scholarly journals Integrative genetic and epigenetic analysis uncovers regulatory mechanisms of autoimmune disease

2016 ◽  
Author(s):  
Parisa Shooshtari ◽  
Hailieng Huang ◽  
Chris Cotsapas
Keyword(s):  
Disease Risk ◽  
Inflammatory Diseases ◽  
Association Studies ◽  
Single Gene ◽  
Genome Wide Association Studies ◽  
Regulatory Regions ◽  
Risk Alleles ◽  
Molecular Events ◽  
Public Data ◽  
Autoimmune And Inflammatory Diseases

Genome-wide association studies in autoimmune and inflammatory diseases (AID) have uncovered hundreds of loci mediating risk1,2. These associations are preferentially located in non-coding DNA regions3,4 and in particular to tissue-specific Dnase I hypersensitivity sites (DHS)5,6. Whilst these analyses clearly demonstrate the overall enrichment of disease risk alleles on gene regulatory regions, they are not designed to identify individual regulatory regions mediating risk or the genes under their control, and thus uncover the specific molecular events driving disease risk. To do so we have departed from standard practice by identifying regulatory regions which replicate across samples, and connect them to the genes they control through robust re-analysis of public data. We find substantial evidence of regulatory potential in 132/301 (44%) risk loci across nine autoimmune and inflammatory diseases, and are able to prioritize a single gene in 104/132 (79%) of these. Thus, we are able to generate testable mechanistic hypotheses of the molecular changes that drive disease risk.

ECP06-01 - Genomewide - asscociation studies of psychiatric phenotypes: What they have told us and what to do next

2011 ◽  
Vol 26 (S2) ◽  
pp. 1803-1803
Author(s):  
T.G. Schulze
Keyword(s):  
Psychiatric Disorders ◽  
Disease Risk ◽  
Association Studies ◽  
Future Research ◽  
Allelic Heterogeneity ◽  
List Type ◽  
Genome Wide Association Studies ◽  
Monogenic Disorders ◽  
Complex Genetics ◽  
Risk Alleles

Genome-wide association studies of psychiatric disorders have highlighted several novel susceptibility genes and taught us several importnat lessons.1)Psychiatric disorders are polygenic disorders. The contribution of each locus to risk of disease is modest and disease risk increases substantially with the total burden of risk alleles carried.2)The best findings from GWAS do not necessarily fall within those genes that have previously been widely studied.3)Pursuing a “top-hits-only” strategy may prevent us from understanding the genetic complexity of psychiatric disorders and polygenic disorders in general. A detailed consideration of the wider distribution of association signals across studies may prove to be a valuable strategy in complex genetics.4)Allelic heterogeneity may be an important factor in psychiatric disorders. Allelic heterogeneity means that a phenotype can be caused by different alleles within a gene; this phenomenon has been extensively observed in monogenic disorders such as cystic fibrosis as well as in BRCA1/2-associated breast cancer.5)Finally, as with other complex phenotypes, GWAS in psychiatric disorders demonstrate that the variants identified so far only account for a small fraction of genetic variability.Future research will need to embark on several complementary approaches in order to fill the yet “unexplained” part of the variance. These will among others include sequencing projects, pharmacogenetic studies, detailed genotype-phenotype dissection approaches, and the study of prospectively assessed phenotypes.

scholarly journals Population history of the Sardinian people inferred from whole-genome sequencing

2016 ◽  
Author(s):  
Charleston W K Chiang ◽  
Joseph H Marcus ◽  
Carlo Sidore ◽  
Hussein Al-Asadi ◽  
Magdalena Zoledziewska ◽  
...  
Keyword(s):  
Bronze Age ◽  
Disease Risk ◽  
Association Studies ◽  
Demographic History ◽  
Population History ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Risk Alleles ◽  
Mediterranean Island ◽  
History Of

