scholarly journals Rare risk variants associate with epigenetic dysregulation in migraine

2021 ◽  
Author(s):  
Tanya Ramdal Techlo ◽  
Mona Ameri Chalmer ◽  
Peter Loof Møller ◽  
Lisette Johanna Antonia Kogelman ◽  
Isa Amalie Olofsson ◽  
...  
Keyword(s):  
Large Scale ◽  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Risk Variant ◽  
Polycomb Response Element ◽  
Risk Variants ◽  
Genome Wide ◽  
Independent Case

Migraine has a heritability of up to 65%. Genome-wide association studies (GWAS) on migraine have identified 123 risk loci, explaining only 10.6% of migraine heritability. Thus, there is a considerable genetic component not identified with GWAS. Further, the causality of the identified risk loci remains inconclusive. Rare variants contribute to the risk of migraine but GWAS are often underpowered to detect these. Whole genome sequencing is reliable for analyzing rare variants but is not frequently used in large-scale. We assessed if rare variants in the migraine risk loci associated with migraine. We used a large cohort of whole genome sequenced migraine patients (1,040 individuals from 155 families). The findings were replicated in an independent case-control cohort (2,027 migraine patients, 1,650 controls). We found rare variants (minor allele frequency<0.1%) associated with migraine in a Polycomb Response Element in the ASTN2 locus. The association was independent of the GWAS lead risk variant in the locus. The findings place rare variants as risk factors for migraine. We propose a biological mechanism by which epigenetic regulation by Polycomb Response Elements plays a crucial role in migraine etiology.

scholarly journals Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Ana Viñuela ◽  
Arushi Varshney ◽  
Martijn van de Bunt ◽  
Rashmi B. Prasad ◽  
Olof Asplund ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Cell Types ◽  
Genome Wide Association ◽  
Regulatory Sequences ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Gwas Signal ◽  
Using Data

Abstract Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.

scholarly journals Transcriptome-Wide Association Study Provides Insights Into the Genetic Component of Gene Expression in Anxiety

2021 ◽  
Vol 12 ◽  
Author(s):  
Xi Su ◽  
Wenqiang Li ◽  
Luxian Lv ◽  
Xiaoyan Li ◽  
Jinfeng Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Anxiety Disorders ◽  
Association Study ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Component ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Regulated Expression

Anxiety disorders are common mental disorders that often result in disability. Recently, large-scale genome-wide association studies (GWASs) have identified several novel risk variants and loci for anxiety disorders (or anxiety traits). Nevertheless, how the reported risk variants confer risk of anxiety remains unknown. To identify genes whose cis-regulated expression levels are associated with risk of anxiety traits, we conducted a transcriptome-wide association study (TWAS) by integrating genome-wide associations from a large-scale GWAS (N = 175,163) (which evaluated anxiety traits based on Generalized Anxiety Disorder 2-item scale (GAD-2) score) and brain expression quantitative trait loci (eQTL) data (from the PsychENCODE and GTEx). We identified 19 and 17 transcriptome-wide significant (TWS) genes in the PsychENCODE and GTEx, respectively. Intriguingly, 10 genes showed significant associations with anxiety in both datasets, strongly suggesting that genetic risk variants may confer risk of anxiety traits by regulating the expression of these genes. Top TWS genes included RNF123, KANSL1-AS1, GLYCTK, CRHR1, DND1P1, MAPT and ARHGAP27. Of note, 25 TWS genes were not implicated in the original GWAS. Our TWAS identified 26 risk genes whose cis-regulated expression were significantly associated with anxiety, providing important insights into the genetic component of gene expression in anxiety disorders/traits and new clues for future drug development.

scholarly journals Unique roles of rare variants in the genetics of complex diseases in humans

2020 ◽  
Vol 66 (1) ◽  
pp. 11-23
Author(s):  
Yukihide Momozawa ◽  
Keijiro Mizukami
Keyword(s):  
Rare Variants ◽  
Disease Risk ◽  
Association Studies ◽  
Complex Diseases ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Common Variants ◽  
Distinctive Features ◽  
Genome Wide

AbstractGenome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.

scholarly journals The Parkinson’s Disease GWAS Locus Browser

2020 ◽  
Author(s):  
Francis P. Grenn ◽  
Jonggeol J. Kim ◽  
Mary B. Makarious ◽  
Hirotaka Iwaki ◽  
Anastasia Illarionova ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Large Scale ◽  
Association Studies ◽  
Age At Onset ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Risk Variants ◽  
Genome Wide

