A Phenotypic Cell-Binding Screen Identifies a Novel Compound Targeting Triple-Negative Breast Cancer.

PubMed

Chen, Luxi; Long, Chao; Youn, Jonghae; Lee, Jiyong

2018-06-11

We describe a "phenotypic cell-binding screen" by which therapeutic candidate targeting cancer cells of a particular phenotype can be isolated without knowledge of drug targets. Chemical library beads are incubated with cancer cells of the phenotype of interest in the presence of cancer cells lacking the phenotype of interest, and then the beads bound to only cancer cells of the phenotype of interest are selected as hits. We have applied this screening strategy in discovering a novel compound (LC129-8) targeting triple-negative breast cancer (TNBC). LC129-8 displayed highly specific binding to TNBC in cancer cell lines and patient-derived tumor tissues. LC129-8 exerted anti-TNBC activity by inducing apoptosis, inhibiting proliferation, reversing epithelial-mesenchymal transition, downregulating cancer stem cell activity and blocking in vivo tumor growth.

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

Cancer Drug Addiction is Relayed by an ERK2-Dependent Phenotype Switch

PubMed Central

Kong, Xiangjun; Kuilman, Thomas; Shahrabi, Aida; Boshuizen, Julia; Kemper, Kristel; Song, Ji-Ying; Niessen, Hans W.M.; Rozeman, Elisa A.; Geukes Foppen, Marnix H.; Blank, Christian U.; Peeper, Daniel S.

2017-01-01

Drug addiction denotes the dependency of tumors on the same therapeutic drugs to which they have acquired resistance. Observations from cultured cells1–3, animal models4 and patients5–7 raise the possibility that cancer drug addiction can instigate a potential cancer vulnerability, which may be used therapeutically. However, for this trait to become of clinical interest, it is imperative to first define the underlying mechanism. Therefore, we performed an unbiased CRISPR-Cas9 knockout screen to functionally mine the genome of melanoma cells that are both resistant and addicted to BRAF inhibition for “addiction genes”. Here, we describe a signaling pathway comprising ERK2, JUNB and FRA1, disruption of which allows tumor cells to reverse addiction and survive upon treatment discontinuation. This occurred both in culture and mice, and was irrespective of the acquired drug resistance mechanism. In melanoma and lung cancer cells, death induced by drug withdrawal was preceded by a specific ERK2-dependent phenotype switch, alongside transcriptional reprogramming reminiscent of EMT. In melanoma, this caused shutdown of the lineage survival oncoprotein MITF, restoration of which reversed both phenotype switching and drug addiction-associated lethality. In melanoma patients who had progressed on BRAF inhibition, treatment cessation was followed by increased expression of the phenotype switch-associated receptor tyrosine kinase AXL. Drug discontinuation synergized with the melanoma chemotherapeutic dacarbazine by further suppressing MITF and its prosurvival target BCL2 while inducing DNA damage. Our results uncover a pathway driving cancer drug addiction, which may guide alternating therapeutic strategies for enhanced clinical responses of drug-resistant cancers. PMID:28976960

Towards precision medicine-based therapies for glioblastoma: interrogating human disease genomics and mouse phenotypes.

PubMed

Chen, Yang; Gao, Zhen; Wang, Bingcheng; Xu, Rong

2016-08-22

Glioblastoma (GBM) is the most common and aggressive brain tumors. It has poor prognosis even with optimal radio- and chemo-therapies. Since GBM is highly heterogeneous, drugs that target on specific molecular profiles of individual tumors may achieve maximized efficacy. Currently, the Cancer Genome Atlas (TCGA) projects have identified hundreds of GBM-associated genes. We develop a drug repositioning approach combining disease genomics and mouse phenotype data towards predicting targeted therapies for GBM. We first identified disease specific mouse phenotypes using the most recently discovered GBM genes. Then we systematically searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with GBM. We evaluated the ranks for approved and novel GBM drugs, and compared with an existing approach, which also use the mouse phenotype data but not the disease genomics data. We achieved significantly higher ranks for the approved and novel GBM drugs than the earlier approach. For all positive examples of GBM drugs, we achieved a median rank of 9.2 45.6 of the top predictions have been demonstrated effective in inhibiting the growth of human GBM cells. We developed a computational drug repositioning approach based on both genomic and phenotypic data. Our approach prioritized existing GBM drugs and outperformed a recent approach. Overall, our approach shows potential in discovering new targeted therapies for GBM.

Phenotypic Screening Approaches to Develop Aurora Kinase Inhibitors: Drug Discovery Perspectives.

PubMed

Marugán, Carlos; Torres, Raquel; Lallena, María José

2015-01-01

Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins, such as Aurora-A and -B. Current drugs, which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules), have several side effects (neutropenia, alopecia, and emesis). Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype. We will briefly describe two multiplexing technologies [high-content imaging (HCI) and flow cytometry] and two key processes for drug discovery research (assay development and validation) following our own published industry quality standards. We will further focus on HCI as a useful tool for phenotypic screening and will provide a concrete example of HCI assay to detect Aurora-A or -B selective inhibitors discriminating the off-target effects related to the inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors.

Neoclassic drug discovery: the case for lead generation using phenotypic and functional approaches.

PubMed

Lee, Jonathan A; Berg, Ellen L

2013-12-01

Innovation and new molecular entity production by the pharmaceutical industry has been below expectations. Surprisingly, more first-in-class small-molecule drugs approved by the U.S. Food and Drug Administration (FDA) between 1999 and 2008 were identified by functional phenotypic lead generation strategies reminiscent of pre-genomics pharmacology than contemporary molecular targeted strategies that encompass the vast majority of lead generation efforts. This observation, in conjunction with the difficulty in validating molecular targets for drug discovery, has diminished the impact of the "genomics revolution" and has led to a growing grassroots movement and now broader trend in pharma to reconsider the use of modern physiology-based or phenotypic drug discovery (PDD) strategies. This "From the Guest Editors" column provides an introduction and overview of the two-part special issues of Journal of Biomolecular Screening on PDD. Terminology and the business case for use of PDD are defined. Key issues such as assay performance, chemical optimization, target identification, and challenges to the organization and implementation of PDD are discussed. Possible solutions for these challenges and a new neoclassic vision for PDD that combines phenotypic and functional approaches with technology innovations resulting from the genomics-driven era of target-based drug discovery (TDD) are also described. Finally, an overview of the manuscripts in this special edition is provided.

Cancer drug addiction is relayed by an ERK2-dependent phenotype switch.

PubMed

Kong, Xiangjun; Kuilman, Thomas; Shahrabi, Aida; Boshuizen, Julia; Kemper, Kristel; Song, Ji-Ying; Niessen, Hans W M; Rozeman, Elisa A; Geukes Foppen, Marnix H; Blank, Christian U; Peeper, Daniel S

2017-10-12

Observations from cultured cells, animal models and patients raise the possibility that the dependency of tumours on the therapeutic drugs to which they have acquired resistance represents a vulnerability with potential applications in cancer treatment. However, for this drug addiction trait to become of clinical interest, we must first define the mechanism that underlies it. We performed an unbiased CRISPR-Cas9 knockout screen on melanoma cells that were both resistant and addicted to inhibition of the serine/threonine-protein kinase BRAF, in order to functionally mine their genome for 'addiction genes'. Here we describe a signalling pathway comprising ERK2 kinase and JUNB and FRA1 transcription factors, disruption of which allowed addicted tumour cells to survive on treatment discontinuation. This occurred in both cultured cells and mice and was irrespective of the acquired drug resistance mechanism. In melanoma and lung cancer cells, death induced by drug withdrawal was preceded by a specific ERK2-dependent phenotype switch, alongside transcriptional reprogramming reminiscent of the epithelial-mesenchymal transition. In melanoma cells, this reprogramming caused the shutdown of microphthalmia-associated transcription factor (MITF), a lineage survival oncoprotein; restoring this protein reversed phenotype switching and prevented the lethality associated with drug addiction. In patients with melanoma that had progressed during treatment with a BRAF inhibitor, treatment cessation was followed by increased expression of the receptor tyrosine kinase AXL, which is associated with the phenotype switch. Drug discontinuation synergized with the melanoma chemotherapeutic agent dacarbazine by further suppressing MITF and its prosurvival target, B-cell lymphoma 2 (BCL-2), and by inducing DNA damage in cancer cells. Our results uncover a pathway that underpins drug addiction in cancer cells, which may help to guide the use of alternating therapeutic strategies for enhanced

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

PubMed Central

Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

2015-01-01

Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening.

PubMed

O'Duibhir, Eoghan; Carragher, Neil O; Pollard, Steven M

2017-04-01

Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Targeting the latest hallmark of cancer: another attempt at 'magic bullet' drugs targeting cancers' metabolic phenotype.

PubMed

Cuperlovic-Culf, M; Culf, A S; Touaibia, M; Lefort, N

2012-10-01

The metabolism of tumors is remarkably different from the metabolism of corresponding normal cells and tissues. Metabolic alterations are initiated by oncogenes and are required for malignant transformation, allowing cancer cells to resist some cell death signals while producing energy and fulfilling their biosynthetic needs with limiting resources. The distinct metabolic phenotype of cancers provides an interesting avenue for treatment, potentially with minimal side effects. As many cancers show similar metabolic characteristics, drugs targeting the cancer metabolic phenotype are, perhaps optimistically, expected to be 'magic bullet' treatments. Over the last few years there have been a number of potential drugs developed to specifically target cancer metabolism. Several of these drugs are currently in clinical and preclinical trials. This review outlines examples of drugs developed for different targets of significance to cancer metabolism, with a focus on small molecule leads, chemical biology and clinical results for these drugs.

Identifying transcription factor functions and targets by phenotypic activation

PubMed Central

Chua, Gordon; Morris, Quaid D.; Sopko, Richelle; Robinson, Mark D.; Ryan, Owen; Chan, Esther T.; Frey, Brendan J.; Andrews, Brenda J.; Boone, Charles; Hughes, Timothy R.

2006-01-01

Mapping transcriptional regulatory networks is difficult because many transcription factors (TFs) are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual TFs that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast TFs that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, indicating that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5′-TCACGCAA as a binding sequence for Hms1p, a TF that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of TF activities and mapping targets that could be adapted to any organism with transgenic technology. PMID:16880382

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

PubMed

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

FOXO Regulates Organ-Specific Phenotypic Plasticity In Drosophila

PubMed Central

Tang, Hui Yuan; Smith-Caldas, Martha S. B.; Driscoll, Michael V.; Salhadar, Samy; Shingleton, Alexander W.

2011-01-01

Phenotypic plasticity, the ability for a single genotype to generate different phenotypes in response to environmental conditions, is biologically ubiquitous, and yet almost nothing is known of the developmental mechanisms that regulate the extent of a plastic response. In particular, it is unclear why some traits or individuals are highly sensitive to an environmental variable while other traits or individuals are less so. Here we elucidate the developmental mechanisms that regulate the expression of a particularly important form of phenotypic plasticity: the effect of developmental nutrition on organ size. In all animals, developmental nutrition is signaled to growing organs via the insulin-signaling pathway. Drosophila organs differ in their size response to developmental nutrition and this reflects differences in organ-specific insulin-sensitivity. We show that this variation in insulin-sensitivity is regulated at the level of the forkhead transcription factor FOXO, a negative growth regulator that is activated when nutrition and insulin signaling are low. Individual organs appear to attenuate growth suppression in response to low nutrition through an organ-specific reduction in FOXO expression, thereby reducing their nutritional plasticity. We show that FOXO expression is necessary to maintain organ-specific differences in nutritional-plasticity and insulin-sensitivity, while organ-autonomous changes in FOXO expression are sufficient to autonomously alter an organ's nutritional-plasticity and insulin-sensitivity. These data identify a gene (FOXO) that modulates a plastic response through variation in its expression. FOXO is recognized as a key player in the response of size, immunity, and longevity to changes in developmental nutrition, stress, and oxygen levels. FOXO may therefore act as a more general regulator of plasticity. These data indicate that the extent of phenotypic plasticity may be modified by changes in the expression of genes involved in

Gene signature critical to cancer phenotype as a paradigm for anti-cancer drug discovery

PubMed Central

Sampson, Erik R.; McMurray, Helene R.; Hassane, Duane C.; Newman, Laurel; Salzman, Peter; Jordan, Craig T.; Land, Hartmut

2013-01-01

Malignant cell transformation commonly results in the deregulation of thousands of cellular genes, an observation that suggests a complex biological process and an inherently challenging scenario for the development of effective cancer interventions. To better define the genes/pathways essential to regulating the malignant phenotype, we recently described a novel strategy based on the cooperative nature of carcinogenesis that focuses on genes synergistically deregulated in response to cooperating oncogenic mutations. These so-called “cooperation response genes” (CRGs) are highly enriched for genes critical for the cancer phenotype, thereby suggesting their causal role in the malignant state. Here we show that CRGs play an essential role in drug-mediated anti-cancer activity and that anti-cancer agents can be identified through their ability to antagonize the CRG expression profile. These findings provide proof-of-concept for the use of the CRG signature as a novel means of drug discovery with relevance to underlying anti-cancer drug mechanisms. PMID:22964631

Large-Scale Phenotype-Based Antiepileptic Drug Screening in a Zebrafish Model of Dravet Syndrome1,2,3

PubMed Central

Dinday, Matthew T.

2015-01-01

Abstract Mutations in a voltage-gated sodium channel (SCN1A) result in Dravet Syndrome (DS), a catastrophic childhood epilepsy. Zebrafish with a mutation in scn1Lab recapitulate salient phenotypes associated with DS, including seizures, early fatality, and resistance to antiepileptic drugs. To discover new drug candidates for the treatment of DS, we screened a chemical library of ∼1000 compounds and identified 4 compounds that rescued the behavioral seizure component, including 1 compound (dimethadione) that suppressed associated electrographic seizure activity. Fenfluramine, but not huperzine A, also showed antiepileptic activity in our zebrafish assays. The effectiveness of compounds that block neuronal calcium current (dimethadione) or enhance serotonin signaling (fenfluramine) in our zebrafish model suggests that these may be important therapeutic targets in patients with DS. Over 150 compounds resulting in fatality were also identified. We conclude that the combination of behavioral and electrophysiological assays provide a convenient, sensitive, and rapid basis for phenotype-based drug screening in zebrafish mimicking a genetic form of epilepsy. PMID:26465006

Identifying biologically relevant putative mechanisms in a given phenotype comparison

PubMed Central

Hanoudi, Samer; Donato, Michele; Draghici, Sorin

2017-01-01

A major challenge in life science research is understanding the mechanism involved in a given phenotype. The ability to identify the correct mechanisms is needed in order to understand fundamental and very important phenomena such as mechanisms of disease, immune systems responses to various challenges, and mechanisms of drug action. The current data analysis methods focus on the identification of the differentially expressed (DE) genes using their fold change and/or p-values. Major shortcomings of this approach are that: i) it does not consider the interactions between genes; ii) its results are sensitive to the selection of the threshold(s) used, and iii) the set of genes produced by this approach is not always conducive to formulating mechanistic hypotheses. Here we present a method that can construct networks of genes that can be considered putative mechanisms. The putative mechanisms constructed by this approach are not limited to the set of DE genes, but also considers all known and relevant gene-gene interactions. We analyzed three real datasets for which both the causes of the phenotype, as well as the true mechanisms were known. We show that the method identified the correct mechanisms when applied on microarray datasets from mouse. We compared the results of our method with the results of the classical approach, showing that our method produces more meaningful biological insights. PMID:28486531

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery. In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects. In the first step, we generated a system for multiple drug-target identification based on the application of 3D drug similarity into a large target dataset extracted from the ChEMBL. Next, we developed a target-adverse effect predictor combining targets from ChEMBL with phenotypic information provided by SIDER data source. Both modules were linked to generate a final predictor that establishes hypothesis about new drug-target-adverse effect candidates. Additionally, we showed that leveraging drug-target candidates with phenotypic data is very useful to improve the identification of drug-targets. The integration of phenotypic data into drug-target candidates yielded up to twofold precision improvement. In the opposite direction, leveraging drug-phenotype candidates with target data also yielded a significant enhancement in the performance. The modeling described in the current study is simple and efficient and has applications at large scale in drug repurposing and drug safety through the identification of mechanism of action of biological effects.

Cluster Analysis Identifies 3 Phenotypes within Allergic Asthma.

PubMed

Sendín-Hernández, María Paz; Ávila-Zarza, Carmelo; Sanz, Catalina; García-Sánchez, Asunción; Marcos-Vadillo, Elena; Muñoz-Bellido, Francisco J; Laffond, Elena; Domingo, Christian; Isidoro-García, María; Dávila, Ignacio

Asthma is a heterogeneous chronic disease with different clinical expressions and responses to treatment. In recent years, several unbiased approaches based on clinical, physiological, and molecular features have described several phenotypes of asthma. Some phenotypes are allergic, but little is known about whether these phenotypes can be further subdivided. We aimed to phenotype patients with allergic asthma using an unbiased approach based on multivariate classification techniques (unsupervised hierarchical cluster analysis). From a total of 54 variables of 225 patients with well-characterized allergic asthma diagnosed following American Thoracic Society (ATS) recommendation, positive skin prick test to aeroallergens, and concordant symptoms, we finally selected 19 variables by multiple correspondence analyses. Then a cluster analysis was performed. Three groups were identified. Cluster 1 was constituted by patients with intermittent or mild persistent asthma, without family antecedents of atopy, asthma, or rhinitis. This group showed the lowest total IgE levels. Cluster 2 was constituted by patients with mild asthma with a family history of atopy, asthma, or rhinitis. Total IgE levels were intermediate. Cluster 3 included patients with moderate or severe persistent asthma that needed treatment with corticosteroids and long-acting β-agonists. This group showed the highest total IgE levels. We identified 3 phenotypes of allergic asthma in our population. Furthermore, we described 2 phenotypes of mild atopic asthma mainly differentiated by a family history of allergy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Application of a phenotypic drug discovery strategy to identify biological and chemical starting points for inhibition of TSLP production in lung epithelial cells

PubMed Central

Orellana, Adelina; García-González, Vicente; López, Rosa; Pascual-Guiral, Sonia; Lozoya, Estrella; Díaz, Julia; Casals, Daniel; Barrena, Antolín; Paris, Stephane; Andrés, Miriam; Segarra, Victor; Vilella, Dolors; Malhotra, Rajneesh; Eastwood, Paul; Planagumà, Anna; Miralpeix, Montserrat

2018-01-01

Thymic stromal lymphopoietin (TSLP) is a cytokine released by human lung epithelium in response to external insult. Considered as a master switch in T helper 2 lymphocyte (Th2) mediated responses, TSLP is believed to play a key role in allergic diseases including asthma. The aim of this study was to use a phenotypic approach to identify new biological and chemical starting points for inhibition of TSLP production in human bronchial epithelial cells (NHBE), with the objective of reducing Th2-mediated airway inflammation. To this end, a phenotypic screen was performed using poly I:C / IL-4 stimulated NHBE cells interrogated with a 44,974 compound library. As a result, 85 hits which downregulated TSLP protein and mRNA levels were identified and a representative subset of 7 hits was selected for further characterization. These molecules inhibited the activity of several members of the MAPK, PI3K and tyrosine kinase families and some of them have been reported as modulators of cellular phenotypic endpoints like cell-cell contacts, microtubule polymerization and caspase activation. Characterization of the biological profile of the hits suggested that mTOR could be a key activity involved in the regulation of TSLP production in NHBE cells. Among other targeted kinases, inhibition of p38 MAPK and JAK kinases showed different degrees of correlation with TSLP downregulation, while Syk kinase did not seem to be related. Overall, inhibition of TSLP production by the selected hits, rather than resulting from inhibition of single isolated targets, appeared to be due to a combination of activities with different levels of relevance. Finally, a hit expansion exercise yielded additional active compounds that could be amenable to further optimization, providing an opportunity to dissociate TSLP inhibition from other non-desired activities. This study illustrates the potential of phenotypic drug discovery to complement target based approaches by providing new chemistry and biology

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate

Phenotype, Genotype, and Drug Resistance in Subtype C HIV-1 Infection.

PubMed

Derache, Anne; Wallis, Carole L; Vardhanabhuti, Saran; Bartlett, John; Kumarasamy, Nagalingeswaran; Katzenstein, David

2016-01-15

Virologic failure in subtype C is characterized by high resistance to first-line antiretroviral (ARV) drugs, including efavirenz, nevirapine, and lamivudine, with nucleoside resistance including type 2 thymidine analog mutations, K65R, a T69del, and M184V. However, genotypic algorithms predicting resistance are mainly based on subtype B viruses and may under- or overestimate drug resistance in non-B subtypes. To explore potential treatment strategies after first-line failure, we compared genotypic and phenotypic susceptibility of subtype C human immunodeficiency virus 1 (HIV-1) following first-line ARV failure. AIDS Clinical Trials Group 5230 evaluated patients failing an initial nonnucleoside reverse-transcriptase inhibitor (NNRTI) regimen in Africa and Asia, comparing the genotypic drug resistance and phenotypic profile from the PhenoSense (Monogram). Site-directed mutagenesis studies of K65R and T69del assessed the phenotypic impact of these mutations. Genotypic algorithms overestimated resistance to etravirine and rilpivirine, misclassifying 28% and 32%, respectively. Despite K65R with the T69del in 9 samples, tenofovir retained activity in >60%. Reversion of the K65R increased susceptibility to tenofovir and other nucleosides, while reversion of the T69del showed increased resistance to zidovudine, with little impact on other NRTI. Although genotype and phenotype were largely concordant for first-line drugs, estimates of genotypic resistance to etravirine and rilpivirine may misclassify subtype C isolates compared to phenotype. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

CYP2C9 Genotype vs. Metabolic Phenotype for Individual Drug Dosing—A Correlation Analysis Using Flurbiprofen as Probe Drug

PubMed Central

Vogl, Silvia; Lutz, Roman W.; Schönfelder, Gilbert; Lutz, Werner K.

2015-01-01

Currently, genotyping of patients for polymorphic enzymes responsible for metabolic elimination is considered a possibility to adjust drug dose levels. For a patient to profit from this procedure, the interindividual differences in drug metabolism within one genotype should be smaller than those between different genotypes. We studied a large cohort of healthy young adults (283 subjects), correlating their CYP2C9 genotype to a simple phenotyping metric, using flurbiprofen as probe drug. Genotyping was conducted for CYP2C9*1, *2, *3. The urinary metabolic ratio MR (concentration of CYP2C9-dependent metabolite divided by concentration of flurbiprofen) determined two hours after flurbiprofen (8.75 mg) administration served as phenotyping metric. Linear statistical models correlating genotype and phenotype provided highly significant allele-specific MR estimates of 0.596 for the wild type allele CYP2C9*1, 0.405 for CYP2C9*2 (68 % of wild type), and 0.113 for CYP2C9*3 (19 % of wild type). If these estimates were used for flurbiprofen dose adjustment, taking 100 % for genotype *1/*1, an average reduction to 84 %, 60 %, 68 %, 43 %, and 19 % would result for genotype *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3, respectively. Due to the large individual variation within genotypes with coefficients of variation ≥ 20 % and supposing the normal distribution, one in three individuals would be out of the average optimum dose by more than 20 %, one in 20 would be 40 % off. Whether this problem also applies to other CYPs and other drugs has to be investigated case by case. Our data for the given example, however, puts the benefit of individual drug dosing to question, if it is exclusively based on genotype. PMID:25775139

CYP2C9 genotype vs. metabolic phenotype for individual drug dosing--a correlation analysis using flurbiprofen as probe drug.

PubMed

Vogl, Silvia; Lutz, Roman W; Schönfelder, Gilbert; Lutz, Werner K

2015-01-01

Currently, genotyping of patients for polymorphic enzymes responsible for metabolic elimination is considered a possibility to adjust drug dose levels. For a patient to profit from this procedure, the interindividual differences in drug metabolism within one genotype should be smaller than those between different genotypes. We studied a large cohort of healthy young adults (283 subjects), correlating their CYP2C9 genotype to a simple phenotyping metric, using flurbiprofen as probe drug. Genotyping was conducted for CYP2C9*1, *2, *3. The urinary metabolic ratio MR (concentration of CYP2C9-dependent metabolite divided by concentration of flurbiprofen) determined two hours after flurbiprofen (8.75 mg) administration served as phenotyping metric. Linear statistical models correlating genotype and phenotype provided highly significant allele-specific MR estimates of 0.596 for the wild type allele CYP2C9*1, 0.405 for CYP2C9*2 (68 % of wild type), and 0.113 for CYP2C9*3 (19 % of wild type). If these estimates were used for flurbiprofen dose adjustment, taking 100 % for genotype *1/*1, an average reduction to 84 %, 60 %, 68 %, 43 %, and 19 % would result for genotype *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3, respectively. Due to the large individual variation within genotypes with coefficients of variation ≥ 20 % and supposing the normal distribution, one in three individuals would be out of the average optimum dose by more than 20 %, one in 20 would be 40 % off. Whether this problem also applies to other CYPs and other drugs has to be investigated case by case. Our data for the given example, however, puts the benefit of individual drug dosing to question, if it is exclusively based on genotype.

Identification of genus Acinetobacter: Standardization of in-house PCR and its comparison with conventional phenotypic methods.

PubMed

Kulkarni, Sughosh S; Madalgi, Radhika; Ajantha, Ganavalli S; Kulkarni, Raghavendra D

2017-01-01

Acinetobacter is grouped under nonfermenting Gram-negative bacilli. It is increasingly isolated from pathological samples. The ability of this genus to acquire drug resistance and spread in the hospital settings is posing a grave problem in healthcare. Specific treatment protocols are advocated for Acinetobacter infections. Hence, rapid identification and drug susceptibility profiling are critical in the management of these infections. To standardize an in-house polymerase chain reaction (PCR) for identification of genus Acinetobacter and to compare PCR with two protocols for its phenotypic identification. A total of 96 clinical isolates of Acinetobacter were included in the study. An in-house PCR for genus level identification of Acinetobacter was standardized. All the isolates were phenotypically identified by two protocols. The results of PCR and phenotypic identification protocols were compared. The in-house PCR standardized was highly sensitive and specific for the genus Acinetobacter . There was 100% agreement between the phenotypic and molecular identification of the genus. The preliminary identification tests routinely used in clinical laboratories were also in complete agreement with phenotypic and molecular identification. The in-house PCR for genus level identification is specific and sensitive. However, it may not be essential for routine identification as the preliminary phenotypic identification tests used in the clinical laboratory reliably identify the genus Acinetobacter .

A high-throughput phenotypic screen identifies clofazimine as a potential treatment for cryptosporidiosis

PubMed Central

Jumani, Rajiv S.; Wright, Timothy M.; Chatterjee, Arnab K.; Huston, Christopher D.; Schultz, Peter G.; McNamara, Case W.

2017-01-01

Cryptosporidiosis has emerged as a leading cause of non-viral diarrhea in children under five years of age in the developing world, yet the current standard of care to treat Cryptosporidium infections, nitazoxanide, demonstrates limited and immune-dependent efficacy. Given the lack of treatments with universal efficacy, drug discovery efforts against cryptosporidiosis are necessary to find therapeutics more efficacious than the standard of care. To date, cryptosporidiosis drug discovery efforts have been limited to a few targeted mechanisms in the parasite and whole cell phenotypic screens against small, focused collections of compounds. Using a previous screen as a basis, we initiated the largest known drug discovery effort to identify novel anticryptosporidial agents. A high-content imaging assay for inhibitors of Cryptosporidium parvum proliferation within a human intestinal epithelial cell line was miniaturized and automated to enable high-throughput phenotypic screening against a large, diverse library of small molecules. A screen of 78,942 compounds identified 12 anticryptosporidial hits with sub-micromolar activity, including clofazimine, an FDA-approved drug for the treatment of leprosy, which demonstrated potent and selective in vitro activity (EC50 = 15 nM) against C. parvum. Clofazimine also displayed activity against C. hominis–the other most clinically-relevant species of Cryptosporidium. Importantly, clofazimine is known to accumulate within epithelial cells of the small intestine, the primary site of Cryptosporidium infection. In a mouse model of acute cryptosporidiosis, a once daily dosage regimen for three consecutive days or a single high dose resulted in reduction of oocyst shedding below the limit detectable by flow cytometry. Recently, a target product profile (TPP) for an anticryptosporidial compound was proposed by Huston et al. and highlights the need for a short dosing regimen (< 7 days) and formulations for children < 2 years

A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning.

PubMed

Sun, Yahui; Hameed, Pathima Nusrath; Verspoor, Karin; Halgamuge, Saman

2016-12-05

Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as pharmacological data is large and complex. Subnetwork identification has already been used to simplify the visualization and interpretation of biological data, but it has not been applied to drug repositioning so far. In this paper, we fill this gap by proposing a new Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug repositioning. Drug Similarity Networks (DSN) are generated using the chemical, therapeutic, protein, and phenotype features of drugs. In DSNs, vertex prizes and edge costs represent the similarities and dissimilarities between drugs respectively, and terminals represent drugs in the cardiovascular class, as defined in the Anatomical Therapeutic Chemical classification system. A new Physarum-inspired Prize-Collecting Steiner Tree algorithm is proposed in this paper to identify subnetworks. We apply both the proposed algorithm and the widely-used GW algorithm to identify subnetworks in our 18 generated DSNs. In these DSNs, our proposed algorithm identifies subnetworks with an average Rand Index of 81.1%, while the GW algorithm can only identify subnetworks with an average Rand Index of 64.1%. We select 9 subnetworks with high Rand Index to find drug repositioning opportunities. 10 frequently occurring drugs in these subnetworks are identified as candidates to be repositioned for cardiovascular diseases. We find evidence to support previous discoveries that nitroglycerin, theophylline and acarbose may be able to be repositioned for cardiovascular diseases. Moreover, we identify seven previously unknown drug candidates that also may interact with the biological cardiovascular system. These discoveries show our proposed Prize-Collecting Steiner Tree approach as a promising strategy for drug repositioning.

Literature-based prediction of novel drug indications considering relationships between entities.

PubMed

Jang, Giup; Lee, Taekeon; Lee, Byung Mun; Yoon, Youngmi

2017-06-27

There have been many attempts to identify and develop new uses for existing drugs, which is known as drug repositioning. Among these efforts, text mining is an effective means of discovering novel knowledge from a large amount of literature data. We identify a gene regulation by a drug and a phenotype based on the biomedical literature. Drugs or phenotypes can activate or inhibit gene regulation. We calculate the therapeutic possibility that a drug acts on a phenotype by means of these two types of regulation. We assume that a drug treats a phenotype if the genes regulated by the phenotype are inversely correlated with the genes regulated by the drug. Based on this hypothesis, we identify drug-phenotype associations with therapeutic possibility. To validate the drug-phenotype associations predicted by our method, we make an enrichment comparison with known drug-phenotype associations. We also identify candidate drugs for drug repositioning from novel associations and thus reveal that our method is a novel approach to drug repositioning.

To Genotype or Phenotype for Personalized Medicine? CYP450 Drug Metabolizing Enzyme Genotype-Phenotype Concordance and Discordance in the Ecuadorian Population.

PubMed

De Andrés, Fernando; Terán, Santiago; Hernández, Francisco; Terán, Enrique; LLerena, Adrián

2016-12-01

Genetic variations within the cytochrome P450 (CYP450) superfamily of drug metabolizing enzymes confer substantial person-to-person and between-population differences in pharmacokinetics, and by extension, highly variable clinical effects of medicines. In this context, "personalized medicine," "precision medicine," and "stratified medicine" are related concepts attributed to what is essentially targeted therapeutics and companion diagnostics, aimed at improving safety and effectiveness of health interventions. We report here, to the best of our knowledge, the first comparative clinical pharmacogenomics study, in an Ecuadorian population sample, of five key CYP450s involved in drug metabolism: CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4. In 139 unrelated, medication-free, and healthy Ecuadorian subjects, we measured the phenotypic activity of these drug metabolism pathways using the CEIBA multiplexed phenotyping cocktail. The subjects were genotyped for each CYP450 enzyme gene as well. Notably, based on the CYP450 metabolic phenotypes estimated by the genotype data, 0.75% and 3.10% of the subjects were genotypic poor metabolizers (gPMs) for CYP2C19 and CYP2D6, respectively. Additionally, on the other extreme, genotype-estimated ultrarapid metabolizer (gUMs) phenotype was represented by 15.79% of CYP2C19, and 5.43% of CYP2D6. There was, however, considerable discordance between directly measured phenotypes (mPMs and mUMs) and the above genotype-estimated enzyme phenotypes. For example, among individuals genotypically carrying enhanced activity alleles (gUMs), many showed a lower actual drug metabolism capacity than expected by their genotypes, even lower than individuals with reduced or no activity alleles. In conclusion, for personalized medicine in the Ecuadorian population, we recommend CYP450 multiplexed phenotyping, or genotyping and phenotyping in tandem, rather than CYP450 genotypic tests alone. Additionally, we recommend, in consideration of equity, ethical

Phenotype-specific CpG island methylation events in a murine model of prostate cancer.

PubMed

Camoriano, Marta; Kinney, Shannon R Morey; Moser, Michael T; Foster, Barbara A; Mohler, James L; Trump, Donald L; Karpf, Adam R; Smiraglia, Dominic J

2008-06-01

Aberrant DNA methylation plays a significant role in nearly all human cancers and may contribute to disease progression to advanced phenotypes. Study of advanced prostate cancer phenotypes in the human disease is hampered by limited availability of tissues. We therefore took advantage of the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model to study whether three different phenotypes of TRAMP tumors (PRIM, late-stage primary tumors; AIP, androgen-independent primary tumors; and MET, metastases) displayed specific patterns of CpG island hypermethylation using Restriction Landmark Genomic Scanning. Each tumor phenotype displayed numerous hypermethylation events, with the most homogeneous methylation pattern in AIP and the most heterogeneous pattern in MET. Several loci displayed a phenotype-specific methylation pattern; the most striking pattern being loci methylated at high frequency in PRIM and AIP but rarely in MET. Examination of the mRNA expression of three genes, BC058385, Goosecoid, and Neurexin 2, which exhibited nonpromoter methylation, revealed increased expression associated with downstream methylation. Only methylated samples showed mRNA expression, in which tumor phenotype was a key factor determining the level of expression. The CpG island in the human orthologue of BC058385 was methylated in human AIP but not in primary androgen-stimulated prostate cancer or benign prostate. The clinical data show a proof-of-principle that the TRAMP model can be used to identify targets of aberrant CpG island methylation relevant to human disease. In conclusion, phenotype-specific hypermethylation events were associated with the overexpression of different genes and may provide new markers of prostate tumorigenesis.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii.

PubMed

Shen, Bang; Powell, Robin H; Behnke, Michael S

2017-06-22

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

Identifying the role of pre-and postsynaptic GABAB receptors in behavior

PubMed Central

Kasten, Chelsea R.; Boehm, Stephen L.

2015-01-01

Although many reviews exist characterizing the molecular differences of GABAB receptor isoforms, there is no current review of the in vivo effects of these isoforms. The current review focuses on whether the GABAB1a and GABAB1b isoforms contribute differentially to behaviors in isoform knockout mice. The roles of these receptors have primarily been characterized in cognitive, anxiety, and depressive phenotypes. Currently, the field supports a role of GABAB1a in memory maintenance and protection against an anhedonic phenotype, whereas GABAB1b appears to be involved in memory formation and a susceptibility to developing an anhedonic phenotype. Although GABAB receptors have been strongly implicated in drug abuse phenotypes, no isoform-specific work has been done in this field. Future directions include developing site-specific isoform knockdown to identify the role of different brain regions in behavior, as well as identifying how these isoforms are involved in development of behavioral phenotypes. PMID:26283074

Phenotype- and Genotype-Specific Structural Alterations in Spasmodic Dysphonia

PubMed Central

Bianchi, Serena; Battistella, Giovanni; Huddleston, Hailey; Scharf, Rebecca; Fleysher, Lazar; Rumbach, Anna F.; Frucht, Steven J.; Blitzer, Andrew; Ozelius, Laurie J.; Simonyan, Kristina

2017-01-01

Background Spasmodic dysphonia is a focal dystonia characterized by involuntary spasms in the laryngeal muscles that occur selectively during speaking. Although hereditary trends have been reported in up to 16% of patients, the causative etiology of spasmodic dysphonia is unclear, and the influences of various phenotypes and genotypes on disorder pathophysiology are poorly understood. In this study, we examined structural alterations in cortical gray matter and white matter integrity in relationship to different phenotypes and putative genotypes of spasmodic dysphonia to elucidate the structural component of its complex pathophysiology. Methods Eighty-nine patients with spasmodic dysphonia underwent high-resolution magnetic resonance imaging and diffusion-weighted imaging to examine cortical thickness and white matter fractional anisotropy in adductor versus abductor forms (distinct phenotypes) and in sporadic versus familial cases (distinct genotypes). Results Phenotype-specific abnormalities were localized in the left sensorimotor cortex and angular gyrus and the white matter bundle of the right superior corona radiata. Genotype-specific alterations were found in the left superior temporal gyrus, supplementary motor area, and the arcuate portion of the left superior longitudinal fasciculus. Conclusions Our findings suggest that phenotypic differences in spasmodic dysphonia arise at the level of the primary and associative areas of motor control, whereas genotype-related pathophysiological mechanisms may be associated with dysfunction of regions regulating phonological and sensory processing. Identification of structural alterations specific to disorder phenotype and putative genotype provides an important step toward future delineation of imaging markers and potential targets for novel therapeutic interventions for spasmodic dysphonia. PMID:28186656

Phenotype- and genotype-specific structural alterations in spasmodic dysphonia.

PubMed

Bianchi, Serena; Battistella, Giovanni; Huddleston, Hailey; Scharf, Rebecca; Fleysher, Lazar; Rumbach, Anna F; Frucht, Steven J; Blitzer, Andrew; Ozelius, Laurie J; Simonyan, Kristina

2017-04-01

Spasmodic dysphonia is a focal dystonia characterized by involuntary spasms in the laryngeal muscles that occur selectively during speaking. Although hereditary trends have been reported in up to 16% of patients, the causative etiology of spasmodic dysphonia is unclear, and the influences of various phenotypes and genotypes on disorder pathophysiology are poorly understood. In this study, we examined structural alterations in cortical gray matter and white matter integrity in relationship to different phenotypes and putative genotypes of spasmodic dysphonia to elucidate the structural component of its complex pathophysiology. Eighty-nine patients with spasmodic dysphonia underwent high-resolution magnetic resonance imaging and diffusion-weighted imaging to examine cortical thickness and white matter fractional anisotropy in adductor versus abductor forms (distinct phenotypes) and in sporadic versus familial cases (distinct genotypes). Phenotype-specific abnormalities were localized in the left sensorimotor cortex and angular gyrus and the white matter bundle of the right superior corona radiata. Genotype-specific alterations were found in the left superior temporal gyrus, supplementary motor area, and the arcuate portion of the left superior longitudinal fasciculus. Our findings suggest that phenotypic differences in spasmodic dysphonia arise at the level of the primary and associative areas of motor control, whereas genotype-related pathophysiological mechanisms may be associated with dysfunction of regions regulating phonological and sensory processing. Identification of structural alterations specific to disorder phenotype and putative genotype provides an important step toward future delineation of imaging markers and potential targets for novel therapeutic interventions for spasmodic dysphonia. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

Arylesterase Phenotype-Specific Positive Association Between Arylesterase Activity and Cholinesterase Specific Activity in Human Serum

PubMed Central

Aoki, Yutaka; Helzlsouer, Kathy J.; Strickland, Paul T.

2014-01-01

Context: Cholinesterase (ChE) specific activity is the ratio of ChE activity to ChE mass and, as a biomarker of exposure to cholinesterase inhibitors, has a potential advantage over simple ChE activity. Objective: To examine the association of several potential correlates (serum arylesterase/paraoxonase activity, serum albumin, sex, age, month of blood collection, and smoking) with plasma ChE specific activity. Methods: We analyzed data from 195 cancer-free controls from a nested case-control study, accounting for potential confounding. Results: Arylesterase activity had an independent, statistically significant positive association with ChE specific activity, and its magnitude was the greatest for the arylesterase phenotype corresponding to the QQ PON1192 genotype followed by phenotypes corresponding to QR and RR genotypes. Serum albumin was positively associated with ChE specific activity. Conclusions: Plasma arylesterase activity was positively associated with plasma ChE specific activity. This observation is consistent with protection conferred by a metabolic phenotype resulting in reduced internal dose. PMID:24473115

Drosophila Cancer Models Identify Functional Differences between Ret Fusions.

PubMed

Levinson, Sarah; Cagan, Ross L

2016-09-13

We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient's treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The QDREC web server: determining dose-response characteristics of complex macroparasites in phenotypic drug screens.

PubMed

Asarnow, Daniel; Rojo-Arreola, Liliana; Suzuki, Brian M; Caffrey, Conor R; Singh, Rahul

2015-05-01

Neglected tropical diseases (NTDs) caused by helminths constitute some of the most common infections of the world's poorest people. The etiological agents are complex and recalcitrant to standard techniques of molecular biology. Drug screening against helminths has often been phenotypic and typically involves manual description of drug effect and efficacy. A key challenge is to develop automated, quantitative approaches to drug screening against helminth diseases. The quantal dose-response calculator (QDREC) constitutes a significant step in this direction. It can be used to automatically determine quantitative dose-response characteristics and half-maximal effective concentration (EC50) values using image-based readouts from phenotypic screens, thereby allowing rigorous comparisons of the efficacies of drug compounds. QDREC has been developed and validated in the context of drug screening for schistosomiasis, one of the most important NTDs. However, it is equally applicable to general phenotypic screening involving helminths and other complex parasites. QDREC is publically available at: http://haddock4.sfsu.edu/qdrec2/. Source code and datasets are at: http://tintin.sfsu.edu/projects/phenotypicAssays.html. rahul@sfsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Current cytochrome P450 phenotyping methods applied to metabolic drug-drug interaction prediction in dogs.

PubMed

Mills, Beth Miskimins; Zaya, Matthew J; Walters, Rodney R; Feenstra, Kenneth L; White, Julie A; Gagne, Jason; Locuson, Charles W

2010-03-01

Recombinant cytochrome P450 (P450) phenotyping, different approaches for estimating fraction metabolized (f(m)), and multiple measures of in vivo inhibitor exposure were tested for their ability to predict drug interaction magnitude in dogs. In previous reports, midazolam-ketoconazole interaction studies in dogs have been attributed to inhibition of CYP3A pathways. However, in vitro phenotyping studies demonstrated higher apparent intrinsic clearances (CL(int,app)) of midazolam with canine CYP2B11 and CYP2C21. Application of activity correction factors and isoform hepatic abundance to liver microsome CL(int,app) values further implicated CYP2B11 (f(m) >or= 0.89) as the dog enzyme responsible for midazolam- and temazepam-ketoconazole interactions in vivo. Mean area under the curve (AUC) in the presence of the inhibitor/AUC ratios from intravenous and oral midazolam interaction studies were predicted well with unbound K(i) and estimates of unbound hepatic inlet inhibitor concentrations and intestinal metabolism using the AUC-competitive inhibitor relationship. No interactions were observed in vivo with bufuralol, although significant interactions with bufuralol were predicted with fluoxetine via CYP2D and CYP2C pathways (>2.45-fold) but not with clomipramine (<2-fold). The minor caffeine-fluvoxamine interaction (1.78-fold) was slightly higher than predicted values based on determination of a moderate f(m) value for CYP1A1, although CYP1A2 may also be involved in caffeine metabolism. The findings suggest promise for in vitro approaches to drug interaction assessment in dogs, but they also highlight the need to identify improved substrate and inhibitor probes for canine P450s.

Phenotypic and genotypic analysis of anti-tuberculosis drug resistance in Mycobacterium tuberculosis isolates in Myanmar.

PubMed

Aung, Wah Wah; Ei, Phyu Win; Nyunt, Wint Wint; Swe, Thyn Lei; Lwin, Thandar; Htwe, Mi Mi; Kim, Kyung Jun; Lee, Jong Seok; Kim, Chang Ki; Cho, Sang Nae; Song, Sun Dae; Chang, Chulhun L

2015-09-01

Tuberculosis (TB) is one of the most serious health problems in Myanmar. Because TB drug resistance is associated with genetic mutation(s) relevant to responses to each drug, genotypic methods for detecting these mutations have been proposed to overcome the limitations of classic phenotypic drug susceptibility testing (DST). We explored the current estimates of drug-resistant TB and evaluated the usefulness of genotypic DST in Myanmar. We determined the drug susceptibility of Mycobacterium tuberculosis isolated from sputum smear-positive patients with newly diagnosed pulmonary TB at two main TB centers in Myanmar during 2013 by using conventional phenotypic DST and the GenoType MTBDRplus assay (Hain Lifescience, Germany). Discrepant results were confirmed by sequencing the genes relevant to each type of resistance (rpoB for rifampicin; katG and inhA for isoniazid). Of 191 isolates, phenotypic DST showed that 27.7% (n=53) were resistant to at least one first-line drug and 20.9% (n=40) were resistant to two or more, including 18.3% (n=35) multidrug-resistant TB (MDR-TB) strains. Monoresistant strains accounted for 6.8% (n=13) of the samples. Genotypic assay of 189 isolates showed 17.5% (n=33) MDR-TB and 5.3% (n=10) isoniazid-monoresistant strains. Genotypic susceptibility results were 99.5% (n=188) concordant and agreed almost perfectly with phenotypic DST (kappa=0.99; 95% confidence interval 0.96-1.01). The results highlight the burden of TB drug resistance and prove the usefulness of the genotypic DST in Myanmar.

Impact of human immunodeficiency virus type 1 reverse transcriptase inhibitor drug resistance mutation interactions on phenotypic susceptibility.

PubMed

Trivedi, Vinod; Von Lindern, Jana; Montes-Walters, Miguel; Rojo, Daniel R; Shell, Elisabeth J; Parkin, Neil; O'Brien, William A; Ferguson, Monique R

2008-10-01

The role specific reverse transcriptase (RT) drug resistance mutations play in influencing phenotypic susceptibility to RT inhibitors in virus strains with complex resistance interaction patterns was assessed using recombinant viruses that consisted of RT-PCR-amplified pol fragments derived from plasma HIV-1 RNA from two treatment-experienced patients. Specific modifications of key RT amino acids were performed by site-directed mutagenesis. A panel of viruses with defined genotypic resistance mutations was assessed for phenotypic drug resistance. Introduction of M184V into several different clones expressing various RT resistance mutations uniformly decreased susceptibility to abacavir, lamivudine, and didanosine, and increased susceptibility to zidovudine, stavudine, and tenofovir; replication capacity was decreased. The L74V mutation had similar but slightly different effects, contributing to decreased susceptibility to abacavir, lamivudine, and didanosine and increased susceptibility to zidovudine and tenofovir, but in contrast to M184V, L74V contributed to decreased susceptibility to stavudine. In virus strains with the nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations K101E and G190S, the L74V mutation increased replication capacity, consistent with published observations, but replication capacity was decreased in strains without NNRTI resistance mutations. K101E and G190S together tend to decrease susceptibility to all nucleoside RT inhibitors, but the K103N mutation had little effect on nucleoside RT inhibitor susceptibility. Mutational interactions can have a substantial impact on drug resistance phenotype and replication capacity, and this has been exploited in clinical practice with the development of fixed-dose combination pills. However, we are the first to report these mutational interactions using molecularly cloned recombinant strains derived from viruses that occur naturally in HIV-infected individuals.

Impact of Human Immunodeficiency Virus Type 1 Reverse Transcriptase Inhibitor Drug Resistance Mutation Interactions on Phenotypic Susceptibility

PubMed Central

Trivedi, Vinod; Von Lindern, Jana; Montes-Walters, Miguel; Rojo, Daniel R.; Shell, Elisabeth J.; Parkin, Neil; O'Brien, William A.