AbstractThe population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of traits and diseases. The history of the Sardinian population has also been the focus of much research, and in recent ancient DNA (aDNA) studies, Sardinia has provided unique insight into the peopling of Europe and the spread of agriculture. In this study, we analyze whole-genome sequences of 3,514 Sardinians to address hypotheses regarding the founding of Sardinia and its relation to the peopling of Europe, including examining fine-scale substructure, population size history, and signals of admixture. We find the population of the mountainous Gennargentu region shows elevated genetic isolation with higher levels of ancestry associated with mainland Neolithic farmers and depleted ancestry associated with more recent Bronze Age Steppe migrations on the mainland. Notably, the Gennargentu region also has elevated levels of pre-Neolithic hunter-gatherer ancestry and increased affinity to Basque populations. Further, allele sharing with pre-Neolithic and Neolithic mainland populations is larger on the X chromosome compared to the autosome, providing evidence for a sex-biased demographic history in Sardinia. These results give new insight to the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.

scholarly journals Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gloriia Novikova ◽  
Manav Kapoor ◽  
Julia TCW ◽  
Edsel M. Abud ◽  
Anastasia G. Efthymiou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Risk ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Risk Alleles ◽  
Functional Variants ◽  
Analytical Approaches

AbstractGenome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility.

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 A gene co-association network regulating gut microbial communities in a Duroc pig population

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Antonio Reverter ◽  
Maria Ballester ◽  
Pamela A. Alexandre ◽  
Emilio Mármol-Sánchez ◽  
Antoni Dalmau ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Candidate Genes ◽  
Relative Abundance ◽  
Association Studies ◽  
Single Gene ◽  
Host Genome ◽  
Genome Wide Association Studies ◽  
Vaccine Response ◽  
Microbiome Composition ◽  
Host Genetic

Abstract Background Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical “single-gene-single-trait” approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately. Results In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP–P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance. Conclusions Taken together, our results identified regulators, candidate genes, and mechanisms linked with microbiome modulation by the host. They further highlight the value of the proposed analytical pipeline to exploit pleiotropy and the crosstalk between bacteria and protists as significant contributors to host-microbiome interactions and identify genetic markers and candidate genes that can be incorporated in breeding program to improve host-performance and microbial traits.

Abstract 288: Novel Mechanisms of Non-coding Genomic Regulation Identified in Cardiac Disease-in-a-dish Models

2016 ◽  
Vol 119 (suppl_1) ◽  
Author(s):  
Aditya Kumar ◽  
Stephanie Thomas ◽  
Kirsten Wong ◽  
Kevin Tenerelli ◽  
Valentina Lo Sardo ◽  
...  
Keyword(s):  
Heart Attack ◽  
Connexin 43 ◽  
Disease Risk ◽  
Association Studies ◽  
Correlation Coefficients ◽  
Induced Pluripotent Stem Cell ◽  
Genome Wide Association Studies ◽  
Isogenic Line ◽  
Nucleotide Polymorphisms ◽  
Increased Risk

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) at gene loci that affect cardiovascular function, and while mechanisms in protein-coding loci are obvious, those in non-coding loci are difficult to determine. 9p21 is a recently identified locus associated with increased risk of coronary artery disease (CAD) and myocardial infarction. Associations have implicated SNPs in altering smooth muscle and endothelial cell properties but have not identified adverse effects in cardiomyocytes (CMs) despite enhanced disease risk. Using induced pluripotent stem cell-derived CMs from patients that are homozygous risk/risk (R/R) and non-risk/non-risk (N/N) for 9p21 SNPs and either CAD positive or negative, we assessed CM function when cultured on hydrogels capable of mimicking the fibrotic stiffening associated with disease post-heart attack, i.e. “heart attack-in-a-dish” stiffening from 11 kiloPascals (kPa) to 50 kPa. While all CMs independent of genotype and disease beat synchronously on soft matrices, R/R CMs cultured on dynamically stiffened hydrogels exhibited asynchronous contractions and had significantly lower correlation coefficients versus N/N CMs in the same conditions. Dynamic stiffening reduced connexin 43 expression and gap junction assembly in R/R CMs but not N/N CMs. To eliminate patient-to-patient variability, we created an isogenic line by deleting the 9p21 gene locus from a R/R patient using TALEN-mediated gene editing, i.e. R/R KO. Deletion of the 9p21 locus restored synchronous contractility and organized connexin 43 junctions. As a non-coding locus, 9p21 appears to repress connexin transcription, leading to the phenotypes we observe, but only when the niche is stiffened as in disease. These data are the first to demonstrate that disease-specific niche remodeling, e.g. a “heart attack-in-a-dish” model, can differentially affect CM function depending on SNPs within a non-coding locus.

