Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Abstract

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10−4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture

“…Our third major finding was that TWAS models trained in the ancestrally diverse GALA II/SAGE population identified significantly more trait-associated genes than models trained in GTEx and MESA when applied to GWAS results from the multi-ancestry PAGE study. GALA II/SAGE TWAS models benefit from having more similar allele frequency profiles and more accurate modeling of linkage disequilibrium, which is consistent with previous observations 11 , 12 , 40 that ancestry-concordant models improve the power for gene discovery in TWASs. Furthermore, over 40% of significantly associated TWAS genes detected using GALA II/SAGE models were not available in GTEx.…”

Investigating a causal role for neutrophil count onP. falciparumsevere malaria: a Mendelian Randomization study

“…Next, we found a marked difference between the genetic architecture of neutrophil count in people of African vs. European ancestry [38]. Interestingly, tissue expression for BCTs has been found to vary between ancestries as well [73], further showing the importance of conducting GWAS in diverse populations to improve the understanding of BCT biology. We investigated some of the GCTA-COJO index SNPs in relation to a biological mechanism that could explain how allele variation might affect neutrophil count levels in people of African ancestry.…”

Improved multi-ancestry fine-mapping identifiescis-regulatory variants underlying molecular traits and disease risk

“…We applied the Bonferroni correction to adjust the reported P-values with n=23,000. To validate our TWAS results, we compared them to five independent TWAS studies: Lu and Gopalan et al 36 , Kachuri et al 31 , Tapia et al 82 , Rowland et al 84 , and Wen et al 83 We released our cis -molQTL prediction weights to the public, which can be found at the Data Availability section. To test the association between T/PWAS chi-square statistics and genes’ constraint scores: pLI 75 , LOEUF 76 , EDS 77 , RVIS 78 , and s het 79 , we used linear regression adjusted for phenotype and study and reported one-sided P values.…”