scholarly journals Expanding the drug discovery space with predicted metabolite–target interactions

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andrea Nuzzo ◽  
Somdutta Saha ◽  
Ellen Berg ◽  
Channa Jayawickreme ◽  
Joel Tocker ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Drug Targets ◽  
Large Scale ◽  
Association Studies ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Host Protein ◽  
Multiple Drug ◽  
Genome Wide Association Studies

AbstractMetabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite–host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potential metabolite–target interactions using the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2). Using a consensus of multiple machine learning methods, we ranked metabolites based on importance to IBD, followed by virtual ligand-based screening to identify possible human targets and adding evidence from compound assay, differential gene expression, pathway enrichment, and genome-wide association studies. We confirmed known metabolite–target pairs such as nicotinic acid–GPR109a or linoleoyl ethanolamide–GPR119 and inferred interactions of interest including oleanolic acid–GABRG2 and alpha-CEHC–THRB. Eleven metabolites were tested for bioactivity in vitro using human primary cell-types. By expanding the universe of possible microbial metabolite–host protein interactions, we provide multiple drug targets for potential immune-therapies.

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

2018 ◽  
Vol 21 (2) ◽  
pp. 84-88 ◽  
Author(s):  
W. David Hill
Keyword(s):  
Genetic Information ◽  
Drug Targets ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Nootropic Drug ◽  
Genome Wide

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.

scholarly journals Genetic architecture of host proteins interacting with SARS-CoV-2

2020 ◽  
Author(s):  
Maik Pietzner ◽  
Eleanor Wheeler ◽  
Julia Carrasco-Zanini ◽  
Johannes Raffler ◽  
Nicola D. Kerrison ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Host Response ◽  
Drug Targets ◽  
Genetic Architecture ◽  
Large Scale ◽  
Adverse Outcomes ◽  
Host Protein ◽  
Host Proteins ◽  
Proteomic Data ◽  
Cellular Assays

ABSTRACTStrategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid ‘in silico’ assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).

Drug response in association with pharmacogenomics and pharmacomicrobiomics: towards a better personalized medicine

2020 ◽  
Author(s):  
Radia Hassan ◽  
Imane Allali ◽  
Francis E Agamah ◽  
Samar S M Elsheikh ◽  
Nicholas E Thomford ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Drug Targets ◽  
Drug Response ◽  
Association Studies ◽  
Human Microbiome ◽  
Drug Efficacy ◽  
Genome Wide Association Studies ◽  
Therapeutic Drugs ◽  
Complex Interactions ◽  
Challenges And Opportunities

Abstract Researchers have long been presented with the challenge imposed by the role of genetic heterogeneity in drug response. For many years, Pharmacogenomics and pharmacomicrobiomics has been investigating the influence of an individual’s genetic background to drug response and disposition. More recently, the human gut microbiome has proven to play a crucial role in the way patients respond to different therapeutic drugs and it has been shown that by understanding the composition of the human microbiome, we can improve the drug efficacy and effectively identify drug targets. However, our knowledge on the effect of host genetics on specific gut microbes related to variation in drug metabolizing enzymes, the drug remains limited and therefore limits the application of joint host–microbiome genome-wide association studies. In this paper, we provide a historical overview of the complex interactions between the host, human microbiome and drugs. While discussing applications, challenges and opportunities of these studies, we draw attention to the critical need for inclusion of diverse populations and the development of an innovative and combined pharmacogenomics and pharmacomicrobiomics approach, that may provide an important basis in personalized medicine.

scholarly journals Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

2021 ◽  
Author(s):  
Max Lam ◽  
Chia-Yen Chen ◽  
Tian Ge ◽  
Yan Xia ◽  
David W. Hill ◽  
...  
Keyword(s):  
Drug Targets ◽  
Large Scale ◽  
Association Studies ◽  
Drug Repurposing ◽  
Genome Wide Association Studies ◽  
Data Set ◽  
Nootropic Drug ◽  
Gene Sets ◽  
Genome Wide ◽  
Novel Drug

AbstractBroad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify “druggable” targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

scholarly journals Genetics of Atopic Dermatitis: From DNA Sequence to Clinical Relevance

