kenya, 2311 in Nigeria, and 1613 in Senegal. We conducted descriptive analyses and multivariate logistic regression analyses to assess the associations of interest. All analyses were weighted to account for the study design and non-response rates using Stata version 13. The proportion of men who reported use of modern contraceptive methods was 58 % in Kenya, 43 % in Nigeria, and 27 % in Senegal. About 80 % were exposed to at least one URHI demand-generation activity in each country. Certain URHI demand-generation activities were significantly associated with men's reported use of modern contraception. In Kenya, those who participated in URHI-led community events had four times higher odds of reporting use of modern methods (aOR: 3.70; p < 0.05) while in Senegal, exposure to URHI-television programs (aOR: 1.40; p < 0.05) and having heard a religious leader speak favorably about FP (aOR: 1.72; p < 0.05) were associated with modern contraceptive method use. No such associations were observed in Nigeria. Study findings are important for informing future FP program activities that seek to engage men. Program activities should be tailored by geographic context as results from this study indicate city and country-level variations. These types of gender-comprehensive and context-specific programs are likely to be the most successful at reducing unmet need for FP.

The Association between Outpatient Buprenorphine Detoxification Duration and Clinical Treatment Outcomes: A Review

PubMed Central

Sigmon, Stacey C.; Strain, Eric C.; Heil, Sarah H.; Higgins, Stephen T.

2011-01-01

Background The association between buprenorphine taper duration and treatment outcomes is not well understood. This review evaluated whether duration of outpatient buprenorphine taper is significantly associated with treatment outcomes. Methods Studies that were published in peer-reviewed journals, administered buprenorphine as an outpatient taper to opioid-dependent participants, and provided data on at least one of three primary treatment outcome measures (opioid abstinence, retention, peak withdrawal severity) were reviewed. Primary treatment outcomes were evaluated as a function of taper duration using hierarchical linear regressions using pre-taper maintenance as a cofactor. Results Twenty-eight studies were reviewed. Taper duration significantly predicted percent of opioid-negative samples provided during treatment, however pre-taper maintenance period predicted percent participants abstinent on the final day of treatment. High rates of relapse were reported. No significant association between taper duration and retention in treatment or peak withdrawal severity was observed. Conclusion The data reviewed here suggest taper duration is associated with opioid abstinence achieved during detoxification but not with other markers of treatment outcome. The reviewed studies varied widely on several parameters (e.g., frequency of urinalysis testing, provision of ancillary medications) that may influence treatment outcome and thus could have interfered with the ability to identify relationships between taper duration and outcomes. Future studies evaluating opioid detoxification should utilize rigorous experimental methods and report a wider range of outcome measures in order to help advance our understanding of the association between taper duration and treatment outcomes. PMID:21741781

Accounting for linkage disequilibrium in association analysis of diverse populations.

PubMed

Charles, Bashira A; Shriner, Daniel; Rotimi, Charles N

2014-04-01

The National Human Genome Research Institute's catalog of published genome-wide association studies (GWAS) lists over 10,000 genetic variants collectively associated with over 800 human diseases or traits. Most of these GWAS have been conducted in European-ancestry populations. Findings gleaned from these studies have led to identification of disease-associated loci and biologic pathways involved in disease etiology. In multiple instances, these genomic findings have led to the development of novel medical therapies or evidence for prescribing a given drug as the appropriate treatment for a given individual beyond phenotypic appearances or socially defined constructs of race or ethnicity. Such findings have implications for populations throughout the globe and GWAS are increasingly being conducted in more diverse populations. A major challenge for investigators seeking to follow up genomic findings between diverse populations is discordant patterns of linkage disequilibrium (LD). We provide an overview of common measures of LD and opportunities for their use in novel methods designed to address challenges associated with following up GWAS conducted in European-ancestry populations in African-ancestry populations or, more generally, between populations with discordant LD patterns. We detail the strengths and weaknesses associated with different approaches. We also describe application of these strategies in follow-up studies of populations with concordant LD patterns (replication) or discordant LD patterns (transferability) as well as fine-mapping studies. We review application of these methods to a variety of traits and diseases. © 2014 WILEY PERIODICALS, INC.

Genetic Classification of Populations Using Supervised Learning

PubMed Central

Bridges, Michael; Heron, Elizabeth A.; O'Dushlaine, Colm; Segurado, Ricardo; Morris, Derek; Corvin, Aiden; Gill, Michael; Pinto, Carlos

2011-01-01

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies. PMID:21589856

Flooding and Mental Health: A Systematic Mapping Review

PubMed Central

Fernandez, Ana; Black, John; Jones, Mairwen; Wilson, Leigh; Salvador-Carulla, Luis; Astell-Burt, Thomas; Black, Deborah

2015-01-01

Background Floods are the most common type of global natural disaster. Floods have a negative impact on mental health. Comprehensive evaluation and review of the literature are lacking. Objective To systematically map and review available scientific evidence on mental health impacts of floods caused by extended periods of heavy rain in river catchments. Methods We performed a systematic mapping review of published scientific literature in five languages for mixed studies on floods and mental health. PUBMED and Web of Science were searched to identify all relevant articles from 1994 to May 2014 (no restrictions). Results The electronic search strategy identified 1331 potentially relevant papers. Finally, 83 papers met the inclusion criteria. Four broad areas are identified: i) the main mental health disorders—post-traumatic stress disorder, depression and anxiety; ii] the factors associated with mental health among those affected by floods; iii) the narratives associated with flooding, which focuses on the long-term impacts of flooding on mental health as a consequence of the secondary stressors; and iv) the management actions identified. The quantitative and qualitative studies have consistent findings. However, very few studies have used mixed methods to quantify the size of the mental health burden as well as exploration of in-depth narratives. Methodological limitations include control of potential confounders and short-term follow up. Limitations Floods following extreme events were excluded from our review. Conclusions Although the level of exposure to floods has been systematically associated with mental health problems, the paucity of longitudinal studies and lack of confounding controls precludes strong conclusions. Implications We recommend that future research in this area include mixed-method studies that are purposefully designed, using more rigorous methods. Studies should also focus on vulnerable groups and include analyses of policy and practical responses. PMID:25860572

Comparison of Online and Traditional Basic Life Support Renewal Training Methods for Registered Professional Nurses.