2008-01-01

Abstract The role specific reverse transcriptase (RT) drug resistance mutations play in influencing phenotypic susceptibility to RT inhibitors in virus strains with complex resistance interaction patterns was assessed using recombinant viruses that consisted of RT-PCR-amplified pol fragments derived from plasma HIV-1 RNA from two treatment-experienced patients. Specific modifications of key RT amino acids were performed by site-directed mutagenesis. A panel of viruses with defined genotypic resistance mutations was assessed for phenotypic drug resistance. Introduction of M184V into several different clones expressing various RT resistance mutations uniformly decreased susceptibility to abacavir, lamivudine, and didanosine, and increased susceptibility to zidovudine, stavudine, and tenofovir; replication capacity was decreased. The L74V mutation had similar but slightly different effects, contributing to decreased susceptibility to abacavir, lamivudine, and didanosine and increased susceptibility to zidovudine and tenofovir, but in contrast to M184V, L74V contributed to decreased susceptibility to stavudine. In virus strains with the nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations K101E and G190S, the L74V mutation increased replication capacity, consistent with published observations, but replication capacity was decreased in strains without NNRTI resistance mutations. K101E and G190S together tend to decrease susceptibility to all nucleoside RT inhibitors, but the K103N mutation had little effect on nucleoside RT inhibitor susceptibility. Mutational interactions can have a substantial impact on drug resistance phenotype and replication capacity, and this has been exploited in clinical practice with the development of fixed-dose combination pills. However, we are the first to report these mutational interactions using molecularly cloned recombinant strains derived from viruses that occur naturally in HIV-infected individuals. PMID:18844463

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

PubMed Central

Shen, Bang; Powell, Robin H.; Behnke, Michael S.

2017-01-01

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites. PMID:28671645

Walking on thin ice! Identifying methamphetamine "drug mules" on digital plain radiography.

PubMed

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J; Flach, P M

2014-04-01

The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in "drug mules" by plain abdominal digital radiography (DR). The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all "drug mules" and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. There were 16 true-positive "drug mules" identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA "drug mules", although DR is associated with high diagnostic insecurity and underreports the total internal payload.

A review of approaches to identifying patient phenotype cohorts using electronic health records

PubMed Central

Shivade, Chaitanya; Raghavan, Preethi; Fosler-Lussier, Eric; Embi, Peter J; Elhadad, Noemie; Johnson, Stephen B; Lai, Albert M

2014-01-01

Objective To summarize literature describing approaches aimed at automatically identifying patients with a common phenotype. Materials and methods We performed a review of studies describing systems or reporting techniques developed for identifying cohorts of patients with specific phenotypes. Every full text article published in (1) Journal of American Medical Informatics Association, (2) Journal of Biomedical Informatics, (3) Proceedings of the Annual American Medical Informatics Association Symposium, and (4) Proceedings of Clinical Research Informatics Conference within the past 3 years was assessed for inclusion in the review. Only articles using automated techniques were included. Results Ninety-seven articles met our inclusion criteria. Forty-six used natural language processing (NLP)-based techniques, 24 described rule-based systems, 41 used statistical analyses, data mining, or machine learning techniques, while 22 described hybrid systems. Nine articles described the architecture of large-scale systems developed for determining cohort eligibility of patients. Discussion We observe that there is a rise in the number of studies associated with cohort identification using electronic medical records. Statistical analyses or machine learning, followed by NLP techniques, are gaining popularity over the years in comparison with rule-based systems. Conclusions There are a variety of approaches for classifying patients into a particular phenotype. Different techniques and data sources are used, and good performance is reported on datasets at respective institutions. However, no system makes comprehensive use of electronic medical records addressing all of their known weaknesses. PMID:24201027

A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.

PubMed

Davis, Allan Peter; Wiegers, Thomas C; Roberts, Phoebe M; King, Benjamin L; Lay, Jean M; Lennon-Hopkins, Kelley; Sciaky, Daniela; Johnson, Robin; Keating, Heather; Greene, Nigel; Hernandez, Robert; McConnell, Kevin J; Enayetallah, Ahmed E; Mattingly, Carolyn J

2013-01-01

Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88,629 articles relating over 1,200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 254,173 toxicogenomic interactions (152,173 chemical-disease, 58,572 chemical-gene, 5,345 gene-disease and 38,083 phenotype interactions). All chemical-gene-disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer's text-mining process to collate the articles, and CTD's curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug-disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades' worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/

Walking on thin ice! Identifying methamphetamine “drug mules” on digital plain radiography

PubMed Central

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J

2014-01-01

Objective: The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in “drug mules” by plain abdominal digital radiography (DR). Methods: The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all “drug mules” and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. Results: There were 16 true-positive “drug mules” identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. Conclusion: DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Advances in knowledge: Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA “drug mules”, although DR is associated with high diagnostic insecurity and underreports the total internal payload. PMID:24472728

DNA methylation analysis of phenotype specific stratified Indian population.

PubMed

Rotti, Harish; Mallya, Sandeep; Kabekkodu, Shama Prasada; Chakrabarty, Sanjiban; Bhale, Sameer; Bharadwaj, Ramachandra; Bhat, Balakrishna K; Dedge, Amrish P; Dhumal, Vikram Ram; Gangadharan, G G; Gopinath, Puthiya M; Govindaraj, Periyasamy; Joshi, Kalpana S; Kondaiah, Paturu; Nair, Sreekumaran; Nair, S N Venugopalan; Nayak, Jayakrishna; Prasanna, B V; Shintre, Pooja; Sule, Mayura; Thangaraj, Kumarasamy; Patwardhan, Bhushan; Valiathan, Marthanda Varma Sankaran; Satyamoorthy, Kapaettu

2015-05-08

DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments.

PubMed

Jessen, Leon Eyrich; Hoof, Ilka; Lund, Ole; Nielsen, Morten

2013-07-01

Identifying which mutation(s) within a given genotype is responsible for an observable phenotype is important in many aspects of molecular biology. Here, we present SigniSite, an online application for subgroup-free residue-level genotype-phenotype correlation. In contrast to similar methods, SigniSite does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set phenotype. As output, SigniSite displays a sequence logo, depicting the strength of the phenotype association of each residue and a heat-map identifying 'hot' or 'cold' regions. SigniSite was benchmarked against SPEER, a state-of-the-art method for the prediction of specificity determining positions (SDP) using a set of human immunodeficiency virus protease-inhibitor genotype-phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found to outperform SPEER. SigniSite is available at: http://www.cbs.dtu.dk/services/SigniSite/.

High-Throughput Phenotypic Screening of Human Astrocytes to Identify Compounds That Protect Against Oxidative Stress.

PubMed

Thorne, Natasha; Malik, Nasir; Shah, Sonia; Zhao, Jean; Class, Bradley; Aguisanda, Francis; Southall, Noel; Xia, Menghang; McKew, John C; Rao, Mahendra; Zheng, Wei

2016-05-01

Astrocytes are the predominant cell type in the nervous system and play a significant role in maintaining neuronal health and homeostasis. Recently, astrocyte dysfunction has been implicated in the pathogenesis of many neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Astrocytes are thus an attractive new target for drug discovery for neurological disorders. Using astrocytes differentiated from human embryonic stem cells, we have developed an assay to identify compounds that protect against oxidative stress, a condition associated with many neurodegenerative diseases. This phenotypic oxidative stress assay has been optimized for high-throughput screening in a 1,536-well plate format. From a screen of approximately 4,100 bioactive tool compounds and approved drugs, we identified a set of 22 that acutely protect human astrocytes from the consequences of hydrogen peroxide-induced oxidative stress. Nine of these compounds were also found to be protective of induced pluripotent stem cell-differentiated astrocytes in a related assay. These compounds are thought to confer protection through hormesis, activating stress-response pathways and preconditioning astrocytes to handle subsequent exposure to hydrogen peroxide. In fact, four of these compounds were found to activate the antioxidant response element/nuclear factor-E2-related factor 2 pathway, a protective pathway induced by toxic insults. Our results demonstrate the relevancy and utility of using astrocytes differentiated from human stem cells as a disease model for drug discovery and development. Astrocytes play a key role in neurological diseases. Drug discovery efforts that target astrocytes can identify novel therapeutics. Human astrocytes are difficult to obtain and thus are challenging to use for high-throughput screening, which requires large numbers of cells. Using human embryonic stem cell-derived astrocytes and an

Use of microdose phenotyping to individualise dosing of patients.

PubMed

Hohmann, Nicolas; Haefeli, Walter E; Mikus, Gerd

2015-09-01

Administering the right amount of the right drug at the right time is a key mission of clinical medicine. This comprises dose adaptation according to a patient's intrinsic and extrinsic factors influencing drug disposition. Several biomarkers are available for dose adaptation; still, prediction of individual drug disposition may be improved. Phenotyping is the quantification of drug metabolism with probe substrates specific to drug-metabolising enzymes. This allows measurement of baseline metabolism and changes after modulation of drug metabolism. This article explores the concept of phenotyping using pharmacologically ineffective microdoses of probe substrates to obtain information on drug metabolism. Several probe drugs such as midazolam for cytochrome P450 3A have already been used, but validation of other microdosed probe drugs, analytical procedures and drug formulations still face some challenges that have to be overcome. Since microdosed probe drugs have no risk of adverse drug reactions or interference with therapy, more widespread use is possible. This allows drug-drug interaction data to be safely obtained during first-in-man studies, enhancing the clinical safety of human healthy volunteers and patients in clinical trials, and, most importantly, allows determination of the drug-metabolising phenotype in severely ill patients. With harmless probe drugs at hand quantifying drug metabolism and adapting the dose accordingly, a phenotyping-based dosing strategy could become reality, offering the possibility of individualised drug therapy with reduced adverse effects and fewer therapeutic failures.

Genotype–phenotype correlations in Down syndrome identified by array CGH in 30 cases of partial trisomy and partial monosomy chromosome 21

PubMed Central

Lyle, Robert; Béna, Frédérique; Gagos, Sarantis; Gehrig, Corinne; Lopez, Gipsy; Schinzel, Albert; Lespinasse, James; Bottani, Armand; Dahoun, Sophie; Taine, Laurence; Doco-Fenzy, Martine; Cornillet-Lefèbvre, Pascale; Pelet, Anna; Lyonnet, Stanislas; Toutain, Annick; Colleaux, Laurence; Horst, Jürgen; Kennerknecht, Ingo; Wakamatsu, Nobuaki; Descartes, Maria; Franklin, Judy C; Florentin-Arar, Lina; Kitsiou, Sophia; Aït Yahya-Graison, Emilie; Costantine, Maher; Sinet, Pierre-Marie; Delabar, Jean M; Antonarakis, Stylianos E

2009-01-01

Down syndrome (DS) is one of the most frequent congenital birth defects, and the most common genetic cause of mental retardation. In most cases, DS results from the presence of an extra copy of chromosome 21. DS has a complex phenotype, and a major goal of DS research is to identify genotype–phenotype correlations. Cases of partial trisomy 21 and other HSA21 rearrangements associated with DS features could identify genomic regions associated with specific phenotypes. We have developed a BAC array spanning HSA21q and used array comparative genome hybridization (aCGH) to enable high-resolution mapping of pathogenic partial aneuploidies and unbalanced translocations involving HSA21. We report the identification and mapping of 30 pathogenic chromosomal aberrations of HSA21 consisting of 19 partial trisomies and 11 partial monosomies for different segments of HSA21. The breakpoints have been mapped to within ∼85 kb. The majority of the breakpoints (26 of 30) for the partial aneuploidies map within a 10-Mb region. Our data argue against a single DS critical region. We identify susceptibility regions for 25 phenotypes for DS and 27 regions for monosomy 21. However, most of these regions are still broad, and more cases are needed to narrow down the phenotypic maps to a reasonable number of candidate genomic elements per phenotype. PMID:19002211

Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

PubMed

Ravichandran, Srikanth; Del Sol, Antonio

2017-02-01

Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Identifying novel drug indications through automated reasoning.

PubMed

Tari, Luis; Vo, Nguyen; Liang, Shanshan; Patel, Jagruti; Baral, Chitta; Cai, James

2012-01-01

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

The wake-promoting drug modafinil stimulates specific hypothalamic circuits to promote adaptive stress responses in an animal model of PTSD

PubMed Central

Cohen, S; Ifergane, G; Vainer, E; Matar, M A; Kaplan, Z; Zohar, J; Mathé, A A; Cohen, H

2016-01-01

Pharmacotherapeutic intervention during traumatic memory consolidation has been suggested to alleviate or even prevent the development of posttraumatic stress disorder (PTSD). We recently reported that, in a controlled, prospective animal model, depriving rats of sleep following stress exposure prevents the development of a PTSD-like phenotype. Here, we report that administering the wake-promoting drug modafinil to rats in the aftermath of a stressogenic experience has a similar prophylactic effect, as it significantly reduces the prevalence of PTSD-like phenotype. Moreover, we show that the therapeutic value of modafinil appears to stem from its ability to stimulate a specific circuit within the hypothalamus, which ties together the neuropeptide Y, the orexin system and the HPA axis, to promote adaptive stress responses. The study not only confirms the value of sleep prevention and identifies the mechanism of action of a potential prophylactic treatment after traumatic exposure, but also contributes to understanding mechanisms underlying the shift towards adaptive behavioral response. PMID:27727245

Discovery of novel drug targets and their functions using phenotypic screening of natural products.

PubMed

Chang, Junghwa; Kwon, Ho Jeong

2016-03-01

Natural products are valuable resources that provide a variety of bioactive compounds and natural pharmacophores in modern drug discovery. Discovery of biologically active natural products and unraveling their target proteins to understand their mode of action have always been critical hurdles for their development into clinical drugs. For effective discovery and development of bioactive natural products into novel therapeutic drugs, comprehensive screening and identification of target proteins are indispensable. In this review, a systematic approach to understanding the mode of action of natural products isolated using phenotypic screening involving chemical proteomics-based target identification is introduced. This review highlights three natural products recently discovered via phenotypic screening, namely glucopiericidin A, ecumicin, and terpestacin, as representative case studies to revisit the pivotal role of natural products as powerful tools in discovering the novel functions and druggability of targets in biological systems and pathological diseases of interest.

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.

PubMed

Sun, Yi; Zhang, Wei; Chen, Yunqin; Ma, Qin; Wei, Jia; Liu, Qi

2016-02-23

Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses. To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data. Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients.

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python).

PubMed

Irizarry, Kristopher J L; Rutllant, Josep

2016-01-01

Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

Association of Liver Injury From Specific Drugs, or Groups of Drugs, With Polymorphisms in HLA and Other Genes in a Genome-wide Association Study

PubMed Central

Nicoletti, Paola; Aithal, Guruprasad P.; Bjornsson, Einar S.; Andrade, Raul J.; Sawle, Ashley; Arrese, Marco; Barnhart, Huiman X.; Bondon-Guitton, Emmanuelle; Hayashi, Paul H.; Bessone, Fernando; Carvajal, Alfonso; Cascorbi, Ingolf; Cirulli, Elizabeth T.; Chalasani, Naga; Conforti, Anita; Coulthard, Sally A.; Daly, Mark J.; Day, Christopher P.; Dillon, John F.; Fontana, Robert J.; Grove, Jane I.; Hallberg, Pär; Hernández, Nelia; Ibáñez, Luisa; Kullak-Ublick, Gerd A.; Laitinen, Tarja; Larrey, Dominique; Lucena, M. Isabel; Maitland-van der Zee, Anke H.; Martin, Jennifer H.; Molokhia, Mariam; Pirmohamed, Munir; Powell, Elizabeth E.; Qin, Shengying; Serrano, Jose; Stephens, Camilla; Stolz, Andrew; Wadelius, Mia; Watkins, Paul B.; Floratos, Aris; Shen, Yufeng; Nelson, Matthew R.; Urban, Thomas J.; Daly, Ann K.

2017-01-01

BACKGROUND & AIMS We performed a genome-wide association study (GWAS) to identify genetic risk factors for drug-induced liver injury (DILI) from licensed drugs without previously reported genetic risk factors. METHODS We performed a GWAS of 862 persons with DILI and 10588 population-matched controls. The first set of cases was recruited prior to May 2009 in Europe (n=137) or the USA (n=274). The second set of cases were identified from May 2009 through May 2013 from international collaborative studies performed in Europe, the USA and South America. For the GWAS, we included only cases of European ancestry associated with a particular drug (but not flucloxacillin or amoxicillin-clavulanate). We used DNA samples from all subjects to analyze human leukocyte antigen (HLA) genes and single nucleotide polymorphisms (SNPs). After the discovery analysis was concluded, we validated our findings using data from 283 European patients with diagnosis of DILI associated with various drugs. RESULTS We associated DILI with rs114577328 (a proxy for A*33:01 a HLA class I allele; odds ratio [OR], 2.7; 95% CI, 1.9–3.8; P=2.4×10−8) and with rs72631567 on chromosome 2 (OR, 2.0; 95% CI, 1.6–2.5; P=9.7×10−9). The association with A*33:01 was mediated by large effects for terbinafine-, fenofibrate-, and ticlopidine-related DILI. The variant on chromosome 2 was associated with DILI from a variety of drugs. Further phenotypic analysis indicated that the association between DILI and A*33:01 was significant, genome wide, for cholestatic and mixed DILI, but not for hepatocellular DILI; the polymorphism on chromosome 2 associated with cholestatic and mixed DILI as well as hepatocellular DILI. We identified an association between rs28521457 (within the LRBA gene) and only hepatocellular DILI (OR, 2.1; 95% CI, 1.6–2.7; P=4.8×10−9). We did not associate any specific drug classes with genetic polymorphisms, except for statin-associated DILI, which was associated with rs116561224 on

Genetic determinants of drug responsiveness and drug interactions.

PubMed

Caraco, Y

1998-10-01

Six cytochrome P450 enzymes mediate the oxidative metabolism of most drugs in common use: CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4. These enzymes have selective substrate specificity, and their activity is characterized by marked interindividual variation. Some of these systems (CYP2C19, CYP2D6) are polymorphically distributed; thus, a subset of the population may be genetically deficient in enzyme activity. Phenotyping procedures designed to identify subjects with impaired metabolism who may be at increased risk for drug toxicity have been developed and validated. This has been supplemented in recent years by the availability of genetic analysis and the identification of specific alleles that are associated with altered (i.e., reduced, deficient, or increased) enzyme activity. The potential of genotyping to predict pharmacodynamics holds great promise for the future because it does not involve the administration of exogenous compound and is not confounded by drug therapy. Drug interactions caused by the inhibition or induction of oxidative drug metabolism may be of great clinical importance because they may result in drug toxicity or therapeutic failure. Further understanding of cytochrome P450 complexity may allow, through a combined in vitro-in vivo approach, the reliable prediction and possible prevention of deleterious drug interactions.

Association of Immunological Cell Profiles with Specific Clinical Phenotypes of Scleroderma Disease

PubMed Central

Calzada, David; Mayayo, Teodoro; González-Rodríguez, María Luisa; Rabasco, Antonio María; Lahoz, Carlos

2014-01-01

This study aimed to search the correlation among immunological profiles and clinical phenotypes of scleroderma in well-characterized groups of scleroderma patients, comparing forty-nine scleroderma patients stratified according to specific clinical phenotypes with forty-nine healthy controls. Five immunological cell subpopulations (B, CD4+ and CD8+ T-cells, NK, and monocytes) and their respective stages of apoptosis and activation were analyzed by flow cytometry, in samples of peripheral blood mononuclear cells (PBMCs). Analyses of results were stratified according to disease stage, time since the diagnosis, and visceral damage (pulmonary fibrosis, pulmonary hypertension, and cardiac affliction) and by time of treatment with corticosteroids. An increase in the percentages of monocytes and a decrease in the B cells were mainly related to the disease progression. A general apoptosis decrease was found in all phenotypes studied, except in localized scleroderma. An increase of B and NK cells activation was found in patients diagnosed more than 10 years ago. Specific cell populations like monocytes, NK, and B cells were associated with the type of affected organ. This study shows how, in a heterogeneous disease, proper patient's stratification according to clinical phenotypes allows finding specific cellular profiles. Our data may lead to improvements in the knowledge of prognosis factors and to aid in the analysis of future specific therapies. PMID:24818126

RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma.

PubMed

Arora, Shilpi; Gonzales, Irma M; Hagelstrom, R Tanner; Beaudry, Christian; Choudhary, Ashish; Sima, Chao; Tibes, Raoul; Mousses, Spyro; Azorsa, David O

2010-08-18

Ewing's sarcomas are aggressive musculoskeletal tumors occurring most frequently in the long and flat bones as a solitary lesion mostly during the teen-age years of life. With current treatments, significant number of patients relapse and survival is poor for those with metastatic disease. As part of novel target discovery in Ewing's sarcoma, we applied RNAi mediated phenotypic profiling to identify kinase targets involved in growth and survival of Ewing's sarcoma cells. Four Ewing's sarcoma cell lines TC-32, TC-71, SK-ES-1 and RD-ES were tested in high throughput-RNAi screens using a siRNA library targeting 572 kinases. Knockdown of 25 siRNAs reduced the growth of all four Ewing's sarcoma cell lines in replicate screens. Of these, 16 siRNA were specific and reduced proliferation of Ewing's sarcoma cells as compared to normal fibroblasts. Secondary validation and preliminary mechanistic studies highlighted the kinases STK10 and TNK2 as having important roles in growth and survival of Ewing's sarcoma cells. Furthermore, knockdown of STK10 and TNK2 by siRNA showed increased apoptosis. In summary, RNAi-based phenotypic profiling proved to be a powerful gene target discovery strategy, leading to successful identification and validation of STK10 and TNK2 as two novel potential therapeutic targets for Ewing's sarcoma.

Utility of Phenotypic and Genotypic Testing in the Study of Mycobacterium tuberculosis Resistance to First-Line Anti-Tuberculosis drugs.

PubMed

Alba Álvarez, Luz María; García García, José María; Pérez Hernández, M Dolores; Martínez González, Susana; Palacios Gutiérrez, Juan José

2017-04-01

To determine the utility of molecular techniques in the diagnosis of resistance and the extent of resistance to first-line drugs in our region. From 2004 to 2013, 1,889 strains of Mycobacterium tuberculosis complex isolated in Asturias, Spain, were studied using phenotypic (Clinical and Laboratory Standards Institute guidelines) and molecular (INNOLiPA RIF-TB © ; GenotypeMDRplus © ; GenotypeMDRsl © ) sensitivity tests. 1,759 strains (94.52%) were sensitive to all first-line drugs, and 102 strains (5.48%) showed some resistance: 81 strains (4.35%) were resistant to 1 single drug, 14 (0.75%) were polyresistant, and 7 (0.37%) were multiresistant (resistant to rifampicin and isoniazid). In total, 137 resistances were identified: 60 to isoniazid (3.22%), 7 to rifampicin (0.37%), 9 to pyrazinamide (0.48%), 11 to ethambutol (0.59%), and 50 to streptomycin (2.68%). Of the mutations detected, 75.9% (63/83) correlated with resistance, while 24.09% of mutations detected (20/83) were not associated with resistance; 16 of these involved a silent mutation at codon 514 of the rpoB gene. Between 0 and 90% of strains, depending on the drug under consideration, were resistant even when no gene mutations were detected using marketed systems. Molecular techniques are very useful, particularly for obtaining rapid results, but these must be confirmed with standard phenotypic sensitivity testing. The rate of resistance in our region is low and multi-drug resistantcases (0.37%) are sporadic. Copyright © 2016 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

PubMed

Darlington, T M; Pimentel, R; Smith, K; Bakian, A V; Jerominski, L; Cardon, J; Camp, N J; Callor, W B; Grey, T; Singleton, M; Yandell, M; Renshaw, P F; Yurgelun-Todd, D A; Gray, D; Coon, H

2014-10-21

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma

PubMed Central

Darlington, T M; Pimentel, R; Smith, K; Bakian, A V; Jerominski, L; Cardon, J; Camp, N J; Callor, W B; Grey, T; Singleton, M; Yandell, M; Renshaw, P F; Yurgelun-Todd, D A; Gray, D; Coon, H

2014-01-01

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12 000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to

Clinical and molecular characterization of a novel INS mutation identified in patients with MODY phenotype.

PubMed

Piccini, Barbara; Artuso, Rosangela; Lenzi, Lorenzo; Guasti, Monica; Braccesi, Giulia; Barni, Federica; Casalini, Emilio; Giglio, Sabrina; Toni, Sonia

2016-11-01

Correct diagnosis of Maturity-Onset Diabetes of the Young (MODY) is based on genetic tests requiring an appropriate subject selection by clinicians. Mutations in the insulin (INS) gene rarely occur in patients with MODY. This study is aimed at determining the genetic background and clinical phenotype in patients with suspected MODY. 34 patients with suspected MODY, negative for mutations in the GCK, HNF1α, HNF4α, HNF1β and PDX1 genes, were screened by next generation sequencing (NGS). A heterozygous INS mutation was identified in 4 members of the same family. First genetic tests performed identified two heterozygous silent nucleotide substitutions in MODY3/HNF1α gene. An ineffective attempt to suspend insulin therapy, administering repaglinide and sulphonylureas, was made. DNA was re-sequenced by NGS investigating a set of 102 genes. Genes implicated in the pathway of pancreatic β-cells, candidate genes for type 2 diabetes mellitus and genes causative of diabetes in mice were selected. A novel heterozygous variant in human preproinsulin INS gene (c.125T > C) was found in the affected family members. The new INS mutation broadens the spectrum of possible INS phenotypes. Screening for INS mutations is warranted not only in neonatal diabetes but also in MODYx patients and in selected patients with type 1 diabetes mellitus negative for autoantibodies. Subjects with complex diseases without a specific phenotype should be studied by NGS because Sanger sequencing is ineffective and time consuming in detecting rare variants. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The genetics of alcoholism: identifying specific genes through family studies.

PubMed

Edenberg, Howard J; Foroud, Tatiana

2006-09-01

Alcoholism is a complex disorder with both genetic and environmental risk factors. Studies in humans have begun to elucidate the genetic underpinnings of the risk for alcoholism. Here we briefly review strategies for identifying individual genes in which variations affect the risk for alcoholism and related phenotypes, in the context of one large study that has successfully identified such genes. The Collaborative Study on the Genetics of Alcoholism (COGA) is a family-based study that has collected detailed phenotypic data on individuals in families with multiple alcoholic members. A genome-wide linkage approach led to the identification of chromosomal regions containing genes that influenced alcoholism risk and related phenotypes. Subsequently, single nucleotide polymorphisms (SNPs) were genotyped in positional candidate genes located within the linked chromosomal regions, and analyzed for association with these phenotypes. Using this sequential approach, COGA has detected association with GABRA2, CHRM2 and ADH4; these associations have all been replicated by other researchers. COGA has detected association to additional genes including GABRG3, TAS2R16, SNCA, OPRK1 and PDYN, results that are awaiting confirmation. These successes demonstrate that genes contributing to the risk for alcoholism can be reliably identified using human subjects.

Systematic Phenotyping of a Large-Scale Candida glabrata Deletion Collection Reveals Novel Antifungal Tolerance Genes

PubMed Central

Hiller, Ekkehard; Istel, Fabian; Tscherner, Michael; Brunke, Sascha; Ames, Lauren; Firon, Arnaud; Green, Brian; Cabral, Vitor; Marcet-Houben, Marina; Jacobsen, Ilse D.; Quintin, Jessica; Seider, Katja; Frohner, Ingrid; Glaser, Walter; Jungwirth, Helmut; Bachellier-Bassi, Sophie; Chauvel, Murielle; Zeidler, Ute; Ferrandon, Dominique; Gabaldón, Toni; Hube, Bernhard; d'Enfert, Christophe; Rupp, Steffen; Cormack, Brendan; Haynes, Ken; Kuchler, Karl

2014-01-01

The opportunistic fungal pathogen Candida glabrata is a frequent cause of candidiasis, causing infections ranging from superficial to life-threatening disseminated disease. The inherent tolerance of C. glabrata to azole drugs makes this pathogen a serious clinical threat. To identify novel genes implicated in antifungal drug tolerance, we have constructed a large-scale C. glabrata deletion library consisting of 619 unique, individually bar-coded mutant strains, each lacking one specific gene, all together representing almost 12% of the genome. Functional analysis of this library in a series of phenotypic and fitness assays identified numerous genes required for growth of C. glabrata under normal or specific stress conditions, as well as a number of novel genes involved in tolerance to clinically important antifungal drugs such as azoles and echinocandins. We identified 38 deletion strains displaying strongly increased susceptibility to caspofungin, 28 of which encoding proteins that have not previously been linked to echinocandin tolerance. Our results demonstrate the potential of the C. glabrata mutant collection as a valuable resource in functional genomics studies of this important fungal pathogen of humans, and to facilitate the identification of putative novel antifungal drug target and virulence genes. PMID:24945925

Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

PubMed

Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

2014-12-01

Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p < 0.0001), and respiratory cause mortality (HR 21.5, p < 0.0001) than those in the other four groups. Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

Identifying Novel Phenotypes of Vulnerability and Resistance to Activity-Based Anorexia in Adolescent Female Rats

PubMed Central

Barbarich-Marsteller, Nicole C.; Underwood, Mark D.; Foltin, Richard W.; Myers, Michael M.; Walsh, B. Timothy; Barrett, Jeffrey S.; Marsteller, Douglas A.

2018-01-01

Objective Activity-based anorexia is a translational rodent model that results in severe weight loss, hyperactivity, and voluntary self-starvation. The goal of our investigation was to identify vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats. Method Sprague-Dawley rats were maintained under conditions of restricted access to food (N = 64; or unlimited access, N = 16) until experimental exit, predefined as a target weight loss of 30–35% or meeting predefined criteria for animal health. Nonlinear mixed effects statistical modeling was used to describe wheel running behavior, time to event analysis was used to assess experimental exit, and a regressive partitioning algorithm was used to classify phenotypes. Results Objective criteria were identified for distinguishing novel phenotypes of activity-based anorexia, including a vulnerable phenotype that conferred maximal hyperactivity, minimal food intake, and the shortest time to experimental exit, and a resistant phenotype that conferred minimal activity and the longest time to experimental exit. Discussion The identification of objective criteria for defining vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats provides an important framework for studying the neural mechanisms that promote vulnerability to or protection against the development of self-starvation and hyperactivity during adolescence. Ultimately, future studies using these novel phenotypes may provide important translational insights into the mechanisms that promote these maladaptive behaviors characteristic of anorexia nervosa. PMID:23853140

Identifying novel phenotypes of vulnerability and resistance to activity-based anorexia in adolescent female rats.

PubMed

Barbarich-Marsteller, Nicole C; Underwood, Mark D; Foltin, Richard W; Myers, Michael M; Walsh, B Timothy; Barrett, Jeffrey S; Marsteller, Douglas A

2013-11-01

Activity-based anorexia is a translational rodent model that results in severe weight loss, hyperactivity, and voluntary self-starvation. The goal of our investigation was to identify vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats. Sprague-Dawley rats were maintained under conditions of restricted access to food (N = 64; or unlimited access, N = 16) until experimental exit, predefined as a target weight loss of 30-35% or meeting predefined criteria for animal health. Nonlinear mixed effects statistical modeling was used to describe wheel running behavior, time to event analysis was used to assess experimental exit, and a regressive partitioning algorithm was used to classify phenotypes. Objective criteria were identified for distinguishing novel phenotypes of activity-based anorexia, including a vulnerable phenotype that conferred maximal hyperactivity, minimal food intake, and the shortest time to experimental exit, and a resistant phenotype that conferred minimal activity and the longest time to experimental exit. The identification of objective criteria for defining vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats provides an important framework for studying the neural mechanisms that promote vulnerability to or protection against the development of self-starvation and hyperactivity during adolescence. Ultimately, future studies using these novel phenotypes may provide important translational insights into the mechanisms that promote these maladaptive behaviors characteristic of anorexia nervosa. Copyright © 2013 Wiley Periodicals, Inc.

Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

PubMed

Zhou, Xionghui; Liu, Juan

2014-01-01

Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

PubMed Central

Rutllant, Josep

2016-01-01

Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value. PMID:27200191

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

Novel mutations and phenotypic associations identified through APC, MUTYH, NTHL1, POLD1, POLE gene analysis in Indian Familial Adenomatous Polyposis cohort.

PubMed

Khan, Nikhat; Lipsa, Anuja; Arunachal, Gautham; Ramadwar, Mukta; Sarin, Rajiv

2017-05-22

Colo-Rectal Cancer is a common cancer worldwide with 5-10% cases being hereditary. Familial Adenomatous Polyposis (FAP) syndrome is due to germline mutations in the APC or rarely MUTYH gene. NTHL1, POLD1, POLE have been recently reported in previously unexplained FAP cases. Unlike the Caucasian population, FAP phenotype and its genotypic associations have not been widely studied in several geoethnic groups. We report the first FAP cohort from South Asia and the only non-Caucasian cohort with comprehensive analysis of APC, MUTYH, NTHL1, POLD1, POLE genes. In this cohort of 112 individuals from 53 FAP families, we detected germline APC mutations in 60 individuals (45 families) and biallelic MUTYH mutations in 4 individuals (2 families). No NTHL1, POLD1, POLE mutations were identified. Fifteen novel APC mutations and a new Indian APC mutational hotspot at codon 935 were identified. Eight very rare FAP phenotype or phenotypes rarely associated with mutations outside specific APC regions were observed. APC genotype-phenotype association studies in different geo-ethnic groups can enrich the existing knowledge about phenotypic consequences of distinct APC mutations and guide counseling and risk management in different populations. A stepwise cost-effective mutation screening approach is proposed for genetic testing of south Asian FAP patients.

IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

PubMed

Hepler, N Lance; Scheffler, Konrad; Weaver, Steven; Murrell, Ben; Richman, Douglas D; Burton, Dennis R; Poignard, Pascal; Smith, Davey M; Kosakovsky Pond, Sergei L

2014-09-01

Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes) for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab), determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license), documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.

2009-01-01

Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435

Analytic Complexity and Challenges in Identifying Mixtures of Exposures Associated with Phenotypes in the Exposome Era.

PubMed

Patel, Chirag J

2017-01-01

Mixtures, or combinations and interactions between multiple environmental exposures, are hypothesized to be causally linked with disease and health-related phenotypes. Established and emerging molecular measurement technologies to assay the exposome , the comprehensive battery of exposures encountered from birth to death, promise a new way of identifying mixtures in disease in the epidemiological setting. In this opinion, we describe the analytic complexity and challenges in identifying mixtures associated with phenotype and disease. Existing and emerging machine-learning methods and data analytic approaches (e.g., "environment-wide association studies" [EWASs]), as well as large cohorts may enhance possibilities to identify mixtures of correlated exposures associated with phenotypes; however, the analytic complexity of identifying mixtures is immense. If the exposome concept is realized, new analytical methods and large sample sizes will be required to ascertain how mixtures are associated with disease. The author recommends documenting prevalent correlated exposures and replicated main effects prior to identifying mixtures.

CXCR6, a newly defined biomarker of tissue-specific stem cell asymmetric self-renewal, identifies more aggressive human melanoma cancer stem cells.

PubMed

Taghizadeh, Rouzbeh; Noh, Minsoo; Huh, Yang Hoon; Ciusani, Emilio; Sigalotti, Luca; Maio, Michele; Arosio, Beatrice; Nicotra, Maria R; Natali, PierGiorgio; Sherley, James L; La Porta, Caterina A M

2010-12-22

A fundamental problem in cancer research is identifying the cell type that is capable of sustaining neoplastic growth and its origin from normal tissue cells. Recent investigations of a variety of tumor types have shown that phenotypically identifiable and isolable subfractions of cells possess the tumor-forming ability. In the present paper, using two lineage-related human melanoma cell lines, primary melanoma line IGR39 and its metastatic derivative line IGR37, two main observations are reported. The first one is the first phenotypic evidence to support the origin of melanoma cancer stem cells (CSCs) from mutated tissue-specific stem cells; and the second one is the identification of a more aggressive subpopulation of CSCs in melanoma that are CXCR6+. We defined CXCR6 as a new biomarker for tissue-specific stem cell asymmetric self-renewal. Thus, the relationship between melanoma formation and ABCG2 and CXCR6 expression was investigated. Consistent with their non-metastatic character, unsorted IGR39 cells formed significantly smaller tumors than unsorted IGR37 cells. In addition, ABCG2+ cells produced tumors that had a 2-fold greater mass than tumors produced by unsorted cells or ABCG2- cells. CXCR6+ cells produced more aggressive tumors. CXCR6 identifies a more discrete subpopulation of cultured human melanoma cells with a more aggressive MCSC phenotype than cells selected on the basis of the ABCG2+ phenotype alone. The association of a more aggressive tumor phenotype with asymmetric self-renewal phenotype reveals a previously unrecognized aspect of tumor cell physiology. Namely, the retention of some tissue-specific stem cell attributes, like the ability to asymmetrically self-renew, impacts the natural history of human tumor development. Knowledge of this new aspect of tumor development and progression may provide new targets for cancer prevention and treatment.

Phenotypes of Recessive Pediatric Cataract in a Cohort of Children with Identified Homozygous Gene Mutations (An American Ophthalmological Society Thesis)

PubMed Central

Khan, Arif O.; Aldahmesh, Mohammed A.; Alkuraya, Fowzan S.

2015-01-01

Purpose: To assess for phenotype-genotype correlations in families with recessive pediatric cataract and identified gene mutations. Methods: Retrospective review (2004 through 2013) of 26 Saudi Arabian apparently nonsyndromic pediatric cataract families referred to one of the authors (A.O.K.) and for which recessive gene mutations were identified. Results: Fifteen different homozygous recessive gene mutations were identified in the 26 consanguineous families; two genes and five families are novel to this study. Ten families had a founder CRYBB1 deletion (all with bilateral central pulverulent cataract), two had the same missense mutation in CRYAB (both with bilateral juvenile cataract with marked variable expressivity), and two had different mutations in FYCO1 (both with bilateral posterior capsular abnormality). The remaining 12 families each had mutations in 12 different genes (CRYAA, CRYBA1, AKR1E2, AGK, BFSP2, CYP27A1, CYP51A1, EPHA2, GCNT2, LONP1, RNLS, WDR87) with unique phenotypes noted for CYP27A1 (bilateral juvenile fleck with anterior and/or posterior capsular cataract and later cerebrotendinous xanthomatosis), EPHA2 (bilateral anterior persistent fetal vasculature), and BFSP2 (bilateral flecklike with cloudy cortex). Potential carrier signs were documented for several families. Conclusions: In this recessive pediatric cataract case series most identified genes are noncrystallin. Recessive pediatric cataract phenotypes are generally nonspecific, but some notable phenotypes are distinct and associated with specific gene mutations. Marked variable expressivity can occur from a recessive missense CRYAB mutation. Genetic analysis of apparently isolated pediatric cataract can sometimes uncover mutations in a syndromic gene. Some gene mutations seem to be associated with apparent heterozygous carrier signs. PMID:26622071

Emerging molecular phenotypes of asthma

PubMed Central

Ray, Anuradha; Oriss, Timothy B.

2014-01-01

Although asthma has long been considered a heterogeneous disease, attempts to define subgroups of asthma have been limited. In recent years, both clinical and statistical approaches have been utilized to better merge clinical characteristics, biology, and genetics. These combined characteristics have been used to define phenotypes of asthma, the observable characteristics of a patient determined by the interaction of genes and environment. Identification of consistent clinical phenotypes has now been reported across studies. Now the addition of various 'omics and identification of specific molecular pathways have moved the concept of clinical phenotypes toward the concept of molecular phenotypes. The importance of these molecular phenotypes is being confirmed through the integration of molecularly targeted biological therapies. Thus the global term asthma is poised to become obsolete, being replaced by terms that more specifically identify the pathology associated with the disease. PMID:25326577

[Phenotype-based primary screening for drugs promoting neuronal subtype differentiation in embryonic stem cells with light microscope].

PubMed

Gao, Yi-ning; Wang, Dan-ying; Pan, Zong-fu; Mei, Yu-qin; Wang, Zhi-qiang; Zhu, Dan-yan; Lou, Yi-jia

2012-07-01

To set up a platform for phenotype-based primary screening of drug candidates promoting neuronal subtype differentiation in embryonic stem cells (ES) with light microscope. Hanging drop culture 4-/4+ method was employed to harvest the cells around embryoid body (EB) at differentiation endpoint. Morphological evaluation for neuron-like cells was performed with light microscope. Axons for more than three times of the length of the cell body were considered as neuron-like cells. The compound(s) that promote neuron-like cells was further evaluated. Icariin (ICA, 10(-6)mol/L) and Isobavachin (IBA, 10(-7)mol/L) were selected to screen the differentiation-promoting activity on ES cells. Immunofluorescence staining with specific antibodies (ChAT, GABA) was used to evaluate the neuron subtypes. The cells treated with IBA showed neuron-like phenotype, but the cells treated with ICA did not exhibit the morphological changes. ES cells treated with IBA was further confirmed to be cholinergic and GABAergic neurons. Phenotypic screening with light microscope for molecules promoting neuronal differentiation is an effective method with advantages of less labor and material consuming and time saving, and false-positive results derived from immunofluorescence can be avoided. The method confirms that IBA is able to facilitate ES cells differentiating into neuronal cells, including cholinergic neurons and GABAergic neurons.

Elucidating the genotype-phenotype relationships and network perturbations of human shared and specific disease genes from an evolutionary perspective.

PubMed

Begum, Tina; Ghosh, Tapash Chandra

2014-10-05

To date, numerous studies have been attempted to determine the extent of variation in evolutionary rates between human disease and nondisease (ND) genes. In our present study, we have considered human autosomal monogenic (Mendelian) disease genes, which were classified into two groups according to the number of phenotypic defects, that is, specific disease (SPD) gene (one gene: one defect) and shared disease (SHD) gene (one gene: multiple defects). Here, we have compared the evolutionary rates of these two groups of genes, that is, SPD genes and SHD genes with respect to ND genes. We observed that the average evolutionary rates are slow in SHD group, intermediate in SPD group, and fast in ND group. Group-to-group evolutionary rate differences remain statistically significant regardless of their gene expression levels and number of defects. We demonstrated that disease genes are under strong selective constraint if they emerge through edgetic perturbation or drug-induced perturbation of the interactome network, show tissue-restricted expression, and are involved in transmembrane transport. Among all the factors, our regression analyses interestingly suggest the independent effects of 1) drug-induced perturbation and 2) the interaction term of expression breadth and transmembrane transport on protein evolutionary rates. We reasoned that the drug-induced network disruption is a combination of several edgetic perturbations and, thus, has more severe effect on gene phenotypes. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Micropatterned mammalian cells exhibit phenotype-specific left-right asymmetry.

PubMed

Wan, Leo Q; Ronaldson, Kacey; Park, Miri; Taylor, Grace; Zhang, Yue; Gimble, Jeffrey M; Vunjak-Novakovic, Gordana

2011-07-26

Left-right (LR) asymmetry (handedness, chirality) is a well-conserved biological property of critical importance to normal development. Changes in orientation of the LR axis due to genetic or environmental factors can lead to malformations and disease. While the LR asymmetry of organs and whole organisms has been extensively studied, little is known about the LR asymmetry at cellular and multicellular levels. Here we show that the cultivation of cell populations on micropatterns with defined boundaries reveals intrinsic cell chirality that can be readily determined by image analysis of cell alignment and directional motion. By patterning 11 different types of cells on ring-shaped micropatterns of various sizes, we found that each cell type exhibited definite LR asymmetry (p value down to 10(-185)) that was different between normal and cancer cells of the same type, and not dependent on surface chemistry, protein coating, or the orientation of the gravitational field. Interestingly, drugs interfering with actin but not microtubule function reversed the LR asymmetry in some cell types. Our results show that micropatterned cell populations exhibit phenotype-specific LR asymmetry that is dependent on the functionality of the actin cytoskeleton. We propose that micropatterning could potentially be used as an effective in vitro tool to study the initiation of LR asymmetry in cell populations, to diagnose disease, and to study factors involved with birth defects in laterality.

Surprisal analysis of Glioblastoma Multiform (GBM) microRNA dynamics unveils tumor specific phenotype.

PubMed

Zadran, Sohila; Remacle, Francoise; Levine, Raphael

2014-01-01

Gliomablastoma multiform (GBM) is the most fatal form of all brain cancers in humans. Currently there are limited diagnostic tools for GBM detection. Here, we applied surprisal analysis, a theory grounded in thermodynamics, to unveil how biomolecule energetics, specifically a redistribution of free energy amongst microRNAs (miRNAs), results in a system deviating from a non-cancer state to the GBM cancer -specific phenotypic state. Utilizing global miRNA microarray expression data of normal and GBM patients tumors, surprisal analysis characterizes a miRNA system response capable of distinguishing GBM samples from normal tissue biopsy samples. We indicate that the miRNAs contributing to this system behavior is a disease phenotypic state specific to GBM and is therefore a unique GBM-specific thermodynamic signature. MiRNAs implicated in the regulation of stochastic signaling processes crucial in the hallmarks of human cancer, dominate this GBM-cancer phenotypic state. With this theory, we were able to distinguish with high fidelity GBM patients solely by monitoring the dynamics of miRNAs present in patients' biopsy samples. We anticipate that the GBM-specific thermodynamic signature will provide a critical translational tool in better characterizing cancer types and in the development of future therapeutics for GBM.

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the contribution of genes and environments to disease expression. To determine the minimum number of sets of features required to characterize subjects with asthma which will be useful in identifying important genetic and environmental contributors. Methods Probands aged 7-35 years with physician diagnosed asthma and symptomatic siblings were identified in 1022 nuclear families from 11 centres in six countries forming the Genetics of Asthma International Network. Factor analysis was used to identify distinct phenotypes from questionnaire, clinical, and laboratory data, including baseline pulmonary function, allergen skin prick test (SPT). Five distinct factors were identified:(1) baseline pulmonary function measures [forced expiratory volume in 1 s (FEV(1)) and forced vital capacity (FVC)], (2) specific allergen sensitization by SPT, (3) self-reported allergies, (4) symptoms characteristic of rhinitis and (5) symptoms characteristic of asthma. Replication in symptomatic siblings was consistent with shared genetic and/or environmental effects, and was robust across age groups, gender, and centres. Cronbach's alpha ranged from 0.719 to 0.983 suggesting acceptable internal scale consistencies. Derived scales were correlated with serum IgE, methacholine PC(20), age and asthma severity (interrupted sleep). IgE correlated with all three atopy-related factors, the strongest with the SPT factor whereas severity only correlated with baseline lung function, and with symptoms characteristic of rhinitis and of asthma. In children and adolescents with established asthma, five distinct sets of correlated patient characteristics appear to represent important aspects of the disease. Factor scores as

A systematic approach to identify therapeutic effects of natural products based on human metabolite information.

PubMed

Noh, Kyungrin; Yoo, Sunyong; Lee, Doheon

2018-06-13

Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.

Identifying injection drug use and estimating population size of people who inject drugs using healthcare administrative datasets.

PubMed

Janjua, Naveed Zafar; Islam, Nazrul; Kuo, Margot; Yu, Amanda; Wong, Stanley; Butt, Zahid A; Gilbert, Mark; Buxton, Jane; Chapinal, Nuria; Samji, Hasina; Chong, Mei; Alvarez, Maria; Wong, Jason; Tyndall, Mark W; Krajden, Mel

2018-05-01

Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data. The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values. Sensitivity was highest (90-94%), and specificity was lowest (42-73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57-60%) and higher specificity (90-92%). An optimal sensitivity and specificity combination was found with two medical visits or a single hospitalization for injectable drugs with (83%/82%) and without OST (78%/83%), respectively. Based on algorithms that included two medical visits, a single hospitalization or OST records, there were 41,358 (1.2% of 11-65 years individuals in BC) recent PWID in BC based on health encounters during 3- year period (2013-2015). Algorithms for identifying PWID using diagnostic codes in linked administrative

Individualized Hydrocodone Therapy Based on Phenotype, Pharmacogenetics, and Pharmacokinetic Dosing.