Dermatology ◽  
2019 ◽  
Vol 235 (5) ◽  
pp. 355-364 ◽  
Author(s):  
Mari Løset ◽  
Sara J. Brown ◽  
Marit Saunes ◽  
Kristian Hveem
Keyword(s):  
Atopic Dermatitis ◽  
Genetic Risk ◽  
Drug Targets ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Skin Barrier Function ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Genetic Sequencing

Atopic dermatitis (AD) is a complex disease that is thought to be triggered by environmental factors in genetically susceptible individuals. Twin studies have estimated the heritability of AD to be approximately 75%, with the null (loss-of-function) mutations of the gene encoding filaggrin (FLG) (chromosome 1q21.3) as the strongest known genetic risk factor. The discovery of the filaggrin gene was important in the emerging model for AD pathogenesis, combining skin barrier function with adaptive and innate immunity. Assisted by the recent development of large-scale high-throughput genomics, more than 30 genetic loci have been linked to AD across different populations. Identification of these loci, together with functional studies, has already provided new insights into disease biology and identified novel drug targets. Further, these susceptibility loci are laying the groundwork for phenome-wide association studies to test their multiple phenotype relationships and application of Mendelian randomization to investigate causal relationships. Despite many known genes, a majority of the genetic risk for AD is yet unexplored. Therefore, studies investigating refined phenotype groups, low-frequency and rare genetic variation, gene-gene and/or gene-environment interactions, epigenetic mechanisms and data from multi-omics technologies are warranted. In this review, we describe genetic discoveries for AD, including results from candidate gene studies, studies of AD-like genetic diseases, genome-wide association studies and genetic sequencing studies. We explain how some of these genetic discoveries have unraveled new mechanistic insights into the pathogenesis of AD and exemplify how personal genetic data could be used for preventive strategies and a tailored treatment regimen (i.e., precision medicine).

scholarly journals RETRACTION: Illuminating the dark road from schizophrenia genetic associations to disease mechanisms

2016 ◽  
Vol 4 (2) ◽  
pp. 240-251 ◽  
Author(s):  
Ming Li ◽  
Daniel R Weinberger
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Molecular Approaches ◽  
Disease Biology

Abstract Recent large-scale genome-wide association studies (GWAS) have enabled the discovery of common genetic variations contributing to risk architectures of schizophrenia in human populations; however, the majority of GWAS-identified variants are located in large genomic regions spanning multiple genes, and recognizing the precise targets and mechanisms of these clinical associations is now the major challenge. Here, we review recent progress in schizophrenia genetics, functional genomics and related neuroscience research, and propose a functional pipeline to translate schizophrenia GWAS risk loci into disease biology and information for drug discovery. The pipeline includes identification of underlying molecular mechanisms using transcriptomic data in human brain, prioritization of putative functional causative variants by the integration of genetic epidemiological and bioinformatics methods as well as molecular approaches, and in vitro and in vivo experimental characterizations of the identified targeted species and causative variants to dissect the relevant disease biology. These approaches will accelerate progress from schizophrenia genetic studies to biological mechanisms and ultimately guide the development of prognostic, preventive and therapeutic measures.

scholarly journals The open targets post-GWAS analysis pipeline

2020 ◽  
Vol 36 (9) ◽  
pp. 2936-2937 ◽  
Author(s):  
Gareth Peat ◽  
William Jones ◽  
Michael Nuhn ◽  
José Carlos Marugán ◽  
William Newell ◽  
...  
Keyword(s):  
Drug Targets ◽  
Gene Expression Regulation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Data Resource ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Genes ◽  
Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

scholarly journals Molecular Mechanisms of ZC3H12C/Reg-3 Biological Activity and Its Involvement in Psoriasis Pathology

2021 ◽  
Vol 22 (14) ◽  
pp. 7311
Author(s):  
Mateusz Wawro ◽  
Jakub Kochan ◽  
Weronika Sowinska ◽  
Aleksandra Solecka ◽  
Karolina Wawro ◽  
...  
Keyword(s):  
Family Member ◽  
Cellular Localization ◽  
Molecular Mechanisms ◽  
Inflammatory Diseases ◽  
Association Studies ◽  
Psoriasis Patient ◽  
Genome Wide Association Studies ◽  
Mrna Levels ◽  
Transcript Levels