AbstractParkinson’s disease (PD) is a neurodegenerative disease with an often complex genetic component identifiable by genome-wide association studies (GWAS). The most recent large scale PD GWASes have identified more than 90 independent risk variants for PD risk and progression across 80 loci. One major challenge in current genomics is identifying the causal gene(s) and variant(s) from each GWAS locus. Here we present a GWAS locus browser application that combines data from multiple databases to aid in the prioritization of genes associated with PD GWAS loci. We included 92 independent genome-wide significant signals from multiple recent PD GWAS studies including the PD risk GWAS, age-at-onset GWAS and progression GWAS. We gathered data for all 2336 genes within 1Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Our aim is that the information contained in this browser (https://pdgenetics.shinyapps.io/GWASBrowser/) will assist the PD research community with the prioritization of genes for follow-up functional studies and as potential therapeutic targets.

scholarly journals Rare ABCA7 variants in 2 German families with Alzheimer disease

2018 ◽  
Vol 4 (2) ◽  
pp. e224 ◽  
Author(s):  
Patrick May ◽  
Sabrina Pichler ◽  
Daniela Hartl ◽  
Dheeraj R. Bobbili ◽  
Manuel Mayhaus ◽  
...  
Keyword(s):  
Alzheimer Disease ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rare Variants ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Pathogenic Variants ◽  
Genome Wide

ObjectiveThe aim of this study was to identify variants associated with familial late-onset Alzheimer disease (AD) using whole-genome sequencing.MethodsSeveral families with an autosomal dominant inheritance pattern of AD were analyzed by whole-genome sequencing. Variants were prioritized for rare, likely pathogenic variants in genes already known to be associated with AD and confirmed by Sanger sequencing using standard protocols.ResultsWe identified 2 rare ABCA7 variants (rs143718918 and rs538591288) with varying penetrance in 2 independent German AD families, respectively. The single nucleotide variant (SNV) rs143718918 causes a missense mutation, and the deletion rs538591288 causes a frameshift mutation of ABCA7. Both variants have previously been reported in larger cohorts but with incomplete segregation information. ABCA7 is one of more than 20 AD risk loci that have so far been identified by genome-wide association studies, and both common and rare variants of ABCA7 have previously been described in different populations with higher frequencies in AD cases than in controls and varying penetrance. Furthermore, ABCA7 is known to be involved in several AD-relevant pathways.ConclusionsWe conclude that both SNVs might contribute to the development of AD in the examined family members. Together with previous findings, our data confirm ABCA7 as one of the most relevant AD risk genes.

scholarly journals Evolution, revolution and heresy in the genetics of infectious disease susceptibility

2012 ◽  
Vol 367 (1590) ◽  
pp. 840-849 ◽  
Author(s):  
Adrian V. S. Hill
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Large Scale ◽  
Disease Susceptibility ◽  
Rare Variants ◽  
Association Studies ◽  
Common Disease ◽  
Genome Wide Association Studies ◽  
Case Control Studies ◽  
Genome Wide

Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case–control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference.

scholarly journals Genome-Wide Meta-Analysis Identifies Two Novel Risk Loci for Epilepsy

2021 ◽  
Vol 15 ◽  
Author(s):  
Meng Song ◽  
Jiewei Liu ◽  
Yongfeng Yang ◽  
Luxian Lv ◽  
Wenqiang Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
New Drugs ◽  
Normal Brain ◽  
Genome Wide Association Studies ◽  
Metabotropic Receptor ◽  
Risk Variants ◽  
Genome Wide ◽  
Normal Brain Function

Epilepsy (affects about 70 million people worldwide) is one of the most prevalent brain disorders and imposes a huge economic burden on society. Epilepsy has a strong genetic component. In this study, we perform the largest genome-wide meta-analysis of epilepsy (N = 8,00,869 subjects) by integrating four large-scale genome-wide association studies (GWASs) of epilepsy. We identified three genome-wide significant (GWS) (p &lt; 5 × 10–8) risk loci for epilepsy. The risk loci on 7q21.11 [lead single nucleotide polymorphism (SNP) rs11978015, p = 9.26 × 10–9] and 8p23.1 (lead SNP rs28634186, p = 4.39 × 10–8) are newly identified in the present study. Of note, rs11978015 resides in upstream of GRM3, which encodes glutamate metabotropic receptor 3. GRM3 has pivotal roles in neurotransmission and is involved in most aspects of normal brain function. In addition, we also identified three genes (TTC21B, RP11-375N15.2, and TNKS) whose cis-regulated expression level are associated with epilepsy, indicating that risk variants may confer epilepsy risk through regulating the expression of these genes. Our study not only provides new insights into genetic architecture of epilepsy but also prioritizes potential molecular targets (including GRM3 and TTC21B) for development of new drugs and therapeutics for epilepsy.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

scholarly journals Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Nature ◽  
2021 ◽  
Vol 590 (7845) ◽  
pp. 290-299 ◽  
Author(s):  
Daniel Taliun ◽  
◽  
Daniel N. Harris ◽  
Michael D. Kessler ◽  
Jedidiah Carlson ◽  
...  
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Phenotypic Data ◽  
Treatment And Prevention ◽  
Genome Wide ◽  
Diverse Backgrounds ◽  
Unmapped Reads

AbstractThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

scholarly journals Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

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