PubMed

Linares, Oscar A; Fudin, Jeffrey; Daly, Annemarie L; Boston, Raymond C

2015-12-01

(1) To quantify hydrocodone (HC) and hydromorphone (HM) metabolite pharmacokinetics with pharmacogenetics in CYP2D6 ultra-rapid metabolizer (UM), extensive metabolizer (EM), and poor metabolizer (PM) metabolizer phenotypes. (2) To develop an HC phenotype-specific dosing strategy for HC that accounts for HM production using clinical pharmacokinetics integrated with pharmacogenetics for patient safety. In silico clinical trial simulation. Healthy white men and women without comorbidities or history of opioid, or any other drug or nutraceutical use, age 26.3±5.7 years (mean±SD; range, 19 to 36 y) and weight 71.9±16.8 kg (range, 50 to 108 kg). CYP2D6 phenotype-specific HC clinical pharmacokinetic parameter estimates and phenotype-specific percentages of HM formed from HC. PMs had lower indices of HC disposition compared with UMs and EMs. Clearance was reduced by nearly 60% and the t1/2 was increased by about 68% compared with EMs. The canonical order for HC clearance was UM>EM>PM. HC elimination mainly by the liver, represented by ke, was reduced about 70% in PM. However, HC's apparent Vd was not significantly different among UMs, EMs, and PM. The canonical order of predicted plasma HM concentrations was UM>EM>PM. For each of the CYP2D6 phenotypes, the mean predicted HM levels were within HM's therapeutic range, which indicates HC has significant phenotype-dependent pro-drug effects. Our results demonstrate that pharmacogenetics afford clinicians an opportunity to individualize HC dosing, while adding enhanced opportunity to account for its conversion to HM in the body.

An integrated chemical biology approach identifies specific vulnerability of Ewing's sarcoma to combined inhibition of Aurora kinases A and B.

PubMed

Winter, Georg E; Rix, Uwe; Lissat, Andrej; Stukalov, Alexey; Müllner, Markus K; Bennett, Keiryn L; Colinge, Jacques; Nijman, Sebastian M; Kubicek, Stefan; Kovar, Heinrich; Kontny, Udo; Superti-Furga, Giulio

2011-10-01

Ewing's sarcoma is a pediatric cancer of the bone that is characterized by the expression of the chimeric transcription factor EWS-FLI1 that confers a highly malignant phenotype and results from the chromosomal translocation t(11;22)(q24;q12). Poor overall survival and pronounced long-term side effects associated with traditional chemotherapy necessitate the development of novel, targeted, therapeutic strategies. We therefore conducted a focused viability screen with 200 small molecule kinase inhibitors in 2 different Ewing's sarcoma cell lines. This resulted in the identification of several potential molecular intervention points. Most notably, tozasertib (VX-680, MK-0457) displayed unique nanomolar efficacy, which extended to other cell lines, but was specific for Ewing's sarcoma. Furthermore, tozasertib showed strong synergies with the chemotherapeutic drugs etoposide and doxorubicin, the current standard agents for Ewing's sarcoma. To identify the relevant targets underlying the specific vulnerability toward tozasertib, we determined its cellular target profile by chemical proteomics. We identified 20 known and unknown serine/threonine and tyrosine protein kinase targets. Additional target deconvolution and functional validation by RNAi showed simultaneous inhibition of Aurora kinases A and B to be responsible for the observed tozasertib sensitivity, thereby revealing a new mechanism for targeting Ewing's sarcoma. We further corroborated our cellular observations with xenograft mouse models. In summary, the multilayered chemical biology approach presented here identified a specific vulnerability of Ewing's sarcoma to concomitant inhibition of Aurora kinases A and B by tozasertib and danusertib, which has the potential to become a new therapeutic option.

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Differential epigenetic reprogramming in response to specific endocrine therapies promotes cholesterol biosynthesis and cellular invasion

PubMed Central

Nguyen, Van T. M.; Barozzi, Iros; Faronato, Monica; Lombardo, Ylenia; Steel, Jennifer H.; Patel, Naina; Darbre, Philippa; Castellano, Leandro; Győrffy, Balázs; Woodley, Laura; Meira, Alba; Patten, Darren K.; Vircillo, Valentina; Periyasamy, Manikandan; Ali, Simak; Frige, Gianmaria; Minucci, Saverio; Coombes, R. Charles; Magnani, Luca

2015-01-01

Endocrine therapies target the activation of the oestrogen receptor alpha (ERα) via distinct mechanisms, but it is not clear whether breast cancer cells can adapt to treatment using drug-specific mechanisms. Here we demonstrate that resistance emerges via drug-specific epigenetic reprogramming. Resistant cells display a spectrum of phenotypical changes with invasive phenotypes evolving in lines resistant to the aromatase inhibitor (AI). Orthogonal genomics analysis of reprogrammed regulatory regions identifies individual drug-induced epigenetic states involving large topologically associating domains (TADs) and the activation of super-enhancers. AI-resistant cells activate endogenous cholesterol biosynthesis (CB) through stable epigenetic activation in vitro and in vivo. Mechanistically, CB sparks the constitutive activation of oestrogen receptors alpha (ERα) in AI-resistant cells, partly via the biosynthesis of 27-hydroxycholesterol. By targeting CB using statins, ERα binding is reduced and cell invasion is prevented. Epigenomic-led stratification can predict resistance to AI in a subset of ERα-positive patients. PMID:26610607

Inferring protein domains associated with drug side effects based on drug-target interaction network

PubMed Central

2013-01-01

Background Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. PMID:24565527

Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

PubMed Central

Xu, Rong; Li, Li; Wang, QuanQiu

2013-01-01

Motivation: Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease–phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease–manifestation (D-M) pairs (one specific type of disease–phenotype relationship) from the wide body of published biomedical literature. Data and Methods: Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M–specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. Results: In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. Conclusions: The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. Availability: http://nlp.case.edu/public/data/DMPatternUMLS/ Contact: rxx@case.edu PMID:23828786

Identifying genetic loci affecting antidepressant drug response in depression using drug–gene interaction models

PubMed Central

Noordam, Raymond; Avery, Christy L; Visser, Loes E; Stricker, Bruno H

2016-01-01

Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., ‘treated-only design’, statistical power) and we will discuss how specifically drug–gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression. PMID:27248517

IgE-Api m 4 Is Useful for Identifying a Particular Phenotype of Bee Venom Allergy.

PubMed

Ruiz, B; Serrano, P; Moreno, C

Different clinical behaviors have been identified in patients allergic to bee venom. Compound-resolved diagnosis could be an appropriate tool for investigating these differences. The aims of this study were to analyze whether specific IgE to Api m 4 (sIgE-Api m 4) can identify a particular kind of bee venom allergy and to describe response to bee venom immunotherapy (bVIT). Prospective study of 31 patients allergic to bee venom who were assigned to phenotype group A (sIgE-Api m 4 <0.98 kU/L), treated with native aqueous (NA) extract, or phenotype group B (sIgE-Api m 4 ≥0.98 kU/L), treated with purified aqueous (PA) extract. Sex, age, cardiovascular risk, severity of preceding sting reaction, exposure to beekeeping, and immunological data (intradermal test, sIgE/sIgG4-Apis-nApi m 1, and sIgE-rApi m 2-Api m 4 were analyzed. Systemic reactions (SRs) during bVIT build-up were analyzed. Immunological and sting challenge outcomes were evaluated in each group after 1 and 2 years of bVIT. Phenotype B patients had more severe reactions (P=.049) and higher skin sensitivity (P=.011), baseline sIgE-Apis (P=.0004), sIgE-nApi m 1 (P=.0004), and sIgG4-Apis (P=.027) than phenotype A patients. Furthermore, 41% of patients in group B experienced SRs during the build-up phase with NA; the sting challenge success rate in this group was 82%. There were no significant reductions in serial intradermal test results, but an intense reduction in sIgE-nApi m 1 (P=.013) and sIgE-Api m 4 (P=.004) was observed after the first year of bVIT. Use of IgE-Api m 4 as the only discrimination criterion demonstrated differences in bee venom allergy. Further investigation with larger populations is necessary.

Phenotypic and genotypic characterisation of drug-resistant Plasmodium vivax

PubMed Central

Price, Ric N.; Auburn, Sarah; Marfurt, Jutta; Cheng, Qin

2015-01-01

In this review we present recent developments in the analysis of Plasmodium vivax clinical trials and ex vivo drug-susceptibility assays, as well approaches currently being used to identify molecular markers of drug resistance. Clinical trials incorporating the measurement of in vivo drug concentrations and parasite clearance times are needed to detect early signs of resistance. Analysis of P. vivax growth dynamics ex vivo have defined the criteria for acceptable assay thresholds for drug susceptibility testing, and their subsequent interpretation. Genotyping and next-generation sequencing studies in P. vivax field isolates are set to transform our understanding of the molecular mechanisms of drug resistance. PMID:23044287

Identifying Genetic Sources of Phenotypic Heterogeneity in Orofacial Clefts by Targeted Sequencing.

PubMed

Carlson, Jenna C; Taub, Margaret A; Feingold, Eleanor; Beaty, Terri H; Murray, Jeffrey C; Marazita, Mary L; Leslie, Elizabeth J

2017-07-17

Orofacial clefts (OFCs), including nonsyndromic cleft lip with or without cleft palate (NSCL/P), are common birth defects. NSCL/P is highly heterogeneous with multiple phenotypic presentations. Two common subtypes of NSCL/P are cleft lip (CL) and cleft lip with cleft palate (CLP) which have different population prevalence. Similarly, NSCL/P can be divided into bilateral and unilateral clefts, with unilateral being the most common. Individuals with unilateral NSCL/P are more likely to be affected on the left side of the upper lip, but right side affection also occurs. Moreover, NSCL/P is twice as common in males as in females. The goal of this study is to discover genetic variants that have different effects in case subgroups. We conducted both common variant and rare variant analyses in 1034 individuals of Asian ancestry with NSCL/P, examining four sources of heterogeneity within CL/P: cleft type, sex, laterality, and side. We identified several regions associated with subtype differentiation: cleft type differences in 8q24 (p = 1.00 × 10 -4 ), laterality differences in IRF6, a gene previously implicated with wound healing (p = 2.166 × 10 -4 ), sex differences and side of unilateral CL differences in FGFR2 (p = 3.00 × 10 -4 ; p = 6.00 × 10 -4 ), and sex differences in VAX1 (p < 1.00 × 10 -4 ) among others. Many of the regions associated with phenotypic modification were either adjacent to or overlapping functional elements based on ENCODE chromatin marks and published craniofacial enhancers. We have identified multiple common and rare variants as potential phenotypic modifiers of NSCL/P, and suggest plausible elements responsible for phenotypic heterogeneity, further elucidating the complex genetic architecture of OFCs. Birth Defects Research 109:1030-1038, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The digital revolution in phenotyping

PubMed Central

Oellrich, Anika; Collier, Nigel; Groza, Tudor; Rebholz-Schuhmann, Dietrich; Shah, Nigam; Bodenreider, Olivier; Boland, Mary Regina; Georgiev, Ivo; Liu, Hongfang; Livingston, Kevin; Luna, Augustin; Mallon, Ann-Marie; Manda, Prashanti; Robinson, Peter N.; Rustici, Gabriella; Simon, Michelle; Wang, Liqin; Winnenburg, Rainer; Dumontier, Michel

2016-01-01

Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental findings into clinical applications and thereby support ‘bench to bedside’ efforts. However, to build this translational bridge, a common and universal understanding of phenotypes is required that goes beyond domain-specific definitions. To achieve this ambitious goal, a digital revolution is ongoing that enables the encoding of data in computer-readable formats and the data storage in specialized repositories, ready for integration, enabling translational research. While phenome research is an ongoing endeavor, the true potential hidden in the currently available data still needs to be unlocked, offering exciting opportunities for the forthcoming years. Here, we provide insights into the state-of-the-art in digital phenotyping, by means of representing, acquiring and analyzing phenotype data. In addition, we provide visions of this field for future research work that could enable better applications of phenotype data. PMID:26420780

Analysis of National Drug Code Identifiers in Ambulatory E-Prescribing.

PubMed

Dhavle, Ajit A; Ward-Charlerie, Stacy; Rupp, Michael T; Amin, Vishal P; Ruiz, Joshua

2015-11-01

Communication of an accurate and interpretable drug identifier between prescriber and pharmacist is critically important for realizing the potential benefits of electronic prescribing (e-prescribing) while minimizing its risk. The National Drug Code (NDC) is the most commonly used codified drug identifier in ambulatory care e-prescribing, but concerns have been raised regarding its use for this purpose.  To (a) assess the frequency of NDC identifier transmission in ambulatory e-prescribing; (b) characterize the type of NDC identifier transmitted (representative, repackaged, obsolete, private label, and unit dose); and (c) assess the level of agreement between drug descriptions corresponding to NDC identifiers in electronic prescriptions (e-prescriptions) and the free-text drug descriptions that were entered by prescribers.  We analyzed a sample of 49,997 e-prescriptions that were transmitted by ambulatory care prescribers to outlets of a national retail drugstore chain during a single day in April 2014. The First Databank MedKnowledge drug database was used as the primary reference data base to assess the frequency and types of NDC numbers in the e-prescription messages. The FDA's Comprehensive NDC Standard Product Labeling Data Elements File and the National Library of Medicine's RxNorm data file were used as secondary and tertiary references, respectively, to identify NDC numbers that could not be located in the primary reference file. Three experienced reviewers compared the free-text drug description that had been entered by the prescriber with the drug description corresponding to the NDC number from 1 of the 3 reference database files to identify discrepancies. Two licensed pharmacists with residency training and ambulatory care experience served as final adjudicators. A total of 42,602 e-prescriptions contained a value in the NDC field, of which 42,335 (84.71%) were found in 1 of the 3 study reference databases and were thus considered to be valid NDC

Network pharmacology: reigning in drug attrition?

PubMed

Alian, Osama M; Shah, Minjel; Mohammad, Momin; Mohammad, Ramzi M

2013-06-01

In the process of drug development, there has been an exceptionally high attrition rate in oncological compounds entering late phases of testing. This has seen a concurrent reduction in approved NCEs (new chemical entities) reaching patients. Network pharmacology has become a valuable tool in understanding the fine details of drug-target interactions as well as painting a more practical picture of phenotype relationships to patients and drugs. By utilizing all the tools achieved through molecular medicine and combining it with high throughput data analysis, interactions and mechanisms can be elucidated and treatments reasonably tailored to patients expressing specific phenotypes (or genotypes) of disease, essentially reigning in the phenomenon of drug attrition.

A screen to identify drug resistant variants to target-directed anti-cancer agents

PubMed Central

Azam, Mohammad; Raz, Tal; Nardi, Valentina; Opitz, Sarah L.

2003-01-01

The discovery of oncogenes and signal transduction pathways important for mitogenesis has triggered the development of target-specific small molecule anti-cancer compounds. As exemplified by imatinib (Gleevec), a specific inhibitor of the Chronic Myeloid Leukemia (CML)-associated Bcr-Abl kinase, these agents promise impressive activity in clinical trials, with low levels of clinical toxicity. However, such therapy is susceptible to the emergence of drug resistance due to amino acid substitutions in the target protein. Defining the spectrum of such mutations is important for patient monitoring and the design of next-generation inhibitors. Using imatinib and BCR/ABL as a paradigm for a drug-target pair, we recently reported a retroviral vector-based screening strategy to identify the spectrum of resistance-conferring mutations. Here we provide a detailed methodology for the screen, which can be generally applied to any drug-target pair. PMID:14615817

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

A High-Throughput (HTS) Assay for Enzyme Reaction Phenotyping in Human Recombinant P450 Enzymes Using LC-MS/MS.

PubMed

Li, Xiaofeng; Suhar, Tom; Glass, Lateca; Rajaraman, Ganesh

2014-03-03

Enzyme reaction phenotyping is employed extensively during the early stages of drug discovery to identify the enzymes responsible for the metabolism of new chemical entities (NCEs). Early identification of metabolic pathways facilitates prediction of potential drug-drug interactions associated with enzyme polymorphism, induction, or inhibition, and aids in the design of clinical trials. Incubation of NCEs with human recombinant enzymes is a popular method for such work because of the specificity, simplicity, and high-throughput nature of this approach for phenotyping studies. The availability of a relative abundance factor and calculated intersystem extrapolation factor for the expressed recombinant enzymes facilitates easy scaling of in vitro data, enabling in vitro-in vivo extrapolation. Described in this unit is a high-throughput screen for identifying enzymes involved in the metabolism of NCEs. Emphasis is placed on the analysis of the human recombinant enzymes CYP1A2, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2B6, and CYP3A4, including the calculation of the intrinsic clearance for each. Copyright © 2014 John Wiley & Sons, Inc. All rights reserved.

PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes.

PubMed

Soto-Feliciano, Yadira M; Bartlebaugh, Jordan M E; Liu, Yunpeng; Sánchez-Rivera, Francisco J; Bhutkar, Arjun; Weintraub, Abraham S; Buenrostro, Jason D; Cheng, Christine S; Regev, Aviv; Jacks, Tyler E; Young, Richard A; Hemann, Michael T

2017-05-15

Developmental and lineage plasticity have been observed in numerous malignancies and have been correlated with tumor progression and drug resistance. However, little is known about the molecular mechanisms that enable such plasticity to occur. Here, we describe the function of the plant homeodomain finger protein 6 (PHF6) in leukemia and define its role in regulating chromatin accessibility to lineage-specific transcription factors. We show that loss of Phf6 in B-cell leukemia results in systematic changes in gene expression via alteration of the chromatin landscape at the transcriptional start sites of B-cell- and T-cell-specific factors. Additionally, Phf6 KO cells show significant down-regulation of genes involved in the development and function of normal B cells, show up-regulation of genes involved in T-cell signaling, and give rise to mixed-lineage lymphoma in vivo. Engagement of divergent transcriptional programs results in phenotypic plasticity that leads to altered disease presentation in vivo, tolerance of aberrant oncogenic signaling, and differential sensitivity to frontline and targeted therapies. These findings suggest that active maintenance of a precise chromatin landscape is essential for sustaining proper leukemia cell identity and that loss of a single factor (PHF6) can cause focal changes in chromatin accessibility and nucleosome positioning that render cells susceptible to lineage transition. © 2017 Soto-Feliciano et al.; Published by Cold Spring Harbor Laboratory Press.

The Culturable Soil Antibiotic Resistome: A Community of Multi-Drug Resistant Bacteria

PubMed Central

Walsh, Fiona; Duffy, Brion

2013-01-01

Understanding the soil bacterial resistome is essential to understanding the evolution and development of antibiotic resistance, and its spread between species and biomes. We have identified and characterized multi-drug resistance (MDR) mechanisms in the culturable soil antibiotic resistome and linked the resistance profiles to bacterial species. We isolated 412 antibiotic resistant bacteria from agricultural, urban and pristine soils. All isolates were multi-drug resistant, of which greater than 80% were resistant to 16–23 antibiotics, comprising almost all classes of antibiotic. The mobile resistance genes investigated, (ESBL, bla NDM-1, and plasmid mediated quinolone resistance (PMQR) resistance genes) were not responsible for the respective resistance phenotypes nor were they present in the extracted soil DNA. Efflux was demonstrated to play an important role in MDR and many resistance phenotypes. Clinically relevant Burkholderia species are intrinsically resistant to ciprofloxacin but the soil Burkholderia species were not intrinsically resistant to ciprofloxacin. Using a phenotypic enzyme assay we identified the antibiotic specific inactivation of trimethoprim in 21 bacteria from different soils. The results of this study identified the importance of the efflux mechanism in the soil resistome and variations between the intrinsic resistance profiles of clinical and soil bacteria of the same family. PMID:23776501

The culturable soil antibiotic resistome: a community of multi-drug resistant bacteria.

PubMed

Walsh, Fiona; Duffy, Brion

2013-01-01

Understanding the soil bacterial resistome is essential to understanding the evolution and development of antibiotic resistance, and its spread between species and biomes. We have identified and characterized multi-drug resistance (MDR) mechanisms in the culturable soil antibiotic resistome and linked the resistance profiles to bacterial species. We isolated 412 antibiotic resistant bacteria from agricultural, urban and pristine soils. All isolates were multi-drug resistant, of which greater than 80% were resistant to 16-23 antibiotics, comprising almost all classes of antibiotic. The mobile resistance genes investigated, (ESBL, bla NDM-1, and plasmid mediated quinolone resistance (PMQR) resistance genes) were not responsible for the respective resistance phenotypes nor were they present in the extracted soil DNA. Efflux was demonstrated to play an important role in MDR and many resistance phenotypes. Clinically relevant Burkholderia species are intrinsically resistant to ciprofloxacin but the soil Burkholderia species were not intrinsically resistant to ciprofloxacin. Using a phenotypic enzyme assay we identified the antibiotic specific inactivation of trimethoprim in 21 bacteria from different soils. The results of this study identified the importance of the efflux mechanism in the soil resistome and variations between the intrinsic resistance profiles of clinical and soil bacteria of the same family.

Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations

PubMed Central

Edwards, Robert R.; Dworkin, Robert H.; Turk, Dennis C.; Angst, Martin S.; Dionne, Raymond; Freeman, Roy; Hansson, Per; Haroutounian, Simon; Arendt-Nielsen, Lars; Attal, Nadine; Baron, Ralf; Brell, Joanna; Bujanover, Shay; Burke, Laurie B.; Carr, Daniel; Chappell, Amy S.; Cowan, Penney; Etropolski, Mila; Fillingim, Roger B.; Gewandter, Jennifer S.; Katz, Nathaniel P.; Kopecky, Ernest A.; Markman, John D.; Nomikos, George; Porter, Linda; Rappaport, Bob A.; Rice, Andrew S.C.; Scavone, Joseph M.; Scholz, Joachim; Simon, Lee S.; Smith, Shannon M.; Tobias, Jeffrey; Tockarshewsky, Tina; Veasley, Christine; Versavel, Mark; Wasan, Ajay D.; Wen, Warren; Yarnitsky, David

2018-01-01

There is tremendous inter-patient variability in the response to analgesic therapy (even for efficacious treatments), which can be the source of great frustration in clinical practice. This has led to calls for “precision medicine”, or personalized pain therapeutics (i.e., empirically-based algorithms that determine the optimal treatments, or treatment combinations, for individual patients) that would presumably improve both the clinical care of patients with pain, and the success rates for putative analgesic drugs in Phase 2 and 3 clinical trials. However, before implementing this approach, the characteristics of individual patients or subgroups of patients that increase or decrease the response to a specific treatment need to be identified. The challenge is to identify the measurable phenotypic characteristics of patients that are most predictive of individual variation in analgesic treatment outcomes, and the measurement tools that are best suited to evaluate these characteristics. In this article, we present evidence on the most promising of these phenotypic characteristics for use in future research, including psychosocial factors, symptom characteristics, sleep patterns, responses to noxious stimulation, endogenous pain-modulatory processes, and response to pharmacologic challenge. We provide evidence-based recommendations for core phenotyping domains and recommend measures of each domain. PMID:27152687

Dose-specific adverse drug reaction identification in electronic patient records: temporal data mining in an inpatient psychiatric population.

PubMed

Eriksson, Robert; Werge, Thomas; Jensen, Lars Juhl; Brunak, Søren

2014-04-01

Data collected for medical, filing and administrative purposes in electronic patient records (EPRs) represent a rich source of individualised clinical data, which has great potential for improved detection of patients experiencing adverse drug reactions (ADRs), across all approved drugs and across all indication areas. The aim of this study was to take advantage of techniques for temporal data mining of EPRs in order to detect ADRs in a patient- and dose-specific manner. We used a psychiatric hospital's EPR system to investigate undesired drug effects. Within one workflow the method identified patient-specific adverse events (AEs) and links these to specific drugs and dosages in a temporal manner, based on integration of text mining results and structured data. The structured data contained precise information on drug identity, dosage and strength. When applying the method to the 3,394 patients in the cohort, we identified AEs linked with a drug in 2,402 patients (70.8 %). Of the 43,528 patient-specific drug substances prescribed, 14,736 (33.9 %) were linked with AEs. From these links we identified multiple ADRs (p < 0.05) and found them to occur at similar frequencies, as stated by the manufacturer and in the literature. We showed that drugs displaying similar ADR profiles share targets, and we compared submitted spontaneous AE reports with our findings. For nine of the ten most prescribed antipsychotics in the patient population, larger doses were prescribed to sedated patients than non-sedated patients; five antipsychotics [corrected] exhibited a significant difference (p<0.05). Finally, we present two cases (p < 0.05) identified by the workflow. The method identified the potentially fatal AE QT prolongation caused by methadone, and a non-described likely ADR between levomepromazine and nightmares found among the hundreds of identified novel links between drugs and AEs (p < 0.05). The developed method can be used to extract dose-dependent ADR information from

Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets.

PubMed

Miller, Martin L; Molinelli, Evan J; Nair, Jayasree S; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M; Singer, Samuel; Schwartz, Gary K; Sander, Chris

2013-09-24

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depends on the activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies.

Tissue-Specific Profiling Reveals Transcriptome Alterations in Arabidopsis Mutants Lacking Morphological Phenotypes[C][W

PubMed Central

Simon, Marissa; Bruex, Angela; Kainkaryam, Raghunandan M.; Zheng, Xiaohua; Huang, Ling; Woolf, Peter J.; Schiefelbein, John

2013-01-01

Traditional genetic analysis relies on mutants with observable phenotypes. Mutants lacking visible abnormalities may nevertheless exhibit molecular differences useful for defining gene function. To examine this, we analyzed tissue-specific transcript profiles from Arabidopsis thaliana transcription factor gene mutants with known roles in root epidermis development, but lacking a single-gene mutant phenotype due to genetic redundancy. We discovered substantial transcriptional changes in each mutant, preferentially affecting root epidermal genes in a manner consistent with the known double mutant effects. Furthermore, comparing transcript profiles of single and double mutants, we observed remarkable variation in the sensitivity of target genes to the loss of one or both paralogous genes, including preferential effects on specific branches of the epidermal gene network, likely reflecting the pathways of paralog subfunctionalization during evolution. In addition, we analyzed the root epidermal transcriptome of the transparent testa glabra2 mutant to clarify its role in the network. These findings provide insight into the molecular basis of genetic redundancy and duplicate gene diversification at the level of a specific gene regulatory network, and they demonstrate the usefulness of tissue-specific transcript profiling to define gene function in mutants lacking informative visible changes in phenotype. PMID:24014549

A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

PubMed Central

2014-01-01

Background Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. Methods 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). Results No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance. Conclusions Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. PMID:23871474

A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.

PubMed

Bramon, Elvira; Pirinen, Matti; Strange, Amy; Lin, Kuang; Freeman, Colin; Bellenguez, Céline; Su, Zhan; Band, Gavin; Pearson, Richard; Vukcevic, Damjan; Langford, Cordelia; Deloukas, Panos; Hunt, Sarah; Gray, Emma; Dronov, Serge; Potter, Simon C; Tashakkori-Ghanbaria, Avazeh; Edkins, Sarah; Bumpstead, Suzannah J; Arranz, Maria J; Bakker, Steven; Bender, Stephan; Bruggeman, Richard; Cahn, Wiepke; Chandler, David; Collier, David A; Crespo-Facorro, Benedicto; Dazzan, Paola; de Haan, Lieuwe; Di Forti, Marta; Dragović, Milan; Giegling, Ina; Hall, Jeremy; Iyegbe, Conrad; Jablensky, Assen; Kahn, René S; Kalaydjieva, Luba; Kravariti, Eugenia; Lawrie, Stephen; Linszen, Don H; Mata, Ignacio; McDonald, Colm; McIntosh, Andrew; Myin-Germeys, Inez; Ophoff, Roel A; Pariante, Carmine M; Paunio, Tiina; Picchioni, Marco; Ripke, Stephan; Rujescu, Dan; Sauer, Heinrich; Shaikh, Madiha; Sussmann, Jessika; Suvisaari, Jaana; Tosato, Sarah; Toulopoulou, Timothea; Van Os, Jim; Walshe, Muriel; Weisbrod, Matthias; Whalley, Heather; Wiersma, Durk; Blackwell, Jenefer M; Brown, Matthew A; Casas, Juan P; Corvin, Aiden; Duncanson, Audrey; Jankowski, Janusz A Z; Markus, Hugh S; Mathew, Christopher G; Palmer, Colin N A; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J; Trembath, Richard C; Wood, Nicholas W; Barroso, Ines; Peltonen, Leena; Lewis, Cathryn M; Murray, Robin M; Donnelly, Peter; Powell, John; Spencer, Chris C A

2014-03-01

Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium's panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10(-14)) and explained approximately 2% of the phenotypic variance. Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka

2013-01-01

Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery

Serum Biochemical Phenotypes in the Domestic Dog

PubMed Central

Chang, Yu-Mei; Hadox, Erin; Szladovits, Balazs; Garden, Oliver A.

2016-01-01

The serum or plasma biochemical profile is essential in the diagnosis and monitoring of systemic disease in veterinary medicine, but current reference intervals typically take no account of breed-specific differences. Breed-specific hematological phenotypes have been documented in the domestic dog, but little has been published on serum biochemical phenotypes in this species. Serum biochemical profiles of dogs in which all measurements fell within the existing reference intervals were retrieved from a large veterinary database. Serum biochemical profiles from 3045 dogs were retrieved, of which 1495 had an accompanying normal glucose concentration. Sixty pure breeds plus a mixed breed control group were represented by at least 10 individuals. All analytes, except for sodium, chloride and glucose, showed variation with age. Total protein, globulin, potassium, chloride, creatinine, cholesterol, total bilirubin, ALT, CK, amylase, and lipase varied between sexes. Neutering status significantly impacted all analytes except albumin, sodium, calcium, urea, and glucose. Principal component analysis of serum biochemical data revealed 36 pure breeds with distinctive phenotypes. Furthermore, comparative analysis identified 23 breeds with significant differences from the mixed breed group in all biochemical analytes except urea and glucose. Eighteen breeds were identified by both principal component and comparative analysis. Tentative reference intervals were generated for breeds with a distinctive phenotype identified by comparative analysis and represented by at least 120 individuals. This is the first large-scale analysis of breed-specific serum biochemical phenotypes in the domestic dog and highlights potential genetic components of biochemical traits in this species. PMID:26919479

SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments.

PubMed

Hall, Barry G

2014-01-01

SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.

High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

PubMed

Kassir, Yona

2017-01-01

Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

Geographically multifarious phenotypic divergence during speciation

PubMed Central

Gompert, Zachariah; Lucas, Lauren K; Nice, Chris C; Fordyce, James A; Alex Buerkle, C; Forister, Matthew L

2013-01-01

Speciation is an important evolutionary process that occurs when barriers to gene flow evolve between previously panmictic populations. Although individual barriers to gene flow have been studied extensively, we know relatively little regarding the number of barriers that isolate species or whether these barriers are polymorphic within species. Herein, we use a series of field and lab experiments to quantify phenotypic divergence and identify possible barriers to gene flow between the butterfly species Lycaeides idas and Lycaeides melissa. We found evidence that L. idas and L. melissa have diverged along multiple phenotypic axes. Specifically, we identified major phenotypic differences in female oviposition preference and diapause initiation, and more moderate divergence in mate preference. Multiple phenotypic differences might operate as barriers to gene flow, as shown by correlations between genetic distance and phenotypic divergence and patterns of phenotypic variation in admixed Lycaeides populations. Although some of these traits differed primarily between species (e.g., diapause initiation), several traits also varied among conspecific populations (e.g., male mate preference and oviposition preference). PMID:23532669

A Whole-Cell Phenotypic Screening Platform for Identifying Methylerythritol Phosphate Pathway-Selective Inhibitors as Novel Antibacterial Agents

PubMed Central

Johnson, L. Jeffrey

2012-01-01

Isoprenoid biosynthesis is essential for survival of all living organisms. More than 50,000 unique isoprenoids occur naturally, with each constructed from two simple five-carbon precursors: isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). Two pathways for the biosynthesis of IPP and DMAPP are found in nature. Humans exclusively use the mevalonate (MVA) pathway, while most bacteria, including all Gram-negative and many Gram-positive species, use the unrelated methylerythritol phosphate (MEP) pathway. Here we report the development of a novel, whole-cell phenotypic screening platform to identify compounds that selectively inhibit the MEP pathway. Strains of Salmonella enterica serovar Typhimurium were engineered to have separately inducible MEP (native) and MVA (nonnative) pathways. These strains, RMC26 and CT31-7d, were then used to differentiate MVA pathway- and MEP pathway-specific perturbation. Compounds that inhibit MEP pathway-dependent bacterial growth but leave MVA-dependent growth unaffected represent MEP pathway-selective antibacterials. This screening platform offers three significant results. First, the compound is antibacterial and is therefore cell permeant, enabling access to the intracellular target. Second, the compound inhibits one or more MEP pathway enzymes. Third, the MVA pathway is unaffected, suggesting selectivity for targeting the bacterial versus host pathway. The cell lines also display increased sensitivity to two reported MEP pathway-specific inhibitors, further biasing the platform toward inhibitors selective for the MEP pathway. We demonstrate development of a robust, high-throughput screening platform that combines phenotypic and target-based screening that can identify MEP pathway-selective antibacterials simply by monitoring optical density as the readout for cell growth/inhibition. PMID:22777049

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

Two distinct phenotypes of asthma in elite athletes identified by latent class analysis.

PubMed

Couto, Mariana; Stang, Julie; Horta, Luís; Stensrud, Trine; Severo, Milton; Mowinckel, Petter; Silva, Diana; Delgado, Luís; Moreira, André; Carlsen, Kai-Håkon

2015-01-01

Clusters of asthma in athletes have been insufficiently studied. Therefore, the present study aimed to characterize asthma phenotypes in elite athletes using latent class analysis (LCA) and to evaluate its association with the type of sport practiced. In the present cross-sectional study, an analysis of athletes' records was carried out in databases of the Portuguese National Anti-Doping Committee and the Norwegian School of Sport Sciences. Athletes with asthma, diagnosed according to criteria given by the International Olympic Committee, were included for LCA. Sports practiced were categorized into water, winter and other sports. Of 324 files screened, 150 files belonged to asthmatic athletes (91 Portuguese; 59 Norwegian). LCA retrieved two clusters: "atopic asthma" defined by allergic sensitization, rhinitis and allergic co-morbidities and increased exhaled nitric oxide levels; and "sports asthma", defined by exercise-induced respiratory symptoms and airway hyperesponsiveness without allergic features. The risk of developing the phenotype "sports asthma" was significantly increased in athletes practicing water (OR = 2.87; 95% CI [1.82-4.51]) and winter (OR = 8.65; 95% CI [2.67-28.03]) sports, when compared with other athletes. Two asthma phenotypes were identified in elite athletes: "atopic asthma" and "sports asthma". The type of sport practiced was associated with different phenotypes: water and winter sport athletes had three- and ninefold increased risk of "sports asthma". Recognizing different phenotypes is clinically relevant as it would lead to distinct targeted treatments.

High-throughput matrix screening identifies synergistic and antagonistic antimalarial drug combinations

PubMed Central

Mott, Bryan T.; Eastman, Richard T.; Guha, Rajarshi; Sherlach, Katy S.; Siriwardana, Amila; Shinn, Paul; McKnight, Crystal; Michael, Sam; Lacerda-Queiroz, Norinne; Patel, Paresma R.; Khine, Pwint; Sun, Hongmao; Kasbekar, Monica; Aghdam, Nima; Fontaine, Shaun D.; Liu, Dongbo; Mierzwa, Tim; Mathews-Griner, Lesley A.; Ferrer, Marc; Renslo, Adam R.; Inglese, James; Yuan, Jing; Roepe, Paul D.; Su, Xin-zhuan; Thomas, Craig J.

2015-01-01

Drug resistance in Plasmodium parasites is a constant threat. Novel therapeutics, especially new drug combinations, must be identified at a faster rate. In response to the urgent need for new antimalarial drug combinations we screened a large collection of approved and investigational drugs, tested 13,910 drug pairs, and identified many promising antimalarial drug combinations. The activity of known antimalarial drug regimens was confirmed and a myriad of new classes of positively interacting drug pairings were discovered. Network and clustering analyses reinforced established mechanistic relationships for known drug combinations and identified several novel mechanistic hypotheses. From eleven screens comprising >4,600 combinations per parasite strain (including duplicates) we further investigated interactions between approved antimalarials, calcium homeostasis modulators, and inhibitors of phosphatidylinositide 3-kinases (PI3K) and the mammalian target of rapamycin (mTOR). These studies highlight important targets and pathways and provide promising leads for clinically actionable antimalarial therapy. PMID:26403635

Limited Efficiency of Drug Delivery to Specific Intracellular Organelles Using Subcellularly "Targeted" Drug Delivery Systems.

PubMed

Maity, Amit Ranjan; Stepensky, David

2016-01-04

Many drugs have been designed to act on intracellular targets and to affect intracellular processes inside target cells. For the desired effects to be exerted, these drugs should permeate target cells and reach specific intracellular organelles. This subcellular drug targeting approach has been proposed for enhancement of accumulation of these drugs in target organelles and improved efficiency. This approach is based on drug encapsulation in drug delivery systems (DDSs) and/or their decoration with specific targeting moieties that are intended to enhance the drug/DDS accumulation in the intracellular organelle of interest. During recent years, there has been a constant increase in interest in DDSs targeted to specific intracellular organelles, and many different approaches have been proposed for attaining efficient drug delivery to specific organelles of interest. However, it appears that in many studies insufficient efforts have been devoted to quantitative analysis of the major formulation parameters of the DDSs disposition (efficiency of DDS endocytosis and endosomal escape, intracellular trafficking, and efficiency of DDS delivery to the target organelle) and of the resulting pharmacological effects. Thus, in many cases, claims regarding efficient delivery of drug/DDS to a specific organelle and efficient subcellular targeting appear to be exaggerated. On the basis of the available experimental data, it appears that drugs/DDS decoration with specific targeting residues can affect their intracellular fate and result in preferential drug accumulation within an organelle of interest. However, it is not clear whether these approaches will be efficient in in vivo settings and be translated into preclinical and clinical applications. Studies that quantitatively assess the mechanisms, barriers, and efficiencies of subcellular drug delivery and of the associated toxic effects are required to determine the therapeutic potential of subcellular DDS targeting.

Computational Biology Tools for Identifying Specific Ligand Binding Residues for Novel Agrochemical and Drug Design.

PubMed

Neshich, Izabella Agostinho Pena; Nishimura, Leticia; de Moraes, Fabio Rogerio; Salim, Jose Augusto; Villalta-Romero, Fabian; Borro, Luiz; Yano, Inacio Henrique; Mazoni, Ivan; Tasic, Ljubica; Jardine, Jose Gilberto; Neshich, Goran

2015-01-01

The term "agrochemicals" is used in its generic form to represent a spectrum of pesticides, such as insecticides, fungicides or bactericides. They contain active components designed for optimized pest management and control, therefore allowing for economically sound and labor efficient agricultural production. A "drug" on the other side is a term that is used for compounds designed for controlling human diseases. Although drugs are subjected to much more severe testing and regulation procedures before reaching the market, they might contain exactly the same active ingredient as certain agrochemicals, what is the case described in present work, showing how a small chemical compound might be used to control pathogenicity of Gram negative bacteria Xylella fastidiosa which devastates citrus plantations, as well as for control of, for example, meningitis in humans. It is also clear that so far the production of new agrochemicals is not benefiting as much from the in silico new chemical compound identification/discovery as pharmaceutical production. Rational drug design crucially depends on detailed knowledge of structural information about the receptor (target protein) and the ligand (drug/agrochemical). The interaction between the two molecules is the subject of analysis that aims to understand relationship between structure and function, mainly deciphering some fundamental elements of the nanoenvironment where the interaction occurs. In this work we will emphasize the role of understanding nanoenvironmental factors that guide recognition and interaction of target protein and its function modifier, an agrochemical or a drug. The repertoire of nanoenvironment descriptors is used for two selected and specific cases we have approached in order to offer a technological solution for some very important problems that needs special attention in agriculture: elimination of pathogenicity of a bacterium which is attacking citrus plants and formulation of a new fungicide. Finally

Drug Synergy Screen and Network Modeling in Dedifferentiated Liposarcoma Identifies CDK4 and IGF1R as Synergistic Drug Targets

PubMed Central

Miller, Martin L.; Molinelli, Evan J.; Nair, Jayasree S.; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M.; Singer, Samuel; Schwartz, Gary K.; Sander, Chris

2014-01-01

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depend on activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies. PMID:24065146

Novel Phenotype Issues Raised in Cross-National Epidemiological Research on Drug Dependence

PubMed Central

Anthony, James C.

2010-01-01

Stage-transition models based on the American Diagnostic and Statistical Manual (DSM) generally are applied in epidemiology and genetics research on drug dependence syndromes associated with cannabis, cocaine, and other internationally regulated drugs (IRD). Difficulties with DSM stage-transition models have surfaced during cross-national research intended to provide a truly global perspective, such as the work of the World Mental Health Surveys (WMHS) Consortium. Alternative simpler dependence-related phenotypes are possible, including population-level count process models for steps early and before coalescence of clinical features into a coherent syndrome (e.g., zero-inflated Poisson regression). Selected findings are reviewed, based on ZIP modeling of alcohol, tobacco, and IRD count processes, with an illustration that may stimulate new research on genetic susceptibility traits. The annual National Surveys on Drug Use and Health can be readily modified for this purpose, along the lines of a truly anonymous research approach that can help make NSDUH-type cross-national epidemiological surveys more useful in the context of subsequent genome wide association (GWAS) research and post-GWAS investigations with a truly global health perspective. PMID:20201862

A basal stem cell signature identifies aggressive prostate cancer phenotypes

PubMed Central

Smith, Bryan A.; Sokolov, Artem; Uzunangelov, Vladislav; Baertsch, Robert; Newton, Yulia; Graim, Kiley; Mathis, Colleen; Cheng, Donghui; Stuart, Joshua M.; Witte, Owen N.

2015-01-01

Evidence from numerous cancers suggests that increased aggressiveness is accompanied by up-regulation of signaling pathways and acquisition of properties common to stem cells. It is unclear if different subtypes of late-stage cancer vary in stemness properties and whether or not these subtypes are transcriptionally similar to normal tissue stem cells. We report a gene signature specific for human prostate basal cells that is differentially enriched in various phenotypes of late-stage metastatic prostate cancer. We FACS-purified and transcriptionally profiled basal and luminal epithelial populations from the benign and cancerous regions of primary human prostates. High-throughput RNA sequencing showed the basal population to be defined by genes associated with stem cell signaling programs and invasiveness. Application of a 91-gene basal signature to gene expression datasets from patients with organ-confined or hormone-refractory metastatic prostate cancer revealed that metastatic small cell neuroendocrine carcinoma was molecularly more stem-like than either metastatic adenocarcinoma or organ-confined adenocarcinoma. Bioinformatic analysis of the basal cell and two human small cell gene signatures identified a set of E2F target genes common between prostate small cell neuroendocrine carcinoma and primary prostate basal cells. Taken together, our data suggest that aggressive prostate cancer shares a conserved transcriptional program with normal adult prostate basal stem cells. PMID:26460041

Sensitivity and Specificity of Emergency Physicians and Trainees for Identifying Internally Concealed Drug Packages on Abdominal Computed Tomography Scan: Do Lung Windows Improve Accuracy?

PubMed

Asha, Stephen Edward; Cooke, Andrew

2015-09-01

Suspected body packers may be brought to emergency departments (EDs) close to international airports for abdominal computed tomography (CT) scanning. Senior emergency clinicians may be asked to interpret these CT scans. Missing concealed drug packages have important clinical and forensic implications. The accuracy of emergency clinician interpretation of abdominal CT scans for concealed drugs is not known. Limited evidence suggests that accuracy for identification of concealed packages can be increased by viewing CT images on "lung window" settings. To determine the accuracy of senior emergency clinicians in interpreting abdominal CT scans for concealed drugs, and to determine if this accuracy was improved by viewing scans on both abdominal and lung window settings. Emergency clinicians blinded to all patient identifiers and the radiology report interpreted CT scans of suspected body packers using standard abdominal window settings and then with the addition of lung window settings. The reference standard was the radiologist's report. Fifty-five emergency clinicians reported 235 CT scans. The sensitivity, specificity, and accuracy of interpretation using abdominal windows was 89.9% (95% confidence interval [CI] 83.0-94.7), 81.9% (95% CI 73.7-88.4), and 86.0% (95% CI 81.5-90.4), respectively, and with both window settings was 94.1% (95% CI 88.3-97.6), 76.7% (95% CI 68.0-84.1), 85.5% (95% CI 81.0-90.0), respectively. Diagnostic accuracy was similar regardless of the clinician's experience. Interrater reliability was moderate (kappa 0.46). The accuracy of interpretation of abdominal CT scans performed for the purpose of detecting concealed drug packages by emergency clinicians is not high enough to safely discharge these patients from the ED. The use of lung windows improved sensitivity, but at the expense of specificity. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Ability of the VITEK 2 Advanced Expert System To Identify β-Lactam Phenotypes in Isolates of Enterobacteriaceae and Pseudomonas aeruginosa

PubMed Central

Sanders, Christine C.; Peyret, Michel; Moland, Ellen Smith; Shubert, Carole; Thomson, Kenneth S.; Boeufgras, Jean-Marc; Sanders, W. Eugene

2000-01-01

The Advanced Expert System (AES) was used in conjunction with the VITEK 2 automated antimicrobial susceptibility test system to ascertain the β-lactam phenotypes of 196 isolates of the family Enterobacteriaceae and the species Pseudomonas aeruginosa. These isolates represented a panel of strains that had been collected from laboratories worldwide and whose β-lactam phenotypes had been characterized by biochemical and molecular techniques. The antimicrobial susceptibility of each isolate was determined with the VITEK 2 instrument, and the results were analyzed with the AES to ascertain the β-lactam phenotype. The results were then compared to the β-lactam resistance mechanism determined by biochemical and molecular techniques. Overall, the AES was able to ascertain a β-lactam phenotype for 183 of the 196 (93.4%) isolates tested. For 111 of these 183 (60.7%) isolates, the correct β-lactam phenotype was identified definitively in a single choice by the AES, while for an additional 46 isolates (25.1%), the AES identified the correct β-lactam phenotype provisionally within two or more choices. For the remaining 26 isolates (14.2%), the β-lactam phenotype identified by the AES was incorrect. However, for a number of these isolates, the error was due to remediable problems. These results suggest that the AES is capable of accurate identification of the β-lactam phenotypes of gram-negative isolates and that certain modifications can improve its performance even further. PMID:10655347

HPMA Copolymer-Drug Conjugates with Controlled Tumor-Specific Drug Release.

