scholarly journals The accuracy of LD Score regression as an estimator of confounding and genetic correlations in genome‐wide association studies

2018 ◽  
Vol 42 (8) ◽  
pp. 783-795 ◽  
Author(s):  
James J. Lee ◽  
Matt McGue ◽  
William G. Iacono ◽  
Carson C. Chow
Keyword(s):  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence

2017 ◽  
Author(s):  
W. D. Hill ◽  
G. Davies ◽  
A. M. McIntosh ◽  
C. R. Gale ◽  
I. J. Deary
Keyword(s):  
Household Income ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Correlated Traits ◽  
Single Measure ◽  
Combined Analysis ◽  
Genome Wide

AbstractIntelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including many physical and mental health variables. Both education and household income are strongly genetically correlated with intelligence, at rg =0.73 and rg =0.70 respectively. This allowed us to utilize a novel approach, Multi-Trait Analysis of Genome-wide association studies (MTAG; Turley et al. 2017), to combine two large genome-wide association studies (GWASs) of education and household income to increase power in the largest GWAS on intelligence so far (Sniekers et al. 2017). This study had four goals: firstly, to facilitate the discovery of new genetic loci associated with intelligence; secondly, to add to our understanding of the biology of intelligence differences; thirdly, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predict phenotypic intelligence variance in an independent sample. We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system. We show that the results of our combined analysis demonstrate the same pattern of genetic correlations as a single measure/the simple measure of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. We find that our MTAG meta-analysis of intelligence shows similar genetic correlations to 26 other phenotypes when compared with a GWAS consisting solely of cognitive tests. Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.

scholarly journals Joint Genome-Wide Association Study Identifies Twenty-One Novel Loci for Age at Menarche and Highlights Its Causal Association with Other Complex Diseases

2021 ◽  
Author(s):  
Gui-Juan Feng ◽  
Qian Xu ◽  
Jing-Jing Ni ◽  
Shan-Shan Yang ◽  
Bai-Xue Han ◽  
...  
Keyword(s):  
Association Study ◽  
Complex Traits ◽  
Causal Effect ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Age At Menarche ◽  
Luteinizing Hormone Level ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Age at menarche (AAM) is a sign of puberty of females. It is a heritable trait associated with various adult diseases. However, the genetic mechanism that determines AAM and links it to disease risk is poorly understood. Aiming to uncover the genetic basis for AAM, we conducted a joint association study in up to 438,089 participants from 3 genome-wide association studies of European and East Asian ancestries. Twenty-one novel genomic loci were identified at the genome-wide significance level. Besides, we observed significant genetic correlations between AAM and 67 complex traits, and the highest genetic correlation was observed between AAM and body mass index (rg=-0.19, P=6.11×10−31). Latent causal variable analyses demonstrate that there is a genetically causal effect of AAM on high blood pressure (GCP=0.47, P=0.02), forced vital capacity (GCP=0.63, P=0.02), age at first live birth (GCP=0.51, P=0.03), impedance of right arm (GCP=0.41, P<1×10-7) and right leg fat percentage (GCP=-0.10, P=0.02), etc. Enrichment analysis identified 5 enriched tissues and 51 enriched gene sets. Four of the five enriched tissues were related to the nervous system, including the hypothalamus middle, hypothalamo hypophyseal system, neurosecretory systems and hypothalamus. The fifth tissue was the retina in the sensory organ. The most significant gene set was the ‘decreased circulating luteinizing hormone level’ (P=2.45×10-6). Our findings may provide useful insights that elucidate the mechanisms determining AAM and the genetic interplay between AAM and some traits of women.

scholarly journals Geographic Confounding in Genome-Wide Association Studies

2021 ◽  
Author(s):  
Abdel Abdellaoui ◽  
Karin Verweij ◽  
Michel G Nivard
Keyword(s):  
Educational Attainment ◽  
Social Stratification ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Geographic Region ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Environment ◽  
Genome Wide

Abstract Gene-environment correlations can bias associations between genetic variants and complex traits in genome-wide association studies (GWASs). Here, we control for geographic sources of gene-environment correlation in GWASs on 56 complex traits (N = 69,772–271,457). Controlling for geographic region significantly decreases heritability signals for SES-related traits, most strongly for educational attainment and income, indicating that socio-economic differences between regions induce gene-environment correlations that become part of the polygenic signal. For most other complex traits investigated, genetic correlations with educational attainment and income are significantly reduced, most significantly for traits related to BMI, sedentary behavior, and substance use. Controlling for current address has greater impact on the polygenic signal than birth place, suggesting both active and passive sources of gene-environment correlations. Our results show that societal sources of social stratification that extend beyond families introduce regional-level gene-environment correlations that affect GWAS results.

