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 ); 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 ). 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.

Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

“…[6][7][8] With improved imputation, increased sample sizes, and deeper interrogation of coding regions of the genome, additional common variants associated with RBC indices with progressively smaller effect sizes and coding variants of larger effect with lower minor allele frequency (MAF) have been identified. [9][10][11][12][13][14][15][16][17][18][19] However, the full allelic spectrum (e.g., lower frequency non-coding variants, indels, structural variants) that explain the genetic architecture of complex traits remains incomplete. 9 In addition, non-European populations (including admixed U.S. minority populations such as African Americans and Hispanics/Latinos) have been under-represented in these studies.…”

“…Emerging studies with greater inclusion of East Asian, African, and Hispanic ancestry populations have identified ancestry-specific variants associated with RBC quantitative traits. [15][16][17]20,21 These may account, at least in part, for inter-population differences in RBC indices as well as ethnic disparities in rates of hematologic and other related chronic diseases. 18,22 Whole-genome sequencing (WGS) data have been generated through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program in very large and ethnically diverse population samples with existing hematologic laboratory measures.…”

Whole genome sequencing association analysis of quantitative red blood cell phenotypes: the NHLBI TOPMed program

“…The alpha-globin gene region on chromosome 16p13.3 contains a large, 3.7kb structural variant common among African ancestry individuals known to be highly significantly associated with all RBC traits 15,18 . This large copy number variant is not well-tagged by SNVs in the region.…”

“…Since RBCs play a key role in pathogen invasion and defense, associated quantitative trait loci may be relatively isolated to a particular ancestral population due to local evolutionary selective pressures and population history. Emerging studies with greater inclusion of East Asian, African, and Hispanic ancestry populations have identified ancestry-specific variants associated with RBC quantitative traits 15–17,20,21 . These may account, at least in part, for inter-population differences in RBC indices as well as ethnic disparities in rates of hematologic and other related chronic diseases 18,22 .…”

“…Early GWAS identified common genetic variants with relatively large effects associated with RBC indices 6,7,8 . With improved imputation, increased sample sizes and deeper interrogation of coding regions of the genome, additional common variants associated with RBC indices with progressively smaller effect sizes and coding variants of larger effect with lower minor allele frequency (MAF) have been identified [9][10][11][12][13][14][15][16][17][18][19] . However, the full allelic spectrum (e.g., lower frequency non-coding variants, indels, structural variants) that explain the genetic architecture of complex traits remains incomplete 9 .…”