- Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics. - The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. - If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. - In the average adult, 200 billion red blood cells (RBCs) are generated daily from hematopoietic stem cells in the bone marrow. - First, previously published RBC trait genome-wide association study (GWAS) populations have mostly been ancestrally homogeneous [31–39].. - Self-reported race/ethnicity in the total study population was approximately 20% African American, 30% Hispanic/Latino, and 40% European American (Table S3).. - Combined-phenotype analyses. - SNP associations with the combined phenotype multi- ethnic meta-analysis exceeded genome-wide significance at 39 loci (p <. - (n = 37) exceeded genome-wide significance for the combined-phenotype lead SNP in two or more traits.. - 0.8 in the combined MEGA-genotyped study population).. - Only one of nine associations was in a trait pair exhibiting moderate correlation: HGB and RBCC (ρ = 0.68) exhibit- ing opposite directions of effect for rs9924561, the lead SNP in the HBA1/2 region on chromosome 16.. - 3 Mb of the lead SNP [48]. - Of note, the HBA1/2 locus demonstrated ancestry spe- cificity (i.e., the lead SNP was monomorphic in one or more ancestries) at 11 of 14 conditionally independent SNPs (Fig. - Low-frequency and rare alleles exhibit larger magnitude of effect across RBC traits in the total multi- ethnic study population. - Trait-specific sensitivity analyses identified two previously- unreported variants exceeded genome-wide significance for a single RBC trait in the univariate analyses, yet did not meet genome-wide significance in the combined pheno- type. - 1%) in all popu- lations, only meeting the inclusion criteria in the MEGA pooled sample and one study sub-population (Figure S4, Table S7). - Ancestry-specific sensitivity analyses did not un- cover any significant association signals that did not achieve genome-wide significance in the overall study population.. - When adjusting for esv3637548 deletion dosage in the MEGA-genotyped subgroup, we observed evidence of both attenuation and strengthening of effect at otherwise conditionally independent lead SNPs at the HBA1/2 locus (Table S8). - All other PAGE lead SNPs in the HBA1/2 re- gion either did not pass QC or imputation criteria for the custom array used in that study, or had p >. - 1E-07 in the primary analysis.. - Ancestry-specific generalization varied by trait, with the highest proportion of generalization oc- curring in the European-ancestry sub-population and the lowest occurring in African Americans, which may be due to power differences to detect associations by ancestry.. - 1%) in the European-ancestry GTEx population and had available information in whole blood, liver, spleen, and/or thyroid tissues. - 1% in the GTEx study population and hence could not be evaluated for cis-eQTLs.. - Here, we examine the benefits of identifying and characterizing RBC trait associ- ations in the ancestrally diverse PAGE study population using a combined-phenotype approach. - However, sample sizes of previous RBC trait GWAS suggest that many loci with modest effects and lead SNPs in the low to common allele frequency range in European or East Asian populations have already been identified. - However, rs8051004 was reported as “monoallelic” in spleen tissue in GTEx, despite having a 10% allele frequency in PAGE African Americans and 12 and 11% in the 1000G African and East Asian super- populations, respectively. - RBCs enucleate in the bone marrow prior to entering circulation, with no nuclear transcription and extremely limited translation occurring in mature RBCs. - RBC trait values that exceeded four standard deviations from the mean of the trait in the overall study population were excluded, mirroring protocols established by prior GWAS [28, 45]. - Pairwise correlation coefficients were cal- culated in the MEGA-genotyped analytic subgroup (see below) adjusting for all the covariates used in univariate regression analysis, specifically age at blood draw, sex, study site or region, and ancestral principal components.. - The adaptive aspect of the test lies in the potential for dif- ferent γ values to yield the maximal SPU across SNPs, maintaining power compared to a test with only a single possible alternative hypothesis.. - Given the number of known ancestry-specific variants driving blood trait values, it was necessary to ensure that all self-reported race/ethnic groups be evaluated individually for associations that may be undetectable in the larger population. - Al- though RBC traits are expected to share genetic under- pinnings, particularly within pairs of correlated traits, association signals which were trait-specific in the well- powered UK BioBank blood trait GWAS suggest that each trait has its own unique suite of associations [12].. - Finally, in an attempt to examine the influence of the previously identified 3.7 kb structural variant esv3637548 in the HBA1/2 region of chromosome 16, we also ad- justed for esv3637548 dosage (r 2 = 0.86) in the MEGA- genotyped subgroup [28]. - The duplication was not able to be imputed, and the deletion only met im- putation quality criteria in the MEGA-genotyped study population, hence esv3637548 could not be evaluated within the entire study population in which this variant may be present. - All SNPs located within 500 kb of a variant previously reported for any RBC trait were evaluated for evidence of association in the combined-phenotype analysis as well as each individual trait analysis. - Iterative conditional analysis was performed to identify all independent, genome-wide-significant combined- phenotype lead SNPs as described above. - Additional rounds of conditional analyses were performed as an it- erative process until no genome-wide-significant SNPs remained in the combined phenotype analysis.. - Manhattan and Quantile-Quantile plots for individual RBC traits in the total study population. - Locus-Zoom plot of the association between MCH (A) and MCV (B) and rs145548796 in the total MEGA study population. - Twelve supplemental tables supporting findings reported in the main text. - GWAS: Genome-wide association study. - None of the funding bodies described herein played a role in the design of the study. - Genotype data quality control and quality assurance services were provided by the Genetic Analysis Center in the Biostatistics Department of the Univer- sity of Washington, through support provided by the CIDR contract. - All participating studies listed in the methods section obtained Institutional Review Board approval and written informed consent from all participants.. - Kellert L, Martin E, Sykora M, Bauer H, Gussmann P, Diedler J, et al. - Barlas RS, Honney K, Loke YK, McCall SJ, Bettencourt-Silva JH, Clark AB, et al.. - Genetic and environmental influences on the size and number of cells in the blood. - 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