scholarly journals Multi-breed Genetic Parameters and Genome-wide Association Studies for Mortality Rate at Birth in Pigs

2021 ◽  
Author(s):  
Meijing An ◽  
Guangliang Zhou ◽  
Yang Li ◽  
Tao Xiang ◽  
Yunlong Ma ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Genetic Parameters ◽  
Association Studies ◽  
Genetic Correlations ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Expressions ◽  
Genome Wide ◽  
Piglet Mortality

Abstract Background Piglet mortality is an economically important complex trait that impacts sow prolificacy in the pig industry. The genetic parameters estimations and genome-wide association studies will help us to better understand the genetic fundamentals of piglet mortality. However, compared with other economically important traits, a little breakthrough in the genetic analyses of the trait has been achieved. Results In this study, we used multi-breed data sets from Yorkshire, Landrace, and Duroc sows and characterized the genetic and genomic properties of mortality rate at birth by treating each parity as a different trait. The heritability of mortality rate from parity I to III were estimated to be 0.0630, 0.1031, and 0.1140, respectively. The phenotypic and genetic correlations with its component traits were all positive with ranges from 0.0897 to 0.9054, and 0.2388 to 0.9999, respectively. Integrating the results, we identified 21 loci that were detected at least by two tools from standard MLM, FarmCPU, BLINK and mrMLM, and these loci were annotated to 22 genes. The annotations revealed that the gene expressions were associated with the reproductive system, nervous system, digestive system, and embryonic development, which are reasonably related to the piglet mortality. Conclusions In brief, the genetic properties of piglet mortality at birth were reported. These findings are expected to provide much information for understanding the genetic and genomic fundamentals of farrowing mortality and also identify candidate molecular markers for breeding practice.

scholarly journals Recent advances in the genetic association between osteoporotic fracture and sarcopenia

2021 ◽  
Vol 3 (1) ◽  
pp. 02-09
Author(s):  
Qiaocong Chen ◽  
◽  
Huiling Lou ◽  
Cheng Peng
Keyword(s):  
Fracture Risk ◽  
Osteoporotic Fracture ◽  
Musculoskeletal Diseases ◽  
Association Studies ◽  
Genetic Correlations ◽  
Osteoporotic Fractures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide

The risk of osteoporotic fracture can be viewed as a function of loading conditions and the ability of the bone to withstand the load. Skeletal loads are dominated by muscle action. Recently, it has become clear that bone and muscle share genetic determinants. Involvement of the musculoskeletal system manifests as bone loss (osteoporosis) and muscle wasting (sarcopenia). There is clinical evidence that osteoporotic fractures are significantly associated with sarcopenia, and sarcopenia may be a potential predictive factor for fracture risk, which suggests that there may be shared genetic determinants between sarcopenia and osteoporotic fracture. In recent years, genome-wide association studies (GWASs) studies have found that both lean mass and hand grip strength are associated with fracture risk, which may provide a possible endophenotype for elucidating the potential genetic study of fracture risk. Our effort to understand the clinical and genetic correlations between osteoporotic fracture and sarcopenia is helpful to understand the interaction between muscle and bone, and to study the etiology of complex musculoskeletal diseases. Identifying potentially important genetic variations in bone and muscle, measuring these variations using state-of-the-art technology, and replicating these experiments in humans and large animals will provide potential drug or intervention targets for osteoporotic fracture valuable in the future. Keywords: Genetics, osteoporosis, fracture, sarcopenia, genome-wide association studies, single nucleotide polymorphism

scholarly journals Geographic Confounding in Genome-Wide Association Studies

2021 ◽  
Author(s):  
Abdel Abdellaoui ◽  
Karin J.H. Verweij ◽  
Michel G. Nivard
Keyword(s):  
Educational Attainment ◽  
Social Stratification ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Geographic Region ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Environment ◽  
Genome Wide

Gene-environment correlations can bias associations between genetic variants and complex traits in genome-wide association studies (GWASs). Here, we control for geographic sources of gene-environment correlation in GWASs on 56 complex traits (N=69,772-271,457). Controlling for geographic region significantly decreases heritability signals for SES-related traits, most strongly for educational attainment and income, indicating that socio-economic differences between regions induce gene-environment correlations that become part of the polygenic signal. For most other complex traits investigated, genetic correlations with educational attainment and income are significantly reduced, most significantly for traits related to BMI, sedentary behavior, and substance use. Controlling for current address has greater impact on the polygenic signal than birth place, suggesting both active and passive sources of gene-environment correlations. Our results show that societal sources of social stratification that extend beyond families introduce regional-level gene-environment correlations that affect GWAS results.

scholarly journals Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity

2020 ◽  
Vol 10 (3) ◽  
pp. 951-965 ◽  
Author(s):  
Xinzhu Zhou ◽  
Celine L. St. Pierre ◽  
Natalia M. Gonzales ◽  
Jennifer Zou ◽  
Riyan Cheng ◽  
...  
Keyword(s):  
Body Weight ◽  
Locomotor Activity ◽  
Coat Color ◽  
Environmental Control ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Advanced Intercross Line ◽  
Genome Wide

There has been extensive discussion of the “Replication Crisis” in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner’s Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

scholarly journals Genome-Wide Association Studies Dissect the G×E Interaction for Agronomic Traits in a Worldwide Collection of Safflower (Carthamus Tinctorius L.)

