Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

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  • Odessica Hughes
  • Amy R. Bentley
  • Charles E. Breeze
  • Francois Aguet
  • Xiaoguang Xu
  • Girish Nadkarni
  • Quan Sun
  • Bridget M. Lin
  • Thomas Gilliland
  • Mariah C. Meyer
  • Jiawen Du
  • Laura M. Raffield
  • Holly Kramer
  • Robert W. Morton
  • Mateus H. Gouveia
  • Elizabeth G. Atkinson
  • Adan Valladares-Salgado
  • Niels Wacher-Rodarte
  • Nicole D. Dueker
  • Xiuqing Guo
  • Yang Hai
  • Adebowale Adeyemo
  • Lyle G. Best
  • Jianwen Cai
  • Guanjie Chen
  • Michael Chong
  • Ayo Doumatey
  • James Eales
  • Mark O. Goodarzi
  • Eli Ipp
  • Marguerite Ryan Irvin
  • Minzhi Jiang
  • Alana C. Jones
  • Charles Kooperberg
  • Jose E. Krieger
  • Ethan M. Lange
  • Matthew B. Lanktree
  • James P. Lash
  • Paulo A. Lotufo
  • Vy Thi Ha My
  • Jesús Peralta-Romero
  • Lihong Qi
  • Leslie J. Raffel
  • Stephen S. Rich
  • Erik J. Rodriquez
  • Eduardo Tarazona-Santos
  • Kent D. Taylor
  • Jason G. Umans
  • Jia Wen
  • Bessie A. Young
  • Zhi Yu
  • Ying Zhang
  • Yii Der Ida Chen
  • Tanja Rundek
  • Jerome I. Rotter
  • Miguel Cruz
  • Myriam Fornage
  • Maria Fernanda Lima-Costa
  • Alexandre C. Pereira
  • Guillaume Paré
  • Pradeep Natarajan
  • Shelley A. Cole
  • April P. Carson
  • Leslie A. Lange
  • Yun Li
  • Eliseo J. Perez-Stable
  • Ron Do
  • Fadi J. Charchar
  • Maciej Tomaszewski
  • Josyf C. Mychaleckyj
  • Charles Rotimi
  • Andrew P. Morris
  • Nora Franceschini

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10−8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Original languageEnglish
Article number100468
JournalCell Genomics
Volume4
Issue number1
Number of pages13
ISSN2666-979x
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 2023 The Authors

    Research areas

  • admixed populations, chronic kidney disease, eGFR, expression quantitative trait locus, fine-mapping, genome-wide association study, kidney function, multi-ancestry, polygenic scores

ID: 378809215