PubMed

Chytil, Petr; Koziolová, Eva; Etrych, Tomáš; Ulbrich, Karel

2018-01-01

Over the past few decades, numerous polymer drug carrier systems are designed and synthesized, and their properties are evaluated. Many of these systems are based on water-soluble polymer carriers of low-molecular-weight drugs and compounds, e.g., cytostatic agents, anti-inflammatory drugs, or multidrug resistance inhibitors, all covalently bound to a carrier by a biodegradable spacer that enables controlled release of the active molecule to achieve the desired pharmacological effect. Among others, the synthetic polymer carriers based on N-(2-hydroxypropyl) methacrylamide (HPMA) copolymers are some of the most promising carriers for this purpose. This review focuses on advances in the development of HPMA copolymer carriers and their conjugates with anticancer drugs, with triggered drug activation in tumor tissue and especially in tumor cells. Specifically, this review highlights the improvements in polymer drug carrier design with respect to the structure of a spacer to influence controlled drug release and activation, and its impact on the drug pharmacokinetics, enhanced tumor uptake, cellular trafficking, and in vivo antitumor activity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-Density Genetic Mapping Identifies New Susceptibility Variants in Sarcoidosis Phenotypes and Shows Genomic-driven Phenotypic Differences

PubMed Central

Ronninger, Marcus; Shchetynsky, Klementy; Franke, Andre; Nöthen, Markus M.; Müller-Quernheim, Joachim; Schreiber, Stefan; Adrianto, Indra; Karakaya, Bekir; van Moorsel, Coline H. M.; Navratilova, Zdenka; Kolek, Vitezslav; Rybicki, Benjamin A.; Iannuzzi, Michael C.; Petrek, Martin; Grutters, Jan C.; Montgomery, Courtney; Fischer, Annegret; Eklund, Anders; Padyukov, Leonid; Grunewald, Johan

2016-01-01

Rationale: Sarcoidosis is a multisystem disease of unknown cause. Löfgren’s syndrome (LS) is a characteristic subgroup of sarcoidosis that is associated with a good prognosis in sarcoidosis. However, little is known about its genetic architecture or its broader phenotype, non-LS sarcoidosis. Objectives: To address the genetic architecture of sarcoidosis phenotypes, LS and non-LS. Methods: An association study in a white Swedish cohort of 384 LS, 664 non-LS, and 2,086 control subjects, totaling 3,134 subjects using a fine-mapping genotyping platform was conducted. Replication was performed in four independent cohorts, three of white European descent (Germany, n = 4,975; the Netherlands, n = 613; and Czech Republic, n = 521), and one of black African descent (United States, n = 1,657), totaling 7,766 subjects. Measurements and Main Results: A total of 727 LS-associated variants expanding throughout the extended major histocompatibility complex (MHC) region and 68 non-LS–associated variants located in the MHC class II region were identified and confirmed. A shared overlap between LS and non-LS defined by 17 variants located in the MHC class II region was found. Outside the MHC region, two LS-associated loci, in ADCY3 and between CSMD1 and MCPH1, were observed and replicated. Conclusions: Comprehensive and integrative analyses of genetics, transcription, and pathway modeling on LS and non-LS indicates that these sarcoidosis phenotypes have different genetic susceptibility, genomic distributions, and cellular activities, suggesting distinct molecular mechanisms in pathways related to immune response with a common region. PMID:26651848

CaMKII inhibition rectifies arrhythmic phenotype in a patient-specific model of catecholaminergic polymorphic ventricular tachycardia

PubMed Central

Di Pasquale, E; Lodola, F; Miragoli, M; Denegri, M; Avelino-Cruz, J E; Buonocore, M; Nakahama, H; Portararo, P; Bloise, R; Napolitano, C; Condorelli, G; Priori, S G

2013-01-01

Induced pluripotent stem cells (iPSC) offer a unique opportunity for developmental studies, disease modeling and regenerative medicine approaches in humans. The aim of our study was to create an in vitro ‘patient-specific cell-based system' that could facilitate the screening of new therapeutic molecules for the treatment of catecholaminergic polymorphic ventricular tachycardia (CPVT), an inherited form of fatal arrhythmia. Here, we report the development of a cardiac model of CPVT through the generation of iPSC from a CPVT patient carrying a heterozygous mutation in the cardiac ryanodine receptor gene (RyR2) and their subsequent differentiation into cardiomyocytes (CMs). Whole-cell patch-clamp and intracellular electrical recordings of spontaneously beating cells revealed the presence of delayed afterdepolarizations (DADs) in CPVT-CMs, both in resting conditions and after β-adrenergic stimulation, resembling the cardiac phenotype of the patients. Furthermore, treatment with KN-93 (2-[N-(2-hydroxyethyl)]-N-(4methoxybenzenesulfonyl)]amino-N-(4-chlorocinnamyl)-N-methylbenzylamine), an antiarrhythmic drug that inhibits Ca2+/calmodulin-dependent serine–threonine protein kinase II (CaMKII), drastically reduced the presence of DADs in CVPT-CMs, rescuing the arrhythmic phenotype induced by catecholaminergic stress. In addition, intracellular calcium transient measurements on 3D beating clusters by fast resolution optical mapping showed that CPVT clusters developed multiple calcium transients, whereas in the wild-type clusters, only single initiations were detected. Such instability is aggravated in the presence of isoproterenol and is attenuated by KN-93. As seen in our RyR2 knock-in CPVT mice, the antiarrhythmic effect of KN-93 is confirmed in these human iPSC-derived cardiac cells, supporting the role of this in vitro system for drug screening and optimization of clinical treatment strategies. PMID:24113177

Female-specific flightless (fsRIDL) phenotype for control of Aedes albopictus.

PubMed

Labbé, Geneviève M C; Scaife, Sarah; Morgan, Siân A; Curtis, Zoë H; Alphey, Luke

2012-01-01

Aedes albopictus, the Asian tiger mosquito, is a vector of several arboviruses including dengue and chikungunya, and is also a significant nuisance mosquito. It is one of the most invasive of mosquitoes with a relentlessly increasing geographic distribution. Conventional control methods have so far failed to control Ae. albopictus adequately. Novel genetics-based strategies offer a promising alternative or aid towards efficient control of this mosquito. We describe here the isolation, characterisation and use of the Ae. albopictus Actin-4 gene to drive a dominant lethal gene in the indirect flight muscles of Ae. albopictus, thus inducing a conditional female-specific late-acting flightless phenotype. We also show that in this context, the Actin-4 regulatory regions from both Ae. albopictus and Ae. aegypti can be used to provide conditional female-specific flightlessness in either species. With the disease-transmitting females incapacitated, the female flightless phenotype encompasses a genetic sexing mechanism and would be suitable for controlling Ae. albopictus using a male-only release approach as part of an integrated pest management strategy.

Targeted Nanodiamonds as Phenotype Specific Photoacoustic Contrast Agents for Breast Cancer

PubMed Central

Zhang, Ti; Cui, Huizhong; Fang, Chia-Yi; Cheng, Kun; Yang, Xinmai; Chang, Huan-Cheng; Forrest, M. Laird

2015-01-01

Aim The aim is to develop irradiated nanodiamonds (INDs) as a molecularly-targeted contrast agent for high resolution and phenotype-specific detection of breast cancer with photoacoustic (PA) imaging. Materials & Methods The surface of acid treated radiation-damaged nanodiamonds was grafted with polyethylene glycol (PEG) to improve its stability and circulation time in blood, followed by conjugation to an anti-Human epidermal growth factor receptor-2 (HER2) peptide (KCCYSL) with a final nanoparticle size of ca. 92 nm. Immunocompetent mice bearing orthotopic HER2 positive or negative tumors were administered INDs and PA imaged using an 820-nm near infrared laser. Results PA images demonstrated that INDs accumulate in tumors and completely delineated the entire tumor within 10 hours. HER2 targeting significantly enhanced imaging of HER2-positive tumors. Pathological examination demonstrated INDs are non-toxic. Conclusions PA technology is adaptable to low-cost bedside medicine, and with new contrast agents described herein, PA can achieve high resolution (sub-mm) and phenotype specific monitoring of cancer growth. PMID:25723091

Social-Cognition and the Broad Autism Phenotype: Identifying Genetically Meaningful Phenotypes

ERIC Educational Resources Information Center

Losh, Molly; Piven, Joseph

2007-01-01

Background: Strong evidence from twin and family studies suggests that the genetic liability to autism may be expressed through personality and language characteristics qualitatively similar, but more subtly expressed than those defining the full syndrome. This study examined behavioral features of this "broad autism phenotype" (BAP) in relation…

Antiretroviral drug susceptibility among drug-naive adults with recent HIV infection in Rakai, Uganda

PubMed Central

Eshleman, Susan H.; Laeyendecker, Oliver; Parkin, Neil; Huang, Wei; Chappey, Colombe; Paquet, Agnes C.; Serwadda, David; Reynolds, Steven J.; Kiwanuka, Noah; Quinn, Thomas C.; Gray, Ronald; Wawer, Maria

2009-01-01

Objective To analyze antiretroviral drug susceptibility in HIV from recently infected adults in Rakai, Uganda, prior to the availability of antiretroviral drug treatment. Methods Samples obtained at the time of HIV seroconversion (1998–2003) were analyzed using the GeneSeq HIV and PhenoSense HIV assays (Monogram Biosciences, Inc., South San Francisco, California, USA). Results Test results were obtained for 104 samples (subtypes: 26A, 1C, 66D, 9A/D, 1C/D, 1 intersubtype recombinant). Mutations used for genotypic surveillance of transmitted antiretroviral drug resistance were identified in six samples: three had nucleoside reverse transcriptase inhibitor (NRTI) surveillance mutations (two had M41L, one had K219R), and three had protease inhibitor surveillance mutations (I47V, F53L, N88D); none had nonnucleoside reverse transcriptase inhibitor (NNRTI) surveillance mutations. Other resistance-associated mutations were identified in some samples. However, none of the samples had a sufficient number of mutations to predict reduced antiretroviral drug susceptibility. Ten (9.6%) of the samples had reduced phenotypic susceptibility to at least one drug (one had partial susceptibility to didanosine, one had nevirapine resistance, and eight had resistance or partial susceptibility to at least one protease inhibitor). Fifty-three (51%) of the samples had hypersusceptibility to at least one drug (seven had zidovudine hypersusceptibility, 28 had NNRTI hypersusceptibility, 34 had protease inhibitor hypersusceptibility). Delavirdine hyper-susceptibility was more frequent in subtype A than D. In subtype D, efavirenz hypersusceptibility was associated with substitutions at codon 11 in HIV-reverse transcriptase. Conclusion Phenotyping detected reduced antiretroviral drug susceptibility and hypersusceptibility in HIV from some antiretroviral-naive Ugandan adults that was not predicted by genotyping. Phenotyping may complement genotyping for analysis of antiretroviral drug

Antiretroviral drug susceptibility among drug-naive adults with recent HIV infection in Rakai, Uganda.

PubMed

Eshleman, Susan H; Laeyendecker, Oliver; Parkin, Neil; Huang, Wei; Chappey, Colombe; Paquet, Agnes C; Serwadda, David; Reynolds, Steven J; Kiwanuka, Noah; Quinn, Thomas C; Gray, Ronald; Wawer, Maria

2009-04-27

To analyze antiretroviral drug susceptibility in HIV from recently infected adults in Rakai, Uganda, prior to the availability of antiretroviral drug treatment. Samples obtained at the time of HIV seroconversion (1998-2003) were analyzed using the GeneSeq HIV and PhenoSense HIV assays (Monogram Biosciences, Inc., South San Francisco, California, USA). Test results were obtained for 104 samples (subtypes: 26A, 1C, 66D, 9A/D, 1C/D, 1 intersubtype recombinant). Mutations used for genotypic surveillance of transmitted antiretroviral drug resistance were identified in six samples: three had nucleoside reverse transcriptase inhibitor (NRTI) surveillance mutations (two had M41L, one had K219R), and three had protease inhibitor surveillance mutations (I47V, F53L, N88D); none had nonnucleoside reverse transcriptase inhibitor (NNRTI) surveillance mutations. Other resistance-associated mutations were identified in some samples. However, none of the samples had a sufficient number of mutations to predict reduced antiretroviral drug susceptibility. Ten (9.6%) of the samples had reduced phenotypic susceptibility to at least one drug (one had partial susceptibility to didanosine, one had nevirapine resistance, and eight had resistance or partial susceptibility to at least one protease inhibitor). Fifty-three (51%) of the samples had hypersusceptibility to at least one drug (seven had zidovudine hypersusceptibility, 28 had NNRTI hypersusceptibility, 34 had protease inhibitor hypersusceptibility). Delavirdine hypersusceptibility was more frequent in subtype A than D. In subtype D, efavirenz hypersusceptibility was associated with substitutions at codon 11 in HIV-reverse transcriptase. Phenotyping detected reduced antiretroviral drug susceptibility and hypersusceptibility in HIV from some antiretroviral-naive Ugandan adults that was not predicted by genotyping. Phenotyping may complement genotyping for analysis of antiretroviral drug susceptibility in populations with nonsubtype B

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

PubMed

Andrews, Tallulah; Meader, Stephen; Vulto-van Silfhout, Anneke; Taylor, Avigail; Steinberg, Julia; Hehir-Kwa, Jayne; Pfundt, Rolph; de Leeuw, Nicole; de Vries, Bert B A; Webber, Caleb

2015-03-01

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records.

PubMed

Chen, Chia-Yen; Lee, Phil H; Castro, Victor M; Minnier, Jessica; Charney, Alexander W; Stahl, Eli A; Ruderfer, Douglas M; Murphy, Shawn N; Gainer, Vivian; Cai, Tianxi; Jones, Ian; Pato, Carlos N; Pato, Michele T; Landén, Mikael; Sklar, Pamela; Perlis, Roy H; Smoller, Jordan W

2018-04-18

Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363-372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h 2 g ) and genetic correlation (r g ) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency-"coded-strict", "coded-broad", and "coded-broad based on a single clinical encounter" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h 2 g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h 2 g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h 2 g ) was 0.12 (p�

A side-effect free method for identifying cancer drug targets.

PubMed

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

Tightly congruent bursts of lineage and phenotypic diversification identified in a continental ant radiation.

PubMed

Price, Shauna L; Etienne, Rampal S; Powell, Scott

2016-04-01

Adaptive diversification is thought to be shaped by ecological opportunity. A prediction of this ecological process of diversification is that it should result in congruent bursts of lineage and phenotypic diversification, but few studies have found this expected association. Here, we study the relationship between rates of lineage diversification and body size evolution in the turtle ants, a diverse Neotropical clade. Using a near complete, time-calibrated phylogeny we investigated lineage diversification dynamics and body size disparity through model fitting analyses and estimation of per-lineage rates of cladogenesis and phenotypic evolution. We identify an exceptionally high degree of congruence between the high rates of lineage and body size diversification in a young clade undergoing renewed diversification in the ecologically distinct Chacoan biogeographical region of South America. It is likely that the region presented turtle ants with novel ecological opportunity, which facilitated a nested burst of diversification and phenotypic evolution within the group. Our results provide a compelling quantitative example of tight congruence between rates of lineage and phenotypic diversification, meeting the key predicted pattern of adaptive diversification shaped by ecological opportunity. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Towards improving phenotype representation in OWL

PubMed Central

2012-01-01

Background Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected entities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies. Methods We analyze formalizations of complex phenotype descriptions in the Web Ontology Language (OWL) that are based on the EQ model, identify several representational challenges and analyze potential solutions to address these challenges. Results In particular, we suggest a novel, role-based approach to represent relational qualities such as concentration of iron in spleen, discuss its ontological foundation in the General Formal Ontology (GFO) and evaluate its representation in OWL and the benefits it can bring to the representation of phenotype annotations. Conclusion Our analysis of OWL-based representations of phenotypes can contribute to improving consistency and expressiveness of formal phenotype descriptions. PMID:23046625

Drug Screening Using a Library of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes Reveals Disease Specific Patterns of Cardiotoxicity

PubMed Central

Liang, Ping; Lan, Feng; Lee, Andrew S.; Gong, Tingyu; Sanchez-Freire, Veronica; Wang, Yongming; Diecke, Sebastian; Sallam, Karim; Knowles, Joshua W.; Wang, Paul J.; Nguyen, Patricia K.; Bers, Donald M.; Robbins, Robert C.; Wu, Joseph C.

2013-01-01

Background Cardiotoxicity is a leading cause for drug attrition during pharmaceutical development and has resulted in numerous preventable patient deaths. Incidents of adverse cardiac drug reactions are more common in patients with pre-existing heart disease than the general population. Here we generated a library of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with various hereditary cardiac disorders to model differences in cardiac drug toxicity susceptibility for patients of different genetic backgrounds. Methods and Results Action potential duration (APD) and drug-induced arrhythmia were measured at the single cell level in hiPSC-CMs derived from healthy subjects and patients with hereditary long QT syndrome (LQT), familial hypertrophic cardiomyopathy (HCM), and familial dilated cardiomyopathy (DCM). Disease phenotypes were verified in LQT, HCM, and DCM iPSC-CMs by immunostaining and single cell patch clamp. Human embryonic stem cell-derived cardiomyocytes (hESC-CMs) and the human ether-a-go-go-related gene (hERG) expressing human embryonic kidney (HEK293) cells were used as controls. Single cell PCR confirmed expression of all cardiac ion channels in patient-specific hiPSC-CMs as well as hESC-CMs, but not in HEK293 cells. Disease-specific hiPSC-CMs demonstrated increased susceptibility to known cardiotoxic drugs as measured by APD and quantification of drug-induced arrhythmias such as early after depolarizations (EADs) and delayed after depolarizations (DADs). Conclusions We have recapitulated drug-induced cardiotoxicity profiles for healthy subjects, LQT, HCM, and DCM patients at the single cell level for the first time. Our data indicate that healthy and diseased individuals exhibit different susceptibilities to cardiotoxic drugs and that use of disease-specific hiPSC-CMs may predict adverse drug responses more accurately than standard hERG test or healthy control hiPSC-CM/hESC-CM screening assays. PMID:23519760

Allele-specific RNA interference rescues the long-QT syndrome phenotype in human-induced pluripotency stem cell cardiomyocytes.

PubMed

Matsa, Elena; Dixon, James E; Medway, Christopher; Georgiou, Orestis; Patel, Minal J; Morgan, Kevin; Kemp, Paul J; Staniforth, Andrew; Mellor, Ian; Denning, Chris

2014-04-01

Long-QT syndromes (LQTS) are mostly autosomal-dominant congenital disorders associated with a 1:1000 mutation frequency, cardiac arrest, and sudden death. We sought to use cardiomyocytes derived from human-induced pluripotency stem cells (hiPSCs) as an in vitro model to develop and evaluate gene-based therapeutics for the treatment of LQTS. We produced LQTS-type 2 (LQT2) hiPSC cardiomyocytes carrying a KCNH2 c.G1681A mutation in a IKr ion-channel pore, which caused impaired glycosylation and channel transport to cell surface. Allele-specific RNA interference (RNAi) directed towards the mutated KCNH2 mRNA caused knockdown, while leaving the wild-type mRNA unaffected. Electrophysiological analysis of patient-derived LQT2 hiPSC cardiomyocytes treated with mutation-specific siRNAs showed normalized action potential durations (APDs) and K(+) currents with the concurrent rescue of spontaneous and drug-induced arrhythmias (presented as early-afterdepolarizations). These findings provide in vitro evidence that allele-specific RNAi can rescue diseased phenotype in LQTS cardiomyocytes. This is a potentially novel route for the treatment of many autosomal-dominant-negative disorders, including those of the heart.

Allele-specific RNA interference rescues the long-QT syndrome phenotype in human-induced pluripotency stem cell cardiomyocytes

PubMed Central

Matsa, Elena; Dixon, James E.; Medway, Christopher; Georgiou, Orestis; Patel, Minal J.; Morgan, Kevin; Kemp, Paul J.; Staniforth, Andrew; Mellor, Ian; Denning, Chris

2014-01-01

Aims Long-QT syndromes (LQTS) are mostly autosomal-dominant congenital disorders associated with a 1:1000 mutation frequency, cardiac arrest, and sudden death. We sought to use cardiomyocytes derived from human-induced pluripotency stem cells (hiPSCs) as an in vitro model to develop and evaluate gene-based therapeutics for the treatment of LQTS. Methods and results We produced LQTS-type 2 (LQT2) hiPSC cardiomyocytes carrying a KCNH2 c.G1681A mutation in a IKr ion-channel pore, which caused impaired glycosylation and channel transport to cell surface. Allele-specific RNA interference (RNAi) directed towards the mutated KCNH2 mRNA caused knockdown, while leaving the wild-type mRNA unaffected. Electrophysiological analysis of patient-derived LQT2 hiPSC cardiomyocytes treated with mutation-specific siRNAs showed normalized action potential durations (APDs) and K+ currents with the concurrent rescue of spontaneous and drug-induced arrhythmias (presented as early-afterdepolarizations). Conclusions These findings provide in vitro evidence that allele-specific RNAi can rescue diseased phenotype in LQTS cardiomyocytes. This is a potentially novel route for the treatment of many autosomal-dominant-negative disorders, including those of the heart. PMID:23470493

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Silver nanoparticles induce developmental stage-specific embryonic phenotypes in zebrafish

NASA Astrophysics Data System (ADS)

Lee, Kerry J.; Browning, Lauren M.; Nallathamby, Prakash D.; Osgood, Christopher J.; Xu, Xiao-Hong Nancy

2013-11-01

Much is anticipated from the development and deployment of nanomaterials in biological organisms, but concerns remain regarding their biocompatibility and target specificity. Here we report our study of the transport, biocompatibility and toxicity of purified and stable silver nanoparticles (Ag NPs, 13.1 +/- 2.5 nm in diameter) upon the specific developmental stages of zebrafish embryos using single NP plasmonic spectroscopy. We find that single Ag NPs passively diffuse into five different developmental stages of embryos (cleavage, early-gastrula, early-segmentation, late-segmentation, and hatching stages), showing stage-independent diffusion modes and diffusion coefficients. Notably, the Ag NPs induce distinctive stage and dose-dependent phenotypes and nanotoxicity, upon their acute exposure to the Ag NPs (0-0.7 nM) for only 2 h. The late-segmentation embryos are most sensitive to the NPs with the lowest critical concentration (CNP,c << 0.02 nM) and highest percentages of cardiac abnormalities, followed by early-segmentation embryos (CNP,c < 0.02 nM), suggesting that disruption of cell differentiation by the NPs causes the most toxic effects on embryonic development. The cleavage-stage embryos treated with the NPs develop into a wide variety of phenotypes (abnormal finfold, tail/spinal cord flexure, cardiac malformation/edema, yolk sac edema, and acephaly). These organ structures are not yet developed in cleavage-stage embryos, suggesting that the earliest determinative events to create these structures are ongoing, and disrupted by NPs, which leads to the downstream effects. In contrast, the hatching embryos are most resistant to the Ag NPs, and majority of embryos (94%) develop normally, and none of them develop abnormally. Interestingly, early-gastrula embryos are less sensitive to the NPs than cleavage and segmentation stage embryos, and do not develop abnormally. These important findings suggest that the Ag NPs are not simple poisons, and they can target

Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.

PubMed

Hansen, Peter Wæde; Clemmensen, Line; Sehested, Thomas S G; Fosbøl, Emil Loldrup; Torp-Pedersen, Christian; Køber, Lars; Gislason, Gunnar H; Andersson, Charlotte

2016-11-01

Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without prior hypotheses using data mining. We focused on warfarin-drug interactions as the prototype. We analyzed altered prothrombin time (measured as international normalized ratio [INR]) after initiation of a novel prescription in previously INR-stable warfarin-treated patients with nonvalvular atrial fibrillation. Data sets were retrieved from clinical work. Random forest (a machine-learning method) was set up to predict altered INR levels after novel prescriptions. The most important drug groups from the analysis were further investigated using logistic regression in a new data set. Two hundred and twenty drug groups were analyzed in 61 190 novel prescriptions. We rediscovered 2 drug groups having known interactions (β-lactamase-resistant penicillins [dicloxacillin] and carboxamide derivatives) and 3 antithrombotic/anticoagulant agents (platelet aggregation inhibitors excluding heparin, direct thrombin inhibitors [dabigatran etexilate], and heparins) causing decreasing INR. Six drug groups with known interactions were rediscovered causing increasing INR (antiarrhythmics class III [amiodarone], other opioids [tramadol], glucocorticoids, triazole derivatives, and combinations of penicillins, including β-lactamase inhibitors) and two had a known interaction in a closely related drug group (oripavine derivatives [buprenorphine] and natural opium alkaloids). Antipropulsives had an unknown signal of increasing INR. We were able to identify known warfarin-drug interactions without a prior hypothesis using clinical registries. Additionally, we discovered a few potentially novel interactions. This opens up for the use of data mining to discover unknown drug-drug interactions in cardiovascular medicine. © 2016 American Heart Association

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Systematic drug repositioning for a wide range of diseases with integrative analyses of phenotypic and molecular data.

PubMed

Iwata, Hiroaki; Sawada, Ryusuke; Mizutani, Sayaka; Yamanishi, Yoshihiro

2015-02-23

Drug repositioning, or the application of known drugs to new indications, is a challenging issue in pharmaceutical science. In this study, we developed a new computational method to predict unknown drug indications for systematic drug repositioning in a framework of supervised network inference. We defined a descriptor for each drug-disease pair based on the phenotypic features of drugs (e.g., medicinal effects and side effects) and various molecular features of diseases (e.g., disease-causing genes, diagnostic markers, disease-related pathways, and environmental factors) and constructed a statistical model to predict new drug-disease associations for a wide range of diseases in the International Classification of Diseases. Our results show that the proposed method outperforms previous methods in terms of accuracy and applicability, and its performance does not depend on drug chemical structure similarity. Finally, we performed a comprehensive prediction of a drug-disease association network consisting of 2349 drugs and 858 diseases and described biologically meaningful examples of newly predicted drug indications for several types of cancers and nonhereditary diseases.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE PAGES

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; ...

2017-02-21

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

Overeating phenotypes in overweight and obese children.

PubMed

Boutelle, Kerri N; Peterson, Carol B; Crosby, Ross D; Rydell, Sarah A; Zucker, Nancy; Harnack, Lisa

2014-05-01

The purpose of this study was to identify overeating phenotypes and their correlates in overweight and obese children. One hundred and seventeen treatment-seeking overweight and obese 8-12year-old children and their parents completed the study. Children completed an eating in the absence of hunger (EAH) paradigm, the Eating Disorder Examination interview, and measurements of height and weight. Parents and children completed questionnaires that evaluated satiety responsiveness, food responsiveness, negative affect eating, external eating and eating in the absence of hunger. Latent profile analysis was used to identify heterogeneity in overeating phenotypes in the child participants. Latent classes were then compared on measures of demographics, obesity status and nutritional intake. Three latent classes of overweight and obese children were identified: High Satiety Responsive, High Food Responsive, and Moderate Satiety and Food Responsive. Results indicated that the High Food Responsive group had higher BMI and BMI-Z scores compared to the High Satiety Responsive group. No differences were found among classes in demographics or nutritional intake. This study identified three overeating phenotypes, supporting the heterogeneity of eating patterns associated with overweight and obesity in treatment-seeking children. These finding suggest that these phenotypes can potentially be used to identify high risk groups, inform prevention and intervention targets, and develop specific treatments for these behavioral phenotypes. Copyright © 2014. Published by Elsevier Ltd.

Identifying drugs that cause acute thrombocytopenia: an analysis using 3 distinct methods

PubMed Central

Reese, Jessica A.; Li, Xiaoning; Hauben, Manfred; Aster, Richard H.; Bougie, Daniel W.; Curtis, Brian R.; George, James N.

2010-01-01

Drug-induced immune thrombocytopenia (DITP) is often suspected in patients with acute thrombocytopenia unexplained by other causes, but documenting that a drug is the cause of thrombocytopenia can be challenging. To provide a resource for diagnosis of DITP and for drug safety surveillance, we analyzed 3 distinct methods for identifying drugs that may cause thrombocytopenia. (1) Published case reports of DITP have described 253 drugs suspected of causing thrombocytopenia; using defined clinical criteria, 87 (34%) were identified with evidence that the drug caused thrombocytopenia. (2) Serum samples from patients with suspected DITP were tested for 202 drugs; drug-dependent, platelet-reactive antibodies were identified for 67 drugs (33%). (3) The Food and Drug Administration's Adverse Event Reporting System database was searched for drugs associated with thrombocytopenia by use of data mining algorithms; 1444 drugs had at least 1 report associated with thrombocytopenia, and 573 (40%) drugs demonstrated a statistically distinctive reporting association with thrombocytopenia. Among 1468 drugs suspected of causing thrombocytopenia, 102 were evaluated by all 3 methods, and 23 of these 102 drugs had evidence for an association with thrombocytopenia by all 3 methods. Multiple methods, each with a distinct perspective, can contribute to the identification of drugs that can cause thrombocytopenia. PMID:20530792

Recapitulation of spinal motor neuron-specific disease phenotypes in a human cell model of spinal muscular atrophy

PubMed Central

Wang, Zhi-Bo; Zhang, Xiaoqing; Li, Xue-Jun

2013-01-01

Establishing human cell models of spinal muscular atrophy (SMA) to mimic motor neuron-specific phenotypes holds the key to understanding the pathogenesis of this devastating disease. Here, we developed a closely representative cell model of SMA by knocking down the disease-determining gene, survival motor neuron (SMN), in human embryonic stem cells (hESCs). Our study with this cell model demonstrated that knocking down of SMN does not interfere with neural induction or the initial specification of spinal motor neurons. Notably, the axonal outgrowth of spinal motor neurons was significantly impaired and these disease-mimicking neurons subsequently degenerated. Furthermore, these disease phenotypes were caused by SMN-full length (SMN-FL) but not SMN-Δ7 (lacking exon 7) knockdown, and were specific to spinal motor neurons. Restoring the expression of SMN-FL completely ameliorated all of the disease phenotypes, including specific axonal defects and motor neuron loss. Finally, knockdown of SMN-FL led to excessive mitochondrial oxidative stress in human motor neuron progenitors. The involvement of oxidative stress in the degeneration of spinal motor neurons in the SMA cell model was further confirmed by the administration of N-acetylcysteine, a potent antioxidant, which prevented disease-related apoptosis and subsequent motor neuron death. Thus, we report here the successful establishment of an hESC-based SMA model, which exhibits disease gene isoform specificity, cell type specificity, and phenotype reversibility. Our model provides a unique paradigm for studying how motor neurons specifically degenerate and highlights the potential importance of antioxidants for the treatment of SMA. PMID:23208423

Genome-Wide Association Studies of Drug-Resistance Determinants.

PubMed

Volkman, Sarah K; Herman, Jonathan; Lukens, Amanda K; Hartl, Daniel L

2017-03-01

Population genetic strategies that leverage association, selection, and linkage have identified drug-resistant loci. However, challenges and limitations persist in identifying drug-resistance loci in malaria. In this review we discuss the genetic basis of drug resistance and the use of genome-wide association studies, complemented by selection and linkage studies, to identify and understand mechanisms of drug resistance and response. We also discuss the implications of nongenetic mechanisms of drug resistance recently reported in the literature, and present models of the interplay between nongenetic and genetic processes that contribute to the emergence of drug resistance. Throughout, we examine artemisinin resistance as an example to emphasize challenges in identifying phenotypes suitable for population genetic studies as well as complications due to multiple-factor drug resistance. Copyright © 2016. Published by Elsevier Ltd.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Simultaneous titration and phenotypic antiviral drug susceptibility testing for herpes simplex virus 1 and 2.

PubMed

Tardif, Keith D; Jorgensen, Shane; Langer, Janine; Prichard, Mark; Schlaberg, Robert

2014-11-01

Most herpes simplex virus (HSV) isolates from treatment-naïve patients are susceptible to antivirals. However, prolonged antiviral therapy can select for drug-resistant strains, especially in immunocompromised patients. Standard phenotypic methods for antiviral resistance testing are labor and time-intense and molecular resistance determinants are insufficiently understood for routine diagnostic use of genotypic resistance testing. To enable rapid, scalable antiviral susceptibility testing and minimize viral passage, we developed a 7-day, 96-well assay for simultaneous HSV 1/2 titration and phenotypic resistance testing for acyclovir and foscarnet. The assay was optimized and validated by testing clinical isolates and laboratory strains (n=39) with known IC50 for acyclovir (23 resistant) and foscarnet (1 resistant) based on plaque reduction or dye-uptake assays. A chemiluminescent detection reagent is used for quantification of cytopathic effect instead of plaque counting or measuring dye-uptake. Drug concentrations inhibiting 50% of chemiluminescent signal reduction (IC50) were determined concurrently at each of three virus dilutions. Results agree for 92.3% (acyclovir) and 100% (foscarnet) of isolates. For all three discordant samples, results of reference testing by plaque reduction agreed with the chemiluminescent assay. Reproducibility studies showed 100% qualitative agreement and 3-37% coefficient of variation based on IC50. Chemiluminescence detection as a surrogate for cellular viability with an automated plate reader provides improved throughput and workflow, as well as high accuracy and reproducibility for antiviral drug susceptibility testing. Copyright © 2014 Elsevier B.V. All rights reserved.

Phenotypic Screening Identifies Protein Synthesis Inhibitors as H-Ras-Nanocluster-Increasing Tumor Growth Inducers.

PubMed

Najumudeen, Arafath K; Posada, Itziar M D; Lectez, Benoit; Zhou, Yong; Landor, Sebastian K-J; Fallarero, Adyary; Vuorela, Pia; Hancock, John; Abankwa, Daniel

2015-12-15

Ras isoforms H-, N-, and K-ras are each mutated in specific cancer types at varying frequencies and have different activities in cell fate control. On the plasma membrane, Ras proteins are laterally segregated into isoform-specific nanoscale signaling hubs, termed nanoclusters. As Ras nanoclusters are required for Ras signaling, chemical modulators of nanoclusters represent ideal candidates for the specific modulation of Ras activity in cancer drug development. We therefore conducted a chemical screen with commercial and in-house natural product libraries using a cell-based H-ras-nanoclustering FRET assay. Next to established Ras inhibitors, such as a statin and farnesyl-transferase inhibitor, we surprisingly identified five protein synthesis inhibitors as positive regulators. Using commonly employed cycloheximide as a representative compound, we show that protein synthesis inhibition increased nanoclustering and effector recruitment specifically of active H-ras but not of K-ras. Consistent with these data, cycloheximide treatment activated both Erk and Akt kinases and specifically promoted H-rasG12V-induced, but not K-rasG12V-induced, PC12 cell differentiation. Intriguingly, cycloheximide increased the number of mammospheres, which are enriched for cancer stem cells. Depletion of H-ras in combination with cycloheximide significantly reduced mammosphere formation, suggesting an exquisite synthetic lethality. The potential of cycloheximide to promote tumor cell growth was also reflected in its ability to increase breast cancer cell tumors grown in ovo. These results illustrate the possibility of identifying Ras-isoform-specific modulators using nanocluster-directed screening. They also suggest an unexpected feedback from protein synthesis inhibition to Ras signaling, which might present a vulnerability in certain tumor cell types.

The Human Phenotype Ontology in 2017

PubMed Central

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin; McMurry, Julie; Aymé, Ségolène; Baynam, Gareth; Bello, Susan M.; Boerkoel, Cornelius F.; Boycott, Kym M.; Brudno, Michael; Buske, Orion J.; Chinnery, Patrick F.; Cipriani, Valentina; Connell, Laureen E.; Dawkins, Hugh J.S.; DeMare, Laura E.; Devereau, Andrew D.; de Vries, Bert B.A.; Firth, Helen V.; Freson, Kathleen; Greene, Daniel; Hamosh, Ada; Helbig, Ingo; Hum, Courtney; Jähn, Johanna A.; James, Roger; Krause, Roland; F. Laulederkind, Stanley J.; Lochmüller, Hanns; Lyon, Gholson J.; Ogishima, Soichi; Olry, Annie; Ouwehand, Willem H.; Pontikos, Nikolas; Rath, Ana; Schaefer, Franz; Scott, Richard H.; Segal, Michael; Sergouniotis, Panagiotis I.; Sever, Richard; Smith, Cynthia L.; Straub, Volker; Thompson, Rachel; Turner, Catherine; Turro, Ernest; Veltman, Marijcke W.M.; Vulliamy, Tom; Yu, Jing; von Ziegenweidt, Julie; Zankl, Andreas; Züchner, Stephan; Zemojtel, Tomasz; Jacobsen, Julius O.B.; Groza, Tudor; Smedley, Damian; Mungall, Christopher J.; Haendel, Melissa; Robinson, Peter N.

2017-01-01

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology. PMID:27899602

The Human Phenotype Ontology in 2017

DOE PAGES

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; ...

2016-11-24

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical softwaremore » tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.« less

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype

PubMed Central

Ferreira, Manuel A. R.; Matheson, Melanie C.; Tang, Clara S.; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K.; Duffy, David L.; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D.; Eriksson, Nicholas; Madden, Pamela A.; Abramson, Michael J.; Holt, Patrick G.; Heath, Andrew C.; Hunter, Michael; Musk, Bill; Robertson, Colin F.; Le Souëf, Peter; Montgomery, Grant W.; Henderson, A. John; Tung, Joyce Y.; Dharmage, Shyamali C.; Brown, Matthew A.; James, Alan; Thompson, Philip J.; Pennell, Craig; Martin, Nicholas G.; Evans, David M.; Hinds, David A.; Hopper, John L.

2014-01-01

Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. PMID:24388013

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype.

PubMed

Ferreira, Manuel A R; Matheson, Melanie C; Tang, Clara S; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K; Duffy, David L; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D; Eriksson, Nicholas; Madden, Pamela A; Abramson, Michael J; Holt, Patrick G; Heath, Andrew C; Hunter, Michael; Musk, Bill; Robertson, Colin F; Le Souëf, Peter; Montgomery, Grant W; Henderson, A John; Tung, Joyce Y; Dharmage, Shyamali C; Brown, Matthew A; James, Alan; Thompson, Philip J; Pennell, Craig; Martin, Nicholas G; Evans, David M; Hinds, David A; Hopper, John L

2014-06-01

To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10(-9)) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10(-8)). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10(-7)) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10(-6)). By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Phenotype/genotype correlation in a case series of Stargardt's patients identifies novel mutations in the ABCA4 gene.

PubMed

Gemenetzi, M; Lotery, A J

2013-11-01

To investigate phenotypic variability in terms of best-corrected visual acuity (BCVA) in patients with Stargardt disease (STGD) and confirmed ABCA4 mutations. Entire coding region analysis of the ABCA4 gene by direct sequencing of seven patients with clinical findings of STGD seen in the Retina Clinics of Southampton Eye Unit between 2002 and 2011.Phenotypic variables recorded were BCVA, fluorescein angiographic appearance, electrophysiology, and visual fields. All patients had heterozygous amino acid-changing variants (missense mutations) in the ABCA4 gene. A splice sequence change was found in a 30-year-old patient with severly affected vision. Two novel sequence changes were identified: a missense mutation in a mildly affected 44-year-old patient and a frameshift mutation in a severly affected 34-year-old patient. The identified ABCA4 mutations were compatible with the resulting phenotypes in terms of BCVA. Higher BCVAs were recorded in patients with missense mutations. Sequence changes, predicted to have more deleterious effect on protein function, resulted in a more severe phenotype. This case series of STGD patients demonstrates novel genotype/phenotype correlations, which may be useful to counselling of patients. This information may prove useful in selection of candidates for clinical trials in ABCA4 disease.

Predicting new drug indications from network analysis

NASA Astrophysics Data System (ADS)

Mohd Ali, Yousoff Effendy; Kwa, Kiam Heong; Ratnavelu, Kurunathan

This work adapts centrality measures commonly used in social network analysis to identify drugs with better positions in drug-side effect network and drug-indication network for the purpose of drug repositioning. Our basic hypothesis is that drugs having similar phenotypic profiles such as side effects may also share similar therapeutic properties based on related mechanism of action and vice versa. The networks were constructed from Side Effect Resource (SIDER) 4.1 which contains 1430 unique drugs with side effects and 1437 unique drugs with indications. Within the giant components of these networks, drugs were ranked based on their centrality scores whereby 18 prominent drugs from the drug-side effect network and 15 prominent drugs from the drug-indication network were identified. Indications and side effects of prominent drugs were deduced from the profiles of their neighbors in the networks and compared to existing clinical studies while an optimum threshold of similarity among drugs was sought for. The threshold can then be utilized for predicting indications and side effects of all drugs. Similarities of drugs were measured by the extent to which they share phenotypic profiles and neighbors. To improve the likelihood of accurate predictions, only profiles such as side effects of common or very common frequencies were considered. In summary, our work is an attempt to offer an alternative approach to drug repositioning using centrality measures commonly used for analyzing social networks.

2010 drug packaging review: identifying problems to prevent errors.

PubMed

2011-06-01

Prescrire's analyses showed that the quality of drug packaging in 2010 still left much to be desired. Potentially dangerous packaging remains a significant problem: unclear labelling is source of medication errors; dosing devices for some psychotropic drugs create a risk of overdose; child-proof caps are often lacking; and too many patient information leaflets are misleading or difficult to understand. Everything that is needed for safe drug packaging is available; it is now up to regulatory agencies and drug companies to act responsibly. In the meantime, health professionals can help their patients by learning to identify the pitfalls of drug packaging and providing safe information to help prevent medication errors.

PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors

PubMed Central

Gros, Alena; Robbins, Paul F.; Yao, Xin; Li, Yong F.; Turcotte, Simon; Tran, Eric; Wunderlich, John R.; Mixon, Arnold; Farid, Shawn; Dudley, Mark E.; Hanada, Ken-ichi; Almeida, Jorge R.; Darko, Sam; Douek, Daniel C.; Yang, James C.; Rosenberg, Steven A.

2014-01-01

Adoptive transfer of tumor-infiltrating lymphocytes (TILs) can mediate regression of metastatic melanoma; however, TILs are a heterogeneous population, and there are no effective markers to specifically identify and select the repertoire of tumor-reactive and mutation-specific CD8+ lymphocytes. The lack of biomarkers limits the ability to study these cells and develop strategies to enhance clinical efficacy and extend this therapy to other malignancies. Here, we evaluated unique phenotypic traits of CD8+ TILs and TCR β chain (TCRβ) clonotypic frequency in melanoma tumors to identify patient-specific repertoires of tumor-reactive CD8+ lymphocytes. In all 6 tumors studied, expression of the inhibitory receptors programmed cell death 1 (PD-1; also known as CD279), lymphocyte-activation gene 3 (LAG-3; also known as CD223), and T cell immunoglobulin and mucin domain 3 (TIM-3) on CD8+ TILs identified the autologous tumor-reactive repertoire, including mutated neoantigen-specific CD8+ lymphocytes, whereas only a fraction of the tumor-reactive population expressed the costimulatory receptor 4-1BB (also known as CD137). TCRβ deep sequencing revealed oligoclonal expansion of specific TCRβ clonotypes in CD8+PD-1+ compared with CD8+PD-1– TIL populations. Furthermore, the most highly expanded TCRβ clonotypes in the CD8+ and the CD8+PD-1+ populations recognized the autologous tumor and included clonotypes targeting mutated antigens. Thus, in addition to the well-documented negative regulatory role of PD-1 in T cells, our findings demonstrate that PD-1 expression on CD8+ TILs also accurately identifies the repertoire of clonally expanded tumor-reactive cells and reveal a dual importance of PD-1 expression in the tumor microenvironment. PMID:24667641

Switch-backs associated with generic drugs approved using product-specific determinations of therapeutic equivalence.

PubMed

Gagne, Joshua J; Polinski, Jennifer M; Jiang, Wenlei; Dutcher, Sarah K; Xie, Jing; Lii, Joyce; Fulchino, Lisa A; Kesselheim, Aaron S

2016-08-01

US Food and Drug Administration approval for generic drugs relies on demonstrating pharmaceutical equivalence and bioequivalence; however, some drug products have unique attributes that necessitate product-specific approval pathways. We evaluated rates of patients' switching back to brand-name versions from generic versions of four drugs approved via such approaches. We used data from Optum LifeSciences Research Database to identify patients using a brand-name version of a study drug (acarbose tablets, salmon calcitonin nasal spray, enoxaparin sodium injection, and venlafaxine extended release tablets) or a control drug. We followed patients to identify switching to generic versions and then followed those who switched to identify whether they switched back to brand-name versions. We calculated switch and switch-back rates and used Kaplan-Meier and log-rank tests to compare rates between study and control drugs. Our cohort included 201 959 eligible patients. Brand-to-generic switch rates ranged from 66 to 106 switches per 100 person-years for study drugs and 80 to 110 for control drugs. Rates of switch-back to brand-name versions ranged from 5 to 37 among study drugs and 3 to 53 among control drugs. Switch-back rates were higher for venlafaxine vs. sertraline (p < 0.01) and calcitonin vs. alendronate (p = 0.01). Switch-back rates were lower for venlafaxine vs. paroxetine (p < 0.01) and acarbose vs. nateglinide (p < 0.01). Rates were similar for acarbose vs. glimepiride (p = 0.97) and for enoxaparin vs. fondiparinux (p = 0.11). As compared to control drugs, patients were not more likely to systematically switch back from generic to brand-name versions of the four study drugs. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Towards soft robotic devices for site-specific drug delivery.

PubMed

Alici, Gursel

2015-01-01

Considerable research efforts have recently been dedicated to the establishment of various drug delivery systems (DDS) that are mechanical/physical, chemical and biological/molecular DDS. In this paper, we report on the recent advances in site-specific drug delivery (site-specific, controlled, targeted or smart drug delivery are terms used interchangeably in the literature, to mean to transport a drug or a therapeutic agent to a desired location within the body and release it as desired with negligibly small toxicity and side effect compared to classical drug administration means such as peroral, parenteral, transmucosal, topical and inhalation) based on mechanical/physical systems consisting of implantable and robotic drug delivery systems. While we specifically focus on the robotic or autonomous DDS, which can be reprogrammable and provide multiple doses of a drug at a required time and rate, we briefly cover the implanted DDS, which are well-developed relative to the robotic DDS, to highlight the design and performance requirements, and investigate issues associated with the robotic DDS. Critical research issues associated with both DDSs are presented to describe the research challenges ahead of us in order to establish soft robotic devices for clinical and biomedical applications.

T-cell involvement in drug-induced acute generalized exanthematous pustulosis

PubMed Central

Britschgi, Markus; Steiner, Urs C.; Schmid, Simone; Depta, Jan P.H.; Senti, Gabriela; Bircher, Andreas; Burkhart, Christoph; Yawalkar, Nikhil; Pichler, Werner J.

2001-01-01

Acute generalized exanthematous pustulosis (AGEP) is an uncommon eruption most often provoked by drugs, by acute infections with enteroviruses, or by mercury. It is characterized by acute, extensive formation of nonfollicular sterile pustules on erythematous background, fever, and peripheral blood leukocytosis. We present clinical and immunological data on four patients with this disease, which is caused by different drugs. An involvement of T cells could be implied by positive skin patch tests and lymphocyte transformation tests. Immunohistochemistry revealed a massive cell infiltrate consisting of neutrophils in pustules and T cells in the dermis and epidermis. Expression of the potent neutrophil-attracting chemokine IL-8 was elevated in keratinocytes and infiltrating mononuclear cells. Drug-specific T cells were generated from the blood and skin of three patients, and phenotypic characterization showed a heterogeneous distribution of CD4/CD8 phenotype and of T-cell receptor Vβ-expression. Analysis of cytokine/chemokine profiles revealed that IL-8 is produced significantly more by drug-specific T cells from patients with AGEP compared with drug-specific T cells from patients that had non-AGEP exanthemas. In conclusion, our data demonstrate the involvement of drug-specific T cells in the pathomechanism of this rather rare and peculiar form of drug allergy. In addition, they indicate that even in some neutrophil-rich inflammatory responses specific T cells are engaged and might orchestrate the immune reaction. PMID:11390425

Drug Target Validation Methods in Malaria - Protein Interference Assay (PIA) as a Tool for Highly Specific Drug Target Validation.

PubMed

Meissner, Kamila A; Lunev, Sergey; Wang, Yuan-Ze; Linzke, Marleen; de Assis Batista, Fernando; Wrenger, Carsten; Groves, Matthew R

2017-01-01

The validation of drug targets in malaria and other human diseases remains a highly difficult and laborious process. In the vast majority of cases, highly specific small molecule tools to inhibit a proteins function in vivo are simply not available. Additionally, the use of genetic tools in the analysis of malarial pathways is challenging. These issues result in difficulties in specifically modulating a hypothetical drug target's function in vivo. The current "toolbox" of various methods and techniques to identify a protein's function in vivo remains very limited and there is a pressing need for expansion. New approaches are urgently required to support target validation in the drug discovery process. Oligomerisation is the natural assembly of multiple copies of a single protein into one object and this self-assembly is present in more than half of all protein structures. Thus, oligomerisation plays a central role in the generation of functional biomolecules. A key feature of oligomerisation is that the oligomeric interfaces between the individual parts of the final assembly are highly specific. However, these interfaces have not yet been systematically explored or exploited to dissect biochemical pathways in vivo. This mini review will describe the current state of the antimalarial toolset as well as the potentially druggable malarial pathways. A specific focus is drawn to the initial efforts to exploit oligomerisation surfaces in drug target validation. As alternative to the conventional methods, Protein Interference Assay (PIA) can be used for specific distortion of the target protein function and pathway assessment in vivo. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Image-based drug screen identifies HDAC inhibitors as novel Golgi disruptors synergizing with JQ1

PubMed Central

Gendarme, Mathieu; Baumann, Jan; Ignashkova, Tatiana I.; Lindemann, Ralph K.; Reiling, Jan H.

