scholarly journals Integrative genomics analysis identifies ACVR1B as a candidate causal gene of emphysema distribution in non-alpha 1-antitrypsin deficient smokers

2017 ◽  
Author(s):  
Adel Boueiz ◽  
Robert Chase ◽  
Andrew Lamb ◽  
Sool Lee ◽  
Zun Zar Chi Naing ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Cell Types ◽  
Causal Variant ◽  
Dnase I ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Integrative Genomics ◽  
Functional Validation ◽  
Regulatory Variants

ABSTRACTBackgroundSeveral genetic risk loci associated with emphysema apico-basal distribution (EABD) have been identified through genome-wide association studies (GWAS), but the biological functions of these variants are unknown. To characterize gene regulatory functions of EABD-associated variants, we integrated EABD GWAS results with 1) a multi-tissue panel of expression quantitative trait loci (eQTL) from subjects with COPD and the GTEx project and 2) epigenomic marks from 127 cell types in the Roadmap Epigenomics project. Functional validation was performed for a variant near ACVR1B.ResultsSNPs from 168 loci with P-values<5x10-5 in the largest GWAS meta-analysis of EABD (Boueiz A. et al, AJRCCM 2017) were analyzed. 54 loci overlapped eQTL regions from our multi-tissue panel, and 7 of these loci showed a high probability of harboring a single, shared GWAS and eQTL causal variant (colocalization posterior probability≥0.9). 17 cell types exhibited greater than expected overlap between EABD loci and DNase-I hypersensitive peaks, DNaseI hotspots, enhancer marks, or digital DNaseI footprints (permutation P-value < 0.05), with the strongest enrichment observed in CD4+, CD8+, and regulatory T cells. A region near ACVR1B demonstrated significant colocalization with a lung eQTL and overlapped DNase-I hypersensitive regions in multiple cell types, and reporter assays in human bronchial epithelial cells confirmed allele-specific regulatory activity for the lead variant, rs7962469.ConclusionsIntegrative analysis highlights candidate causal genes, regulatory variants, and cell types that may contribute to the pathogenesis of emphysema distribution. These findings will enable more accurate functional validation studies and better understanding of emphysema distribution biology.

scholarly journals 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Mathias Gorski ◽  
Peter J. van der Most ◽  
Alexander Teumer ◽  
Audrey Y. Chu ◽  
Man Li ◽  
...  
Keyword(s):  
Kidney Function ◽  
Kidney Development ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
P Value ◽  
Genome Wide Association Studies ◽  
1000 Genomes ◽  
Gene Sets ◽  
Project Promise

Abstract HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.

scholarly journals Genome-wide association and multi-omic analyses reveal new mechanisms for Heart Failure

2019 ◽  
Author(s):  
Marios Arvanitis ◽  
Yanxiao Zhang ◽  
Wei Wang ◽  
Adam Auton ◽  
Ali Keramati ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cardiac Muscle ◽  
Association Studies ◽  
Meta Analysis ◽  
Regulatory Region ◽  
Causal Variant ◽  
Left Ventricular ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractHeart failure is a major medical and economic burden in the healthcare system affecting over 23 million people worldwide. Although recent pedigree studies estimate heart failure heritability around 26%, genome-wide association studies (GWAS) have had limited success in explaining disease pathogenesis. We conducted the largest meta-analysis of heart failure GWAS to-date and replicated our findings in a comparable sized cohort to identify one known and two novel variants associated with heart failure. Leveraging heart failure sub-phenotyping and fine-mapping, we reveal a putative causal variant found in a cardiac muscle specific regulatory region that binds to the ACTN2 cardiac sarcolemmal gene and affects left ventricular adverse remodeling and clinical heart failure in response to different initial cardiac muscle insults. Via genetic correlation, we show evidence of broadly shared heritability between heart failure and multiple musculoskeletal traits. Our findings extend our understanding of biological mechanisms underlying heart failure.

scholarly journals A meta-analysis of the genome-wide association studies on two genetically correlated phenotypes (self-reported headache and self-reported migraine) identifies four new risk loci for headaches (N=397,385)

2021 ◽  
Author(s):  
Weihua Meng ◽  
Parminder Reel ◽  
Charvi Nangia ◽  
Aravind Rajendrakumar ◽  
Harry Hebert ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
The Self ◽  
Genome Wide Association ◽  
P Value ◽  
Clinical Settings ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genetic Mechanisms ◽  
The Uk

Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank cohort and the self-reported migraine phenotype from the 23andMe resource using the metaUSAT for genetically correlated phenotypes (N=397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and 4 loci were newly identified. The LRP1-STAT6-SDR9C7 region in chromosome 12 was the most significantly associated locus with a leading P value of 1.24 x 10-62 of rs11172113. The ONECUT2 gene locus in chromosome 18 was the strongest signal among the 4 new loci with a P value of 1.29 x 10-9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more new variants for headaches. This study has paved way for a large GWAS meta-analysis study involving cohorts of different, though genetically correlated headache phenotypes.

