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Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study.

ABSTRACT: Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson's r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10-4 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10-7 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved.

SUBMITTER: Jo Hodonsky C

PROVIDER: S-EPMC6300146 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study.

Jo Hodonsky Chani C Schurmann Claudia C Schick Ursula M UM Kocarnik Jonathan J Tao Ran R van Rooij Frank Ja FJ Wassel Christina C Buyske Steve S Fornage Myriam M Hindorff Lucia A LA Floyd James S JS Ganesh Santhi K SK Lin Dan-Yu DY North Kari E KE Reiner Alex P AP Loos Ruth Jf RJ Kooperberg Charles C Avery Christy L CL

American journal of hematology 20180615

Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs t ...[more]

PMID: 29905378

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Project description:Aims/hypothesisType 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.MethodsWe conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.ResultsFour novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.Conclusions/interpretationOur findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.Data availabilityFull summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Project description:BACKGROUND/OBJECTIVES:Central adiposity measures such as waist circumference (WC) and waist-to-hip ratio (WHR) are associated with cardiometabolic disorders independently of body mass index (BMI) and are gaining clinically utility. Several studies report genetic variants associated with central adiposity, but most utilize only European ancestry populations. Understanding whether the genetic associations discovered among mainly European descendants are shared with African ancestry populations will help elucidate the biological underpinnings of abdominal fat deposition. SUBJECTS/METHODS:To identify the underlying functional genetic determinants of body fat distribution, we conducted an array-wide association meta-analysis among persons of African ancestry across seven studies/consortia participating in the Population Architecture using Genomics and Epidemiology (PAGE) consortium. We used the Metabochip array, designed for fine-mapping cardiovascular-associated loci, to explore novel array-wide associations with WC and WHR among 15?945 African descendants using all and sex-stratified groups. We further interrogated 17 known WHR regions for African ancestry-specific variants. RESULTS:Of the 17 WHR loci, eight single-nucleotide polymorphisms (SNPs) located in four loci were replicated in the sex-combined or sex-stratified meta-analyses. Two of these eight independently associated with WHR after conditioning on the known variant in European descendants (rs12096179 in TBX15-WARS2 and rs2059092 in ADAMTS9). In the fine-mapping assessment, the putative functional region was reduced across all four loci but to varying degrees (average 40% drop in number of putative SNPs and 20% drop in genomic region). Similar to previous studies, the significant SNPs in the female-stratified analysis were stronger than the significant SNPs from the sex-combined analysis. No novel associations were detected in the array-wide analyses. CONCLUSIONS:Of 17 previously identified loci, four loci replicated in the African ancestry populations of this study. Utilizing different linkage disequilibrium patterns observed between European and African ancestries, we narrowed the suggestive region containing causative variants for all four loci.

Project description:BackgroundSingle nucleotide polymorphisms (SNPs) which capture a significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a crucial impact on the precision of parameter estimates, it also ensures that a desired level of statistical power can be reached. We study the design of experiments for fine-mapping of signals of a quantitative trait locus in such a target region.MethodsA multi-locus model allows to identify causative variants simultaneously, to state their positions more precisely and to account for existing dependencies. Based on the commonly applied SNP-BLUP approach, we determine the z-score statistic for locally testing non-zero SNP effects and investigate its distribution under the alternative hypothesis. This quantity employs the theoretical instead of observed dependence between SNPs; it can be set up as a function of paternal and maternal LD for any given population structure.ResultsWe simulated multiple paternal half-sib families and considered a target region of 1 Mbp. A bimodal distribution of estimated sample size was observed, particularly if more than two causative variants were assumed. The median of estimates constituted the final proposal of optimal sample size; it was consistently less than sample size estimated from single-SNP investigation which was used as a baseline approach. The second mode pointed to inflated sample sizes and could be explained by blocks of varying linkage phases leading to negative correlations between SNPs. Optimal sample size increased almost linearly with number of signals to be identified but depended much stronger on the assumption on heritability. For instance, three times as many samples were required if heritability was 0.1 compared to 0.3. An R package is provided that comprises all required tools.ConclusionsOur approach incorporates information about the population structure into the design of experiments. Compared to a conventional method, this leads to a reduced estimate of sample size enabling the resource-saving design of future experiments for fine-mapping of candidate variants.

Project description:The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

Dataset Information

Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study.

Publications

Generalization and fine mapping of red blood cell trait genetic associations to multi-ethnic populations: The PAGE Study.

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