2021 ◽  
Author(s):  
Huanhuan Zhao ◽  
Keith W. Savin ◽  
Yongjun Li ◽  
Edmond J Breen ◽  
Pankaj Maharjan ◽  
...  
Keyword(s):  
Water Stress ◽  
Genetic Architecture ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Carthamus Tinctorius ◽  
Genome Wide Association ◽  
Oil Yield ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Background: Safflower (Carthamus tinctorius L.) has been cultivated worldwide for centuries, originally as a source of textile dyes. Modern safflower breeding has focused on high grain and oil yield and broad adaptability. Here, a genome-wide association study was conducted using a globally diverse Genebank collection of 406 accessions, which included landraces, breeding lines and elite cultivars. We explored the genetic architecture and genotype-by-environment interaction (G × E) patterns of grain yield (YP), days to flowering (DF ), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Results: Phenotypic variation within the global collection was observed for all traits under differed water stress environments. Two mixed linear models were adopted, and YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. Ninety-two marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites was identified for all traits. Five MTAs were associated with multiple traits, 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR and marker effects were consistent with phenotypic observations in different environments. The thresholds of different GWAS methods used in the study affected the number of MTAs identified for complex traits. Conclusions: This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments. This knowledge is essential to breed for high grain and oil yield and local adaption in safflower.

scholarly journals Carotid intima-media thickness in UK Biobank: Identification of novel genome-wide loci, sex-specific effects and genetic correlations with obesity and glucometabolic traits

2019 ◽  
Author(s):  
Rona J. Strawbridge ◽  
Joey Ward ◽  
Mark E.S. Bailey ◽  
Breda Cullen ◽  
Amy Ferguson ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Association Studies ◽  
Genetic Correlations ◽  
Intima Media Thickness ◽  
Genome Wide Association ◽  
Ultra Sound ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Media Thickness ◽  
Genome Wide

AbstractObjectivesAtherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultra-sound measurement of the carotid artery intima-media thickness (cIMT) can be used to measure vascular remodelling, which is indicative of atherosclerosis. Genome-wide association studies have identified a number of genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here we conducted genome-wide association analyses in UK Biobank (N=22,179), the largest single study with consistent cIMT measurements.Approach and resultsWe used BOLT-LMM to run linear regression of cIMT in UK Biobank, adjusted for age, sex, genotyping platform and population structure. In white British participants, we identified 4 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a female-specific locus on Chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body-mass index and glucometabolic traits were also observed.ConclusionThese findings replicate previously reported associations, highlight novel biology and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

scholarly journals Genome-Wide Association Studies of malaria susceptibility and resistance: progress, pitfalls and prospects

2018 ◽  
Author(s):  
Delesa Damena ◽  
Awany Denis ◽  
Lemu Golassa ◽  
Emile R. Chimusa
Keyword(s):  
Molecular Mechanisms ◽  
Association Studies ◽  
Genetic Correlations ◽  
Sub Saharan Africa ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Malaria Susceptibility ◽  
Endemic Areas ◽  
Susceptibility And Resistance

AbstractP. falciparum malaria is still among the leading causes of child mortality in sub-Saharan Africa; killing hundreds of thousands of children each year. Malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective polymorphisms associated with minimizing the risk of developing severe malaria in endemic areas. A comprehensive understanding of the genetic bases of malaria resistance can shed light to the molecular mechanisms of host-parasite interactions that can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. Despite this success, only few variants did replicate across the studies and the underlying biology is yet to be understood for the majority of the novel variants. Besides, there are several open questions around heritability, polygenic effects, epistatic interactions, genetic correlations and associated molecular pathways among others. In this review, we first assess the progress and pitfalls of malaria susceptibility GWASs. We then, provide an overview of the current progress in post-GWAS approaches and discuss how these approaches can potentially be implemented in malaria susceptibility GWASs to extract further functional information. We conclude by highlighting the importance of multi-step and multidimensional integrative studies for unravelling the genetic basis of malaria susceptibility and resistance at systems biology level.

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