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

Linda Kachuri; Angel C Y Mak; Donglei Hu; Celeste Eng; Scott Huntsman; Jennifer R Elhawary; Namrata Gupta; Stacey Gabriel; Shujie Xiao; Kevin L Keys; Akinyemi Oni-Orisan; José R Rodríguez-Santana; Michael A LeNoir; Luisa N Borrell; Noah A Zaitlen; L Keoki Williams; Christopher R Gignoux; Esteban González Burchard; Elad Ziv

doi:10.1038/s41588-023-01377-z

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

Nat Genet. 2023 Jun;55(6):952-963. doi: 10.1038/s41588-023-01377-z. Epub 2023 May 25.

Authors

Linda Kachuri^#^{1

2}, Angel C Y Mak^#³, Donglei Hu³, Celeste Eng³, Scott Huntsman³, Jennifer R Elhawary³, Namrata Gupta⁴, Stacey Gabriel⁴, Shujie Xiao⁵, Kevin L Keys^{3

6}, Akinyemi Oni-Orisan^{7

8

9}, José R Rodríguez-Santana¹⁰, Michael A LeNoir¹¹, Luisa N Borrell¹², Noah A Zaitlen^{13

14}, L Keoki Williams^{5

15}, Christopher R Gignoux^{16

17}, Esteban González Burchard^{18

19}, Elad Ziv^{20

21

22}

Affiliations

¹ Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
² Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.
³ Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
⁴ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁵ Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, MI, USA.
⁶ Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, USA.
⁷ Department of Clinical Pharmacy, University of California, San Francisco, San Francisco, CA, USA.
⁸ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
⁹ Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
¹⁰ Centro de Neumología Pediátrica, San Juan, Puerto Rico.
¹¹ Bay Area Pediatrics, Oakland, CA, USA.
¹² Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
¹³ Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁴ Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁵ Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA.
¹⁶ Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Chris.Gignoux@cuanschutz.edu.
¹⁷ Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. Chris.Gignoux@cuanschutz.edu.
¹⁸ Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. Esteban.Burchard@ucsf.edu.
¹⁹ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA. Esteban.Burchard@ucsf.edu.
²⁰ Department of Medicine, University of California, San Francisco, San Francisco, CA, USA. Elad.Ziv@ucsf.edu.
²¹ Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. Elad.Ziv@ucsf.edu.
²² Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA. Elad.Ziv@ucsf.edu.

^# Contributed equally.

Abstract

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Black or African American* / genetics
Genome-Wide Association Study
Hispanic or Latino* / genetics
Humans
Mexican Americans* / genetics
Phenotype
Polymorphism, Single Nucleotide
Transcriptome

Abstract

Publication types

MeSH terms

Grants and funding