scholarly journals Application of Genetic Studies to Flow Cytometry Data and Its Impact on Therapeutic Intervention for Autoimmune Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Valeria Orrù ◽  
Maristella Steri ◽  
Francesco Cucca ◽  
Edoardo Fiorillo
Keyword(s):  
Flow Cytometry ◽  
Autoimmune Disease ◽  
Autoimmune Diseases ◽  
Immune Cell ◽  
Disease Risk ◽  
Association Studies ◽  
Large Fraction ◽  
Surface Protein ◽  
Genome Wide Association Studies ◽  
Human Immune System

In recent years, systematic genome-wide association studies of quantitative immune cell traits, represented by circulating levels of cell subtypes established by flow cytometry, have revealed numerous association signals, a large fraction of which overlap perfectly with genetic signals associated with autoimmune diseases. By identifying further overlaps with association signals influencing gene expression and cell surface protein levels, it has also been possible, in several cases, to identify causal genes and infer candidate proteins affecting immune cell traits linked to autoimmune disease risk. Overall, these results provide a more detailed picture of how genetic variation affects the human immune system and autoimmune disease risk. They also highlight druggable proteins in the pathogenesis of autoimmune diseases; predict the efficacy and side effects of existing therapies; provide new indications for use for some of them; and optimize the research and development of new, more effective and safer treatments for autoimmune diseases. Here we review the genetic-driven approach that couples systematic multi-parametric flow cytometry with high-resolution genetics and transcriptomics to identify endophenotypes of autoimmune diseases for the development of new therapies.

scholarly journals Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

2019 ◽  
Author(s):  
Jing Yang ◽  
Amanda McGovern ◽  
Paul Martin ◽  
Kate Duffus ◽  
Xiangyu Ge ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Complex Disease ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Dna Interaction ◽  
Genome Wide Association Studies ◽  
Causal Genes

AbstractGenome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T-cells over 24 hours, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T-cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.

scholarly journals A Network-based Deep Learning Framework Catalyzes GWAS and Multi-Omics Findings to Biology and Drug Repurposing for Alzheimer's Disease

2021 ◽  
Author(s):  
Jielin Xu ◽  
Yuan Hou ◽  
Yadi Zhou ◽  
Ming Hu ◽  
Feixiong Cheng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Disease Risk ◽  
Association Studies ◽  
Open Chromatin ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Learning Framework ◽  
Protein Interactome

Human genome sequencing studies have identified numerous loci associated with complex diseases, including Alzheimer's disease (AD). Translating human genetic findings (i.e., genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery, however, remains a major challenge. To address this critical problem, we present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). NETTAG is capable of integrating multi-genomics data along with the protein-protein interactome to infer putative risk genes and drug targets impacted by GWAS loci. Specifically, we leverage non-coding GWAS loci effects on expression quantitative trait loci (eQTLs), histone-QTLs, and transcription factor binding-QTLs, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions. The key premises of NETTAG are that the disease risk genes exhibit distinct functional characteristics compared to non-risk genes and therefore can be distinguished by their aggregated genomic features under the human protein interactome. Applying NETTAG to the latest AD GWAS data, we identified 156 putative AD-risk genes (i.e., APOE, BIN1, GSK3B, MARK4, and PICALM). We showed that predicted risk genes are: 1) significantly enriched in AD-related pathobiological pathways, 2) more likely to be differentially expressed regarding transcriptome and proteome of AD brains, and 3) enriched in druggable targets with approved medicines (i.e., choline and ibudilast). In summary, our findings suggest that understanding of human pathobiology and therapeutic development could benefit from a network-based deep learning methodology that utilizes GWAS findings under the multimodal genomic analyses.

Sign in / Sign up

Export Citation Format

Share Document