2017-01-01

The Golgi apparatus is increasingly recognized as a major hub for cellular signaling and is involved in numerous pathologies, including neurodegenerative diseases and cancer. The study of Golgi stress-induced signaling pathways relies on the selectivity of the available tool compounds of which currently only a few are known. To discover novel Golgi-fragmenting agents, transcriptomic profiles of cells treated with brefeldin A, golgicide A, or monensin were generated and compared with a database of gene expression profiles from cells treated with other bioactive small molecules. In parallel, a phenotypic screen was performed for compounds that alter normal Golgi structure. Histone deacetylase (HDAC) inhibitors and DNA-damaging agents were identified as novel Golgi disruptors. Further analysis identified HDAC1/HDAC9 as well as BRD8 and DNA-PK as important regulators of Golgi breakdown mediated by HDAC inhibition. We provide evidence that combinatorial HDACi/(+)-JQ1 treatment spurs synergistic Golgi dispersal in several cancer cell lines, pinpointing a possible link between drug-induced toxicity and Golgi morphology alterations. PMID:29074567

Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis.

PubMed

Emond, Mary J; Louie, Tin; Emerson, Julia; Zhao, Wei; Mathias, Rasika A; Knowles, Michael R; Wright, Fred A; Rieder, Mark J; Tabor, Holly K; Nickerson, Deborah A; Barnes, Kathleen C; Gibson, Ronald L; Bamshad, Michael J

2012-07-08

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis.

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Koponen, Marjaana; Tanskanen, Antti; Lavikainen, Piia; Paananen, Jussi; Tiihonen, Jari; Hartikainen, Sirpa

2017-08-01

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions. All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF. Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios. Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use. Copyright © 2017 John Wiley & Sons, Ltd.

Genetic Factors in Systemic Lupus Erythematosus: Contribution to Disease Phenotype

PubMed Central

Ceccarelli, Fulvia; Perricone, Carlo; Borgiani, Paola; Ciccacci, Cinzia; Rufini, Sara; Cipriano, Enrica; Alessandri, Cristiano; Spinelli, Francesca Romana; Sili Scavalli, Antonio; Novelli, Giuseppe; Valesini, Guido; Conti, Fabrizio

2015-01-01

Genetic factors exert an important role in determining Systemic Lupus Erythematosus (SLE) susceptibility, interplaying with environmental factors. Several genetic studies in various SLE populations have identified numerous susceptibility loci. From a clinical point of view, SLE is characterized by a great heterogeneity in terms of clinical and laboratory manifestations. As widely demonstrated, specific laboratory features are associated with clinical disease subset, with different severity degree. Similarly, in the last years, an association between specific phenotypes and genetic variants has been identified, allowing the possibility to elucidate different mechanisms and pathways accountable for disease manifestations. However, except for Lupus Nephritis (LN), no studies have been designed to identify the genetic variants associated with the development of different phenotypes. In this review, we will report data currently known about this specific association. PMID:26798662

Genetic heterogeneity among slow acetylator N-acetyltransferase 2 phenotypes in cryopreserved human hepatocytes.

PubMed

Doll, Mark A; Hein, David W

2017-07-01

Genetic polymorphisms in human N-acetyltransferase 2 (NAT2) modify the metabolism of numerous drugs and carcinogens. These genetic polymorphisms modify both drug efficacy and toxicity and cancer risk associated with carcinogen exposure. Previous studies have suggested phenotypic heterogeneity among different NAT2 slow acetylator genotypes. NAT2 phenotype was investigated in vitro and in situ in samples of human hepatocytes obtained from various NAT2 slow and intermediate NAT2 acetylator genotypes. NAT2 gene dose response (NAT2*5B/*5B > NAT2*5B/*6A > NAT2*6A/*6A) was observed towards the N-acetylation of the NAT2-specific drug sulfamethazine by human hepatocytes both in vitro and in situ. N-acetylation of 4-aminobiphenyl, an arylamine carcinogen substrate for both N-acetyltransferase 1 and NAT2, showed the same trend both in vitro and in situ although the differences were not significant (p > 0.05). The N-acetylation of the N-acetyltransferase 1-specific substrate p-aminobenzoic acid did not follow this trend. In comparisons of NAT2 intermediate acetylator genotypes, differences in N-acetylation between NAT2*4/*5B and NAT2*4/*6B hepatocytes were not observed in vitro or in situ towards any of these substrates. These results further support phenotypic heterogeneity among NAT2 slow acetylator genotypes, consistent with differential risks of drug failure or toxicity and cancer associated with carcinogen exposure.

GNAO1 encephalopathy: Broadening the phenotype and evaluating treatment and outcome.

PubMed

Danti, Federica Rachele; Galosi, Serena; Romani, Marta; Montomoli, Martino; Carss, Keren J; Raymond, F Lucy; Parrini, Elena; Bianchini, Claudia; McShane, Tony; Dale, Russell C; Mohammad, Shekeeb S; Shah, Ubaid; Mahant, Neil; Ng, Joanne; McTague, Amy; Samanta, Rajib; Vadlamani, Gayatri; Valente, Enza Maria; Leuzzi, Vincenzo; Kurian, Manju A; Guerrini, Renzo

2017-04-01

To describe better the motor phenotype, molecular genetic features, and clinical course of GNAO1 -related disease. We reviewed clinical information, video recordings, and neuroimaging of a newly identified cohort of 7 patients with de novo missense and splice site GNAO1 mutations, detected by next-generation sequencing techniques. Patients first presented in early childhood (median age of presentation 10 months, range 0-48 months), with a wide range of clinical symptoms ranging from severe motor and cognitive impairment with marked choreoathetosis, self-injurious behavior, and epileptic encephalopathy to a milder phenotype, featuring moderate developmental delay associated with complex stereotypies, mainly facial dyskinesia and mild epilepsy. Hyperkinetic movements were often exacerbated by specific triggers, such as voluntary movement, intercurrent illnesses, emotion, and high ambient temperature, leading to hospital admissions. Most patients were resistant to drug intervention, although tetrabenazine was effective in partially controlling dyskinesia for 2/7 patients. Emergency deep brain stimulation (DBS) was life saving in 1 patient, resulting in immediate clinical benefit with complete cessation of violent hyperkinetic movements. Five patients had well-controlled epilepsy and 1 had drug-resistant seizures. Structural brain abnormalities, including mild cerebral atrophy and corpus callosum dysgenesis, were evident in 5 patients. One patient had a diffuse astrocytoma (WHO grade II), surgically removed at age 16. Our findings support the causative role of GNAO1 mutations in an expanded spectrum of early-onset epilepsy and movement disorders, frequently exacerbated by specific triggers and at times associated with self-injurious behavior. Tetrabenazine and DBS were the most useful treatments for dyskinesia.

Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

PubMed

Miller, F W; Chen, W; O'Hanlon, T P; Cooper, R G; Vencovsky, J; Rider, L G; Danko, K; Wedderburn, L R; Lundberg, I E; Pachman, L M; Reed, A M; Ytterberg, S R; Padyukov, L; Selva-O'Callaghan, A; Radstake, T R; Isenberg, D A; Chinoy, H; Ollier, W E R; Scheet, P; Peng, B; Lee, A; Byun, J; Lamb, J A; Gregersen, P K; Amos, C I

2015-10-01

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis, 473 juvenile dermatomyositis, 532 polymyositis and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl-tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (P<5×10(-8)) in GWAS were identified in the major histocompatibility complex (MHC) region for all myositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1 comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations.

Genome-wide Association Study Identifies HLA 8.1 Ancestral Haplotype Alleles as Major Genetic Risk Factors for Myositis Phenotypes

PubMed Central

Miller, Frederick W.; Chen, Wei; O’Hanlon, Terrance P.; Cooper, Robert G.; Vencovsky, Jiri; Rider, Lisa G.; Danko, Katalin; Wedderburn, Lucy R.; Lundberg, Ingrid E.; Pachman, Lauren M.; Reed, Ann M.; Ytterberg, Steven R.; Padyukov, Leonid; Selva-O’Callaghan, Albert; Radstake, Timothy R.; Isenberg, David A.; Chinoy, Hector; Ollier, William E.R.; Scheet, Paul; Peng, Bo; Lee, Annette; Byun, Jinyoung; Lamb, Janine A.; Gregersen, Peter K.; Amos, Christopher I.

2016-01-01

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis; 473 juvenile dermatomyositis; 532 polymyositis; and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (P < 5 × 10−8) in GWAS were identified in the major histocompatibility complex (MHC) region for all myositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1haplotype comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations. PMID:26291516

Modified multiple drug resistance phenotype of Chinese hamster ovary cells selected with X-rays and vincristine versus X-rays only.

PubMed Central

McClean, S.; Hill, B. T.

1994-01-01

Exposure of Chinese hamster ovary (CHO) cells to fractionated X-irradiation [ten fractions of 9 Gray (Gy)] resulted in the expression of a multiple drug resistance phenotype which was distinct from that of drug-selected cells in two features: (i) resistance to vinca alkaloids and epipodophyllotoxins but sensitivity to anthracyclines was retained; (ii) overexpression of P-glycoprotein (Pgp) but regulated by post-translational stability rather than by any elevation in Pgp mRNA (Hill et al., 1990). It was also reported that when these cells (designated DXR-10) were subsequently exposed to another ten fractions of 9 Gy (20 x 9 Gy in total), no further increases in drug resistance or in the extent of Pgp expression were observed. To examine this apparent plateauing of the drug resistance phenotype following X-ray pretreatment, DXR-10 cells were instead treated with ten pulsed vincristine exposures. The resultant cell line, designated DXR-10/VCR-10, proved to be more resistant to vincristine, implying that the effect of further drug selection was additive to that of X-ray pretreatment. In addition, these cells showed resistance to doxorubicin and increased Pgp expression which was matched by a concomitant elevation in Pgp mRNA. These findings appear to confirm that Pgp expression is differentially regulated in tumour cells showing drug resistance after drug as opposed to X-ray selection. Images Figure 2 Figure 3 Figure 5 PMID:7908216

1H NMR based pharmacometabolomics analysis of urine identifies metabolic phenotype of clopidogrel high on treatment platelets reactivity in coronary artery disease patients.

PubMed

Amin, Arwa M; Sheau Chin, Lim; Teh, Chin-Hoe; Mostafa, Hamza; Mohamed Noor, Dzul Azri; Sk Abdul Kader, Muhamad Ali; Kah Hay, Yuen; Ibrahim, Baharudin

2017-11-30

Clopidogrel high on treatment platelets reactivity (HTPR) has burdened achieving optimum therapeutic outcome. Although there are known genetic and non-genetic factors associated with clopidogrel HTPR, which explain in part clopidogrel HTPR, yet, great portion remains unknown, often hindering personalizing antiplatelet therapy. Nuclear magnetic resonance ( 1 H NMR) pharmacometabolomics analysis is useful technique to phenotype drug response. We investigated using 1 H NMR analysis to phenotype clopidogrel HTPR in urine. Urine samples were collected from 71 coronary artery disease (CAD) patients who were planned for interventional angiographic procedure prior to taking 600mg clopidogrel loading dose (LD) and 6h post LD. Patients' platelets function testing was assessed with the VerifyNow ® P2Y12 assay at 6h after LD. Urine samples were analysed using 1 H NMR. Multivariate statistical analysis was used to identify metabolites associated with clopidogrel HTPR. In pre-dose samples, 16 metabolites were associated with clopidogrel HTPR. However, 18 metabolites were associated with clopidogrel HTPR in post-dose samples. The pathway analysis of the identified biomarkers reflected that multifactorial conditions are associated with clopidogrel HTPR. It also revealed the implicated role of gut microbiota in clopidogrel HTPR. Pharmacometabolomics not only discovered novel biomarkers of clopidogrel HTPR but also revealed implicated pathways and conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Virus-specific CD4+ memory phenotype T cells are abundant in unexposed adults

PubMed Central

Su, Laura F.; Kidd, Brian A.; Han, Arnold; Kotzin, Jonathan J.; Davis, Mark M.

2013-01-01

While T cell memory is generally thought to require direct antigen exposure, we find an abundance of memory phenotype cells (20–90%, averaging over 50%) of CD4+ T cells specific for viral antigens in adults that have never been infected. These cells express the appropriate memory markers and genes, rapidly produce cytokines, and have clonally expanded. This contrasts with newborns where the same T cell receptor (TCR) specificities are almost entirely naïve, which may explain the vulnerability of young children to infections. One mechanism for this phenomenon is TCR cross-reactivity to environmental antigens and in support of this we find extensive cross-recognition by HIV-1 and influenza-reactive T lymphocytes to other microbial peptides and the expansion of one of these following influenza vaccination. Thus the presence of these memory phenotype T cells has significant implications for immunity to novel pathogens, child and adult health, and the influence of pathogen-rich versus hygienic environments. PMID:23395677

Co-clustering phenome–genome for phenotype classification and disease gene discovery

PubMed Central

Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

2012-01-01

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence.

PubMed

Ahn, Woo-Young; Vassileva, Jasmin

2016-04-01

Recent animal and human studies reveal distinct cognitive and neurobiological differences between opiate and stimulant addictions; however, our understanding of the common and specific effects of these two classes of drugs remains limited due to the high rates of polysubstance-dependence among drug users. The goal of the current study was to identify multivariate substance-specific markers classifying heroin dependence (HD) and amphetamine dependence (AD), by using machine-learning approaches. Participants included 39 amphetamine mono-dependent, 44 heroin mono-dependent, 58 polysubstance dependent, and 81 non-substance dependent individuals. The majority of substance dependent participants were in protracted abstinence. We used demographic, personality (trait impulsivity, trait psychopathy, aggression, sensation seeking), psychiatric (attention deficit hyperactivity disorder, conduct disorder, antisocial personality disorder, psychopathy, anxiety, depression), and neurocognitive impulsivity measures (Delay Discounting, Go/No-Go, Stop Signal, Immediate Memory, Balloon Analogue Risk, Cambridge Gambling, and Iowa Gambling tasks) as predictors in a machine-learning algorithm. The machine-learning approach revealed substance-specific multivariate profiles that classified HD and AD in new samples with high degree of accuracy. Out of 54 predictors, psychopathy was the only classifier common to both types of addiction. Important dissociations emerged between factors classifying HD and AD, which often showed opposite patterns among individuals with HD and AD. These results suggest that different mechanisms may underlie HD and AD, challenging the unitary account of drug addiction. This line of work may shed light on the development of standardized and cost-efficient clinical diagnostic tests and facilitate the development of individualized prevention and intervention programs for HD and AD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence

PubMed Central

Ahn, Woo-Young; Vassileva, Jasmin

2016-01-01

Background Recent animal and human studies reveal distinct cognitive and neurobiological differences between opiate and stimulant addictions; however, our understanding of the common and specific effects of these two classes of drugs remains limited due to the high rates of polysubstance-dependence among drug users. Methods The goal of the current study was to identify multivariate substance-specific markers classifying heroin dependence (HD) and amphetamine dependence (AD), by using machine-learning approaches. Participants included 39 amphetamine mono-dependent, 44 heroin mono-dependent, 58 polysubstance dependent, and 81 non-substance dependent individuals. The majority of substance dependent participants were in protracted abstinence. We used demographic, personality (trait impulsivity, trait psychopathy, aggression, sensation seeking), psychiatric (attention deficit hyperactivity disorder, conduct disorder, antisocial personality disorder, psychopathy, anxiety, depression), and neurocognitive impulsivity measures (Delay Discounting, Go/No-Go, Stop Signal, Immediate Memory, Balloon Analogue Risk, Cambridge Gambling, and Iowa Gambling tasks) as predictors in a machine-learning algorithm. Results The machine-learning approach revealed substance-specific multivariate profiles that classified HD and AD in new samples with high degree of accuracy. Out of 54 predictors, psychopathy was the only classifier common to both types of addiction. Important dissociations emerged between factors classifying HD and AD, which often showed opposite patterns among individuals with HD and AD. Conclusions These results suggest that different mechanisms may underlie HD and AD, challenging the unitary account of drug addiction. This line of work may shed light on the development of standardized and cost-efficient clinical diagnostic tests and facilitate the development of individualized prevention and intervention programs for HD and AD. PMID:26905209

Silver nanoparticles induce developmental stage-specific embryonic phenotypes in zebrafish.

PubMed

Lee, Kerry J; Browning, Lauren M; Nallathamby, Prakash D; Osgood, Christopher J; Xu, Xiao-Hong Nancy

2013-12-07

Much is anticipated from the development and deployment of nanomaterials in biological organisms, but concerns remain regarding their biocompatibility and target specificity. Here we report our study of the transport, biocompatibility and toxicity of purified and stable silver nanoparticles (Ag NPs, 13.1 ± 2.5 nm in diameter) upon the specific developmental stages of zebrafish embryos using single NP plasmonic spectroscopy. We find that single Ag NPs passively diffuse into five different developmental stages of embryos (cleavage, early-gastrula, early-segmentation, late-segmentation, and hatching stages), showing stage-independent diffusion modes and diffusion coefficients. Notably, the Ag NPs induce distinctive stage and dose-dependent phenotypes and nanotoxicity, upon their acute exposure to the Ag NPs (0-0.7 nM) for only 2 h. The late-segmentation embryos are most sensitive to the NPs with the lowest critical concentration (CNP,c < 0.02 nM) and highest percentages of cardiac abnormalities, followed by early-segmentation embryos (CNP,c < 0.02 nM), suggesting that disruption of cell differentiation by the NPs causes the most toxic effects on embryonic development. The cleavage-stage embryos treated with the NPs develop into a wide variety of phenotypes (abnormal finfold, tail/spinal cord flexure, cardiac malformation/edema, yolk sac edema, and acephaly). These organ structures are not yet developed in cleavage-stage embryos, suggesting that the earliest determinative events to create these structures are ongoing, and disrupted by NPs, which leads to the downstream effects. In contrast, the hatching embryos are most resistant to the Ag NPs, and majority of embryos (94%) develop normally, and none of them develop abnormally. Interestingly, early-gastrula embryos are less sensitive to the NPs than cleavage and segmentation stage embryos, and do not develop abnormally. These important findings suggest that the Ag NPs are not simple poisons, and they can target

[Social cognition disorders in Klinefelter syndrome: A specific phenotype? (KS)].

PubMed

Babinet, M-N; Rigard, C; Peyroux, É; Dragomir, A-R; Plotton, I; Lejeune, H; Demily, C

2017-10-01

The Klinefelter syndrome (KS) is a genetic condition characterized by an X supernumerary sex chromosome in males. The syndrome is frequently associated with cognitive impairment. Indeed, the different areas of the executive sphere can be affected such as inhibition, cognitive flexibility but also attentional and visual-spatial domain. Social cognition disorders, predominantly on emotional recognition processes, have also been documented. In addition, the syndrome may be associated with psychiatric symptoms. Our study aims to characterize of the various components of social cognition in the SK: facial emotional recognition, theory of mind and attributional style. For this two groups (SK group versus control group) of participants (n=16) matched for age and sociocultural level were recruited. Participants with intellectual disabilities, psychiatric or neurological disorders were excluded. Three social cognition tests were available: the TREF, the MASC, the AIHQ. Neurocognitive functions were assessed by the fNart, the subtest "logical memory" of the MEM-III, the subtests of the two VOSP battery, the d2, the TMT and the Stroop test. The SK group had specific social cognition disorders in comparison to the control group. Two emotions in particular were less well recognized: fear and contempt. In addition, the SK group had significantly lower results in theory of mind. Regarding the hostile attribution bias, no significant difference was found. Finally, the results showed correlations between specific attentional disorders and facial emotional recognition. Our study emphasizes social cognition disorders in SK. These disorders could be considered as a phenotypic trait in the syndrome. The interest of better characterizing the cognitive phenotype of genetic disorders that can affect the neurodevelopment is to offer specific cognitive remediation strategies. Copyright © 2016. Published by Elsevier Masson SAS.

Fragment-Based Phenotypic Lead Discovery: Cell-Based Assay to Target Leishmaniasis.

PubMed

Ayotte, Yann; Bilodeau, François; Descoteaux, Albert; LaPlante, Steven R

2018-05-02

A rapid and practical approach for the discovery of new chemical matter for targeting pathogens and diseases is described. Fragment-based phenotypic lead discovery (FPLD) combines aspects of traditional fragment-based lead discovery (FBLD), which involves the screening of small-molecule fragment libraries to target specific proteins, with phenotypic lead discovery (PLD), which typically involves the screening of drug-like compounds in cell-based assays. To enable FPLD, a diverse library of fragments was first designed, assembled, and curated. This library of soluble, low-molecular-weight compounds was then pooled to expedite screening. Axenic cultures of Leishmania promastigotes were screened, and single hits were then tested for leishmanicidal activity against intracellular amastigote forms in infected murine bone-marrow-derived macrophages without evidence of toxicity toward mammalian cells. These studies demonstrate that FPLD can be a rapid and effective means to discover hits that can serve as leads for further medicinal chemistry purposes or as tool compounds for identifying known or novel targets. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A European multi-centre External Quality Assessment (EQA) study on phenotypic and genotypic methods used for Herpes Simplex Virus (HSV) drug resistance testing.

PubMed

Afshar, Baharak; Bibby, David F; Piorkowska, Renata; Ohemeng-Kumi, Natasha; Snoeck, Robert; Andrei, Graciela; Gillemot, Sarah; Morfin, Florence; Frobert, Emilie; Burrel, Sonia; Boutolleau, David; Crowley, Brendan; Mbisa, Jean L

2017-11-01

Herpes Simplex Virus (HSV) drug resistance is a significant public health concern among immunocompromised individuals. Phenotypic assays are considered the gold standard method for detecting HSV drug resistance. However, plaque reduction assays (PRAs) are technically demanding, often with long turnaround times of up to four weeks. In contrast, genotypic tests can be performed within a few days. The development and coordination of the first European External Quality Assessment (EQA) study to evaluate phenotypic and genotypic methods used for HSV drug resistance testing in specialised reference laboratories. Four HSV-1 or HSV-2 strains with different antiviral susceptibility profiles were isolated from clinical samples. Isolates were quantified by qPCR, and aliquoted in culture medium. One isolate was distributed at two dilutions to help assess assay sensitivity. The panel was distributed to five European centres with a six-week deadline for the return of phenotypic and genotypic results, together with clinical reports. Four out of five participating labs returned results by the deadline. Limited results were later available from the fifth lab. Phenotypic and genotypic data were largely, but not completely, concordant. An unusual resistance profile shown by one of the samples was explained by the detection of a mixed virus population after extensive further investigation by one of the centres. Discordant clinical outputs reflecting the diversity of phenotypic methodologies demonstrated the utility of this exercise. With emerging genotypic technologies looking to supplant phenotyping, there is a need for curated public databases, accessible interpretation tools and standardised control materials for quality management. By establishing a network of testing laboratories, we hope that this EQA scheme will facilitate ongoing progress in this area. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

A forward chemical screen in zebrafish identifies a retinoic acid derivative with receptor specificity.

PubMed

Das, Bhaskar C; McCartin, Kellie; Liu, Ting-Chun; Peterson, Randall T; Evans, Todd

2010-04-02

Retinoids regulate key developmental pathways throughout life, and have potential uses for differentiation therapy. It should be possible to identify novel retinoids by coupling new chemical reactions with screens using the zebrafish embryonic model. We synthesized novel retinoid analogues and derivatives by amide coupling, obtaining 80-92% yields. A small library of these compounds was screened for bioactivity in living zebrafish embryos. We found that several structurally related compounds significantly affect development. Distinct phenotypes are generated depending on time of exposure, and we characterize one compound (BT10) that produces specific cardiovascular defects when added 1 day post fertilization. When compared to retinoic acid (ATRA), BT10 shows similar but not identical changes in the expression pattern of embryonic genes that are known targets of the retinoid pathway. Reporter assays determined that BT10 interacts with all three RAR receptor sub-types, but has no activity for RXR receptors, at all concentrations tested. Our screen has identified a novel retinoid with specificity for retinoid receptors. This lead compound may be useful for manipulating components of retinoid signaling networks, and may be further derivatized for enhanced activity.

Gravimetric phenotyping of whole plant transpiration responses to atmospheric vapour pressure deficit identifies genotypic variation in water use efficiency.

PubMed

Ryan, Annette C; Dodd, Ian C; Rothwell, Shane A; Jones, Ros; Tardieu, Francois; Draye, Xavier; Davies, William J

2016-10-01

There is increasing interest in rapidly identifying genotypes with improved water use efficiency, exemplified by the development of whole plant phenotyping platforms that automatically measure plant growth and water use. Transpirational responses to atmospheric vapour pressure deficit (VPD) and whole plant water use efficiency (WUE, defined as the accumulation of above ground biomass per unit of water used) were measured in 100 maize (Zea mays L.) genotypes. Using a glasshouse based phenotyping platform with naturally varying VPD (1.5-3.8kPa), a 2-fold variation in WUE was identified in well-watered plants. Regression analysis of transpiration versus VPD under these conditions, and subsequent whole plant gas exchange at imposed VPDs (0.8-3.4kPa) showed identical responses in specific genotypes. Genotype response of transpiration versus VPD fell into two categories: 1) a linear increase in transpiration rate with VPD with low (high WUE) or high (low WUE) transpiration rate at all VPDs, 2) a non-linear response with a pronounced change point at low VPD (high WUE) or high VPD (low WUE). In the latter group, high WUE genotypes required a significantly lower VPD before transpiration was restricted, and had a significantly lower rate of transpiration in response to VPD after this point, when compared to low WUE genotypes. Change point values were significantly positively correlated with stomatal sensitivity to VPD. A change point in stomatal response to VPD may explain why some genotypes show contradictory WUE rankings according to whether they are measured under glasshouse or field conditions. Furthermore, this novel use of a high throughput phenotyping platform successfully reproduced the gas exchange responses of individuals measured in whole plant chambers, accelerating the identification of plants with high WUE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Proteomic study of acute respiratory distress syndrome: current knowledge and implications for drug development

PubMed Central

Levitt, Joseph E.; Rogers, Angela J.

2017-01-01

The acute respiratory distress syndrome (ARDS) is a common cause of acute respiratory failure, and is associated with substantial mortality and morbidity. Dozens of clinical trials targeting ARDS have failed, with no drug specifically targeting lung injury in widespread clinical use. Thus, the need for drug development in ARDS is great. Targeted proteomic studies in ARDS have identified many key pathways in the disease, including inflammation, epithelial injury, endothelial injury or activation, and disordered coagulation and repair. Recent studies reveal the potential for proteomic changes to identify novel subphenotypes of ARDS patients who may be most likely to respond to therapy and could thus be targeted for enrollment in clinical trials. Nontargeted studies of proteomics in ARDS are just beginning and have the potential to identify novel drug targets and key pathways in the disease. Proteomics will play an important role in phenotyping of patients and developing novel therapies for ARDS in the future. PMID:27031735

Phenotypic analysis of perennial airborne allergen-specific CD4+ T cells in atopic and non-atopic individuals.

PubMed

Crack, L R; Chan, H W; McPherson, T; Ogg, G S

2011-11-01

Accumulating evidence suggests that T cells play an important role in the pathogenesis of atopic dermatitis (AD); yet, little is known of the differentiation status of CD4+ T cells specific for common environmental allergens, such as the major cat allergen, Fel d 1. To determine the frequency, differentiation phenotype and function of circulating Fel d 1-specific CD4+ T cells in adult individuals with severe persistent AD in comparison with healthy controls. Using HLA class II tetrameric complexes based on a HLA-DPB1*0401-restricted Fel d 1 epitope, ex vivo and cultured T cell frequency and phenotype were analysed in individuals with AD and healthy controls. Cytokine secretion was measured by ex vivo and cultured IL-4 and IFN-γ ELISpots. Ex vivo Fel d 1-specific DPB1*0401-restricted CD4+ T cells in both atopics and non-atopics express high levels of CCR7, CD62L, CD27 and CD28, placing the cells largely within the central memory subgroup. However, the functional phenotype was distinct, with greater IL-4 production from the cells derived from atopics, which correlated with disease severity. Circulating Fel d 1-specific DPB1*0401-restricted CD4+ T cells in both atopic and non-atopic donors maintain a central memory phenotype; however in atopics, the cells had greater Th2 effector function, compatible with a disease model of altered antigen delivery in atopic individuals. © 2011 Blackwell Publishing Ltd.

Characterization of Mycobacterium tuberculosis isolates from Hebei, China: genotypes and drug susceptibility phenotypes.

PubMed

Li, Yanan; Cao, Xinrui; Li, Shiming; Wang, Hao; Wei, Jianlin; Liu, Peng; Wang, Jing; Zhang, Zhi; Gao, Huixia; Li, Machao; Wan, Kanglin; Dai, Erhei

2016-03-03

Tuberculosis remains a major public health problem in China. The Hebei province is located in the Beijing-Tianjin-Hebei integration region; however little information about the genetic diversity of Mycobacterium tuberculosis was available in this area. This study describes the first attempt to map the molecular epidemiology of MTB strains isolated from Hebei. Spoligotyping and 15-locus MIRU-VNTR were performed in combination to yield specific genetic profiles of 1017 MTB strains isolated from ten cities in the Hebei province in China during 2014. Susceptibility testing to first line anti-TB drugs was also conducted for all strains using the L-J proportion method. Based on the SpolDB4.0 database, the predominant spoligotype belonged to the Beijing family (90.5%), followed by T family (6.3%). Using 15-locus MIRU-VNTR clustering analysis, 846 different patterns were identified, including 84 clusters (2-17 strains per cluster) and 764 individual types. Drug susceptibility pattern showed that 347 strains (34.1%) were resistant to at least one of the first line drugs, including 134 (13.2%) multi-drug resistance strains. Statistical analysis indicated that drug resistance was associated with treatment history. The Beijing family was associated with genetic clustering. However, no significant difference was observed between the Beijing and non-Beijing family in gender, age, treatment history and drug resistance. The Mycobacterium tuberculosis strains in Hebei exhibit high genetic diversity. The Beijing family is the most prevalent lineage in this area. Spoligotyping in combination with 15-locus MIRU-VNTR is a useful tool to study the molecular epidemiology of the MTB strains in Hebei.

Drug Intervention Response Predictions with PARADIGM (DIRPP) identifies drug resistant cancer cell lines and pathway mechanisms of resistance.

PubMed

Brubaker, Douglas; Difeo, Analisa; Chen, Yanwen; Pearl, Taylor; Zhai, Kaide; Bebek, Gurkan; Chance, Mark; Barnholtz-Sloan, Jill

2014-01-01

The revolution in sequencing techniques in the past decade has provided an extensive picture of the molecular mechanisms behind complex diseases such as cancer. The Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Project (CGP) have provided an unprecedented opportunity to examine copy number, gene expression, and mutational information for over 1000 cell lines of multiple tumor types alongside IC50 values for over 150 different drugs and drug related compounds. We present a novel pipeline called DIRPP, Drug Intervention Response Predictions with PARADIGM7, which predicts a cell line's response to a drug intervention from molecular data. PARADIGM (Pathway Recognition Algorithm using Data Integration on Genomic Models) is a probabilistic graphical model used to infer patient specific genetic activity by integrating copy number and gene expression data into a factor graph model of a cellular network. We evaluated the performance of DIRPP on endometrial, ovarian, and breast cancer related cell lines from the CCLE and CGP for nine drugs. The pipeline is sensitive enough to predict the response of a cell line with accuracy and precision across datasets as high as 80 and 88% respectively. We then classify drugs by the specific pathway mechanisms governing drug response. This classification allows us to compare drugs by cellular response mechanisms rather than simply by their specific gene targets. This pipeline represents a novel approach for predicting clinical drug response and generating novel candidates for drug repurposing and repositioning.

Systematic drug screening reveals specific vulnerabilities and co-resistance patterns in endocrine-resistant breast cancer.

PubMed

Kangaspeska, Sara; Hultsch, Susanne; Jaiswal, Alok; Edgren, Henrik; Mpindi, John-Patrick; Eldfors, Samuli; Brück, Oscar; Aittokallio, Tero; Kallioniemi, Olli

2016-07-04

The estrogen receptor (ER) inhibitor tamoxifen reduces breast cancer mortality by 31 % and has served as the standard treatment for ER-positive breast cancers for decades. However, 50 % of advanced ER-positive cancers display de novo resistance to tamoxifen, and acquired resistance evolves in 40 % of patients who initially respond. Mechanisms underlying resistance development remain poorly understood and new therapeutic opportunities are urgently needed. Here, we report the generation and characterization of seven tamoxifen-resistant breast cancer cell lines from four parental strains. Using high throughput drug sensitivity and resistance testing (DSRT) with 279 approved and investigational oncology drugs, exome-sequencing and network analysis, we for the first time, systematically determine the drug response profiles specific to tamoxifen resistance. We discovered emerging vulnerabilities towards specific drugs, such as ERK1/2-, proteasome- and BCL-family inhibitors as the cells became tamoxifen-resistant. Co-resistance to other drugs such as the survivin inhibitor YM155 and the chemotherapeutic agent paclitaxel also occurred. This study indicates that multiple molecular mechanisms dictate endocrine resistance, resulting in unexpected vulnerabilities to initially ineffective drugs, as well as in emerging co-resistances. Thus, combatting drug-resistant tumors will require patient-tailored strategies in order to identify new drug vulnerabilities, and to understand the associated co-resistance patterns.

Characterization of parasite-specific indels and their proposed relevance for selective anthelminthic drug targeting

PubMed Central

Wang, Qi; Heizer, Esley; Rosa, Bruce A.; Wildman, Scott A.; Janetka, James W.; Mitreva, Makedonka

2016-01-01

Insertions and deletions (indels) are important sequence variants that are considered as phylogenetic markers that reflect evolutionary adaptations in different species. In an effort to systematically study indels specific to the phylum Nematoda and their structural impact on the proteins bearing them, we examined over 340,000 polypeptides from 21 nematode species spanning the phylum, compared them to non-nematodes and identified indels unique to nematode proteins in more than 3,000 protein families. Examination of the amino acid composition revealed uneven usage of amino acids for insertions and deletions. The amino acid composition and cost, along with the secondary structure constitution of the indels, were analyzed in the context of their biological pathway associations. Species-specific indels could enable indel-based targeting for drug design in pathogens/parasites. Therefore, we screened the spatial locations of the indels in the parasite’s protein 3D structures, determined the location of the indel and identified potential unique drug targeting sites. These indels could be confirmed by RNA-Seq data. Examples are presented that illustrate the close proximity of the indel to established small-molecule binding pockets that can potentially facilitate selective targeting to the parasites and bypassing their host, thus reducing or eliminating the toxicity of the potential drugs. The study presents an approach for understanding the adaptation of pathogens/parasites at a molecular level, and outlines a strategy to identify such nematode-selective targets that remain essential to the organism. With further experimental characterization and validation, it opens a possible channel for the development of novel treatments with high target specificity, addressing both host toxicity and resistance concerns. PMID:26829384

Characterization of parasite-specific indels and their proposed relevance for selective anthelminthic drug targeting.

PubMed

Wang, Qi; Heizer, Esley; Rosa, Bruce A; Wildman, Scott A; Janetka, James W; Mitreva, Makedonka

2016-04-01

Insertions and deletions (indels) are important sequence variants that are considered as phylogenetic markers that reflect evolutionary adaptations in different species. In an effort to systematically study indels specific to the phylum Nematoda and their structural impact on the proteins bearing them, we examined over 340,000 polypeptides from 21 nematode species spanning the phylum, compared them to non-nematodes and identified indels unique to nematode proteins in more than 3000 protein families. Examination of the amino acid composition revealed uneven usage of amino acids for insertions and deletions. The amino acid composition and cost, along with the secondary structure constitution of the indels, were analyzed in the context of their biological pathway associations. Species-specific indels could enable indel-based targeting for drug design in pathogens/parasites. Therefore, we screened the spatial locations of the indels in the parasite's protein 3D structures, determined the location of the indel and identified potential unique drug targeting sites. These indels could be confirmed by RNA-Seq data. Examples are presented illustrating the close proximity of some indels to established small-molecule binding pockets that can potentially facilitate selective targeting to the parasites and bypassing their host, thus reducing or eliminating the toxicity of the potential drugs. This study presents an approach for understanding the adaptation of pathogens/parasites at a molecular level, and outlines a strategy to identify such nematode-selective targets that remain essential to the organism. With further experimental characterization and validation, it opens a possible channel for the development of novel treatments with high target specificity, addressing both host toxicity and resistance concerns. Copyright © 2016 Elsevier B.V. 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

Identifying the translational gap in the evaluation of drug-induced QTc interval prolongation

PubMed Central

Chain, Anne SY; Dubois, Vincent FS; Danhof, Meindert; Sturkenboom, Miriam CJM; Della Pasqua, Oscar

2013-01-01

Aims Given the similarities in QTc response between dogs and humans, dogs are used in pre-clinical cardiovascular safety studies. The objective of our investigation was to characterize the PKPD relationships and identify translational gaps across species following the administration of three compounds known to cause QTc interval prolongation, namely cisapride, d, l-sotalol and moxifloxacin. Methods Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and clinical trials were included in this analysis. First, pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. A Bayesian PKPD model was then used to describe QT prolongation, allowing discrimination of drug-specific effects from other physiological factors known to alter QT interval duration. A threshold of ≥10 ms was used to explore the probability of prolongation after drug administration. Results A linear relationship was found to best describe the pro-arrhythmic effects of cisapride, d,l-sotalol and moxifloxacin both in dogs and in humans. The drug-specific parameter (slope) in dogs was statistically significantly different from humans. Despite such differences, our results show that the probability of QTc prolongation ≥10 ms in dogs nears 100% for all three compounds at the therapeutic exposure range in humans. Conclusions Our findings indicate that the slope of PKPD relationship in conscious dogs may be used as the basis for the prediction of drug-induced QTc prolongation in humans. Furthermore, the risk of QTc prolongation can be expressed in terms of the probability associated with an increase ≥10 ms, allowing direct inferences about the clinical relevance of the pro-arrhythmic potential of a molecule. PMID:23351036

An Updated Review of the Molecular Mechanisms in Drug Hypersensitivity

PubMed Central

Abe, Riichiro; Pan, Ren-You; Wang, Chuang-Wei

2018-01-01

Drug hypersensitivity may manifest ranging from milder skin reactions (e.g., maculopapular exanthema and urticaria) to severe systemic reactions, such as anaphylaxis, drug reactions with eosinophilia and systemic symptoms (DRESS)/drug-induced hypersensitivity syndrome (DIHS), or Stevens–Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN). Current pharmacogenomic studies have made important strides in the prevention of some drug hypersensitivity through the identification of relevant genetic variants, particularly for genes encoding drug-metabolizing enzymes and human leukocyte antigens (HLAs). The associations identified by these studies are usually drug, phenotype, and ethnic specific. The drug presentation models that explain how small drug antigens might interact with HLA and T cell receptor (TCR) molecules in drug hypersensitivity include the hapten theory, the p-i concept, the altered peptide repertoire model, and the altered TCR repertoire model. The broad spectrum of clinical manifestations of drug hypersensitivity involving different drugs, as well as the various pathomechanisms involved, makes the diagnosis and management of it more challenging. This review highlights recent advances in our understanding of the predisposing factors, immune mechanisms, pathogenesis, diagnostic tools, and therapeutic approaches for drug hypersensitivity. PMID:29651444

Comparative analysis of Edwardsiella isolates from fish in the eastern United States identifies two distinct genetic taxa amongst organisms phenotypically classified as E. tarda

USGS Publications Warehouse

Griffin, Matt J.; Quiniou, Sylvie M.; Cody, Theresa; Tabuchi, Maki; Ware, Cynthia; Cipriano, Rocco C.; Mauel, Michael J.; Soto, Esteban

2013-01-01

Edwardsiella tarda, a Gram-negative member of the family Enterobacteriaceae, has been implicated in significant losses in aquaculture facilities worldwide. Here, we assessed the intra-specific variability of E. tarda isolates from 4 different fish species in the eastern United States. Repetitive sequence mediated PCR (rep-PCR) using 4 different primer sets (ERIC I & II, ERIC II, BOX, and GTG5) and multi-locus sequence analysis of 16S SSU rDNA, groEl, gyrA, gyrB, pho, pgi, pgm, and rpoA gene fragments identified two distinct genotypes of E. tarda (DNA group I; DNA group II). Isolates that fell into DNA group II demonstrated more similarity to E. ictaluri than DNA group I, which contained the reference E. tarda strain (ATCC #15947). Conventional PCR analysis using published E. tarda-specific primer sets yielded variable results, with several primer sets producing no observable amplification of target DNA from some isolates. Fluorometric determination of G + C content demonstrated 56.4% G + C content for DNA group I, 60.2% for DNA group II, and 58.4% for E. ictaluri. Surprisingly, these isolates were indistinguishable using conventional biochemical techniques, with all isolates demonstrating phenotypic characteristics consistent with E. tarda. Analysis using two commercial test kits identified multiple phenotypes, although no single metabolic characteristic could reliably discriminate between genetic groups. Additionally, anti-microbial susceptibility and fatty acid profiles did not demonstrate remarkable differences between groups. The significant genetic variation (<90% similarity at gyrA, gyrB, pho, phi and pgm; <40% similarity by rep-PCR) between these groups suggests organisms from DNA group II may represent an unrecognized, genetically distinct taxa of Edwardsiella that is phenotypically indistinguishable from E. tarda.

Epistasis and Pleiotropy Affect the Modularity of the Genotype-Phenotype Map of Cross-Resistance in HIV-1.

PubMed

Polster, Robert; Petropoulos, Christos J; Bonhoeffer, Sebastian; Guillaume, Frédéric

2016-12-01

The genotype-phenotype (GP) map is a central concept in evolutionary biology as it describes the mapping of molecular genetic variation onto phenotypic trait variation. Our understanding of that mapping remains partial, especially when trying to link functional clustering of pleiotropic gene effects with patterns of phenotypic trait co-variation. Only on rare occasions have studies been able to fully explore that link and tend to show poor correspondence between modular structures within the GP map and among phenotypes. By dissecting the structure of the GP map of the replicative capacity of HIV-1 in 15 drug environments, we provide a detailed view of that mapping from mutational pleiotropic variation to phenotypic co-variation, including epistatic effects of a set of amino-acid substitutions in the reverse transcriptase and protease genes. We show that epistasis increases the pleiotropic degree of single mutations and provides modularity to the GP map of drug resistance in HIV-1. Moreover, modules of epistatic pleiotropic effects within the GP map match the phenotypic modules of correlated replicative capacity among drug classes. Epistasis thus increases the evolvability of cross-resistance in HIV by providing more drug- and class-specific pleiotropic profiles to the main effects of the mutations. We discuss the implications for the evolution of cross-resistance in HIV. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study.

PubMed

Rastegar-Mojarad, Majid; Liu, Hongfang; Nambisan, Priya

2016-06-16

Drug repurposing (defined as discovering new indications for existing drugs) could play a significant role in drug development, especially considering the declining success rates of developing novel drugs. Typically, new indications for existing medications are identified by accident. However, new technologies and a large number of available resources enable the development of systematic approaches to identify and validate drug-repurposing candidates. Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications. Our aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing. We retrieved patient reviews of 180 medications from an online forum, WebMD. Using dictionary-based and machine learning approaches, we identified disease names in the reviews. Several publicly available resources were used to exclude comments containing known indications and adverse drug effects. After manually reviewing some of the remaining comments, we implemented a rule-based system to identify beneficial effects. The dictionary-based system and machine learning system identified 2178 and 6171 disease names respectively in 64,616 patient comments. We provided a list of 10 common patterns that patients used to report any beneficial effects or uses of medication. After manually reviewing the comments tagged by our rule-based system, we identified five potential drug repurposing candidates. To our knowledge, this is the first study to consider using social media data to identify drug-repurposing candidates. We found that even a rule-based system, with a limited number of rules, could identify beneficial effect mentions in patient comments. Our preliminary study shows that social media has the potential to be used in drug repurposing.

Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer.

PubMed

Tang, Yew Chung; Ho, Szu-Chi; Tan, Elisabeth; Ng, Alvin Wei Tian; McPherson, John R; Goh, Germaine Yen Lin; Teh, Bin Tean; Bard, Frederic; Rozen, Steven G

2018-03-22

Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers. To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data. The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets. Six genes showed PTEN

Historeceptomic Fingerprints for Drug-Like Compounds.

PubMed

Shmelkov, Evgeny; Grigoryan, Arsen; Swetnam, James; Xin, Junyang; Tivon, Doreen; Shmelkov, Sergey V; Cardozo, Timothy

2015-01-01

Most drugs exert their beneficial and adverse effects through their combined action on several different molecular targets (polypharmacology). The true molecular fingerprint of the direct action of a drug has two components: the ensemble of all the receptors upon which a drug acts and their level of expression in organs/tissues. Conversely, the fingerprint of the adverse effects of a drug may derive from its action in bystander tissues. The ensemble of targets is almost always only partially known. Here we describe an approach improving upon and integrating both components: in silico identification of a more comprehensive ensemble of targets for any drug weighted by the expression of those receptors in relevant tissues. Our system combines more than 300,000 experimentally determined bioactivity values from the ChEMBL database and 4.2 billion molecular docking scores. We integrated these scores with gene expression data for human receptors across a panel of human tissues to produce drug-specific tissue-receptor (historeceptomics) scores. A statistical model was designed to identify significant scores, which define an improved fingerprint representing the unique activity of any drug. These multi-dimensional historeceptomic fingerprints describe, in a novel, intuitive, and easy to interpret style, the holistic, in vivo picture of the mechanism of any drug's action. Valuable applications in drug discovery and personalized medicine, including the identification of molecular signatures for drugs with polypharmacologic modes of action, detection of tissue-specific adverse effects of drugs, matching molecular signatures of a disease to drugs, target identification for bioactive compounds with unknown receptors, and hypothesis generation for drug/compound phenotypes may be enabled by this approach. The system has been deployed at drugable.org for access through a user-friendly web site.

Active Learning Strategies for Phenotypic Profiling of High-Content Screens.

PubMed

Smith, Kevin; Horvath, Peter

2014-06-01

High-content screening is a powerful method to discover new drugs and carry out basic biological research. Increasingly, high-content screens have come to rely on supervised machine learning (SML) to perform automatic phenotypic classification as an essential step of the analysis. However, this comes at a cost, namely, the labeled examples required to train the predictive model. Classification performance increases with the number of labeled examples, and because labeling examples demands time from an expert, the training process represents a significant time investment. Active learning strategies attempt to overcome this bottleneck by presenting the most relevant examples to the annotator, thereby achieving high accuracy while minimizing the cost of obtaining labeled data. In this article, we investigate the impact of active learning on single-cell-based phenotype recognition, using data from three large-scale RNA interference high-content screens representing diverse phenotypic profiling problems. We consider several combinations of active learning strategies and popular SML methods. Our results show that active learning significantly reduces the time cost and can be used to reveal the same phenotypic targets identified using SML. We also identify combinations of active learning strategies and SML methods which perform better than others on the phenotypic profiling problems we studied. © 2014 Society for Laboratory Automation and Screening.

Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

PubMed Central

van Leeuwen, Elisabeth M.; Karssen, Lennart C.; Deelen, Joris; Isaacs, Aaron; Medina-Gomez, Carolina; Mbarek, Hamdi; Kanterakis, Alexandros; Trompet, Stella; Postmus, Iris; Verweij, Niek; van Enckevort, David J.; Huffman, Jennifer E.; White, Charles C.; Feitosa, Mary F.; Bartz, Traci M.; Manichaikul, Ani; Joshi, Peter K.; Peloso, Gina M.; Deelen, Patrick; van Dijk, Freerk; Willemsen, Gonneke; de Geus, Eco J.; Milaneschi, Yuri; Penninx, Brenda W.J.H.; Francioli, Laurent C.; Menelaou, Androniki; Pulit, Sara L.; Rivadeneira, Fernando; Hofman, Albert; Oostra, Ben A.; Franco, Oscar H.; Leach, Irene Mateo; Beekman, Marian; de Craen, Anton J.M.; Uh, Hae-Won; Trochet, Holly; Hocking, Lynne J.; Porteous, David J.; Sattar, Naveed; Packard, Chris J.; Buckley, Brendan M.; Brody, Jennifer A.; Bis, Joshua C.; Rotter, Jerome I.; Mychaleckyj, Josyf C.; Campbell, Harry; Duan, Qing; Lange, Leslie A.; Wilson, James F.; Hayward, Caroline; Polasek, Ozren; Vitart, Veronique; Rudan, Igor; Wright, Alan F.; Rich, Stephen S.; Psaty, Bruce M.; Borecki, Ingrid B.; Kearney, Patricia M.; Stott, David J.; Adrienne Cupples, L.; Neerincx, Pieter B.T.; Elbers, Clara C.; Francesco Palamara, Pier; Pe'er, Itsik; Abdellaoui, Abdel; Kloosterman, Wigard P.; van Oven, Mannis; Vermaat, Martijn; Li, Mingkun; Laros, Jeroen F.J.; Stoneking, Mark; de Knijff, Peter; Kayser, Manfred; Veldink, Jan H.; van den Berg, Leonard H.; Byelas, Heorhiy; den Dunnen, Johan T.; Dijkstra, Martijn; Amin, Najaf; Joeri van der Velde, K.; van Setten, Jessica; Kattenberg, Mathijs; van Schaik, Barbera D.C.; Bot, Jan; Nijman, Isaäc J.; Mei, Hailiang; Koval, Vyacheslav; Ye, Kai; Lameijer, Eric-Wubbo; Moed, Matthijs H.; Hehir-Kwa, Jayne Y.; Handsaker, Robert E.; Sunyaev, Shamil R.; Sohail, Mashaal; Hormozdiari, Fereydoun; Marschall, Tobias; Schönhuth, Alexander; Guryev, Victor; Suchiman, H. Eka D.; Wolffenbuttel, Bruce H.; Platteel, Mathieu; Pitts, Steven J.; Potluri, Shobha; Cox, David R.; Li, Qibin; Li, Yingrui; Du, Yuanping; Chen, Ruoyan; Cao, Hongzhi; Li, Ning; Cao, Sujie; Wang, Jun; Bovenberg, Jasper A.; Jukema, J. Wouter; van der Harst, Pim; Sijbrands, Eric J.; Hottenga, Jouke-Jan; Uitterlinden, Andre G.; Swertz, Morris A.; van Ommen, Gert-Jan B.; de Bakker, Paul I.W.; Eline Slagboom, P.; Boomsma, Dorret I.; Wijmenga, Cisca; van Duijn, Cornelia M.

2015-01-01

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10−4), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR. PMID:25751400

A simple and predictive phenotypic High Content Imaging assay for Plasmodium falciparum mature gametocytes to identify malaria transmission blocking compounds

PubMed Central

Lucantoni, Leonardo; Silvestrini, Francesco; Signore, Michele; Siciliano, Giulia; Eldering, Maarten; Dechering, Koen J.; Avery, Vicky M.; Alano, Pietro

2015-01-01

Plasmodium falciparum gametocytes, specifically the mature stages, are the only malaria parasite stage in humans transmissible to the mosquito vector. Anti-malarial drugs capable of killing these forms are considered essential for the eradication of malaria and tools allowing the screening of large compound libraries with high predictive power are needed to identify new candidates. As gametocytes are not a replicative stage it is difficult to apply the same drug screening methods used for asexual stages. Here we propose an assay, based on high content imaging, combining “classic” gametocyte viability readout based on gametocyte counts with a functional viability readout, based on gametocyte activation and the discrimination of the typical gamete spherical morphology. This simple and rapid assay has been miniaturized to a 384-well format using acridine orange staining of wild type P. falciparum 3D7A sexual forms, and was validated by screening reference antimalarial drugs and the MMV Malaria Box. The assay demonstrated excellent robustness and ability to identify quality hits with high likelihood of confirmation of transmission reducing activity in subsequent mosquito membrane feeding assays. PMID:26553647

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

Comment on 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' by Lam et al.

PubMed

Hill, W David

2018-04-01

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as 'trait specific' to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

Phenotypes of antibody-mediated rejection in organ transplants.

PubMed

Mengel, Michael; Husain, Sufia; Hidalgo, Luis; Sis, Banu

2012-06-01

Antibody-mediated hyperacute rejection was the first rejection phenotype observed in human organ transplants. This devastating phenotype was eliminated by reliable crossmatch technologies. Since then, the focus was on T-cell-mediated rejection and de novo donor-specific antibodies were considered an epiphenomenon of cognate T-cell activation. The immune theory was that controlling the T-cell response would entail elimination of antibody-mediated rejection (ABMR). With modern immunosuppressive drugs, T-cell-mediated rejection is essentially treatable. However, this did not prevent ABMR from emerging as a significant phenotype in all types of organ transplants. It became obvious that both rejection types require distinct treatment and thus reliable diagnosis. This is the current challenge. ABMR, depending on stage, grade, time course, organ type or prior treatment, can present with a wide spectrum of phenotypes. This review summarizes the current diagnostic consensus for ABMR, describes unmet needs and challenges in diagnostics, and proposes new approaches for consideration. © 2012 The Authors. Transplant International © 2012 European Society for Organ Transplantation.

Drug specificity in drug versus food choice in male rats.

PubMed

Tunstall, Brendan J; Riley, Anthony L; Kearns, David N

2014-08-01

Although different classes of drug differ in their mechanisms of reinforcement and effects on behavior, little research has focused on differences in self-administration behaviors maintained by users of these drugs. Persistent drug choice despite available reinforcement alternatives has been proposed to model behavior relevant to addiction. The present study used a within-subjects procedure, where male rats (Long-Evans, N = 16) were given a choice between cocaine (1.0 mg/kg/infusion) and food (a single 45-mg grain pellet) or between heroin (0.02 mg/kg/infusion) and food in separate phases (drug order counterbalanced). All rats were initially trained to self-administer each drug, and the doses used were based on previous studies showing that small subsets of rats tend to prefer drug over food reinforcement. The goal of the present study was to determine whether rats that prefer cocaine would also prefer heroin. Choice sessions consisted of 2 forced-choice trials with each reinforcer, followed by 14 free-choice trials (all trials separated by 10-min intertrial interval). Replicating previous results, small subsets of rats preferred either cocaine (5 of the 16 rats) or heroin (2 of the 16 rats) to the food alternative. Although 1 of the 16 rats demonstrated a preference for both cocaine and heroin to the food alternative, there was no relationship between degree of cocaine and heroin preference in individual rats. The substance-specific pattern of drug preference observed suggests that at least in this animal model, the tendencies to prefer cocaine or heroin in preference to a nondrug alternative are distinct behavioral phenomena.

Phenotypic and functional characterization of circulating polyomavirus BK VP1-specific CD8+ T cells in healthy adults.

PubMed

van Aalderen, Michiel C; Remmerswaal, Ester B M; Heutinck, Kirstin M; ten Brinke, Anja; Pircher, Hanspeter; van Lier, René A W; ten Berge, Ineke J M

2013-09-01

The human polyomavirus BK virus (BKV) establishes a latent and asymptomatic infection in the majority of the population. In immunocompromised individuals, the virus frequently (re)activates and may cause severe disease such as interstitial nephritis and hemorrhagic cystitis. Currently, the therapeutic options are limited to reconstitution of the antiviral immune response. T cells are particularly important for controlling this virus, and T cell therapies may provide a highly specific and effective mode of treatment. However, little is known about the phenotype and function of BKV-specific T cells in healthy individuals. Using tetrameric BKV peptide-HLA-A02 complexes, we determined the presence, phenotype, and functional characteristics of circulating BKV VP1-specific CD8(+) T cells in 5 healthy individuals. We show that these cells are present in low frequencies in the circulation and that they have a resting CD45RA(-) CD27(+) memory and predominantly CCR7(-) CD127(+) KLRG1(+) CD49d(hi) CXCR3(hi) T-bet(int) Eomesodermin(lo) phenotype. Furthermore, their direct cytotoxic capacity seems to be limited, since they do not readily express granzyme B and express only little granzyme K. We compared these cells to circulating CD8(+) T cells specific for cytomegalovirus (CMV), Epstein-Barr virus (EBV), and influenza virus (Flu) in the same donors and show that BKV-specific T cells have a phenotype that is distinct from that of CMV- and EBV-specific T cells. Lastly, we show that BKV-specific T cells are polyfunctional since they are able to rapidly express interleukin-2 (IL-2), gamma interferon (IFN-γ), tumor necrosis factor α, and also, to a much lower extent, MIP-1β and CD107a.

Phenotypic and Functional Characterization of Circulating Polyomavirus BK VP1-Specific CD8+ T Cells in Healthy Adults

PubMed Central

Remmerswaal, Ester B. M.; Heutinck, Kirstin M.; ten Brinke, Anja; Pircher, Hanspeter; van Lier, René A. W.; ten Berge, Ineke J. M.

2013-01-01

The human polyomavirus BK virus (BKV) establishes a latent and asymptomatic infection in the majority of the population. In immunocompromised individuals, the virus frequently (re)activates and may cause severe disease such as interstitial nephritis and hemorrhagic cystitis. Currently, the therapeutic options are limited to reconstitution of the antiviral immune response. T cells are particularly important for controlling this virus, and T cell therapies may provide a highly specific and effective mode of treatment. However, little is known about the phenotype and function of BKV-specific T cells in healthy individuals. Using tetrameric BKV peptide-HLA-A02 complexes, we determined the presence, phenotype, and functional characteristics of circulating BKV VP1-specific CD8+ T cells in 5 healthy individuals. We show that these cells are present in low frequencies in the circulation and that they have a resting CD45RA− CD27+ memory and predominantly CCR7− CD127+ KLRG1+ CD49dhi CXCR3hi T-betint Eomesoderminlo phenotype. Furthermore, their direct cytotoxic capacity seems to be limited, since they do not readily express granzyme B and express only little granzyme K. We compared these cells to circulating CD8+ T cells specific for cytomegalovirus (CMV), Epstein-Barr virus (EBV), and influenza virus (Flu) in the same donors and show that BKV-specific T cells have a phenotype that is distinct from that of CMV- and EBV-specific T cells. Lastly, we show that BKV-specific T cells are polyfunctional since they are able to rapidly express interleukin-2 (IL-2), gamma interferon (IFN-γ), tumor necrosis factor α, and also, to a much lower extent, MIP-1β and CD107a. PMID:23864628

Rationale and uses of a public HIV drug-resistance database.

PubMed

Shafer, Robert W

2006-09-15

Knowledge regarding the drug resistance of human immunodeficiency virus (HIV) is critical for surveillance of drug resistance, development of antiretroviral drugs, and management of infections with drug-resistant viruses. Such knowledge is derived from studies that correlate genetic variation in the targets of therapy with the antiretroviral treatments received by persons from whom the variant was obtained (genotype-treatment), with drug-susceptibility data on genetic variants (genotype-phenotype), and with virological and clinical response to a new treatment regimen (genotype-outcome). An HIV drug-resistance database is required to represent, store, and analyze the diverse forms of data underlying our knowledge of drug resistance and to make these data available to the broad community of researchers studying drug resistance in HIV and clinicians using HIV drug-resistance tests. Such genotype-treatment, genotype-phenotype, and genotype-outcome correlations are contained in the Stanford HIV RT and Protease Sequence Database and have specific usefulness.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.

PubMed

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-09-07

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

PubMed Central

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-01-01

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications. PMID:27599720

Distinct Phenotypes of Cigarette Smokers Identified by Cluster Analysis of Patients with Severe Asthma.

PubMed

Konno, Satoshi; Taniguchi, Natsuko; Makita, Hironi; Nakamaru, Yuji; Shimizu, Kaoruko; Shijubo, Noriharu; Fuke, Satoshi; Takeyabu, Kimihiro; Oguri, Mitsuru; Kimura, Hirokazu; Maeda, Yukiko; Suzuki, Masaru; Nagai, Katsura; Ito, Yoichi M; Wenzel, Sally E; Nishimura, Masaharu

2015-12-01

Smoking may have multifactorial effects on asthma phenotypes, particularly in severe asthma. Cluster analysis has been applied to explore novel phenotypes, which are not based on any a priori hypotheses. To explore novel severe asthma phenotypes by cluster analysis when including cigarette smokers. We recruited a total of 127 subjects with severe asthma, including 59 current or ex-smokers, from our university hospital and its 29 affiliated hospitals/pulmonary clinics. Twelve clinical variables obtained during a 2-day hospital stay were used for cluster analysis. After clustering using clinical variables, the sputum levels of 14 molecules were measured to biologically characterize the clinical clusters. Five clinical clusters were identified, including two characterized by high pack-year exposure to cigarette smoking and low FEV1/FVC. There were marked differences between the two clusters of cigarette smokers. One had high levels of circulating eosinophils, high IgE levels, and a high sinus disease score. The other was characterized by low levels of the same parameters. Sputum analysis revealed increased levels of IL-5 in the former cluster and increased levels of IL-6 and osteopontin in the latter. The other three clusters were similar to those previously reported: young onset/atopic, nonsmoker/less eosinophilic, and female/obese. Key clinical variables were confirmed to be stable and consistent 1 year later. This study reveals two distinct phenotypes of severe asthma in current and former cigarette smokers with potentially different biological pathways contributing to fixed airflow limitation. Clinical trial registered with www.umin.ac.jp (000003254).

Firm- and drug-specific patterns of generic drug payments by US medicaid programs: 1991-2008.

PubMed

Kelton, Christina M L; Chang, Lenisa V; Guo, Jeff J; Yu, Yan; Berry, Edmund A; Bian, Boyang; Heaton, Pamela C

2014-04-01

The entry of generic drugs into markets previously monopolized by patented, branded drugs often represents large potential savings for healthcare payers in the USA. Our objectives were to describe and explain the trends in drug reimbursement by public Medicaid programmes post-generic entry for as many drug markets and for as long a time period as possible. The data were the Medicaid State Drug Utilization Data maintained by the Centers for Medicare and Medicaid Services. Quarterly utilization and expenditure data from 1991 to 2008 were extracted for 83 drugs, produced by 229 firms, that experienced initial generic entry between 1992 and 2004. A relative 'price' for a specific drug, firm and quarter was constructed as Medicaid reimbursement per unit (e.g. tablet, capsule or vial) divided by average reimbursement per unit for the branded drug the year before entry. Fixed-effects models controlling for time-, firm- and drug-specific differences were estimated to explain reimbursement. Twelve quarters after generic entry, 18 % of drugs had average per-unit reimbursement less than 50 % of the original branded-drug reimbursement. For each additional firm manufacturing the drug, reimbursement per unit, relative to the pre-generic-entry branded-drug reimbursement, was estimated to fall by 17 (p < 0.01) and 3 (p < 0.01) percentage points for generic and branded-drug companies, respectively. Each additional quarter post-generic entry brought a 2 (p < 0.01) percentage point drop in relative reimbursement. State Medicaid programmes generally have been able to obtain relief from high drug prices following patent expirations for many branded-drug medications by adjusting reimbursement following the expanded competition in the pharmaceutical market.

New approaches for identifying and testing potential new anti-asthma agents.

PubMed

Licari, Amelia; Castagnoli, Riccardo; Brambilla, Ilaria; Marseglia, Alessia; Tosca, Maria Angela; Marseglia, Gian Luigi; Ciprandi, Giorgio

2018-01-01

Asthma is a chronic disease with significant heterogeneity in clinical features, disease severity, pattern of underlying disease mechanisms, and responsiveness to specific treatments. While the majority of asthmatic patients are controlled by standard pharmacological strategies, a significant subgroup has limited therapeutic options representing a major unmet need. Ongoing asthma research aims to better characterize distinct clinical phenotypes, molecular endotypes, associated reliable biomarkers, and also to develop a series of new effective targeted treatment modalities. Areas covered: The expanding knowledge on the pathogenetic mechanisms of asthma has allowed researchers to investigate a range of new treatment options matched to patient profiles. The aim of this review is to provide a comprehensive and updated overview of the currently available, new and developing approaches for identifying and testing potential treatment options for asthma management. Expert opinion: Future therapeutic strategies for asthma require the identification of reliable biomarkers that can help with diagnosis and endotyping, in order to determine the most effective drug for the right patient phenotype. Furthermore, in addition to the identification of clinical and inflammatory phenotypes, it is expected that a better understanding of the mechanisms of airway remodeling will likely optimize asthma targeted treatment.

Leaf margin phenotype-specific restriction-site-associated DNA-derived markers for pineapple (Ananas comosus L.).

PubMed

Urasaki, Naoya; Goeku, Satoko; Kaneshima, Risa; Takamine, Tomonori; Tarora, Kazuhiko; Takeuchi, Makoto; Moromizato, Chie; Yonamine, Kaname; Hosaka, Fumiko; Terakami, Shingo; Matsumura, Hideo; Yamamoto, Toshiya; Shoda, Moriyuki

2015-06-01

To explore genome-wide DNA polymorphisms and identify DNA markers for leaf margin phenotypes, a restriction-site-associated DNA sequencing analysis was employed to analyze three bulked DNAs of F1 progeny from a cross between a 'piping-leaf-type' cultivar, 'Yugafu', and a 'spiny-tip-leaf-type' variety, 'Yonekura'. The parents were both Ananas comosus var. comosus. From the analysis, piping-leaf and spiny-tip-leaf gene-specific restriction-site-associated DNA sequencing tags were obtained and designated as PLSTs and STLSTs, respectively. The five PLSTs and two STSLTs were successfully converted to cleaved amplified polymorphic sequence (CAPS) or simple sequence repeat (SSR) markers using the sequence differences between alleles. Based on the genotyping of the F1 with two SSR and three CAPS markers, the five PLST markers were mapped in the vicinity of the P locus, with the closest marker, PLST1_SSR, being located 1.5 cM from the P locus. The two CAPS markers from STLST1 and STLST3 perfectly assessed the 'spiny-leaf type' as homozygotes of the recessive s allele of the S gene. The recombination value between the S locus and STLST loci was 2.4, and STLSTs were located 2.2 cM from the S locus. SSR and CAPS markers are applicable to marker-assisted selection of leaf margin phenotypes in pineapple breeding.

Crystal Structure of an Integron Gene Cassette-Associated Protein from Vibrio cholerae Identifies a Cationic Drug-Binding Module

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deshpande, Chandrika N.; Harrop, Stephen J.; Boucher, Yan

2012-02-15

The direct isolation of integron gene cassettes from cultivated and environmental microbial sources allows an assessment of the impact of the integron/gene cassette system on the emergence of new phenotypes, such as drug resistance or virulence. A structural approach is being exploited to investigate the modularity and function of novel integron gene cassettes. We report the 1.8 {angstrom} crystal structure of Cass2, an integron-associated protein derived from an environmental V. cholerae. The structure defines a monomeric beta-barrel protein with a fold related to the effector-binding portion of AraC/XylS transcription activators. The closest homologs of Cass2 are multi-drug binding proteins, suchmore » as BmrR. Consistent with this, a binding pocket made up of hydrophobic residues and a single glutamate side chain is evident in Cass2, occupied in the crystal form by polyethylene glycol. Fluorescence assays demonstrate that Cass2 is capable of binding cationic drug compounds with submicromolar affinity. The Cass2 module possesses a protein interaction surface proximal to its drug-binding cavity with features homologous to those seen in multi-domain transcriptional regulators. Genetic analysis identifies Cass2 to be representative of a larger family of independent effector-binding proteins associated with lateral gene transfer within Vibrio and closely-related species. We propose that the Cass2 family not only has capacity to form functional transcription regulator complexes, but represents possible evolutionary precursors to multi-domain regulators associated with cationic drug compounds.« less

How to Identify Drug Paraphernalia

MedlinePlus

... red eyes, changes in pupil size, or eye movements Items or associations that may indicate interest in illegal drugs or drug use. Clothing, jewelry, tattoos, teen slang with drug culture messages. Websites, music, or publications that glamorize drug use. Where do ...

Sex-Specific Genetic Loci for Femoral Neck Bone Mass and Strength Identified in Inbred COP and DA Rats

PubMed Central

Alam, Imranul; Sun, Qiwei; Liu, Lixiang; Koller, Daniel L; Carr, Lucinda G; Econs, Michael J; Foroud, Tatiana; Turner, Charles H

2008-01-01

Introduction Hip fracture is the most devastating osteoporotic fracture type with significant morbidity and mortality. Several studies in humans identified chromosomal regions linked to hip size and bone mass. Animal models, particularly the inbred rat, serve as complementary approaches for studying the genetic influence on hip fragility. The purpose of this study is to identify sex-independent and sex-specific quantitative trait loci (QTLs) for femoral neck density, structure, and strength in inbred Copenhagen 2331 (COP) and Dark Agouti (DA) rats. Materials and Methods A total of 828 (405 males and 423 females) F2 progeny derived from the inbred COP and DA strains of rats were phenotyped for femoral neck volumetric BMD (vBMD), cross-sectional area, polar moment of inertia (Ip), neck width, ultimate force, and energy to break. A whole genome screen was performed using 93 microsatellite markers with an average intermarker distance of 20 cM. Recombination-based marker maps were generated using MAPMAKER/EXP from the COP × DA F2 data and compared with published Rat Genome Database (RGD) maps. These maps were used for genome-wide linkage analyses to detect sex-independent and sex-specific QTLs. Results Significant evidence of linkage (p < 0.01) for sex-independent QTLs were detected for (1) femoral neck vBMD on chromosomes (Chrs) 1, 6, 10, and 12, (2) femoral neck structure on Chrs 5, 7, 10, and 18, and (3) biomechanical properties on Chrs 1 and 4. Male-specific QTLs were discovered on Chrs 2, 9, and 18 for total vBMD, on Chr 17 for trabecular vBMD, on Chr 9 for total bone area, and on Chr 15 for ultimate force. A female-specific QTL was discovered on Chr 2 for ultimate force. The effect size of the individual QTL varied between 1% and 4%. Conclusions We detected evidence that sex-independent and sex-specific QTLs contribute to hip fragility in the inbred rat. Several QTLs regions identified in this study are homologous to human chromosomal regions previously linked to

Identifying and Preventing Health Problems among Young Drug-Misusing Offenders

ERIC Educational Resources Information Center

Bennett, Trevor; Holloway, Katy

2008-01-01

Purpose: The purpose of this paper is to identify the health problems and treatment needs of drug-misusing offenders and to draw out the implications of the findings for health education and prevention. Design/methodology/approach: This analysis is based on data collected as part of the New English and Welsh Arrestee Drug Abuse Monitoring…

Identifying mechanism-of-action targets for drugs and probes

PubMed Central

Gregori-Puigjané, Elisabet; Setola, Vincent; Hert, Jérôme; Crews, Brenda A.; Irwin, John J.; Lounkine, Eugen; Marnett, Lawrence; Roth, Bryan L.; Shoichet, Brian K.

2012-01-01

Notwithstanding their key roles in therapy and as biological probes, 7% of approved drugs are purported to have no known primary target, and up to 18% lack a well-defined mechanism of action. Using a chemoinformatics approach, we sought to “de-orphanize” drugs that lack primary targets. Surprisingly, targets could be easily predicted for many: Whereas these targets were not known to us nor to the common databases, most could be confirmed by literature search, leaving only 13 Food and Drug Administration—approved drugs with unknown targets; the number of drugs without molecular targets likely is far fewer than reported. The number of worldwide drugs without reasonable molecular targets similarly dropped, from 352 (25%) to 44 (4%). Nevertheless, there remained at least seven drugs for which reasonable mechanism-of-action targets were unknown but could be predicted, including the antitussives clemastine, cloperastine, and nepinalone; the antiemetic benzquinamide; the muscle relaxant cyclobenzaprine; the analgesic nefopam; and the immunomodulator lobenzarit. For each, predicted targets were confirmed experimentally, with affinities within their physiological concentration ranges. Turning this question on its head, we next asked which drugs were specific enough to act as chemical probes. Over 100 drugs met the standard criteria for probes, and 40 did so by more stringent criteria. A chemical information approach to drug-target association can guide therapeutic development and reveal applications to probe biology, a focus of much current interest. PMID:22711801

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

PubMed

Failmezger, Henrik; Fröhlich, Holger; Tresch, Achim

2013-10-04

Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens. We developed an unsupervised phenotyping approach based on Hidden Markov Models (HMMs) with multivariate Gaussian emissions for the detection of knockdown-specific phenotypes in RNAi time-lapse movies. The automated detection of abnormal cell morphologies allows us to assign a phenotypic fingerprint to each gene knockdown. By applying our method to the Mitocheck database, we show that a phenotypic fingerprint is indicative of a gene's function. Our fully unsupervised HMM-based phenotyping is able to automatically identify cell morphologies that are specific for a certain knockdown. Beyond the identification of genes whose knockdown affects cell morphology, phenotypic fingerprints can be used to find modules of functionally related genes.

A Drug Combination Screen Identifies Drugs Active against Amoxicillin-Induced Round Bodies of In Vitro Borrelia burgdorferi Persisters from an FDA Drug Library

PubMed Central

Feng, Jie; Shi, Wanliang; Zhang, Shuo; Sullivan, David; Auwaerter, Paul G.; Zhang, Ying

2016-01-01

Although currently recommended antibiotics for Lyme disease such as doxycycline or amoxicillin cure the majority of the patients, about 10–20% of patients treated for Lyme disease may experience lingering symptoms including fatigue, pain, or joint and muscle aches. Under experimental stress conditions such as starvation or antibiotic exposure, Borrelia burgdorferi can develop round body forms, which are a type of persister bacteria that appear resistant in vitro to customary first-line antibiotics for Lyme disease. To identify more effective drugs with activity against the round body form of B. burgdorferi, we established a round body persister model induced by exposure to amoxicillin (50 μg/ml) and then screened the Food and Drug Administration drug library consisting of 1581 drug compounds and also 22 drug combinations using the SYBR Green I/propidium iodide viability assay. We identified 23 drug candidates that have higher activity against the round bodies of B. burgdorferi than either amoxicillin or doxycycline. Eleven individual drugs scored better than metronidazole and tinidazole which have been previously described to be active against round bodies. In this amoxicillin-induced round body model, some drug candidates such as daptomycin and clofazimine also displayed enhanced activity which was similar to a previous screen against stationary phase B. burgdorferi persisters not exposure to amoxicillin. Additional candidate drugs active against round bodies identified include artemisinin, ciprofloxacin, nifuroxime, fosfomycin, chlortetracycline, sulfacetamide, sulfamethoxypyridazine and sulfathiozole. Two triple drug combinations had the highest activity against amoxicillin-induced round bodies and stationary phase B. burgdorferi persisters: artemisinin/cefoperazone/doxycycline and sulfachlorpyridazine/daptomycin/doxycycline. These findings confirm and extend previous findings that certain drug combinations have superior activity against B. burgdorferi

A Drug Combination Screen Identifies Drugs Active against Amoxicillin-Induced Round Bodies of In Vitro Borrelia burgdorferi Persisters from an FDA Drug Library.

PubMed

Feng, Jie; Shi, Wanliang; Zhang, Shuo; Sullivan, David; Auwaerter, Paul G; Zhang, Ying

2016-01-01

Although currently recommended antibiotics for Lyme disease such as doxycycline or amoxicillin cure the majority of the patients, about 10-20% of patients treated for Lyme disease may experience lingering symptoms including fatigue, pain, or joint and muscle aches. Under experimental stress conditions such as starvation or antibiotic exposure, Borrelia burgdorferi can develop round body forms, which are a type of persister bacteria that appear resistant in vitro to customary first-line antibiotics for Lyme disease. To identify more effective drugs with activity against the round body form of B. burgdorferi, we established a round body persister model induced by exposure to amoxicillin (50 μg/ml) and then screened the Food and Drug Administration drug library consisting of 1581 drug compounds and also 22 drug combinations using the SYBR Green I/propidium iodide viability assay. We identified 23 drug candidates that have higher activity against the round bodies of B. burgdorferi than either amoxicillin or doxycycline. Eleven individual drugs scored better than metronidazole and tinidazole which have been previously described to be active against round bodies. In this amoxicillin-induced round body model, some drug candidates such as daptomycin and clofazimine also displayed enhanced activity which was similar to a previous screen against stationary phase B. burgdorferi persisters not exposure to amoxicillin. Additional candidate drugs active against round bodies identified include artemisinin, ciprofloxacin, nifuroxime, fosfomycin, chlortetracycline, sulfacetamide, sulfamethoxypyridazine and sulfathiozole. Two triple drug combinations had the highest activity against amoxicillin-induced round bodies and stationary phase B. burgdorferi persisters: artemisinin/cefoperazone/doxycycline and sulfachlorpyridazine/daptomycin/doxycycline. These findings confirm and extend previous findings that certain drug combinations have superior activity against B. burgdorferi

Site-Specific Antibody–Drug Conjugates: The Nexus of Bioorthogonal Chemistry, Protein Engineering, and Drug Development

PubMed Central

2015-01-01

Antibody–drug conjugates (ADCs) combine the specificity of antibodies with the potency of small molecules to create targeted drugs. Despite the simplicity of this concept, generation of clinically successful ADCs has been very difficult. Over the past several decades, scientists have learned a great deal about the constraints on antibodies, linkers, and drugs as they relate to successful construction of ADCs. Once these components are in hand, most ADCs are prepared by nonspecific modification of antibody lysine or cysteine residues with drug-linker reagents, which results in heterogeneous product mixtures that cannot be further purified. With advances in the fields of bioorthogonal chemistry and protein engineering, there is growing interest in producing ADCs by site-specific conjugation to the antibody, yielding more homogeneous products that have demonstrated benefits over their heterogeneous counterparts in vivo. Here, we chronicle the development of a multitude of site-specific conjugation strategies for assembly of ADCs and provide a comprehensive account of key advances and their roots in the fields of bioorthogonal chemistry and protein engineering. PMID:25494884

Site-specific antibody-drug conjugates: the nexus of bioorthogonal chemistry, protein engineering, and drug development.

PubMed

Agarwal, Paresh; Bertozzi, Carolyn R

2015-02-18

Antibody-drug conjugates (ADCs) combine the specificity of antibodies with the potency of small molecules to create targeted drugs. Despite the simplicity of this concept, generation of clinically successful ADCs has been very difficult. Over the past several decades, scientists have learned a great deal about the constraints on antibodies, linkers, and drugs as they relate to successful construction of ADCs. Once these components are in hand, most ADCs are prepared by nonspecific modification of antibody lysine or cysteine residues with drug-linker reagents, which results in heterogeneous product mixtures that cannot be further purified. With advances in the fields of bioorthogonal chemistry and protein engineering, there is growing interest in producing ADCs by site-specific conjugation to the antibody, yielding more homogeneous products that have demonstrated benefits over their heterogeneous counterparts in vivo. Here, we chronicle the development of a multitude of site-specific conjugation strategies for assembly of ADCs and provide a comprehensive account of key advances and their roots in the fields of bioorthogonal chemistry and protein engineering.

Phenotype variations affect genetic association studies of degenerative disc disease: conclusions of analysis of genetic association of 58 single nucleotide polymorphisms with highly specific phenotypes for disc degeneration in 332 subjects.

PubMed

Rajasekaran, S; Kanna, Rishi Mugesh; Senthil, Natesan; Raveendran, Muthuraja; Cheung, Kenneth M C; Chan, Danny; Subramaniam, Sakthikanal; Shetty, Ajoy Prasad

2013-10-01

Although the influence of genetics on the process of disc degeneration is well recognized, in recently published studies, there is a wide variation in the race and selection criteria for such study populations. More importantly, the radiographic features of disc degeneration that are selected to represent the disc degeneration phenotype are variable in these studies. The study presented here evaluates the association between single nucleotide polymorphisms (SNPs) of candidate genes and three distinct radiographic features that can be defined as the degenerative disc disease (DDD) phenotype. The study objectives were to examine the allelic diversity of 58 SNPs related to 35 candidate genes related to lumbar DDD, to evaluate the association in a hitherto unevaluated ethnic Indian population that represents more than one-sixth of the world population, and to analyze how genetic associations can vary in the same study subjects with the choice of phenotype. A cross-sectional, case-control study of an ethnic Indian population was carried out. Fifty-eight SNPs in 35 potential candidate genes were evaluated in 342 subjects and the associations were analyzed against three highly specific markers for DDD, namely disc degeneration by Pfirrmann grading, end-plate damage evaluated by total end-plate damage score, and annular tears evaluated by disc herniations and hyperintense zones. Genotyping of cases and controls was performed on a genome-wide SNP array to identify potential associated disease loci. The results from the genome-wide SNP array were then used to facilitate SNP selection and genotype validation was conducted using Sequenom-based genotyping. Eleven of the 58 SNPs provided evidence of association with one of the phenotypes. For annular tears, rs1042631 SNP of AGC1 and rs467691 SNP of ADAMTS5 were highly significantly associated (p<.01) and SNPs in NGFB, IL1B, IL18RAP, and MMP10 were also significantly associated (p<.05). The rs4076018 SNP of NGFB was highly

Genotype and Phenotype Predictors of Relapse of Graves’ Disease after Antithyroid Drug Withdrawal

PubMed Central

Wang, Pei-Wen; Chen, I-Ya; Juo, Suh-Hang Hank; Hsi, Edward; Liu, Rue-Tsuan; Hsieh, Ching-Jung

2013-01-01

Background For patients with Graves’ disease (GD), the primary goal of antithyroid drug therapy is to temporarily restore the patient to the euthyroid state and wait for a subsequent remission of the disease. This study sought to identify the predictive markers for the relapse of disease. Methods To do this, we studied 262 GD patients with long enough follow-up after drug withdrawal to determine treatment outcome. The patients were divided into three groups by time of relapse: early relapse group (n = 91) had an early relapse within 9 months, late relapse group (n = 65) had a relapse between 10 and 36 months, and long-term remission group (n = 106) were either still in remission after at least 3 years or relapsed after 3 years of drug withdrawal. We assessed the treatment outcome of 23 SNPs of costimulatory genes, phenotype and smoking habits. We used permutation to obtain p values for each SNP as an adjustment for multiple testing. Cox proportional hazards models was performed to assess the strength of association between the treatment outcome and clinical and laboratory variables. Results Four SNPs were significantly associated with disease relapse: rs231775 (OR 1.96, 95% CI 1.18–3.26) at CTLA-4 and rs745307 (OR 7.97, 95% CI 1.01–62.7), rs11569309 (OR 8.09, 95% CI 1.03–63.7), and rs3765457 (OR 2.60, 95% CI 1.08–6.28) at CD40. Combining risk alleles at CTLA-4 and CD40 improved the predictability of relapse. Using 3 years as the cutoff point for multivariate analysis, we found several independent predictors of disease relapse: number of risk alleles (HR 1.30, 95% CI 1.09–1.56), a large goiter size at the end of the treatment (HR 1.30, 95% CI 1.05–1.61), persistent TSH-binding inhibitory Ig (HR 1.64, 95% CI 1.15–2.35), and smoking habit (HR 1.60, 95% CI 1.05–2.42). Conclusion Genetic polymorphism of costimulatory genes, smoking status, persistent goiter, and TSH-binding inhibitory Ig predict disease relapse. PMID:24783027

Genotype and phenotype predictors of relapse of graves' disease after antithyroid drug withdrawal.

PubMed

Wang, Pei-Wen; Chen, I-Ya; Juo, Suh-Hang Hank; Hsi, Edward; Liu, Rue-Tsuan; Hsieh, Ching-Jung

2013-01-01

For patients with Graves' disease (GD), the primary goal of antithyroid drug therapy is to temporarily restore the patient to the euthyroid state and wait for a subsequent remission of the disease. This study sought to identify the predictive markers for the relapse of disease. To do this, we studied 262 GD patients with long enough follow-up after drug withdrawal to determine treatment outcome. The patients were divided into three groups by time of relapse: early relapse group (n = 91) had an early relapse within 9 months, late relapse group (n = 65) had a relapse between 10 and 36 months, and long-term remission group (n = 106) were either still in remission after at least 3 years or relapsed after 3 years of drug withdrawal. We assessed the treatment outcome of 23 SNPs of costimulatory genes, phenotype and smoking habits. We used permutation to obtain p values for each SNP as an adjustment for multiple testing. Cox proportional hazards models was performed to assess the strength of association between the treatment outcome and clinical and laboratory variables. FOUR SNPS WERE SIGNIFICANTLY ASSOCIATED WITH DISEASE RELAPSE: rs231775 (OR 1.96, 95% CI 1.18-3.26) at CTLA-4 and rs745307 (OR 7.97, 95% CI 1.01-62.7), rs11569309 (OR 8.09, 95% CI 1.03-63.7), and rs3765457 (OR 2.60, 95% CI 1.08-6.28) at CD40. Combining risk alleles at CTLA-4 and CD40 improved the predictability of relapse. Using 3 years as the cutoff point for multivariate analysis, we found several independent predictors of disease relapse: number of risk alleles (HR 1.30, 95% CI 1.09-1.56), a large goiter size at the end of the treatment (HR 1.30, 95% CI 1.05-1.61), persistent TSH-binding inhibitory Ig (HR 1.64, 95% CI 1.15-2.35), and smoking habit (HR 1.60, 95% CI 1.05-2.42). Genetic polymorphism of costimulatory genes, smoking status, persistent goiter, and TSH-binding inhibitory Ig predict disease relapse.

The basel cocktail for simultaneous phenotyping of human cytochrome P450 isoforms in plasma, saliva and dried blood spots.

PubMed

Donzelli, Massimiliano; Derungs, Adrian; Serratore, Maria-Giovanna; Noppen, Christoph; Nezic, Lana; Krähenbühl, Stephan; Haschke, Manuel

2014-03-01

Phenotyping cocktails use a combination of cytochrome P450 (CYP)-specific probe drugs to simultaneously assess the activity of different CYP isoforms. To improve the clinical applicability of CYP phenotyping, the main objectives of this study were to develop a new cocktail based on probe drugs that are widely used in clinical practice and to test whether alternative sampling methods such as collection of dried blood spots (DBS) or saliva could be used to simplify the sampling process. In a randomized crossover study, a new combination of commercially available probe drugs (the Basel cocktail) was tested for simultaneous phenotyping of CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6 and CYP3A4. Sixteen subjects received low doses of caffeine, efavirenz, losartan, omeprazole, metoprolol and midazolam in different combinations. All subjects were genotyped, and full pharmacokinetic profiles of the probe drugs and their main metabolites were determined in plasma, dried blood spots and saliva samples. The Basel cocktail was well tolerated, and bioequivalence tests showed no evidence of mutual interactions between the probe drugs. In plasma, single timepoint metabolic ratios at 2 h (for CYP2C19 and CYP3A4) or at 8 h (for the other isoforms) after dosing showed high correlations with corresponding area under the concentration-time curve (AUC) ratios (AUC0-24h parent/AUC0-24h metabolite) and are proposed as simple phenotyping metrics. Metabolic ratios in dried blood spots (for CYP1A2 and CYP2C19) or in saliva samples (for CYP1A2) were comparable to plasma ratios and offer the option of minimally invasive or non-invasive phenotyping of these isoforms. This new combination of phenotyping probe drugs can be used without mutual interactions. The proposed sampling timepoints have the potential to facilitate clinical application of phenotyping but require further validation in conditions of altered CYP activity. The use of DBS or saliva samples seems feasible for phenotyping of the

Identifying eating behavior phenotypes and their correlates: a novel direction toward improving weight management interventions

PubMed Central

Bouhlal, Sofia; McBride, Colleen M.; Trivedi, Niraj S.; Agurs-Collins, Tanya; Persky, Susan

2017-01-01

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n=260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants’ BMI (p=.0002) and dietary self-efficacy (p<.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions. PMID:28043857

The mechanical phenotype of biglycan-deficient mice is bone- and gender-specific.

PubMed

Wallace, Joseph M; Rajachar, Rupak M; Chen, Xiao-Dong; Shi, Songtao; Allen, Matthew R; Bloomfield, Susan A; Les, Clifford M; Robey, Pamela G; Young, Marian F; Kohn, David H

2006-07-01

Biglycan (bgn) is a small leucine-rich proteoglycan (SLRP) enriched in the extracellular matrix of skeletal tissues. While bgn is known to be involved in the growth and differentiation of osteoblast precursor cells and regulation of collagen fibril formation, it is unclear how these functions impact bone's geometric and mechanical properties, properties which are integral to the structural function of bone. Because the genetic control of bone structure and function is both local- and gender-specific and because there is evidence of gender-specific effects associated with genetic deficiencies, it was hypothesized that the engineered deletion of the gene encoding bgn would result in a cortical bone mechanical phenotype that was bone- and gender-specific. In 11-week-old C57BL6/129 mice, the cortical bone in the mid-diaphyses of the femora and tibiae of both genders was examined. Phenotypic changes in bgn-deficient mice relative to wild type controls were assayed by four-point bending tests to determine mechanical properties at the whole bone (structural) and tissue levels, as well as analyses of bone geometry and bone formation using histomorphometry. Of the bones examined, bgn deficiency most strongly affected the male tibiae, where enhanced cross-sectional geometric properties and bone mineral density were accompanied by decreased tissue-level yield strength and pre-yield structural deformation and energy dissipation. Because pre-yield properties alone were impacted, this implies that the gene deletion causes important alterations in mineral and/or the matrix/mineral ultrastructure and suggests a new understanding of the functional role of bgn in regulating bone mineralization in vivo.

Synergy testing of FDA-approved drugs identifies potent drug combinations against Trypanosoma cruzi.

PubMed

Planer, Joseph D; Hulverson, Matthew A; Arif, Jennifer A; Ranade, Ranae M; Don, Robert; Buckner, Frederick S

2014-07-01

An estimated 8 million persons, mainly in Latin America, are infected with Trypanosoma cruzi, the etiologic agent of Chagas disease. Existing antiparasitic drugs for Chagas disease have significant toxicities and suboptimal effectiveness, hence new therapeutic strategies need to be devised to address this neglected tropical disease. Due to the high research and development costs of bringing new chemical entities to the clinic, we and others have investigated the strategy of repurposing existing drugs for Chagas disease. Screens of FDA-approved drugs (described in this paper) have revealed a variety of chemical classes that have growth inhibitory activity against mammalian stage Trypanosoma cruzi parasites. Aside from azole antifungal drugs that have low or sub-nanomolar activity, most of the active compounds revealed in these screens have effective concentrations causing 50% inhibition (EC50's) in the low micromolar or high nanomolar range. For example, we have identified an antihistamine (clemastine, EC50 of 0.4 µM), a selective serotonin reuptake inhibitor (fluoxetine, EC50 of 4.4 µM), and an antifolate drug (pyrimethamine, EC50 of 3.8 µM) and others. When tested alone in the murine model of Trypanosoma cruzi infection, most compounds had insufficient efficacy to lower parasitemia thus we investigated using combinations of compounds for additive or synergistic activity. Twenty-four active compounds were screened in vitro in all possible combinations. Follow up isobologram studies showed at least 8 drug pairs to have synergistic activity on T. cruzi growth. The combination of the calcium channel blocker, amlodipine, plus the antifungal drug, posaconazole, was found to be more effective at lowering parasitemia in mice than either drug alone, as was the combination of clemastine and posaconazole. Using combinations of FDA-approved drugs is a promising strategy for developing new treatments for Chagas disease.

Synergy Testing of FDA-Approved Drugs Identifies Potent Drug Combinations against Trypanosoma cruzi

PubMed Central

Ranade, Ranae M.; Don, Robert; Buckner, Frederick S.

2014-01-01

An estimated 8 million persons, mainly in Latin America, are infected with Trypanosoma cruzi, the etiologic agent of Chagas disease. Existing antiparasitic drugs for Chagas disease have significant toxicities and suboptimal effectiveness, hence new therapeutic strategies need to be devised to address this neglected tropical disease. Due to the high research and development costs of bringing new chemical entities to the clinic, we and others have investigated the strategy of repurposing existing drugs for Chagas disease. Screens of FDA-approved drugs (described in this paper) have revealed a variety of chemical classes that have growth inhibitory activity against mammalian stage Trypanosoma cruzi parasites. Aside from azole antifungal drugs that have low or sub-nanomolar activity, most of the active compounds revealed in these screens have effective concentrations causing 50% inhibition (EC50's) in the low micromolar or high nanomolar range. For example, we have identified an antihistamine (clemastine, EC50 of 0.4 µM), a selective serotonin reuptake inhibitor (fluoxetine, EC50 of 4.4 µM), and an antifolate drug (pyrimethamine, EC50 of 3.8 µM) and others. When tested alone in the murine model of Trypanosoma cruzi infection, most compounds had insufficient efficacy to lower parasitemia thus we investigated using combinations of compounds for additive or synergistic activity. Twenty-four active compounds were screened in vitro in all possible combinations. Follow up isobologram studies showed at least 8 drug pairs to have synergistic activity on T. cruzi growth. The combination of the calcium channel blocker, amlodipine, plus the antifungal drug, posaconazole, was found to be more effective at lowering parasitemia in mice than either drug alone, as was the combination of clemastine and posaconazole. Using combinations of FDA-approved drugs is a promising strategy for developing new treatments for Chagas disease. PMID:25033456

Functional kinomics identifies candidate therapeutic targets in head and neck cancer

PubMed Central

Moser, Russell; Xu, Chang; Kao, Michael; Annis, James; Lerma, Luisa Angelica; Schaupp, Christopher M.; Gurley, Kay E.; Jang, In Sock; Biktasova, Asel; Yarbrough, Wendell G.; Margolin, Adam A.; Grandori, Carla; Kemp, Christopher J.; Méndez, Eduardo

2014-01-01

Purpose To identify novel therapeutic drug targets for p53 mutant head and neck squamous cell carcinoma (HNSCC). Experimental Design RNAi kinome viability screens were performed on HNSCC cells including autologous pairs from primary tumor and recurrent/metastatic lesions, and in parallel on murine squamous cell carcinoma (MSCC) cells derived from tumors of inbred mice bearing germline mutations in Trp53, and p53 regulatory genes: Atm, Prkdc, and p19Arf. Cross-species analysis of cell lines stratified by p53 mutational status and metastatic phenotype was utilized to select 38 kinase targets. Both primary and secondary RNAi validation assays were performed on additional HNSCC cell lines to credential these kinase targets utilizing multiple phenotypic endpoints. Kinase targets were also examined via chemical inhibition utilizing a panel of kinase inhibitors. A preclinical study was conducted on the WEE1 kinase inhibitor, MK-1775. Results Our functional kinomics approach identified novel survival kinases in HNSCC involved in G2/M cell cycle checkpoint, SFK, PI3K and FAK pathways. RNAi mediated knockdown and chemical inhibition of the WEE1 kinase with a specific inhibitor, MK-1775, had a significant effect on both viability and apoptosis. Sensitivity to the MK-1775 kinase inhibitor is in part determined by p53 mutational status, and due to unscheduled mitotic entry. MK-1775 displays single-agent activity and potentiates the efficacy of cisplatin in a p53 mutant HNSCC xenograft model. Conclusions WEE1 kinase is a potential therapeutic drug target for HNSCC. This study supports the application of a functional kinomics strategy to identify novel therapeutic targets for cancer. PMID:25125259

Functional kinomics identifies candidate therapeutic targets in head and neck cancer.

PubMed

Moser, Russell; Xu, Chang; Kao, Michael; Annis, James; Lerma, Luisa Angelica; Schaupp, Christopher M; Gurley, Kay E; Jang, In Sock; Biktasova, Asel; Yarbrough, Wendell G; Margolin, Adam A; Grandori, Carla; Kemp, Christopher J; Méndez, Eduardo

2014-08-15

To identify novel therapeutic drug targets for p53-mutant head and neck squamous cell carcinoma (HNSCC). RNAi kinome viability screens were performed on HNSCC cells, including autologous pairs from primary tumor and recurrent/metastatic lesions, and in parallel on murine squamous cell carcinoma (MSCC) cells derived from tumors of inbred mice bearing germline mutations in Trp53, and p53 regulatory genes: Atm, Prkdc, and p19(Arf). Cross-species analysis of cell lines stratified by p53 mutational status and metastatic phenotype was used to select 38 kinase targets. Both primary and secondary RNAi validation assays were performed on additional HNSCC cell lines to credential these kinase targets using multiple phenotypic endpoints. Kinase targets were also examined via chemical inhibition using a panel of kinase inhibitors. A preclinical study was conducted on the WEE1 kinase inhibitor, MK-1775. Our functional kinomics approach identified novel survival kinases in HNSCC involved in G2-M cell-cycle checkpoint, SFK, PI3K, and FAK pathways. RNAi-mediated knockdown and chemical inhibition of the WEE1 kinase with a specific inhibitor, MK-1775, had a significant effect on both viability and apoptosis. Sensitivity to the MK-1775 kinase inhibitor is in part determined by p53 mutational status, and due to unscheduled mitotic entry. MK-1775 displays single-agent activity and potentiates the efficacy of cisplatin in a p53-mutant HNSCC xenograft model. WEE1 kinase is a potential therapeutic drug target for HNSCC. This study supports the application of a functional kinomics strategy to identify novel therapeutic targets for cancer. ©2014 American Association for Cancer Research.