The members of the ZC3H12/MCPIP/Regnase family of RNases have emerged as important regulators of inflammation. In contrast to Regnase-1, -2 and -4, a thorough characterization of Regnase-3 (Reg-3) has not yet been explored. Here we demonstrate that Reg-3 differs from other family members in terms of NYN/PIN domain features, cellular localization pattern and substrate specificity. Together with Reg-1, the most comprehensively characterized family member, Reg-3 shared IL-6, IER-3 and Reg-1 mRNAs, but not IL-1β mRNA, as substrates. In addition, Reg-3 was found to be the only family member which regulates transcript levels of TNF, a cytokine implicated in chronic inflammatory diseases including psoriasis. Previous meta-analysis of genome-wide association studies revealed Reg-3 to be among new psoriasis susceptibility loci. Here we demonstrate that Reg-3 transcript levels are increased in psoriasis patient skin tissue and in an experimental model of psoriasis, supporting the immunomodulatory role of Reg-3 in psoriasis, possibly through degradation of mRNA for TNF and other factors such as Reg-1. On the other hand, Reg-1 was found to destabilize Reg-3 transcripts, suggesting reciprocal regulation between Reg-3 and Reg-1 in the skin. We found that either Reg-1 or Reg-3 were expressed in human keratinocytes in vitro. However, in contrast to robustly upregulated Reg-1 mRNA levels, Reg-3 expression was not affected in the epidermis of psoriasis patients. Taken together, these data suggest that epidermal levels of Reg-3 are negatively regulated by Reg-1 in psoriasis, and that Reg-1 and Reg-3 are both involved in psoriasis pathophysiology through controlling, at least in part different transcripts.

scholarly journals Sept8/SEPTIN8 involvement in cellular structure and kidney damage is identified by genetic mapping and a novel human tubule hypoxic model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory R. Keele ◽  
Jeremy W. Prokop ◽  
Hong He ◽  
Katie Holl ◽  
John Littrell ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Model ◽  
Association Studies ◽  
Model Systems ◽  
Linear Mixed Effect Model ◽  
Genome Wide Association Studies ◽  
Tubulointerstitial Injury ◽  
Heritable Variation ◽  
Mixed Effect

AbstractChronic kidney disease (CKD), which can ultimately progress to kidney failure, is influenced by genetics and the environment. Genes identified in human genome wide association studies (GWAS) explain only a small proportion of the heritable variation and lack functional validation, indicating the need for additional model systems. Outbred heterogeneous stock (HS) rats have been used for genetic fine-mapping of complex traits, but have not previously been used for CKD traits. We performed GWAS for urinary protein excretion (UPE) and CKD related serum biochemistries in 245 male HS rats. Quantitative trait loci (QTL) were identified using a linear mixed effect model that tested for association with imputed genotypes. Candidate genes were identified using bioinformatics tools and targeted RNAseq followed by testing in a novel in vitro model of human tubule, hypoxia-induced damage. We identified two QTL for UPE and five for serum biochemistries. Protein modeling identified a missense variant within Septin 8 (Sept8) as a candidate for UPE. Sept8/SEPTIN8 expression increased in HS rats with elevated UPE and tubulointerstitial injury and in the in vitro hypoxia model. SEPTIN8 is detected within proximal tubule cells in human kidney samples and localizes with acetyl-alpha tubulin in the culture system. After hypoxia, SEPTIN8 staining becomes diffuse and appears to relocalize with actin. These data suggest a role of SEPTIN8 in cellular organization and structure in response to environmental stress. This study demonstrates that integration of a rat genetic model with an environmentally induced tubule damage system identifies Sept8/SEPTIN8 and informs novel aspects of the complex gene by environmental interactions contributing to CKD risk.

scholarly journals Genomics-driven drug discovery based on disease-susceptibility genes

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Drug Repurposing ◽  
Susceptibility Genes ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

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