Genome-Wide Association Studies and Heritability Estimation in the Functional Genomics Era

2018 ◽  
pp. 361-425 ◽  
Author(s):  
Dunia Pino Del Carpio ◽  
Roberto Lozano ◽  
Marnin D. Wolfe ◽  
Jean-Luc Jannink
Keyword(s):  
Functional Genomics ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Heritability Estimation

scholarly journals The genetic aetiology of cannabis use initiation: a meta-analysis of genome-wide association studies and a SNP-based heritability estimation

2012 ◽  
Vol 18 (5) ◽  
pp. 846-850 ◽  
Author(s):  
Karin J. H. Verweij ◽  
Anna A. E. Vinkhuyzen ◽  
Beben Benyamin ◽  
Michael T. Lynskey ◽  
Lydia Quaye ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Cannabis Use ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Heritability Estimation

scholarly journals Conditions for the validity of SNP-based heritability estimation

2014 ◽  
Author(s):  
James J Lee ◽  
Carson C Chow
Keyword(s):  
Lower Bound ◽  
Association Studies ◽  
Gwas Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Population Variance ◽  
Genome Wide ◽  
Heritability Estimation ◽  
Novel Method ◽  
The Given

The heritability of a trait ($h^2$) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs ($h^2_\textrm{SNP}$). Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining $h^2_\textrm{SNP}$ under circumstances wider than those under which it has so far been derived.

scholarly journals Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data

2016 ◽  
Author(s):  
Daniel S. Tylee ◽  
Jiayin Sun ◽  
Jonathan L. Hess ◽  
Muhammad A. Tahir ◽  
Esha Sharma ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Lupus Erythematosus ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Biliary Cirrhosis ◽  
Genome Wide Association Studies ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Heritability Estimation

AbstractIndividuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies (GWASs) to determine if commonly varying single nucleotide polymorphisms (SNPs) are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (HESS) methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn’s disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations amongst the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.

scholarly journals Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies

2016 ◽  
Vol 46 (8) ◽  
pp. 1613-1623 ◽  
Author(s):  
A. Demirkan ◽  
J. Lahti ◽  
N. Direk ◽  
A. Viktorin ◽  
K. L. Lunetta ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Genome Wide Association ◽  
Depression Symptoms ◽  
Genome Wide Association Studies ◽  
Replication Sample ◽  
Genome Wide ◽  
Heritability Estimation ◽  
Minor Part

BackgroundMajor depressive disorder (MDD) is moderately heritable, however genome-wide association studies (GWAS) for MDD, as well as for related continuous outcomes, have not shown consistent results. Attempts to elucidate the genetic basis of MDD may be hindered by heterogeneity in diagnosis. The Center for Epidemiological Studies Depression (CES-D) scale provides a widely used tool for measuring depressive symptoms clustered in four different domains which can be combined together into a total score but also can be analysed as separate symptom domains.MethodWe performed a meta-analysis of GWAS of the CES-D symptom clusters. We recruited 12 cohorts with the 20- or 10-item CES-D scale (32 528 persons).ResultsOne single nucleotide polymorphism (SNP), rs713224, located near the brain-expressed melatonin receptor (MTNR1A) gene, was associated with the somatic complaints domain of depression symptoms, with borderline genome-wide significance (pdiscovery = 3.82 × 10−8). The SNP was analysed in an additional five cohorts comprising the replication sample (6813 persons). However, the association was not consistent among the replication sample (pdiscovery+replication = 1.10 × 10−6) with evidence of heterogeneity.ConclusionsDespite the effort to harmonize the phenotypes across cohorts and participants, our study is still underpowered to detect consistent association for depression, even by means of symptom classification. On the contrary, the SNP-based heritability and co-heritability estimation results suggest that a very minor part of the variation could be captured by GWAS, explaining the reason of sparse findings.

scholarly journals Redefining replication in multi-ancestry genome-wide association studies

2021 ◽  
Author(s):  
Samuel Pattillo Smith ◽  
Sahar Shahamatdar ◽  
Wei Cheng ◽  
Selena Zhang ◽  
Joseph Paik ◽  
...  
Keyword(s):  
Latin American ◽  
Alaska Native ◽  
Prediction Models ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Heritability Estimation

AbstractSince 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from European ancestry individuals apply heterogeneously in non-European ancestry individuals. Here, we argue that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales—to genes and pathways—have been overlooked and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the insights generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. By testing for statistical associations at multiple genomic scales, enrichment analyses also illustrate the importance of reconciling contrasting results from association tests, heritability estimation, and prediction models in order to make personalized medicine a reality for all.

scholarly journals Genomics of Endometriosis: From Genome Wide Association Studies to Exome Sequencing

2021 ◽  
Vol 22 (14) ◽  
pp. 7297
Author(s):  
Imane Lalami ◽  
Carole Abo ◽  
Bruno Borghese ◽  
Charles Chapron ◽  
Daniel Vaiman
Keyword(s):  
Exome Sequencing ◽  
Complex Disease ◽  
Association Studies ◽  
Chromosome 9 ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Replication Studies ◽  
Genome Wide ◽  
Heritability Estimation ◽  
Functional Explanations

This review aims at better understanding the genetics of endometriosis. Endometriosis is a frequent feminine disease, affecting up to 10% of women, and characterized by pain and infertility. In the most accepted hypothesis, endometriosis is caused by the implantation of uterine tissue at ectopic abdominal places, originating from retrograde menses. Despite the obvious genetic complexity of the disease, analysis of sibs has allowed heritability estimation of endometriosis at ~50%. From 2010, large Genome Wide Association Studies (GWAS), aimed at identifying the genes and loci underlying this genetic determinism. Some of these loci were confirmed in other populations and replication studies, some new loci were also found through meta-analyses using pooled samples. For two loci on chromosomes 1 (near CCD42) and chromosome 9 (near CDKN2A), functional explanations of the SNP (Single Nucleotide Polymorphism) effects have been more thoroughly studied. While a handful of chromosome regions and genes have clearly been identified and statistically demonstrated as at-risk for the disease, only a small part of the heritability is explained (missing heritability). Some attempts of exome sequencing started to identify additional genes from families or populations, but are still scarce. The solution may reside inside a combined effort: increasing the size of the GWAS designs, better categorize the clinical forms of the disease before analyzing genome-wide polymorphisms, and generalizing exome sequencing ventures. We try here to provide a vision of what we have and what we should obtain to completely elucidate the genetics of this complex disease.

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