Towards an informative mutant phenotype for every bacterial gene

DOE PAGES

Deutschbauer, Adam; Price, Morgan N.; Wetmore, Kelly M.; ...

2014-08-11

Mutant phenotypes provide strong clues to the functions of the underlying genes and could allow annotation of the millions of sequenced yet uncharacterized bacterial genes. However, it is not known how many genes have a phenotype under laboratory conditions, how many phenotypes are biologically interpretable for predicting gene function, and what experimental conditions are optimal to maximize the number of genes with a phenotype. To address these issues, we measured the mutant fitness of 1,586 genes of the ethanol-producing bacterium Zymomonas mobilis ZM4 across 492 diverse experiments and found statistically significant phenotypes for 89% of all assayed genes. Thus, inmore » Z. mobilis, most genes have a functional consequence under laboratory conditions. We demonstrate that 41% of Z. mobilis genes have both a strong phenotype and a similar fitness pattern (cofitness) to another gene, and are therefore good candidates for functional annotation using mutant fitness. Among 502 poorly characterized Z. mobilis genes, we identified a significant cofitness relationship for 174. For 57 of these genes without a specific functional annotation, we found additional evidence to support the biological significance of these gene-gene associations, and in 33 instances, we were able to predict specific physiological or biochemical roles for the poorly characterized genes. Last, we identified a set of 79 diverse mutant fitness experiments in Z. mobilis that are nearly as biologically informative as the entire set of 492 experiments. Therefore, our work provides a blueprint for the functional annotation of diverse bacteria using mutant fitness.« less

Sex-specific phenotypes of hyperthyroidism and hypothyroidism in aged mice.

PubMed

Rakov, Helena; Engels, Kathrin; Hönes, Georg Sebastian; Brix, Klaudia; Köhrle, Josef; Moeller, Lars Christian; Zwanziger, Denise; Führer, Dagmar

2017-12-22

Sex and age play a role in the prevalence of thyroid dysfunction (TD), but their interrelationship for manifestation of hyper- and hypothyroidism is still not well understood. Using a murine model, we asked whether sex impacts the phenotypes of hyper- and hypothyroidism at two life stages. Hyper- and hypothyroidism were induced by i.p. T4 or MMI/ClO 4 -/LoI treatment over 7 weeks in 12- and 20-months-old female and male C57BL/6N mice. Control animals underwent PBS treatment (n = 7-11 animals/sex/treatment). Animals were investigated for impact of sex on body weight, food and water intake, body temperature, heart rate, behaviour (locomotor activity, motor coordination and strength) and serum thyroid hormone (TH) status. Distinct sex impact was found in eu- and hyperthyroid mice, while phenotypic traits of hypothyroidism were similar in male and female mice. No sex difference was found in TH status of euthyroid mice; however, T4 treatment resulted in twofold higher TT4, FT4 and FT3 serum concentrations in adult and old females compared to male animals. Hyperthyroid females consistently showed higher locomotor activity and better coordination but more impairment of muscle function by TH excess at adult age. Importantly and in contrast to male mice, adult and old hyperthyroid female mice showed increased body weight. Higher body temperature in female mice was confirmed in all age groups. No sex impact was found on heart rate irrespective of TH status in adult and old mice. By comparison of male and female mice with TD at two life stages, we found that sex modulates TH action in an organ- and function-specific manner. Sex differences were more pronounced under hyperthyroid conditions. Importantly, sex-specific differences in features of TD in adult and old mice were not conclusively explained by serum TH status in mice.

Aptamer-based liposomes improve specific drug loading and release.

PubMed

Plourde, Kevin; Derbali, Rabeb Mouna; Desrosiers, Arnaud; Dubath, Céline; Vallée-Bélisle, Alexis; Leblond, Jeanne

2017-04-10

Aptamer technology has shown much promise in cancer therapeutics for its targeting abilities. However, its potential to improve drug loading and release from nanocarriers has not been thoroughly explored. In this study, we employed drug-binding aptamers to actively load drugs into liposomes. We designed a series of DNA aptamer sequences specific to doxorubicin, displaying multiple binding sites and various binding affinities. The binding ability of aptamers was preserved when incorporated into cationic liposomes, binding up to 15equivalents of doxorubicin per aptamer, therefore drawing the drug into liposomes. Optimization of the charge and drug/aptamer ratios resulted in ≥80% encapsulation efficiency of doxorubicin, ten times higher than classical passively-encapsulating liposomal formulations and similar to a pH-gradient active loading strategy. In addition, kinetic release profiles and cytotoxicity assay on HeLa cells demonstrated that the release and therapeutic efficacy of liposomal doxorubicin could be controlled by the aptamer's structure. Our results suggest that the aptamer exhibiting a specific intermediate affinity is the best suited to achieve high drug loading while maintaining efficient drug release and therapeutic activity. This strategy was successfully applied to tobramycin, a hydrophilic drug suffering from low encapsulation into liposomes, where its loading was improved six-fold using aptamers. Overall, we demonstrate that aptamers could act, in addition to their targeting properties, as multifunctional excipients for liposomal formulations. Copyright © 2017 Elsevier B.V. All rights reserved.

Whole-Transcriptome and -Genome Analysis of Extensively Drug-Resistant Mycobacterium tuberculosis Clinical Isolates Identifies Downregulation of ethA as a Mechanism of Ethionamide Resistance

PubMed Central

de Welzen, Lynne; Eldholm, Vegard; Maharaj, Kashmeel; Manson, Abigail L.; Earl, Ashlee M.

2017-01-01

ABSTRACT Genetics-based drug susceptibility testing has improved the diagnosis of drug-resistant tuberculosis but is limited by our lack of knowledge of all resistance mechanisms. Next-generation sequencing has assisted in identifying the principal genetic mechanisms of resistance for many drugs, but a significant proportion of phenotypic drug resistance is unexplained genetically. Few studies have formally compared the transcriptomes of susceptible and resistant Mycobacterium tuberculosis strains. We carried out comparative whole-genome transcriptomics of extensively drug-resistant (XDR) clinical isolates using RNA sequencing (RNA-seq) to find novel transcription-mediated mechanisms of resistance. We identified a promoter mutation (t to c) at position −11 (t−11c) relative to the start codon of ethA that reduces the expression of a monooxygenase (EthA) that activates ethionamide. (In this article, nucleotide changes are lowercase and amino acid substitutions are uppercase.) Using a flow cytometry-based reporter assay, we show that the reduced transcription of ethA is not due to transcriptional repression by ethR. Clinical strains harboring this mutation were resistant to ethionamide. Other ethA promoter mutations were identified in a global genomic survey of resistant M. tuberculosis strains. These results demonstrate a new mechanism of ethionamide resistance that can cause high-level resistance when it is combined with other ethionamide resistance-conferring mutations. Our study revealed many other genes which were highly up- or downregulated in XDR strains, including a toxin-antitoxin module (mazF5 mazE5) and tRNAs (leuX and thrU). This suggests that global transcriptional modifications could contribute to resistance or the maintenance of bacterial fitness have also occurred in XDR strains. PMID:28993337

Redefining Aging in HIV Infection Using Phenotypes.

PubMed

Stoff, David M; Goodkin, Karl; Jeste, Dilip; Marquine, Maria

2017-10-01

This article critically reviews the utility of "phenotypes" as behavioral descriptors in aging/HIV research that inform biological underpinnings and treatment development. We adopt a phenotypic redefinition of aging conceptualized within a broader context of HIV infection and of aging. Phenotypes are defined as dimensions of behavior, closely related to fundamental mechanisms, and, thus, may be more informative than chronological age. Primary emphasis in this review is given to comorbid aging and cognitive aging, though other phenotypes (i.e., disability, frailty, accelerated aging, successful aging) are also discussed in relation to comorbid aging and cognitive aging. The main findings that emerged from this review are as follows: (1) the phenotypes, comorbid aging and cognitive aging, are distinct from each other, yet overlapping; (2) associative relationships are the rule in HIV for comorbid and cognitive aging phenotypes; and (3) HIV behavioral interventions for both comorbid aging and cognitive aging have been limited. Three paths for research progress are identified for phenotype-defined aging/HIV research (i.e., clinical and behavioral specification, biological mechanisms, intervention targets), and some important research questions are suggested within each of these research paths.

Muscular dystrophy in a dish: engineered human skeletal muscle mimetics for disease modeling and drug discovery

PubMed Central

Smith, Alec S.T.; Davis, Jennifer; Lee, Gabsang; Mack, David L.

2016-01-01

Engineered in vitro models using human cells, particularly patient-derived induced pluripotent stem cells (iPSCs), offer a potential solution to issues associated with the use of animals for studying disease pathology and drug efficacy. Given the prevalence of muscle diseases in human populations, an engineered tissue model of human skeletal muscle could provide a biologically accurate platform to study basic muscle physiology, disease progression, and drug efficacy and/or toxicity. Such platforms could be used as phenotypic drug screens to identify compounds capable of alleviating or reversing congenital myopathies, such as Duchene muscular dystrophy (DMD). Here, we review current skeletal muscle modeling technologies with a specific focus on efforts to generate biomimetic systems for investigating the pathophysiology of dystrophic muscle. PMID:27109386

Three-Dimensional Cell Culture-Based Screening Identifies the Anthelmintic Drug Nitazoxanide as a Candidate for Treatment of Colorectal Cancer.

PubMed

Senkowski, Wojciech; Zhang, Xiaonan; Olofsson, Maria Hägg; Isacson, Ruben; Höglund, Urban; Gustafsson, Mats; Nygren, Peter; Linder, Stig; Larsson, Rolf; Fryknäs, Mårten

2015-06-01

Because dormant cancer cells in hypoxic and nutrient-deprived regions of solid tumors provide a major obstacle to treatment, compounds targeting those cells might have clinical benefits. Here, we describe a high-throughput drug screening approach, using glucose-deprived multicellular tumor spheroids (MCTS) with inner hypoxia, to identify compounds that specifically target this cell population. We used a concept of drug repositioning-using known molecules for new indications. This is a promising strategy to identify molecules for rapid clinical advancement. By screening 1,600 compounds with documented clinical history, we aimed to identify candidates with unforeseen potential for repositioning as anticancer drugs. Our screen identified five molecules with pronounced MCTS-selective activity: nitazoxanide, niclosamide, closantel, pyrvinium pamoate, and salinomycin. Herein, we show that all five compounds inhibit mitochondrial respiration. This suggests that cancer cells in low glucose concentrations depend on oxidative phosphorylation rather than solely glycolysis. Importantly, continuous exposure to the compounds was required to achieve effective treatment. Nitazoxanide, an FDA-approved antiprotozoal drug with excellent pharmacokinetic and safety profile, is the only molecule among the screening hits that reaches high plasma concentrations persisting for up to a few hours after single oral dose. Nitazoxanide activated the AMPK pathway and downregulated c-Myc, mTOR, and Wnt signaling at clinically achievable concentrations. Nitazoxanide combined with the cytotoxic drug irinotecan showed anticancer activity in vivo. We here report that the FDA-approved anthelmintic drug nitazoxanide could be a potential candidate for advancement into cancer clinical trials. ©2015 American Association for Cancer Research.

Mechanobiological simulations of peri-acetabular bone ingrowth: a comparative analysis of cell-phenotype specific and phenomenological algorithms.

PubMed

Mukherjee, Kaushik; Gupta, Sanjay

2017-03-01

Several mechanobiology algorithms have been employed to simulate bone ingrowth around porous coated implants. However, there is a scarcity of quantitative comparison between the efficacies of commonly used mechanoregulatory algorithms. The objectives of this study are: (1) to predict peri-acetabular bone ingrowth using cell-phenotype specific algorithm and to compare these predictions with those obtained using phenomenological algorithm and (2) to investigate the influences of cellular parameters on bone ingrowth. The variation in host bone material property and interfacial micromotion of the implanted pelvis were mapped onto the microscale model of implant-bone interface. An overall variation of 17-88 % in peri-acetabular bone ingrowth was observed. Despite differences in predicted tissue differentiation patterns during the initial period, both the algorithms predicted similar spatial distribution of neo-tissue layer, after attainment of equilibrium. Results indicated that phenomenological algorithm, being computationally faster than the cell-phenotype specific algorithm, might be used to predict peri-prosthetic bone ingrowth. The cell-phenotype specific algorithm, however, was found to be useful in numerically investigating the influence of alterations in cellular activities on bone ingrowth, owing to biologically related factors. Amongst the host of cellular activities, matrix production rate of bone tissue was found to have predominant influence on peri-acetabular bone ingrowth.

Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers.

PubMed

Kaluarachchi, Manuja R; Boulangé, Claire L; Garcia-Perez, Isabel; Lindon, John C; Minet, Emmanuel F

2016-10-01

Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events. A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC-MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed. Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Repurposing drugs to treat l-DOPA-induced dyskinesia in Parkinson's disease.

PubMed

Johnston, Tom H; Lacoste, Alix M B; Visanji, Naomi P; Lang, Anthony E; Fox, Susan H; Brotchie, Jonathan M

2018-06-01

In this review, we discuss the opportunity for repurposing drugs for use in l-DOPA-induced dyskinesia (LID) in Parkinson's disease. LID is a particularly suitable indication for drug repurposing given its pharmacological diversity, translatability of animal-models, availability of Phase II proof-of-concept (PoC) methodologies and the indication-specific regulatory environment. A compound fit for repurposing is defined as one with appropriate human safety-data as well as animal safety, toxicology and pharmacokinetic data as found in an Investigational New Drug (IND) package for another indication. We first focus on how such repurposing candidates can be identified and then discuss development strategies that might progress such a candidate towards a Phase II clinical PoC. We discuss traditional means for identifying repurposing candidates and contrast these with newer approaches, especially focussing on the use of computational and artificial intelligence (AI) platforms. We discuss strategies that can be categorised broadly as: in vivo phenotypic screening in a hypothesis-free manner; in vivo phenotypic screening based on analogy to a related disorder; hypothesis-driven evaluation of candidates in vivo and in silico screening with a hypothesis-agnostic component to the selection. To highlight the power of AI approaches, we describe a case study using IBM Watson where a training set of compounds, with demonstrated ability to reduce LID, were employed to identify novel repurposing candidates. Using the approaches discussed, many diverse candidates for repurposing in LID, originally envisaged for other indications, will be described that have already been evaluated for efficacy in non-human primate models of LID and/or clinically. Copyright © 2018 Elsevier Ltd. All rights reserved.

Use of a single alcohol screening question to identify other drug use.

PubMed

Smith, Peter C; Cheng, Debbie M; Allensworth-Davies, Donald; Winter, Michael R; Saitz, Richard

2014-06-01

People who consume unhealthy amounts of alcohol are more likely to use illicit drugs. We tested the ability of a screening test for unhealthy alcohol use to simultaneously detect drug use. Adult English speaking patients (n=286) were enrolled from a primary care waiting room. They were asked the screening question for unhealthy alcohol use "How many times in the past year have you had X or more drinks in a day?", where X is 5 for men and 4 for women, and a response of one or more is considered positive. A standard diagnostic interview was used to determine current (past year) drug use or a drug use disorder (abuse or dependence). Oral fluid testing was also used to detect recent use of common drugs of abuse. The single screening question for unhealthy alcohol use was 67.6% sensitive (95% confidence interval [CI], 50.2-82.0%) and 64.7% specific (95% CI, 58.4-70.6%) for the detection of a drug use disorder. It was similarly insensitive for drug use detected by oral fluid testing and/or self-report. Although a patient with a drug use disorder has twice the odds of screening positive for unhealthy alcohol use compared to one without a drug use disorder, suggesting patients who screen positive for alcohol should be asked about drug use, a single screening question for unhealthy alcohol use was not sensitive or specific for the detection of other drug use or drug use disorders in a sample of primary care patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Leaf margin phenotype-specific restriction-site-associated DNA-derived markers for pineapple (Ananas comosus L.)

PubMed Central

Urasaki, Naoya; Goeku, Satoko; Kaneshima, Risa; Takamine, Tomonori; Tarora, Kazuhiko; Takeuchi, Makoto; Moromizato, Chie; Yonamine, Kaname; Hosaka, Fumiko; Terakami, Shingo; Matsumura, Hideo; Yamamoto, Toshiya; Shoda, Moriyuki

2015-01-01

To explore genome-wide DNA polymorphisms and identify DNA markers for leaf margin phenotypes, a restriction-site-associated DNA sequencing analysis was employed to analyze three bulked DNAs of F1 progeny from a cross between a ‘piping-leaf-type’ cultivar, ‘Yugafu’, and a ‘spiny-tip-leaf-type’ variety, ‘Yonekura’. The parents were both Ananas comosus var. comosus. From the analysis, piping-leaf and spiny-tip-leaf gene-specific restriction-site-associated DNA sequencing tags were obtained and designated as PLSTs and STLSTs, respectively. The five PLSTs and two STSLTs were successfully converted to cleaved amplified polymorphic sequence (CAPS) or simple sequence repeat (SSR) markers using the sequence differences between alleles. Based on the genotyping of the F1 with two SSR and three CAPS markers, the five PLST markers were mapped in the vicinity of the P locus, with the closest marker, PLST1_SSR, being located 1.5 cM from the P locus. The two CAPS markers from STLST1 and STLST3 perfectly assessed the ‘spiny-leaf type’ as homozygotes of the recessive s allele of the S gene. The recombination value between the S locus and STLST loci was 2.4, and STLSTs were located 2.2 cM from the S locus. SSR and CAPS markers are applicable to marker-assisted selection of leaf margin phenotypes in pineapple breeding. PMID:26175625

Genetic Mapping of Fixed Phenotypes: Disease Frequency as a Breed Characteristic

PubMed Central

Jones, Paul; Martin, Alan; Ostrander, Elaine A.; Lark, Karl G.

2009-01-01

Traits that have been stringently selected to conform to specific criteria in a closed population are phenotypic stereotypes. In dogs, Canis familiaris, such stereotypes have been produced by breeding for conformation, performance (behaviors), etc. We measured phenotypes on a representative sample to establish breed stereotypes. DNA samples from 147 dog breeds were used to characterize single nucleotide polymorphism allele frequencies for association mapping of breed stereotypes. We identified significant size loci (quantitative trait loci [QTLs]), implicating candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Behavioral loci for herding, pointing, and boldness implicated candidate genes appropriate to behavior (e.g., MC2R, DRD1, and PCDH9). Significant loci for longevity, a breed characteristic inversely correlated with breed size, were identified. The power of this approach to identify loci regulating the incidence of specific polygenic diseases is demonstrated by the association of a specific IGF1 haplotype with hip dysplasia, patella luxation, and pacreatitis. PMID:19321632

Genetic mapping of fixed phenotypes: disease frequency as a breed characteristic.

PubMed

Chase, Kevin; Jones, Paul; Martin, Alan; Ostrander, Elaine A; Lark, Karl G

2009-01-01

Traits that have been stringently selected to conform to specific criteria in a closed population are phenotypic stereotypes. In dogs, Canis familiaris, such stereotypes have been produced by breeding for conformation, performance (behaviors), etc. We measured phenotypes on a representative sample to establish breed stereotypes. DNA samples from 147 dog breeds were used to characterize single nucleotide polymorphism allele frequencies for association mapping of breed stereotypes. We identified significant size loci (quantitative trait loci [QTLs]), implicating candidate genes appropriate to regulation of size (e.g., IGF1, IGF2BP2 SMAD2, etc.). Analysis of other morphological stereotypes, also under extreme selection, identified many additional significant loci. Behavioral loci for herding, pointing, and boldness implicated candidate genes appropriate to behavior (e.g., MC2R, DRD1, and PCDH9). Significant loci for longevity, a breed characteristic inversely correlated with breed size, were identified. The power of this approach to identify loci regulating the incidence of specific polygenic diseases is demonstrated by the association of a specific IGF1 haplotype with hip dysplasia, patella luxation, and pancreatitis.

Phenotype heterogeneity in cancer cell populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean

2016-06-08

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a fewmore » results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as “bet hedging” of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms

Phenotype heterogeneity in cancer cell populations

NASA Astrophysics Data System (ADS)

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean; Escargueil, Alexandre; Lorenzi, Tommaso; Lorz, Alexander; Trélat, Emmanuel

2016-06-01

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a few results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as "bet hedging" of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to

Phenotype-information-phenotype cycle for deconvolution of combinatorial antibody libraries selected against complex systems.

PubMed

Zhang, Hongkai; Torkamani, Ali; Jones, Teresa M; Ruiz, Diana I; Pons, Jaume; Lerner, Richard A

2011-08-16

Use of large combinatorial antibody libraries and next-generation sequencing of nucleic acids are two of the most powerful methods in modern molecular biology. The libraries are screened using the principles of evolutionary selection, albeit in real time, to enrich for members with a particular phenotype. This selective process necessarily results in the loss of information about less-fit molecules. On the other hand, sequencing of the library, by itself, gives information that is mostly unrelated to phenotype. If the two methods could be combined, the full potential of very large molecular libraries could be realized. Here we report the implementation of a phenotype-information-phenotype cycle that integrates information and gene recovery. After selection for phage-encoded antibodies that bind to targets expressed on the surface of Escherichia coli, the information content of the selected pool is obtained by pyrosequencing. Sequences that encode specific antibodies are identified by a bioinformatic analysis and recovered by a stringent affinity method that is uniquely suited for gene isolation from a highly degenerate collection of nucleic acids. This approach can be generalized for selection of antibodies against targets that are present as minor components of complex systems.

Phenotypic switching in bacteria

NASA Astrophysics Data System (ADS)

Merrin, Jack

Living matter is a non-equilibrium system in which many components work in parallel to perpetuate themselves through a fluctuating environment. Physiological states or functionalities revealed by a particular environment are called phenotypes. Transitions between phenotypes may occur either spontaneously or via interaction with the environment. Even in the same environment, genetically identical bacteria can exhibit different phenotypes of a continuous or discrete nature. In this thesis, we pursued three lines of investigation into discrete phenotypic heterogeneity in bacterial populations: the quantitative characterization of the so-called bacterial persistence, a theoretical model of phenotypic switching based on those measurements, and the design of artificial genetic networks which implement this model. Persistence is the phenotype of a subpopulation of bacteria with a reduced sensitivity to antibiotics. We developed a microfluidic apparatus, which allowed us to monitor the growth rates of individual cells while applying repeated cycles of antibiotic treatments. We were able to identify distinct phenotypes (normal and persistent) and characterize the stochastic transitions between them. We also found that phenotypic heterogeneity was present prior to any environmental cue such as antibiotic exposure. Motivated by the experiments with persisters, we formulated a theoretical model describing the dynamic behavior of several discrete phenotypes in a periodically varying environment. This theoretical framework allowed us to quantitatively predict the fitness of dynamic populations and to compare survival strategies according to environmental time-symmetries. These calculations suggested that persistence is a strategy used by bacterial populations to adapt to fluctuating environments. Knowledge of the phenotypic transition rates for persistence may provide statistical information about the typical environments of bacteria. We also describe a design of artificial

Behavioural phenotypes associated with specific genetic disorders: evidence from a population-based study of people with Prader-Willi syndrome.

PubMed

Holland, A J; Whittington, J E; Butler, J; Webb, T; Boer, H; Clarke, D

2003-01-01

Prader-Willi syndrome (PWS) is a genetic disorder resulting in obesity, short stature, cryptorchidism, learning disabilities (mental retardation) and severe neonatal hypotonia. Associated with the syndrome are a number of behaviours that are sufficiently distinctive that the syndrome is considered to have a specific 'behavioural phenotype'. Through multiple sources we attempted to identify all people with PWS living in one region in the U K. This cohort was augmented by people with PWS from other regions, and a contrast group of people with learning disabilities of varied aetiologies. The main carers were interviewed, using structured and semi-structured interview schedules, to establish the presence and severity of specific behaviours, and PWS diagnostic criteria. The intellectual functioning and attainments of all were determined. Blood samples were obtained for genetic diagnosis from all consenting participants. Although excessive eating was recognized as a potentially severe problem in those with PWS, it was almost universally controlled by food restriction, and therefore not seen as a 'problem behaviour'. Those with PWS differed from a learning disabled group of other aetiologies in the prevalence rates of skin picking, temper tantrums, compulsive behaviours and mood fluctuations, and also in the profile of their adaptive behaviours. The study confirms the distinct behavioural phenotype of PWS. Specific behaviours occurred significantly more frequently in PWS, compared with an age and BMI matched learning disabled comparison group. A factor analysis of the behaviours involved resulted in three factors that we hypothesized to be independent, and to arise from different mechanisms.

[Genotype/phenotype correlation in autism: genetic models and phenotypic characterization].

PubMed

Bonnet-Brilhault, F

2011-02-01

Autism spectrum disorders are a class of conditions categorized by communication problems, ritualistic behaviors, and deficits in social behaviors. This class of disorders merges a heterogeneous group of neurodevelopmental disorders regarding some phenotypic and probably physiopathological aspects. Genetic basis is well admitted, however, considering phenotypic and genotypic heterogeneity, correspondences between genotype and phenotype have yet to be established. To better identify such correspondences, genetic models have to be identified and phenotypic markers have to be characterized. Recent insights show that a variety of genetic mechanisms may be involved in autism spectrum disorders, i.e. single gene disorders, copy number variations and polygenic mechanisms. These current genetic models are described. Regarding clinical aspects, several approaches can be used in genetic studies. Nosographical approach, especially with the concept of autism spectrum disorders, merges a large group of disorders with clinical heterogeneity and may fail to identify clear genotype/phenotype correlations. Dimensional approach referred in genetic studies to the notion of "Broad Autism Phenotype" related to a constellation of language, personality, and social-behavioral features present in relatives that mirror the symptom domains of autism, but are much milder in expression. Studies of this broad autism phenotype may provide a potentially important complementary approach for detecting the genes involved in these domains. However, control population used in those studies need to be well characterized too. Identification of endophenotypes seems to offer more promising results. Endophenotypes, which are supposed to be more proximal markers of gene action in the same biological pathway, linking genes and complex clinical symptoms, are thought to be less genetically complex than the broader disease phenotype, indexing a limited aspect of genetic risk for the disorder as a whole. However

Identifying eating behavior phenotypes and their correlates: A novel direction toward improving weight management interventions.

PubMed

Bouhlal, Sofia; McBride, Colleen M; Trivedi, Niraj S; Agurs-Collins, Tanya; Persky, Susan

2017-04-01

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n = 260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants' BMI (p = 0.0002) and dietary self-efficacy (p < 0.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions. Published by Elsevier Ltd.

Identifying Neurobiological Markers of the Broader Autism Phenotype

DTIC Science & Technology

2013-09-01

2014; proposed extended deadline: Jan 19, 2015). 15. SUBJECT TERMS Broader Autism Phenotype (BAP), Autism Spectrum Disorder (ASD), Social...difficulties in autism and the BAP. In this way, the current project not only changes how autistic traits are viewed; as falling along a spectrum ...than can be experienced by people with autism spectrum disorders . BODY The information below describes the research accomplishments

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.

PubMed

Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J; Murcray, Cassandra Elizabeth; Conti, David

2011-12-01

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. © 2011 Wiley Periodicals, Inc.

Using Extreme Phenotype Sampling to Identify the Rare Causal Variants of Quantitative Traits in Association Studies

PubMed Central

Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David

2014-01-01

Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. PMID:21922541

Structural specificity of mucosal-cell transport and metabolism of peptide drugs: implication for oral peptide drug delivery

NASA Technical Reports Server (NTRS)

Bai, J. P.; Amidon, G. L.

1992-01-01

The brush border membrane of intestinal mucosal cells contains a peptide carrier system with rather broad substrate specificity and various endo- and exopeptidase activities. Small peptide (di-/tripeptide)-type drugs with or without an N-terminal alpha-amino group, including beta-lactam antibiotics and angiotensin-converting enzyme (ACE) inhibitors, are transported by the peptide transporter. Polypeptide drugs are hydrolyzed by brush border membrane proteolytic enzymes to di-/tripeptides and amino acids. Therefore, while the intestinal brush border membrane has a carrier system facilitating the absorption of di-/tripeptide drugs, it is a major barrier limiting oral availability of polypeptide drugs. In this paper, the specificity of peptide transport and metabolism in the intestinal brush border membrane is reviewed.

Optogenetic Approaches to Drug Discovery in Neuroscience and Beyond.

PubMed

Zhang, Hongkang; Cohen, Adam E

2017-07-01

Recent advances in optogenetics have opened new routes to drug discovery, particularly in neuroscience. Physiological cellular assays probe functional phenotypes that connect genomic data to patient health. Optogenetic tools, in particular tools for all-optical electrophysiology, now provide a means to probe cellular disease models with unprecedented throughput and information content. These techniques promise to identify functional phenotypes associated with disease states and to identify compounds that improve cellular function regardless of whether the compound acts directly on a target or through a bypass mechanism. This review discusses opportunities and unresolved challenges in applying optogenetic techniques throughout the discovery pipeline - from target identification and validation, to target-based and phenotypic screens, to clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Progeny Clustering: A Method to Identify Biological Phenotypes

PubMed Central

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Phenotypic Screen in Zebrafish Identifies a Novel Small-Molecule Inducer of Ectopic Tail Formation Suggestive of Alterations in Non-Canonical Wnt/PCP Signaling

PubMed Central

Gebruers, Evelien; Cordero-Maldonado, María Lorena; Gray, Alexander I.; Clements, Carol; Harvey, Alan L.; Edrada-Ebel, Ruangelie; de Witte, Peter A. M.; Crawford, Alexander D.; Esguerra, Camila V.

2013-01-01

Zebrafish have recently emerged as an attractive model for the in vivo bioassay-guided isolation and characterization of pharmacologically active small molecules of natural origin. We carried out a zebrafish-based phenotypic screen of over 3000 plant-derived secondary metabolite extracts with the goal of identifying novel small-molecule modulators of the BMP and Wnt signaling pathways. One of the bioactive plant extracts identified in this screen – Jasminum gilgianum, an Oleaceae species native to Papua New Guinea – induced ectopic tails during zebrafish embryonic development. As ectopic tail formation occurs when BMP or non-canonical Wnt signaling is inhibited during the tail protrusion process, we suspected a constituent of this extract to act as a modulator of these pathways. A bioassay-guided isolation was carried out on the basis of this zebrafish phenotype, identifying para-coumaric acid methyl ester (pCAME) as the active compound. We then performed an in-depth phenotypic analysis of pCAME-treated zebrafish embryos, including a tissue-specific marker analysis of the secondary tails. We found pCAME to synergize with the BMP-inhibitors dorsomorphin and LDN-193189 in inducing ectopic tails, and causing convergence-extension defects in compound-treated embryos. These results indicate that pCAME may interfere with non-canonical Wnt signaling. Inhibition of Jnk, a downstream target of Wnt/PCP signaling (via morpholino antisense knockdown and pharmacological inhibition with the kinase inhibitor SP600125) phenocopied pCAME-treated embryos. However, immunoblotting experiments revealed pCAME to not directly inhibit Jnk-mediated phosphorylation of c-Jun, suggesting additional targets of SP600125, and/or other pathways, as possibly being involved in the ectopic tail formation activity of pCAME. Further investigation of pCAME’s mechanism of action will help determine this compound’s pharmacological utility. PMID:24349481

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it.

PubMed

Kell, Douglas B

2013-12-01

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that

EuroPhenome: a repository for high-throughput mouse phenotyping data

PubMed Central

Morgan, Hugh; Beck, Tim; Blake, Andrew; Gates, Hilary; Adams, Niels; Debouzy, Guillaume; Leblanc, Sophie; Lengger, Christoph; Maier, Holger; Melvin, David; Meziane, Hamid; Richardson, Dave; Wells, Sara; White, Jacqui; Wood, Joe; de Angelis, Martin Hrabé; Brown, Steve D. M.; Hancock, John M.; Mallon, Ann-Marie

2010-01-01

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. PMID:19933761

Systematic identification of proteins that elicit drug side effects

PubMed Central

Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica; Jensen, Lars Juhl; Gross, Cornelius; Gavin, Anne-Claude; Bork, Peer

2013-01-01

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug–target relations to identify overrepresented protein–side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations. PMID:23632385

Identifying types of drug intoxication : laboratory evaluation of a subject-examination procedure

DOT National Transportation Integrated Search

1985-05-01

The Los Angeles Police Department (LAPD) has developed a rating procedures for use in detecting drug-impaired drivers. The purpose of the rating procedures is to determine whether the driver is impaired and to identify the responsible drug class (e.g...

Mutant phenotypes for thousands of bacterial genes of unknown function

DOE PAGES

Price, Morgan N.; Wetmore, Kelly M.; Waters, R. Jordan; ...

2018-05-16

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because theymore » are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Lastly, our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.« less

Mutant phenotypes for thousands of bacterial genes of unknown function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, Morgan N.; Wetmore, Kelly M.; Waters, R. Jordan

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because theymore » are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Lastly, our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.« less

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

Cell Death Pathways in Mutant Rhodopsin Rat Models Identifies Genotype-Specific Targets Controlling Retinal Degeneration.

PubMed

Viringipurampeer, Ishaq A; Gregory-Evans, Cheryl Y; Metcalfe, Andrew L; Bashar, Emran; Moritz, Orson L; Gregory-Evans, Kevin

2018-06-18

Retinitis pigmentosa (RP) is a group of inherited neurological disorders characterized by rod photoreceptor cell death, followed by secondary cone cell death leading to progressive blindness. Currently, there are no viable treatment options for RP. Due to incomplete knowledge of the molecular signaling pathways associated with RP pathogenesis, designing therapeutic strategies remains a challenge. In particular, preventing secondary cone photoreceptor cell loss is a key goal in designing potential therapies. In this study, we identified the main drivers of rod cell death and secondary cone loss in the transgenic S334ter rhodopsin rat model, tested the efficacy of specific cell death inhibitors on retinal function, and compared the effect of combining drugs to target multiple pathways in the S334ter and P23H rhodopsin rat models. The primary driver of early rod cell death in the S334ter model was a caspase-dependent process, whereas cone cell death occurred though RIP3-dependent necroptosis. In comparison, rod cell death in the P23H model was via necroptotic signaling, whereas cone cell loss occurred through inflammasome activation. Combination therapy of four drugs worked better than the individual drugs in the P23H model but not in the S334ter model. These differences imply that treatment modalities need to be tailored for each genotype. Taken together, our data demonstrate that rationally designed genotype-specific drug combinations will be an important requisite to effectively target primary rod cell loss and more importantly secondary cone survival.

Drugs Most Frequently Involved in Drug Overdose Deaths: United States, 2010-2014.

PubMed

Warner, Margaret; Trinidad, James P; Bastian, Brigham A; Minino, Arialdi M; Hedegaard, Holly

2016-12-01

Objectives-This report identifies the specific drugs most frequently involved in drug overdose deaths in the United States from 2010 through 2014. Methods-The 2010-2014 National Vital Statistics System mortality files were linked to electronic files containing literal text information from death certificates. Drug overdose was defined using the International Classification of Diseases, Tenth Revision underlying cause-of-death codes X40-X44 (unintentional), X60-X64 (suicide), X85 (homicide), and Y10-Y14 (undetermined intent). Among deaths with an underlying cause of death of drug overdose, the literal text in three fields of the death certificate (i.e., the cause of death from Part I, significant conditions contributing to death from Part II, and a description of how the injury occurred from Box 43) were searched to identify drug mentions. Search term lists were developed using existing drug classification systems as well as from manual review of the literal text. The search term list was then used to identify the specific drugs involved in overdose deaths. Descriptive statistics were reported for drug overdose deaths involving the 10 most frequently mentioned drugs on death certificates. Tables and figures presenting information on the specific drugs involved in deaths are based on deaths with mention of at least one specific drug on the death certificate. Results-From 2010 through 2014, the number of drug overdose deaths per year increased 23%, from 38,329 in 2010 to 47,055 in 2014. During this time period, the percentage of drug overdose deaths involving at least one specific drug increased, from 67% in 2010 to 78% in 2014. Among drug overdose deaths with at least one drug specified on the death certificate, the 10 drugs most frequently involved in overdose deaths included the following opioids: heroin, oxycodone, methadone, morphine, hydrocodone, and fentanyl; the following benzodiazepines: alprazolam and diazepam; and the following stimulants: cocaine and

Exome sequencing in children of women with skewed X-inactivation identifies atypical cases and complex phenotypes.

PubMed

Giorgio, Elisa; Brussino, Alessandro; Biamino, Elisa; Belligni, Elga Fabia; Bruselles, Alessandro; Ciolfi, Andrea; Caputo, Viviana; Pizzi, Simone; Calcia, Alessandro; Di Gregorio, Eleonora; Cavalieri, Simona; Mancini, Cecilia; Pozzi, Elisa; Ferrero, Marta; Riberi, Evelise; Borelli, Iolanda; Amoroso, Antonio; Ferrero, Giovanni Battista; Tartaglia, Marco; Brusco, Alfredo

2017-05-01

More than 100 X-linked intellectual disability (X-LID) genes have been identified to be involved in 10-15% of intellectual disability (ID). To identify novel possible candidates, we selected 18 families with a male proband affected by isolated or syndromic ID. Pedigree and/or clinical presentation suggested an X-LID disorder. After exclusion of known genetic diseases, we identified seven cases whose mother showed a skewed X-inactivation (>80%) that underwent whole exome sequencing (WES, 50X average depth). WES allowed to solve the genetic basis in four cases, two of which (Coffin-Lowry syndrome, RPS6K3 gene; ATRX syndrome, ATRX gene) had been missed by previous clinical/genetics tests. One further ATRX case showed a complex phenotype including pontocerebellar atrophy (PCA), possibly associated to an unidentified PCA gene mutation. In a case with suspected Lujan-Fryns syndrome, a c.649C>T (p.Pro217Ser) MECP2 missense change was identified, likely explaining the neurological impairment, but not the marfanoid features, which were possibly associated to the p.Thr1020Ala variant in fibrillin 1. Finally, a c.707T>G variant (p.Phe236Cys) in the DMD gene was identified in a patient retrospectively recognized to be affected by Becker muscular dystrophy (BMD, OMIM 300376). Overall, our data show that WES may give hints to solve complex ID phenotypes with a likely X-linked transmission, and that a significant proportion of these orphan conditions might result from concomitant mutations affecting different clinically associated genes. Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Naturally Occurring Deletion Mutants of the Pig-Specific, Intestinal Crypt Epithelial Cell Protein CLCA4b without Apparent Phenotype

PubMed Central

Plog, Stephanie; Klymiuk, Nikolai; Binder, Stefanie; Van Hook, Matthew J.; Thoreson, Wallace B.; Gruber, Achim D.; Mundhenk, Lars

2015-01-01

The human CLCA4 (chloride channel regulator, calcium-activated) modulates the intestinal phenotype of cystic fibrosis (CF) patients via an as yet unknown pathway. With the generation of new porcine CF models, species-specific differences between human modifiers of CF and their porcine orthologs are considered critical for the translation of experimental data. Specifically, the porcine ortholog to the human CF modulator gene CLCA4 has recently been shown to be duplicated into two separate genes, CLCA4a and CLCA4b. Here, we characterize the duplication product, CLCA4b, in terms of its genomic structure, tissue and cellular expression patterns as well as its in vitro electrophysiological properties. The CLCA4b gene is a pig-specific duplication product of the CLCA4 ancestor and its protein is exclusively expressed in small and large intestinal crypt epithelial cells, a niche specifically occupied by no other porcine CLCA family member. Surprisingly, a unique deleterious mutation of the CLCA4b gene is spread among modern and ancient breeds in the pig population, but this mutation did not result in an apparent phenotype in homozygously affected animals. Electrophysiologically, neither the products of the wild type nor of the mutated CLCA4b genes were able to evoke a calcium-activated anion conductance, a consensus feature of other CLCA proteins. The apparently pig-specific duplication of the CLCA4 gene with unique expression of the CLCA4b protein variant in intestinal crypt epithelial cells where the porcine CFTR is also present raises the question of whether it may modulate the porcine CF phenotype. Moreover, the naturally occurring null variant of CLCA4b will be valuable for the understanding of CLCA protein function and their relevance in modulating the CF phenotype. PMID:26474299

Population differences in platinum toxicity as a means to identify novel genetic susceptibility variants

PubMed Central

O'Donnell, Peter H.; Gamazon, Eric; Zhang, Wei; Stark, Amy L.; Kistner-Griffin, Emily O.; Huang, R. Stephanie; Dolan, M. Eileen

2010-01-01

Objectives Clinical studies show that Asians (ASN) are more susceptible to toxicities associated with platinum-containing regimens. We hypothesized that studying ASN as an `enriched phenotype' population could enable the discovery of novel genetic determinants of platinum susceptibility. Methods Using well-genotyped lymphoblastoid cell lines from the HapMap, we determined cisplatin and carboplatin cytotoxicity phenotypes (IC50s) for ASN, Caucasians (CEU), and Africans (YRI). IC50s were used in genome-wide association studies. Results ASN were most sensitive to platinums, corroborating clinical findings. ASN genome-wide association studies produced 479 single-nucleotide polymorphisms (SNPs) associating with cisplatin susceptibility and 199 with carboplatin susceptibility (P<10−4). Considering only the most significant variants (P< 9.99 × 10−6), backwards elimination was then used to identify reduced-model SNPs, which robustly described the drug phenotypes within ASN. These SNPs comprised highly descriptive genetic signatures of susceptibility, with 12 SNPs explaining more than 95% of the susceptibility phenotype variation for cisplatin, and eight SNPs approximately 75% for carboplatin. To determine the possible function of these variants in ASN, the SNPs were tested for association with differential expression of target genes. SNPs were highly associated with the expression of multiple target genes, and notably, the histone H3 family was implicated for both drugs, suggesting a platinum-class mechanism. Histone H3 has repeatedly been described as regulating the formation of platinum-DNA adducts, but this is the first evidence that specific genetic variants might mediate these interactions in a pharmacogenetic manner. Finally, to determine whether any ASN-identified SNPs might also be important in other human populations, we interrogated all 479/199 SNPs for association with platinum susceptibility in an independent combined CEU/YRI population. Three unique SNPs

Mechanistically Distinct Pathways of Divergent Regulatory DNA Creation Contribute to Evolution of Human-Specific Genomic Regulatory Networks Driving Phenotypic Divergence of Homo sapiens.

PubMed

Glinsky, Gennadi V

2016-09-19

Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Collectively, a compendium of multiple diverse families of HSRS that are functionally and structurally divergent from Great Apes could be defined as the backbone of human-specific genomic regulatory networks. Here, the conservation patterns analysis of 18,364 candidate HSRS was carried out requiring that 100% of bases must remap during the alignments of human, chimpanzee, and bonobo sequences. A total of 5,535 candidate HSRS were identified that are: (i) highly conserved in Great Apes; (ii) evolved by the exaptation of highly conserved ancestral DNA; (iii) defined by either the acceleration of mutation rates on the human lineage or the functional divergence from non-human primates. The exaptation of highly conserved ancestral DNA pathway seems mechanistically distinct from the evolution of regulatory DNA segments driven by the species-specific expansion of transposable elements. Genome-wide proximity placement analysis of HSRS revealed that a small fraction of topologically associating domains (TADs) contain more than half of HSRS from four distinct families. TADs that are enriched for HSRS and termed rapidly evolving in humans TADs (revTADs) comprise 0.8-10.3% of 3,127 TADs in the hESC genome. RevTADs manifest distinct correlation patterns between placements of human accelerated regions, human-specific transcription factor-binding sites, and recombination rates. There is a significant enrichment within revTAD boundaries of hESC-enhancers, primate-specific CTCF-binding sites, human-specific RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific enrichment at TSS in prefrontal cortex neurons (P < 0.0001 in all instances). Present analysis supports the idea that phenotypic divergence of Homo sapiens is driven by the evolution of human-specific

Mechanistically Distinct Pathways of Divergent Regulatory DNA Creation Contribute to Evolution of Human-Specific Genomic Regulatory Networks Driving Phenotypic Divergence of Homo sapiens

PubMed Central

Glinsky, Gennadi V.

2016-01-01

Abstract Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Collectively, a compendium of multiple diverse families of HSRS that are functionally and structurally divergent from Great Apes could be defined as the backbone of human-specific genomic regulatory networks. Here, the conservation patterns analysis of 18,364 candidate HSRS was carried out requiring that 100% of bases must remap during the alignments of human, chimpanzee, and bonobo sequences. A total of 5,535 candidate HSRS were identified that are: (i) highly conserved in Great Apes; (ii) evolved by the exaptation of highly conserved ancestral DNA; (iii) defined by either the acceleration of mutation rates on the human lineage or the functional divergence from non-human primates. The exaptation of highly conserved ancestral DNA pathway seems mechanistically distinct from the evolution of regulatory DNA segments driven by the species-specific expansion of transposable elements. Genome-wide proximity placement analysis of HSRS revealed that a small fraction of topologically associating domains (TADs) contain more than half of HSRS from four distinct families. TADs that are enriched for HSRS and termed rapidly evolving in humans TADs (revTADs) comprise 0.8–10.3% of 3,127 TADs in the hESC genome. RevTADs manifest distinct correlation patterns between placements of human accelerated regions, human-specific transcription factor-binding sites, and recombination rates. There is a significant enrichment within revTAD boundaries of hESC-enhancers, primate-specific CTCF-binding sites, human-specific RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific enrichment at TSS in prefrontal cortex neurons (P < 0.0001 in all instances). Present analysis supports the idea that phenotypic divergence of Homo sapiens is driven by the evolution of

Cell-specific prediction and application of drug-induced gene expression profiles.

PubMed

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Cell-specific prediction and application of drug-induced gene expression profiles

PubMed Central

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

2017-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Phenotypic assays for Mycobacterium tuberculosis infection.

PubMed

Song, Ok-Ryul; Deboosere, Nathalie; Delorme, Vincent; Queval, Christophe J; Deloison, Gaspard; Werkmeister, Elisabeth; Lafont, Frank; Baulard, Alain; Iantomasi, Raffaella; Brodin, Priscille

2017-10-01

Tuberculosis (TB) is still a major global threat, killing more than one million persons each year. With the constant increase of Mycobacterium tuberculosis strains resistant to first- and second-line drugs, there is an urgent need for the development of new drugs to control the propagation of TB. Although screenings of small molecules on axenic M. tuberculosis cultures were successful for the identification of novel putative anti-TB drugs, new drugs in the development pipeline remains scarce. Host-directed therapy may represent an alternative for drug development against TB. Indeed, M. tuberculosis has multiple specific interactions within host phagocytes, which may be targeted by small molecules. In order to enable drug discovery strategies against microbes residing within host macrophages, we developed multiple fluorescence-based HT/CS phenotypic assays monitoring the intracellular replication of M. tuberculosis as well as its intracellular trafficking. What we propose here is a population-based, multi-parametric analysis pipeline that can be used to monitor the intracellular fate of M. tuberculosis and the dynamics of cellular events such as phagosomal maturation (acidification and permeabilization), zinc poisoning system or lipid body accumulation. Such analysis allows the quantification of biological events considering the host-pathogen interplay and may thus be derived to other intracellular pathogens. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Role of specific IgE to β-lactoglobulin in the gastrointestinal phenotype of cow's milk allergy.