scholarly journals Open Targets Genetics: An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci

2020 ◽  
Author(s):  
Edward Mountjoy ◽  
Ellen M. Schmidt ◽  
Miguel Carmona ◽  
Gareth Peat ◽  
Alfredo Miranda ◽  
...  
Keyword(s):  
Complex Traits ◽  
Drug Targets ◽  
Association Studies ◽  
Single Gene ◽  
Cell Types ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Open Approach ◽  
Protein Coding ◽  
Causal Genes

AbstractGenome-wide association studies (GWAS) have identified many variants robustly associated with complex traits but identifying the gene(s) mediating such associations is a major challenge. Here we present an open resource that provides systematic fine-mapping and protein-coding gene prioritization across 133,441 published human GWAS loci. We integrate diverse data sources, including genetics (from GWAS Catalog and UK Biobank) as well as transcriptomic, proteomic and epigenomic data across many tissues and cell types. We also provide systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues and identify 729 loci fine-mapped to a single coding causal variant and colocalized with a single gene. We trained a machine learning model using the fine mapped genetics and functional genomics data using 445 gold standard curated GWAS loci to distinguish causal genes from background genes at the same loci, outperforming a naive distance based model. Genes prioritized by our model are enriched for known approved drug targets (OR = 8.1, 95% CI: [5.7, 11.5]). These results will be regularly updated and are publicly available through a web portal, Open Targets Genetics (OTG, http://genetics.opentargets.org), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.

scholarly journals Differential and spatial expression meta-analysis of genes identified in genome-wide association studies of depression

2020 ◽  
Author(s):  
Wennie Wu ◽  
Derek Howard ◽  
Etienne Sibille ◽  
Leon French
Keyword(s):  
Differential Expression ◽  
Association Studies ◽  
Meta Analysis ◽  
Cell Types ◽  
Brain Regions ◽  
Enteric Neurons ◽  
Dorsal Lateral Geniculate Nucleus ◽  
Genome Wide Association Studies ◽  
Specific Effects ◽  
Dorsal Lateral Geniculate

AbstractMajor depressive disorder (MDD) is the most prevalent psychiatric disorder worldwide and affects individuals of all ages. It causes significant psychosocial impairments and is a major cause of disability. A recent consortium study identified 102 genetic variants and 269 genes associated with depression. To provide targets for future depression research, we prioritized these recently identified genes using expression data. We examined differential expression of these genes in three studies that profiled gene expression of MDD cases and controls across multiple brain regions. In addition, we integrated anatomical expression information to determine which brain regions and transcriptomic cell-types highly express the candidate genes. We highlight 11 of the 269 genes with the most consistent differential expression: MANEA, UBE2M, CKB, ITPR3, SPRY2, SAMD5, TMEM106B, ZC3H7B, LST1, ASXL3 and HSPA1A. The majority of these top genes were found to have sex-specific differential expression. We place greater emphasis on MANEA as it is the top gene in a more conservative analysis of the 269. Specifically, differential expression of MANEA was strongest in cerebral cortex regions and had opposing sex-specific effects. Anatomically, our results suggest the importance of the dorsal lateral geniculate nucleus, cholinergic, monoaminergic, and enteric neurons. These findings provide a guide for targeted experiments to advance our understanding of the genetic underpinnings of depression.

scholarly journals GWAS Meta-Analysis of Neuroticism (N=449,484) Identifies Novel Genetic Loci and Pathways

2017 ◽  
Author(s):  
Mats Nagel ◽  
Philip R Jansen ◽  
Sven Stringer ◽  
Kyoko Watanabe ◽  
Christiaan A de Leeuw ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Cell Types ◽  
Brain Regions ◽  
Specific Cell ◽  
Medium Spiny Neurons ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genetic Signal

Neuroticism is an important risk factor for psychiatric traits including depression1, anxiety2,3, and schizophrenia4–6. Previous genome-wide association studies7–12 (GWAS) reported 16 genomic loci10–12. Here we report the largest neuroticism GWAS meta-analysis to date (N=449,484), and identify 136 independent genome-wide significant loci (124 novel), implicating 599 genes. Extensive functional follow-up analyses show enrichment in several brain regions and involvement of specific cell-types, including dopaminergic neuroblasts (P=3×10-8), medium spiny neurons (P=4×10-8) and serotonergic neurons (P=1×10-7). Gene-set analyses implicate three specific pathways: neurogenesis (P=4.4×10-9), behavioural response to cocaine processes (P=1.84×10-7), and axon part (P=5.26×10-8). We show that neuroticism’s genetic signal partly originates in two genetically distinguishable subclusters13 (depressed affect and worry, the former being genetically strongly related to depression, rg=0.84), suggesting distinct causal mechanisms for subtypes of individuals. These results vastly enhance our neurobiological understanding of neuroticism, and provide specific leads for functional follow-up experiments.