PubMed

Serwetnyk, Tara M; Filmore, Kristi; VonBacho, Stephanie; Cole, Robert; Miterko, Cindy; Smith, Caitlin; Smith, Charlene M

2015-01-01

Basic Life Support certification for nursing staff is achieved through various training methods. This study compared three American Heart Association training methods for nurses seeking Basic Life Support renewal: a traditional classroom approach and two online options. Findings indicate that online methods for Basic Life Support renewal deliver cost and time savings, while maintaining positive learning outcomes, satisfaction, and confidence level of participants.

Methods of Costing in Universities. Brief Comparison Between the NCHEMS Approach and the Approach Used by the French-Speaking Research Group Associated with the IMHE Programme.

ERIC Educational Resources Information Center

Cossu, Claude

1975-01-01

A group of French universities modified the NCHEMS accounting method for use in a study of its budget control procedures and cost-evaluation methods. The conceptual differences in French university education (as compared to American higher education) are keyed to the adjustments in the accounting method. French universities, rather than being…

SecureMA: protecting participant privacy in genetic association meta-analysis.

PubMed

Xie, Wei; Kantarcioglu, Murat; Bush, William S; Crawford, Dana; Denny, Joshua C; Heatherly, Raymond; Malin, Bradley A

2014-12-01

Sharing genomic data is crucial to support scientific investigation such as genome-wide association studies. However, recent investigations suggest the privacy of the individual participants in these studies can be compromised, leading to serious concerns and consequences, such as overly restricted access to data. We introduce a novel cryptographic strategy to securely perform meta-analysis for genetic association studies in large consortia. Our methodology is useful for supporting joint studies among disparate data sites, where privacy or confidentiality is of concern. We validate our method using three multisite association studies. Our research shows that genetic associations can be analyzed efficiently and accurately across substudy sites, without leaking information on individual participants and site-level association summaries. Our software for secure meta-analysis of genetic association studies, SecureMA, is publicly available at http://github.com/XieConnect/SecureMA. Our customized secure computation framework is also publicly available at http://github.com/XieConnect/CircuitService. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A prospective study of musculoskeletal outcomes among manufacturing workers: II. Effects of psychosocial stress and work organization factors.

PubMed

Gerr, Fredric; Fethke, Nathan B; Anton, Dan; Merlino, Linda; Rosecrance, John; Marcus, Michele; Jones, Michael P

2014-02-01

The aim of this study was to characterize associations between psychosocial and work organizational risk factors and upper-extremity musculoskeletal symptoms and disorders. Methodological limitations of previous studies of psychosocial and work organizational risk factors and musculoskeletal outcomes have produced inconsistent associations. In this prospective epidemiologic study of 386 workers, questionnaires to assess decision latitude ("control") and psychological job demands ("demand") were administered to study participants and were used to classify them into job strain "quadrants". Measures of job stress and job change were collected during each week of follow-up. Incident hand/arm and neck/shoulder symptoms and disorders were ascertained weekly. Associations between exposure measures and musculoskeletal outcomes were estimated with proportional hazard methods. When compared to the low-demand/high-control job strain referent category, large increases in risk of hand/arm disorders were observed for both high-demand/high-control (hazard ratio [HR] = 4.49, 95% confidence interval [CI] = [1.23, 16.4]) and high-demand/low-control job strain categories (HR = 5.18,95% CI = [1.39, 19.4]). Similar associations were observed for hand/arm symptoms. A strong association was also observed between the low-demand/low-control job strain category and neck/shoulder disorders (HR = 6.46, 95% CI = [1.46, 28.6]). Statistically significant associations were also observed between weekly stress level and weekly job change and several musculoskeletal outcomes. Associations between psychosocial risk factors and work organizational factors and musculoskeletal outcomes were large and in the hypothesized direction. Prevention of occupational musculoskeletal disorders may require attention to psychosocial and work organizational factors in addition to physical factors. Methods to control adverse effects of psychosocial and work organizational risk factors should be explored.

Determining Biology Student Teachers' Cognitive Structure on the Concept of "Diffusion" through the Free Word-Association Test and the Drawing-Writing Technique

ERIC Educational Resources Information Center

Kurt, Hakan; Ekici, Gülay; Aktas, Murat; Aksu, Özlem

2013-01-01

The aim of the current study is to investigate student biology teachers' cognitive structures related to "diffusion" through the free word-association test and the drawing-writing technique. As the research design of the study, the qualitative research method was applied. The data were collected from 44 student biology teachers. The free…

Turning the pump handle: Evolving methods for integrating the evidence on gene-disease association

USDA-ARS?s Scientific Manuscript database

Recent findings from genome-wide association studies have demonstrated their considerable potential for identifying genetic determinants of common diseases of public health significance such as cancer, heart disease, and diabetes, but they have also highlighted the continued importance of targeted g...