PubMed

Poza-Guedes, Paloma; Barrios, Yvelise; González-Pérez, Ruperto; Sánchez-Machín, Inmaculada; Franco, Andres; Matheu, Víctor

2016-01-01

The prevalence of many phenotypes of food allergy is increasing. Specific gastrointestinal (GI) phenotype of food allergy (GI allergy) is also increasing but it is difficult to know the prevalence because of many entities. METHODS AND RESULTS: A 1 year retrospective study of pediatric patients complaining exclusively gastrointestinal symptoms after cow's milk consumption and at least one positive specific IgE (sIgE) to cow's milk (CM) proteins (CMP) was done (n = 39). The most prevalent symptom was abdominal cramps in 35 patients (90 %), discomfort or abdominal distention in 30 patients (75 %), diarrhea in 10 patients (25 %) and constipation in 5 patients (12 %). IgA anti-transglutaminase antibodies were absent and lactose intolerance was ruled out in all patients. Average of total IgE on this group was 288 UI/ml. sIgE against β-lactoglobulin was the dominant with an average of 4.14 kU/l. sIgE to casein (CAS), which is the dominant protein in systemic anaphylaxis was 1.74 kU/l; sIgE to α-lactoalbumin, the other whey protein, was 0.83 kU/l and sIgE levels to CM were 0.78 kU/l. The quotient sIgE CAS/sIgE β-lactoglobulin in these patients was always lower than 1. Patients experienced an improvement of their symptoms after a CM free diet. An open oral challenge with CM did mimic their initial symptoms in all patients. However, the open oral challenge with dairy products was well tolerated. Patients with a specific phenotype of GI allergy with CM have specific IgE against β-lactoglobulin, as a dominant sIgE. These patients could beneficiate of a diet with dairy products.

A specific pathway can be identified between genetic characteristics and behaviour profiles in Prader-Willi syndrome via cognitive, environmental and physiological mechanisms.

PubMed

Woodcock, K A; Oliver, C; Humphreys, G W

2009-06-01

Behavioural phenotypes associated with genetic syndromes have been extensively investigated in order to generate rich descriptions of phenomenology, determine the degree of specificity of behaviours for a particular syndrome, and examine potential interactions between genetic predispositions for behaviour and environmental influences. However, relationships between different aspects of behavioural phenotypes have been less frequently researched and although recent interest in potential cognitive phenotypes or endophenotypes has increased, these are frequently studied independently of the behavioural phenotypes. Taking Prader-Willi syndrome (PWS) as an example, we discuss evidence suggesting specific relationships between apparently distinct aspects of the PWS behavioural phenotype and relate these to specific endophenotypic characteristics. The framework we describe progresses through biological, cognitive, physiological and behavioural levels to develop a pathway from genetic characteristics to behaviour with scope for interaction with the environment at any stage. We propose this multilevel approach as useful in setting out hypotheses in order to structure research that can more rapidly advance theory.

High-throughput discovery of novel developmental phenotypes

PubMed Central

Dickinson, Mary E.; Flenniken, Ann M.; Ji, Xiao; Teboul, Lydia; Wong, Michael D.; White, Jacqueline K.; Meehan, Terrence F.; Weninger, Wolfgang J.; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N.; Bower, Lynette; Brown, James M.; Caddle, L. Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J.; Denegre, James M.; Doe, Brendan; Dolan, Mary E.; Edie, Sarah M.; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R.; Hsu, Chih-wei; Johnson, Sara J.; Kalaga, Sowmya; Keith, Lance C.; Lanoue, Louise; Lawson, Thomas N.; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L.; Newbigging, Susan; Nutter, Lauryl M.J.; Peterson, Kevin A.; Ramirez-Solis, Ramiro; Rowland, Douglas J.; Ryder, Edward; Samocha, Kaitlin E.; Seavitt, John R.; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B.; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G.; Tocchini-Valentini, Glauco P.; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C.; Justice, Monica J.; Parkinson, Helen E.; Moore, Mark; Wells, Sara; Braun, Robert E.; Svenson, Karen L.; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R. Mark; Brown, Steve D.M.; Adams, David J.; Lloyd, K.C. Kent; McKerlie, Colin; Beaudet, Arthur L.; Bucan, Maja; Murray, Stephen A.

2016-01-01

Approximately one third of all mammalian genes are essential for life. Phenotypes resulting from mouse knockouts of these genes have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5000 knockout mouse lines, we have identified 410 lethal genes during the production of the first 1751 unique gene knockouts. Using a standardised phenotyping platform that incorporates high-resolution 3D imaging, we identified novel phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes identified in our screen, thus providing a novel dataset that facilitates prioritization and validation of mutations identified in clinical sequencing efforts. PMID:27626380

Persistency of use of COX-2-specific inhibitors and non-specific non-steroidal anti-inflammatory drugs (NSAIDs) in Quebec.

PubMed

Moride, Y; Ducruet, T; Rochon, S; Lavoie, F

2003-11-01

The effectiveness of pharmacological therapies is dependent in part on patient persistency with the prescribed therapeutic regimen. In the case of non-specific non-steroidal anti-inflammatory drugs (NSAIDs), effectiveness is often compromised by undesirable side-effects, poor compliance or discontinuation of therapy. While patterns of utilization of non-specific NSAIDs have been investigated, few data are available on the patterns of persistency for cyclooxygenase (COX)-2-specific inhibitors. This study used a provincial health-care system database in Quebec, Canada, to determine the duration of treatment in new users of COX-2-specific inhibitors and non-specific NSAIDs over the first 3 months of treatment, and to characterize the factors associated with treatment persistency. Results demonstrate that the median duration of treatment was longer among patients initially prescribed COX-2-specific inhibitors (30 days and 23 days for celecoxib and rofecoxib respectively) than in those prescribed non-selective NSAIDs (10 days). Although the percentage of patients remaining on COX-2-specific drugs declined over the course of treatment, few patients on either celecoxib or rofecoxib switched drugs, either to the other COX-2-specific inhibitor or to non-specific NSAIDs. Factors associated with persistent drug use were: COX-2-specific inhibitors, age, and the use of gastroprotective agents either at treatment initiation or during follow-up. Dosage, chronic disease score and prescriber's specialty were only marginally associated with persistency. Prior use of gastroprotective agents was associated with lower persistency. Although the limitations of this study, which included lack of information on the indication for the prescription and the reason for switch or discontinuation, preclude definite conclusions regarding patterns of use of these drugs, the data suggest that the use of COX-2-specific inhibitors may result in increased persistency with treatment.

Constellation Pharmacology: A new paradigm for drug discovery

PubMed Central

Schmidt, Eric W.; Olivera, Baldomero M.

2015-01-01

Constellation Pharmacology is a cell-based high-content phenotypic-screening platform that utilizes subtype-selective pharmacological agents to elucidate the cell-specific combinations (“constellations”) of key signaling proteins that define specific cell types. Heterogeneous populations of native cells, in which the different individual cell types have been identified and characterized, are the foundation for this screening platform. Constellation Pharmacology is useful for screening small molecules or for deconvoluting complex mixtures of biologically-active natural products. This platform has been used to purify natural products and discover their molecular mechanisms. In the on-going development of Constellation Pharmacology, there is a positive-feedback loop between the pharmacological characterization of cell types and screening for new drug candidates. As Constellation Pharmacology is used to discover compounds with novel targeting-selectivity profiles, those new compounds then further help to elucidate the constellations of specific cell types, thereby increasing the content of this high-content platform. PMID:25562646

Identifying and assessing highly hazardous drugs within quality risk management programs.

PubMed

Sussman, Robert G; Schatz, Anthony R; Kimmel, Tracy A; Ader, Allan; Naumann, Bruce D; Weideman, Patricia A

2016-08-01

Historically, pharmaceutical industry regulatory guidelines have assigned certain active pharmaceutical ingredients (APIs) to various categories of concern, such as "cytotoxic", "hormones", and "steroids". These categories have been used to identify APIs requiring segregation or dedication in order to prevent cross-contamination and protect the quality and safety of drug products. Since these terms were never defined by regulatory authorities, and many novel pharmacological mechanisms challenge these categories, there is a recognized need to modify the historical use of these terms. The application of a risk-based approach using a health-based limit, such as an acceptable daily exposure (ADE), is more appropriate for the development of a Quality Risk Management Program (QRMP) than the use of categories of concern. The toxicological and pharmacological characteristics of these categories are discussed to help identify and prioritize compounds requiring special attention. Controlling airborne concentrations and the contamination of product contact surfaces in accordance with values derived from quantitative risk assessments can prevent adverse effects in workers and patients, regardless of specific categorical designations to which these APIs have been assigned. The authors acknowledge the movement away from placing compounds into categories and, while not yet universal, the importance of basing QRMPs on compound-specific ADEs and risk assessments. Based on the results of a risk assessment, segregation and dedication may also be required for some compounds to prevent cross contamination during manufacture of APIs. Copyright © 2016 Elsevier Inc. All rights reserved.

Specific Cell Targeting Therapy Bypasses Drug Resistance Mechanisms in African Trypanosomiasis

PubMed Central

Unciti-Broceta, Juan D.; Arias, José L.; Maceira, José; Soriano, Miguel; Ortiz-González, Matilde; Hernández-Quero, José; Muñóz-Torres, Manuel; de Koning, Harry P.; Magez, Stefan; Garcia-Salcedo, José A.

2015-01-01

African trypanosomiasis is a deadly neglected disease caused by the extracellular parasite Trypanosoma brucei. Current therapies are characterized by high drug toxicity and increasing drug resistance mainly associated with loss-of-function mutations in the transporters involved in drug import. The introduction of new antiparasitic drugs into therapeutic use is a slow and expensive process. In contrast, specific targeting of existing drugs could represent a more rapid and cost-effective approach for neglected disease treatment, impacting through reduced systemic toxicity and circumventing resistance acquired through impaired compound uptake. We have generated nanoparticles of chitosan loaded with the trypanocidal drug pentamidine and coated by a single domain nanobody that specifically targets the surface of African trypanosomes. Once loaded into this nanocarrier, pentamidine enters trypanosomes through endocytosis instead of via classical cell surface transporters. The curative dose of pentamidine-loaded nanobody-chitosan nanoparticles was 100-fold lower than pentamidine alone in a murine model of acute African trypanosomiasis. Crucially, this new formulation displayed undiminished in vitro and in vivo activity against a trypanosome cell line resistant to pentamidine as a result of mutations in the surface transporter aquaglyceroporin 2. We conclude that this new drug delivery system increases drug efficacy and has the ability to overcome resistance to some anti-protozoal drugs. PMID:26110623

Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping

PubMed Central

Shafiekhani, Ali; Kadam, Suhas; Fritschi, Felix B.; DeSouza, Guilherme N.

2017-01-01

In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses; second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants; and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable. PMID:28124976

Live Cell in Vitro and in Vivo Imaging Applications: Accelerating Drug Discovery

PubMed Central

Isherwood, Beverley; Timpson, Paul; McGhee, Ewan J; Anderson, Kurt I; Canel, Marta; Serrels, Alan; Brunton, Valerie G; Carragher, Neil O

2011-01-01

Dynamic regulation of specific molecular processes and cellular phenotypes in live cell systems reveal unique insights into cell fate and drug pharmacology that are not gained from traditional fixed endpoint assays. Recent advances in microscopic imaging platform technology combined with the development of novel optical biosensors and sophisticated image analysis solutions have increased the scope of live cell imaging applications in drug discovery. We highlight recent literature examples where live cell imaging has uncovered novel insight into biological mechanism or drug mode-of-action. We survey distinct types of optical biosensors and associated analytical methods for monitoring molecular dynamics, in vitro and in vivo. We describe the recent expansion of live cell imaging into automated target validation and drug screening activities through the development of dedicated brightfield and fluorescence kinetic imaging platforms. We provide specific examples of how temporal profiling of phenotypic response signatures using such kinetic imaging platforms can increase the value of in vitro high-content screening. Finally, we offer a prospective view of how further application and development of live cell imaging technology and reagents can accelerate preclinical lead optimization cycles and enhance the in vitro to in vivo translation of drug candidates. PMID:24310493

Drug conjugated nanoparticles activated by cancer cell specific mRNA.

PubMed

Gossai, Nathan P; Naumann, Jordan A; Li, Nan-Sheng; Zamora, Edward A; Gordon, David J; Piccirilli, Joseph A; Gordon, Peter M

2016-06-21

We describe a customizable approach to cancer therapy in which a gold nanoparticle (Au-NP) delivers a drug that is selectively activated within the cancer cell by the presence of an mRNA unique to the cancer cell. Fundamental to this approach is the observation that the amount of drug released from the Au-NP is proportional to both the presence and abundance of the cancer cell specific mRNA in a cell. As proof-of-principle, we demonstrate both the efficient delivery and selective release of the multi-kinase inhibitor dasatinib from Au-NPs in leukemia cells with resulting efficacy in vitro and in vivo. Furthermore, these Au-NPs reduce toxicity against hematopoietic stem cells and T-cells. This approach has the potential to improve the therapeutic efficacy of a drug and minimize toxicity while being highly customizable with respect to both the cancer cell specific mRNAs targeted and drugs activated.

Distinct prion-like strains of amyloid beta implicated in phenotypic diversity of Alzheimer's disease.

PubMed

Cohen, Mark; Appleby, Brian; Safar, Jiri G

2016-01-01

Vast evidence on human prions demonstrates that variable disease phenotypes, rates of propagation, and targeting of distinct brain structures are determined by unique conformers (strains) of pathogenic prion protein (PrP(Sc)). Recent progress in the development of advanced biophysical tools that inventory structural characteristics of amyloid beta (Aβ) in the brain cortex of phenotypically diverse Alzheimer's disease (AD) patients, revealed unique spectrum of oligomeric particles in the cortex of rapidly progressive cases, implicating these structures in variable rates of propagation in the brain, and in distict disease manifestation. Since only ∼30% of phenotypic diversity of AD can be explained by polymorphisms in risk genes, these and transgenic bioassay data argue that structurally distinct Aβ particles play a major role in the diverse pathogenesis of AD, and may behave as distinct prion-like strains encoding diverse phenotypes. From these observations and our growing understanding of prions, there is a critical need for new strain-specific diagnostic strategies for misfolded proteins causing these elusive disorders. Since targeted drug therapy can induce mutation and evolution of prions into new strains, effective treatments of AD will require drugs that enhance clearance of pathogenic conformers, reduce the precursor protein, or inhibit the conversion of precursors into prion-like states.

Phenotypic Signatures Arising from Unbalanced Bacterial Growth

PubMed Central

Tan, Cheemeng; Smith, Robert Phillip; Tsai, Ming-Chi; Schwartz, Russell; You, Lingchong

2014-01-01

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains. PMID:25101949

Phenotypic signatures arising from unbalanced bacterial growth.

PubMed

Tan, Cheemeng; Smith, Robert Phillip; Tsai, Ming-Chi; Schwartz, Russell; You, Lingchong

2014-08-01

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify "phenotypic signatures" by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis.

PubMed

Lee, Hyokyeong; Moody-Davis, Asher; Saha, Utsab; Suzuki, Brian M; Asarnow, Daniel; Chen, Steven; Arkin, Michelle; Caffrey, Conor R; Singh, Rahul

2012-01-01

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

PubMed Central

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites.

PubMed

Irizarry, Kristopher J L; Bryden, Randall L

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

Genotype-phenotype associations in obesity dependent on definition of the obesity phenotype.

PubMed

Kring, Sofia Inez Iqbal; Larsen, Lesli Hingstrup; Holst, Claus; Toubro, Søren; Hansen, Torben; Astrup, Arne; Pedersen, Oluf; Sørensen, Thorkild I A

2008-01-01

In previous studies of associations of variants in the genes UCP2, UCP3, PPARG2, CART, GRL, MC4R, MKKS, SHP, GHRL, and MCHR1 with obesity, we have used a case-control approach with cases defined by a threshold for BMI. In the present study, we assess the association of seven abdominal, peripheral, and overall obesity phenotypes, which were analyzed quantitatively, and thirteen candidate gene polymorphisms in these ten genes in the same cohort. Obese Caucasian men (n = 234, BMI >or= 31.0 kg/m(2)) and a randomly sampled non-obese group (n = 323), originally identified at the draft board examinations, were re-examined at median ages of 47.0 or 49.0 years by anthropometry and DEXA scanning. Obesity phenotypes included BMI, fat body mass index, waist circumference, waist for given BMI, intra-abdominal adipose tissue, hip circumference and lower body fat mass (%). Using logistic regression models, we estimated the odds for defined genotypes (dominant or recessive genetic transmission) in relation to z-scores of the phenotypes. The minor (rare) allele for SHP 512G>C (rs6659176) was associated with increased hip circumference. The minor allele for UCP2 Ins45bp was associated with increased BMI, increased abdominal obesity, and increased hip circumference. The minor allele for UCP2 -866G>A (rs6593669) was associated with borderline increased fat body mass index. The minor allele for MCHR1 100213G>A (rs133072) was associated with reduced abdominal obesity. None of the other genotype-phenotype combinations showed appreciable associations. If replicated in independent studies with focus on the specific phenotypes, our explorative studies suggest significant associations between some candidate gene polymorphisms and distinct obesity phenotypes, predicting beneficial and detrimental effects, depending on compartments for body fat accumulation. Copyright 2008 S. Karger AG, Basel.

Context-sensitive network-based disease genetics prediction and its implications in drug discovery.

PubMed

Chen, Yang; Xu, Rong

2017-04-01

Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery. We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach ( pdrug target gene for PD, and found its association with neurodegeneration supported by literature. In summary, CSNs lead to significantly improve the disease genetics prediction comparing with SBNs and provide leads for potential drug targets. nlp.case.edu/public/data/. rxx@case.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Context-sensitive network-based disease genetics prediction and its implications in drug discovery

PubMed Central

Chen, Yang; Xu, Rong

2017-01-01

Abstract Motivation: Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery. Results: We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach (pdrug target gene for PD, and found its association with neurodegeneration supported by literature. In summary, CSNs lead to significantly improve the disease genetics prediction comparing with SBNs and provide leads for potential drug targets. Availability and Implementation: nlp.case.edu/public/data/ Contact: rxx@case.edu PMID:28062449

Identifying genomic and developmental causes of adverse drug reactions in children

PubMed Central

Becker, Mara L; Leeder, J Steven

2011-01-01

Adverse drug reactions are a concern for all clinicians who utilize medications to treat adults and children; however, the frequency of adult and pediatric adverse drug reactions is likely to be under-reported. In this age of genomics and personalized medicine, identifying genetic variation that results in differences in drug biotransformation and response has contributed to significant advances in the utilization of several commonly used medications in adults. In order to better understand the variability of drug response in children however, we must not only consider differences in genotype, but also variation in gene expression during growth and development, namely ontogeny. In this article, recommendations for systematically approaching pharmacogenomic studies in children are discussed, and several examples of studies that investigate the genomic and developmental contribution to adverse drug reactions in children are reviewed. PMID:21121777

Fluorescently labeled dengue viruses as probes to identify antigen-specific memory B cells by multiparametric flow cytometry.

PubMed

Woda, Marcia; Mathew, Anuja

2015-01-01

Low frequencies of memory B cells in the peripheral blood make it challenging to measure the functional and phenotypic characteristics of this antigen experienced subset of B cells without in vitro culture. To date, reagents are lacking to measure ex vivo frequencies of dengue virus (DENV)-specific memory B cells. We wanted to explore the possibility of using fluorescently labeled DENV as probes to detect antigen-specific memory B cells in the peripheral blood of DENV immune individuals. Alexa Fluor dye-labeled DENV yielded viable virus that could be stored at -80°C for long periods of time. Using a careful gating strategy and methods to decrease non-specific binding, we were able to identify a small frequency of B cells from dengue immune individuals that bound labeled DENV. Sorted DENV(+) B cells from immune, but not naïve donors secreted antibodies that bound DENV after in vitro stimulation. Overall, Alexa Fluor dye-labeled DENVs are useful reagents to enable the detection and characterization of memory B cells in DENV immune individuals. Copyright © 2014 Elsevier B.V. All rights reserved.

Fluorescently labeled dengue viruses as probes to identify antigen-specific memory B cells by multiparametric flow cytometry

PubMed Central

Woda, Marcia; Mathew, Anuja

2015-01-01

Low frequencies of memory B cells in the peripheral blood make it challenging to measure the functional and phenotypic characteristics of this antigen experienced subset of B cells without in vitro culture. To date, reagents are lacking to measure ex vivo frequencies of dengue virus (DENV)-specific memory B cells. We wanted to explore the possibility of using fluorescently labeled DENV as probes to detect antigen-specific memory B cells in the peripheral blood of DENV immune individuals. Alexa Fluor dye-labeled DENV yielded viable virus that could be stored at −80°C for long periods of time. Using a careful gating strategy and methods to decrease non-specific binding, we were able to identify a small frequency of B cells from dengue immune individuals that bound labeled DENV. Sorted DENV+ B cells from immune, but not naïve donors secreted antibodies that bound intact virions after in vitro stimulation. Overall, Alexa Fluor dye labeled -DENV are useful reagents to enable the detection and characterization of memory B cells in DENV immune individuals. PMID:25497702

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

PubMed

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-12-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

Phenotyping and Visualizing Infusion-Related Reactions for Breast Cancer Patients.

PubMed

Sun, Deyu; Sarda, Gopal; Skube, Steven J; Blaes, Anne H; Khairat, Saif; Melton, Genevieve B; Zhang, Rui

2017-01-01

Infusion-related reactions (IRRs) are typical adverse events for breast cancer patients. Detecting IRRs and visualizing their occurance associated with the drug treatment would potentially assist clinicians to improve patient safety and help researchers model IRRs and analyze their risk factors. We developed and evaluated a phenotyping algorithm to detect IRRs for breast cancer patients. We also designed a visualization prototype to render IRR patients' medications, lab tests and vital signs over time. By comparing with the 42 randomly selected doses that are manually labeled by a domain expert, the sensitivity, positive predictive value, specificity, and negative predictive value of the algorithms are 69%, 60%, 79%, and 85%, respectively. Using the algorithm, an incidence of 6.4% of patients and 1.8% of doses for docetaxel, 8.7% and 3.2% for doxorubicin, 10.4% and 1.2% for paclitaxel, 16.1% and 1.1% for trastuzumab were identified retrospectively. The incidences estimated are consistent with related studies.

Phenotyping and Visualizing Infusion-Related Reactions for Breast Cancer Patients

PubMed Central

Sun, Deyu; Sarda, Gopal; Skube, Steven J.; Blaes, Anne H.; Khairat, Saif; Melton, Genevieve B.; Zhang, Rui

2018-01-01

Infusion-related reactions (IRRs) are typical adverse events for breast cancer patients. Detecting IRRs and visualizing their occurance associated with the drug treatment would potentially assist clinicians to improve patient safety and help researchers model IRRs and analyze their risk factors. We developed and evaluated a phenotyping algorithm to detect IRRs for breast cancer patients. We also designed a visualization prototype to render IRR patients’ medications, lab tests and vital signs over time. By comparing with the 42 randomly selected doses that are manually labeled by a domain expert, the sensitivity, positive predictive value, specificity, and negative predictive value of the algorithms are 69%, 60%, 79%, and 85%, respectively. Using the algorithm, an incidence of 6.4% of patients and 1.8% of doses for docetaxel, 8.7% and 3.2% for doxorubicin, 10.4% and 1.2% for paclitaxel, 16.1% and 1.1% for trastuzumab were identified retrospectively. The incidences estimated are consistent with related studies. PMID:29295166

Pyrimethamine as a Potent and Selective Inhibitor of Acute Myeloid Leukemia Identified by High-throughput Drug Screening.

PubMed

Sharma, Amit; Jyotsana, Nidhi; Lai, Courteney K; Chaturvedi, Anuhar; Gabdoulline, Razif; Görlich, Kerstin; Murphy, Cecilia; Blanchard, Jan E; Ganser, Arnold; Brown, Eric; Hassell, John A; Humphries, R Keith; Morgan, Michael; Heuser, Michael

2016-01-01

Hematopoietic stem and progenitor cell differentiation are blocked in acute myeloid leukemia (AML) resulting in cytopenias and a high risk of death. Most patients with AML become resistant to treatment due to lack of effective cytotoxic and differentiation promoting compounds. High MN1 expression confers poor prognosis to AML patients and induces resistance to cytarabine and alltrans-retinoic acid (ATRA) induced differentiation. Using a high-throughput drug screening, we identified the dihydrofolate reductase (DHFR) antagonist pyrimethamine to be a potent inducer of apoptosis and differentiation in several murine and human leukemia cell lines. Oral pyrimethamine treatment was effective in two xenograft mouse models and specifically targeted leukemic cells in human AML cell lines and primary patient cells, while CD34+ cells from healthy donors were unaffected. The antileukemic effects of PMT could be partially rescued by excess folic acid, suggesting an oncogenic function of folate metabolism in AML. Thus, our study identifies pyrimethamine as a candidate drug that should be further evaluated in AML treatment.

Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value.

PubMed

Farhat, Maha R; Sultana, Razvan; Iartchouk, Oleg; Bozeman, Sam; Galagan, James; Sisk, Peter; Stolte, Christian; Nebenzahl-Guimaraes, Hanna; Jacobson, Karen; Sloutsky, Alexander; Kaur, Devinder; Posey, James; Kreiswirth, Barry N; Kurepina, Natalia; Rigouts, Leen; Streicher, Elizabeth M; Victor, Tommie C; Warren, Robin M; van Soolingen, Dick; Murray, Megan

2016-09-01

The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance-conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs. To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance. We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci. These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs.

Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value

PubMed Central

Sultana, Razvan; Iartchouk, Oleg; Bozeman, Sam; Galagan, James; Sisk, Peter; Stolte, Christian; Nebenzahl-Guimaraes, Hanna; Jacobson, Karen; Sloutsky, Alexander; Kaur, Devinder; Posey, James; Kreiswirth, Barry N.; Kurepina, Natalia; Rigouts, Leen; Streicher, Elizabeth M.; Victor, Tommie C.; Warren, Robin M.; van Soolingen, Dick; Murray, Megan

2016-01-01

Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance–conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs. Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance. Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. Measurements and Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci. Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs. PMID:26910495

MicroRNA-124 controls human vascular smooth muscle cell phenotypic switch via Sp1.

PubMed

Tang, Yangfeng; Yu, Shangyi; Liu, Yang; Zhang, Jiajun; Han, Lin; Xu, Zhiyun

2017-09-01

Phenotypic switch of vascular smooth muscle cells (VSMCs) plays an important role in the pathogenesis of atherosclerosis and aortic dissection. However, the mechanisms of phenotypic modulation are still unclear. MicroRNAs have emerged as important regulators of VSMC function. We recently found that microRNA-124 (miR-124) was downregulated in proliferative vascular diseases that were characterized by a VSMC phenotypic switch. Therefore, we speculated that the aberrant expression of miR-124 might play a critical role in human aortic VSMC phenotypic switch. Using quantitative RT-PCR, we found that miR-124 was dramatically downregulated in the aortic media of clinical specimens of the dissected aorta and correlated with molecular markers of the contractile VSMC phenotype. Overexpression of miR-124 by mimicking transfection significantly attenuated platelet-derived growth factor-BB-induced human aortic VSMC proliferation and phenotypic switch. Furthermore, we identified specificity protein 1 (Sp1) as the downstream target of miR-124. A luciferase reporter assay was used to confirm direct miR-124 targeting of the 3'-untranslated region of the Sp1 gene and repression of Sp1 expression in human aortic VSMCs. Furthermore, constitutively active Sp1 in miR-124-overexpressing VSMCs reversed the antiproliferative effects of miR-124. These results demonstrated a novel mechanism of miR-124 modulation of VSMC phenotypic switch by targeting Sp1 expression. NEW & NOTEWORTHY Previous studies have demonstrated that miR-124 is involved in the proliferation of a variety of cell types. However, miRNAs are expressed in a tissue-specific manner. We first identified miR-124 as a critical regulator in human aortic vascular smooth muscle cell differentiation, proliferation, and phenotype switch by targeting the 3'-untranslated region of specificity protein 1. Copyright © 2017 the American Physiological Society.

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp

Two distinct symptom-based phenotypes of depression in epilepsy yield specific clinical and etiological insights.

PubMed

Rayner, Genevieve; Jackson, Graeme D; Wilson, Sarah J

2016-11-01

Depression is common but underdiagnosed in epilepsy. A quarter of patients meet criteria for a depressive disorder, yet few receive active treatment. We hypothesize that the presentation of depression is less recognizable in epilepsy because the symptoms are heterogeneous and often incorrectly attributed to the secondary effects of seizures or medication. Extending the ILAE's new phenomenological approach to classification of the epilepsies to include psychiatric comorbidity, we use data-driven profiling of the symptoms of depression to perform a preliminary investigation of whether there is a distinctive symptom-based phenotype of depression in epilepsy that could facilitate its recognition in the neurology clinic. The psychiatric and neuropsychological functioning of 91 patients with focal epilepsy was compared with that of 77 healthy controls (N=168). Cluster analysis of current depressive symptoms identified three clusters: one comprising nondepressed patients and two symptom-based phenotypes of depression. The 'Cognitive' phenotype (base rate=17%) was characterized by symptoms taking the form of self-critical cognitions and dysphoria and was accompanied by pervasive memory deficits. The 'Somatic' phenotype (7%) was characterized by vegetative depressive symptoms and anhedonia and was accompanied by greater anxiety. It is hoped that identification of the features of these two phenotypes will ultimately facilitate improved detection and diagnosis of depression in patients with epilepsy and thereby lead to appropriate and timely treatment, to the benefit of patient wellbeing and the potential efficacy of treatment of the seizure disorder. This article is part of a Special Issue entitled "The new approach to classification: Rethinking cognition and behavior in epilepsy". Copyright © 2016 Elsevier Inc. All rights reserved.

CD4 T-helper cell cytokine phenotypes and antibody response following tetanus toxoid booster immunization

USDA-ARS?s Scientific Manuscript database

Routine methods for enumerating antigen-specific T-helper cells may not identify low-frequency phenotypes such as Th2 cells. We compared methods of evaluating such responses to identify tetanus toxoid- (TT) specific Th1, Th2, Th17 and IL10+ cells. Eight healthy subjects were given a TT booster vacci...

Polymeric drug delivery systems for intraoral site-specific chemoprevention of oral cancer.

PubMed

Desai, Kashappa Goud H

2018-04-01

Oral cancer is among the most prevalent cancers in the world. Moreover, it is one of the major health problems and causes of death in many regions of the world. The traditional treatment modalities include surgical removal, radiation therapy, systemic chemotherapy, or a combination of these methods. In recent decades, there has been significant interest in intraoral site-specific chemoprevention via local drug delivery using polymeric systems. Because of its easy accessibility and clear visibility, the oral mucosa is amenable for local drug delivery. A variety of polymeric systems-such as gels, tablets, films, patches, injectable systems (e.g., millicylindrical implants, microparticles, and in situ-forming depots), and nanosized carriers (e.g., polymeric nanoparticles, nanofibers, polymer-drug conjugates, polymeric micelles, nanoliposomes, nanoemulsions, and polymersomes)-have been developed and evaluated for the local delivery of natural and synthetic chemopreventive agents. The findings of in vitro, ex vivo, and in vivo studies and the positive outcome of clinical trials demonstrate that intraoral site-specific drug delivery is an attractive, highly effective and patient-friendly strategy for the management of oral cancer. Intraoral site-specific drug delivery provides unique therapeutic advantages when compared to systemic chemotherapy. Moreover, intraoral drug delivery systems are self-administrable and can be removed when needed, increasing patient compliance. This article covers important aspects and advances related to the design, development, and efficacy of polymeric systems for intraoral site-specific drug delivery. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1383-1413, 2018. © 2017 Wiley Periodicals, Inc.

Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity

PubMed Central

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous

Physicochemical characteristics of structurally determined metabolite-protein and drug-protein binding events with respect to binding specificity.

PubMed

Korkuć, Paula; Walther, Dirk

2015-01-01

To better understand and ultimately predict both the metabolic activities as well as the signaling functions of metabolites, a detailed understanding of the physical interactions of metabolites with proteins is highly desirable. Focusing in particular on protein binding specificity vs. promiscuity, we performed a comprehensive analysis of the physicochemical properties of compound-protein binding events as reported in the Protein Data Bank (PDB). We compared the molecular and structural characteristics obtained for metabolites to those of the well-studied interactions of drug compounds with proteins. Promiscuously binding metabolites and drugs are characterized by low molecular weight and high structural flexibility. Unlike reported for drug compounds, low rather than high hydrophobicity appears associated, albeit weakly, with promiscuous binding for the metabolite set investigated in this study. Across several physicochemical properties, drug compounds exhibit characteristic binding propensities that are distinguishable from those associated with metabolites. Prediction of target diversity and compound promiscuity using physicochemical properties was possible at modest accuracy levels only, but was consistently better for drugs than for metabolites. Compound properties capturing structural flexibility and hydrogen-bond formation descriptors proved most informative in PLS-based prediction models. With regard to diversity of enzymatic activities of the respective metabolite target enzymes, the metabolites benzylsuccinate, hypoxanthine, trimethylamine N-oxide, oleoylglycerol, and resorcinol showed very narrow process involvement, while glycine, imidazole, tryptophan, succinate, and glutathione were identified to possess broad enzymatic reaction scopes. Promiscuous metabolites were found to mainly serve as general energy currency compounds, but were identified to also be involved in signaling processes and to appear in diverse organismal systems (digestive and nervous

LIS1-associated classic lissencephaly: A retrospective, multicenter survey of the epileptogenic phenotype and response to antiepileptic drugs.

PubMed

Herbst, Saskia M; Proepper, Christiane R; Geis, Tobias; Borggraefe, Ingo; Hahn, Andreas; Debus, Otfried; Haeussler, Martin; von Gersdorff, Gero; Kurlemann, Gerhard; Ensslen, Matthias; Beaud, Nathalie; Budde, Joerg; Gilbert, Michael; Heiming, Ralf; Morgner, Rita; Philippi, Heike; Ross, Sophia; Strobl-Wildemann, Gertrud; Muelleder, Kerstin; Vosschulte, Paul; Morris-Rosendahl, Deborah J; Schuierer, Gerhard; Hehr, Ute

2016-04-01

Patients with LIS1-associated classic lissencephaly typically present with severe psychomotor retardation and drug-resistant epilepsy within the first year. To analyze the epileptogenic phenotype and response to antiepileptic therapy in LIS1-associated classic lissencephaly. Retrospective evaluation of 22 patients (8 months-24 years) with genetically and radiologically confirmed LIS1-associated classic lissencephaly in 16 study centers. All patients in our cohort developed drug-resistant epilepsy. In 82% onset of seizures was noted within the first six months of life, most frequently with infantile spasms. Later in infancy the epileptogentic phenotype became more variable and included different forms of focal seizures as well generalized as tonic-clonic seizures, with generalized tonic-clonic seizures being the predominant type. Lamotrigine and valproate were rated most successful with good or partial response rates in 88-100% of the patients. Both were evaluated significantly better than levetiracetam (p<0.05) and sulthiame (p<0.01) in the neuropediatric assessment and better than levetiracetam, sulthiame (p<0.05) and topiramate (p<0.01) in the family survey. Phenobarbital and vigabatrin achieved good or partial response in 62-83% of the patients. Our findings suggest that patients with LIS1-associated lissencephaly might benefit most from lamotrigine, valproate, vigabatrin or phenobarbital. Copyright © 2015 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Gait disorders in the elderly and dual task gait analysis: a new approach for identifying motor phenotypes.

PubMed

Auvinet, Bernard; Touzard, Claude; Montestruc, François; Delafond, Arnaud; Goeb, Vincent

2017-01-31

allowed the identification of 3 motor phenotypes (p < 0.01), without any difference for white matter hyperintensities, but with an increased Scheltens score from the first to the third motor phenotype (p = 0.05). Gait analysis under dual-task conditions in elderly people suffering from gait disorders or memory impairment is of great value in assessing the severity of gait disorders, differentiating between peripheral pathologies and central nervous system pathologies, and identifying motor phenotypes. Correlations between motor phenotypes and brain imaging require further studies.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Application of Combination High-Throughput Phenotypic Screening and Target Identification Methods for the Discovery of Natural Product-Based Combination Drugs.

PubMed

Isgut, Monica; Rao, Mukkavilli; Yang, Chunhua; Subrahmanyam, Vangala; Rida, Padmashree C G; Aneja, Ritu

2018-03-01

Modern drug discovery efforts have had mediocre success rates with increasing developmental costs, and this has encouraged pharmaceutical scientists to seek innovative approaches. Recently with the rise of the fields of systems biology and metabolomics, network pharmacology (NP) has begun to emerge as a new paradigm in drug discovery, with a focus on multiple targets and drug combinations for treating disease. Studies on the benefits of drug combinations lay the groundwork for a renewed focus on natural products in drug discovery. Natural products consist of a multitude of constituents that can act on a variety of targets in the body to induce pharmacodynamic responses that may together culminate in an additive or synergistic therapeutic effect. Although natural products cannot be patented, they can be used as starting points in the discovery of potent combination therapeutics. The optimal mix of bioactive ingredients in natural products can be determined via phenotypic screening. The targets and molecular mechanisms of action of these active ingredients can then be determined using chemical proteomics, and by implementing a reverse pharmacokinetics approach. This review article provides evidence supporting the potential benefits of natural product-based combination drugs, and summarizes drug discovery methods that can be applied to this class of drugs. © 2017 Wiley Periodicals, Inc.

Altered phenotype and functionality of varicella zoster virus-specific cellular immunity in individuals with active infection.

PubMed

Schub, David; Janssen, Eva; Leyking, Sarah; Sester, Urban; Assmann, Gunter; Hennes, Pia; Smola, Sigrun; Vogt, Thomas; Rohrer, Tilman; Sester, Martina; Schmidt, Tina

2015-02-15

Varicella zoster virus (VZV) establishes lifelong persistence and may reactivate in individuals with impaired immune function. To investigate immunologic correlates of protection and VZV reactivation, we characterized specific immunity in 207 nonsymptomatic immunocompetent and 132 immunocompromised individuals in comparison with patients with acute herpes zoster. VZV-specific CD4 T cells were quantified flow cytometrically after stimulation and characterized for expression of interferon-γ, interleukin 2, and tumor necrosis factor α and surface markers for differentiation (CD127) and anergy (cytotoxic T lymphocyte antigen 4 [CTLA-4] and programmed death [PD]-1). Immunoglobulin G and A levels were quantified using an enzyme-linked immunosorbent assay. In healthy individuals, VZV-specific antibody and T-cell levels were age dependent, with the highest median VZV-specific CD4 T-cell frequencies of 0.108% (interquartile range, 0.121%) during adolescence. VZV-specific T-cell profiles were multifunctional with predominant expression of all 3 cytokines, CD127 positivity, and low expression of CTLA-4 and PD-1. Nonsymptomatic immunocompromised patients had similar VZV-specific immunologic properties except for lower T-cell frequencies (P<.001) and restricted cytokine expression. In contrast, significantly elevated antibody- and VZV-specific CD4 T-cell levels were found in patients with zoster. Their specific T cells showed a shift in cytokine expression toward interferon γ single positivity, an increase in CTLA-4 and PD-1, and a decrease in CD127 expression (all P<.001). This phenotype normalized after resolution of symptoms. VZV-specific CD4-T cells in patients with zoster bear typical features of anergy. This phenotype is reversible and may serve as adjunct tool for monitoring VZV reactivations in high-risk patients. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions

Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell- and patient-derived tumor organoids.

PubMed

Huang, Ling; Holtzinger, Audrey; Jagan, Ishaan; BeGora, Michael; Lohse, Ines; Ngai, Nicholas; Nostro, Cristina; Wang, Rennian; Muthuswamy, Lakshmi B; Crawford, Howard C; Arrowsmith, Cheryl; Kalloger, Steve E; Renouf, Daniel J; Connor, Ashton A; Cleary, Sean; Schaeffer, David F; Roehrl, Michael; Tsao, Ming-Sound; Gallinger, Steven; Keller, Gordon; Muthuswamy, Senthil K

2015-11-01

There are few in vitro models of exocrine pancreas development and primary human pancreatic adenocarcinoma (PDAC). We establish three-dimensional culture conditions to induce the differentiation of human pluripotent stem cells into exocrine progenitor organoids that form ductal and acinar structures in culture and in vivo. Expression of mutant KRAS or TP53 in progenitor organoids induces mutation-specific phenotypes in culture and in vivo. Expression of TP53(R175H) induces cytosolic SOX9 localization. In patient tumors bearing TP53 mutations, SOX9 was cytoplasmic and associated with mortality. We also define culture conditions for clonal generation of tumor organoids from freshly resected PDAC. Tumor organoids maintain the differentiation status, histoarchitecture and phenotypic heterogeneity of the primary tumor and retain patient-specific physiological changes, including hypoxia, oxygen consumption, epigenetic marks and differences in sensitivity to inhibition of the histone methyltransferase EZH2. Thus, pancreatic progenitor organoids and tumor organoids can be used to model PDAC and for drug screening to identify precision therapy strategies.

Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell and patient-derived tumor organoids

PubMed Central

Huang, Ling; Holtzinger, Audrey; Jagan, Ishaan; BeGora, Michael; Lohse, Ines; Ngai, Nicholas; Nostro, Cristina; Wang, Rennian; Muthuswamy, Lakshmi B.; Crawford, Howard C.; Arrowsmith, Cheryl; Kalloger, Steve E.; Renouf, Daniel J.; Connor, Ashton A; Cleary, Sean; Schaeffer, David F.; Roehrl, Michael; Tsao, Ming-Sound; Gallinger, Steven; Keller, Gordon; Muthuswamy, Senthil K.

2016-01-01

There are few in vitro models of exocrine pancreas development and primary human pancreatic adenocarcinoma (PDAC). We establish three-dimensional culture conditions to induce the differentiation of human pluripotent stem cells (PSCs) into exocrine progenitor organoids that form ductal and acinar structures in culture and in vivo. Expression of mutant KRAS or TP53 in progenitor organoids induces mutation-specific phenotypes in culture and in vivo. Expression of TP53R175H induced cytosolic SOX9 localization. In patient tumors bearing TP53 mutations, SOX9 was cytoplasmic and associated with mortality. Culture conditions are also defined for clonal generation of tumor organoids from freshly resected PDAC. Tumor organoids maintain the differentiation status, histoarchitecture, phenotypic heterogeneity of the primary tumor, and retain patient-specific physiologic changes including hypoxia, oxygen consumption, epigenetic marks, and differential sensitivity to EZH2 inhibition. Thus, pancreatic progenitor organoids and tumor organoids can be used to model PDAC and for drug screening to identify precision therapy strategies. PMID:26501191

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

PubMed Central

Thompson, Alison L.; Thorp, Kelly R.; Conley, Matthew; Andrade-Sanchez, Pedro; Heun, John T.; Dyer, John M.; White, Jeffery W.

2018-01-01

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions. PMID:29868041

High-throughput discovery of novel developmental phenotypes.

PubMed

Dickinson, Mary E; Flenniken, Ann M; Ji, Xiao; Teboul, Lydia; Wong, Michael D; White, Jacqueline K; Meehan, Terrence F; Weninger, Wolfgang J; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N; Bower, Lynette; Brown, James M; Caddle, L Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J; Denegre, James M; Doe, Brendan; Dolan, Mary E; Edie, Sarah M; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R; Hsu, Chih-Wei; Johnson, Sara J; Kalaga, Sowmya; Keith, Lance C; Lanoue, Louise; Lawson, Thomas N; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L; Newbigging, Susan; Nutter, Lauryl M J; Peterson, Kevin A; Ramirez-Solis, Ramiro; Rowland, Douglas J; Ryder, Edward; Samocha, Kaitlin E; Seavitt, John R; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G; Tocchini-Valentini, Glauco P; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C; Justice, Monica J; Parkinson, Helen E; Moore, Mark; Wells, Sara; Braun, Robert E; Svenson, Karen L; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R Mark; Brown, Steve D M; Adams, David J; Lloyd, K C Kent; McKerlie, Colin; Beaudet, Arthur L; Bućan, Maja; Murray, Stephen A

2016-09-22

Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

Automated drug identification system

NASA Technical Reports Server (NTRS)

Campen, C. F., Jr.

1974-01-01

System speeds up analysis of blood and urine and is capable of identifying 100 commonly abused drugs. System includes computer that controls entire analytical process by ordering various steps in specific sequences. Computer processes data output and has readout of identified drugs.

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post- chemotherapy tissues

PubMed Central

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-01-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens. PMID:26515599

Neurocognitive Allied Phenotypes for Schizophrenia and Bipolar Disorder

PubMed Central

Hill, S. Kristian; Harris, Margret S. H.; Herbener, Ellen S.; Pavuluri, Mani; Sweeney, John A.

2008-01-01

Psychiatric disorders are genetically complex and represent the end product of multiple biological and social factors. Links between genes and disorder-related abnormalities can be effectively captured via assessment of phenotypes that are both associated with genetic effects and potentially contributory to behavioral abnormalities. Identifying intermediate or allied phenotypes as a strategy for clarifying genetic contributions to disorders has been successful in other areas of medicine and is a promising strategy for identifying susceptibility genes in complex psychiatric disorders. There is growing evidence that schizophrenia and bipolar disorder, rather than being wholly distinct disorders, share genetic risk at several loci. Further, there is growing evidence of similarity in the pattern of cognitive and neurobiological deficits in these groups, which may be the result of the effects of these common genetic factors. This review was undertaken to identify patterns of performance on neurocognitive and affective tasks across probands with schizophrenia and bipolar disorder as well as unaffected family members, which warrant further investigation as potential intermediate trait markers. Available evidence indicates that measures of attention regulation, working memory, episodic memory, and emotion processing offer potential for identifying shared and illness-specific allied neurocognitive phenotypes for schizophrenia and bipolar disorder. However, very few studies have evaluated neurocognitive dimensions in bipolar probands or their unaffected relatives, and much work in this area is needed. PMID:18448479

Normalization of urinary drug concentrations with specific gravity and creatinine.

PubMed

Cone, Edward J; Caplan, Yale H; Moser, Frank; Robert, Tim; Shelby, Melinda K; Black, David L

2009-01-01

Excessive fluid intake can substantially dilute urinary drug concentrations and result in false-negative reports for drug users. Methods for correction ("normalization") of drug/metabolite concentrations in urine have been utilized by anti-doping laboratories, pain monitoring programs, and in environmental monitoring programs to compensate for excessive hydration, but such procedures have not been used routinely in workplace, legal, and treatment settings. We evaluated two drug normalization procedures based on specific gravity and creatinine. These corrections were applied to urine specimens collected from three distinct groups (pain patients, heroin users, and marijuana/ cocaine users). Each group was unique in characteristics, study design, and dosing conditions. The results of the two normalization procedures were highly correlated (r=0.94; range, 0.78-0.99). Increases in percent positives by specific gravity and creatinine normalization were small (0.3% and -1.0%, respectively) for heroin users (normally hydrated subjects), modest (4.2-9.8%) for pain patients (unknown hydration state), and substantial (2- to 38-fold increases) for marijuana/cocaine users (excessively hydrated subjects). Despite some limitations, these normalization procedures provide alternative means of dealing with highly dilute, dilute, and concentrated urine specimens. Drug/metabolite concentration normalization by these procedures is recommended for urine testing programs, especially as a means of coping with dilute specimens.

Environmental and genetic modulation of the phenotypic expression of antibiotic resistance

PubMed Central

Andersson, Dan I

2017-01-01

Abstract Antibiotic resistance can be acquired by mutation or horizontal transfer of a resistance gene, and generally an acquired mechanism results in a predictable increase in phenotypic resistance. However, recent findings suggest that the environment and/or the genetic context can modify the phenotypic expression of specific resistance genes/mutations. An important implication from these findings is that a given genotype does not always result in the expected phenotype. This dissociation of genotype and phenotype has important consequences for clinical bacteriology and for our ability to predict resistance phenotypes from genetics and DNA sequences. A related problem concerns the degree to which the genes/mutations currently identified in vitro can fully explain the in vivo resistance phenotype, or whether there is a significant additional amount of presently unknown mutations/genes (genetic ‘dark matter’) that could contribute to resistance in clinical isolates. Finally, a very important question is whether/how we can identify the genetic features that contribute to making a successful pathogen, and predict why some resistant clones are very successful and spread globally? In this review, we describe different environmental and genetic factors that influence phenotypic expression of antibiotic resistance genes/mutations and how this information is needed to understand why particular resistant clones spread worldwide and to what extent we can use DNA sequences to predict evolutionary success. PMID:28333270

Discovery of specific ligands for oral squamous carcinoma to develop anti-cancer drug loaded precise targeting nanotherapeutics.