scholarly journals Dissecting the genetics of chronic mucus hypersecretion in smokers with and without COPD

2014 ◽  
Vol 45 (1) ◽  
pp. 60-75 ◽  
Author(s):  
Akkelies E. Dijkstra ◽  
H. Marike Boezen ◽  
Maarten van den Berge ◽  
Judith M. Vonk ◽  
Pieter S. Hiemstra ◽  
...  
Keyword(s):  
Genetic Model ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Chronic Obstructive ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Mucus Hypersecretion ◽  
Genome Wide

Smoking is a notorious risk factor for chronic mucus hypersecretion (CMH). CMH frequently occurs in chronic obstructive pulmonary disease (COPD). The question arises whether the same single-nucleotide polymorphisms (SNPs) are related to CMH in smokers with and without COPD.We performed two genome-wide association studies of CMH under an additive genetic model in male heavy smokers (≥20 pack-years) with COPD (n=849, 39.9% CMH) and without COPD (n=1348, 25.4% CMH), followed by replication and meta-analysis in comparable populations, and assessment of the functional relevance of significantly associated SNPs.Genome-wide association analysis of CMH in COPD and non-COPD subjects yielded no genome-wide significance after replication. In COPD, our top SNP (rs10461985, p=5.43×10−5) was located in the GDNF-AS1 gene that is functionally associated with the GDNF gene. Expression of GDNF in bronchial biopsies of COPD patients was significantly associated with CMH (p=0.007). In non-COPD subjects, four SNPs had a p-value <10−5 in the meta-analysis, including a SNP (rs4863687) in the MAML3 gene, the T-allele showing modest association with CMH (p=7.57×10−6, OR 1.48) and with significantly increased MAML3 expression in lung tissue (p=2.59×10−12).Our data suggest the potential for differential genetic backgrounds of CMH in individuals with and without COPD.

scholarly journals A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity

2019 ◽  
Vol 28 (19) ◽  
pp. 3327-3338 ◽  
Author(s):  
Jonathan P Bradfield ◽  
Suzanne Vogelezang ◽  
Janine F Felix ◽  
Alessandra Chesi ◽  
Øyvind Helgeland ◽  
...  
Keyword(s):  
Childhood Obesity ◽  
Late Onset ◽  
Association Studies ◽  
Meta Analysis ◽  
Causal Variant ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
South American ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Abstract Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2–18 years old) and 15 599 controls (consistently &lt;50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1888 cases and 4689 controls from seven cohorts of European and North/South American ancestry. In addition to observing 18 previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene, METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

scholarly journals Evidence for Recent Polygenic Selection on Educational Attainment Inferred from GWAS Hits

2016 ◽  
Author(s):  
Davide Piffer
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Association Studies ◽  
Meta Analysis ◽  
Significant Snps ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Model Average ◽  
Polygenic Scores ◽  
Polygenic Selection

The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. The PS of 161 GWAS significant SNPs in a recent meta-analysis was highly correlated to population IQ (r=0.863) and to the polygenic score of four alleles independently associated with general cognitive ability. High&nbsp; correlations with PISA scores for a subsample were observed.SNP p value predicted correlation to population IQ and factors from the two previous GWAS (r= -.25). Factor analysis produced similar estimates of selection pressure for educational attainment across the three datasets. Polygenic and factor scores computed using the top 20 significant SNPs showed very high correlation to population IQ (r=0.88; 0.9). Similar findings were obtained using 52 populations from another database (ALFRED). The results together constitute a replication of preliminary findings and provide strong evidence for recent diversifying polygenic selection on educational attainment and underlying cognitive ability.

scholarly journals Functional consequences of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals

2017 ◽  
Author(s):  
Jonathan R. I. Coleman ◽  
Julien Bryois ◽  
Héléna A. Gaspar ◽  
Philip R. Jansen ◽  
Jeanne Savage ◽  
...  
Keyword(s):  
Pyramidal Neurons ◽  
Association Studies ◽  
Meta Analysis ◽  
Neuronal Cell ◽  
Cell Types ◽  
Model Systems ◽  
Genome Wide Association Studies ◽  
Ca1 Region ◽  
Wide Range ◽  
Neural Underpinnings

AbstractVariance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with an extreme-trait cohort of 1,247 individuals with mean IQ ∼170 and 8,185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.

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