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

By Yao Hu, Adrienne M Stilp, Caitlin P. McHugh, Shuquan Rao, Deepti Jain, Xiuwen Zheng, John Lane, Sébastian Méric de Bellefon, Laura Raffield, Ming-Huei Chen, Lisa R Yanek, Marsha Wheeler, Yao Yao, Chunyan Ren, Jai Broome, Jee-Young Moon, Paul S. de Vries, Brian D. Hobbs, Quan Sun, Praveen Surendran, Jennifer A Brody, Thomas W Blackwell, Hélène Choquet, Kathleen Ryan, Ravindranath Duggirala, Nancy Heard-Costa, Zhe Wang, Nathalie Chami, Michael H Preuss, Nancy Min, Lynette Ekunwe, Leslie A Lange, Mary Cushman, Nauder Faraday, Joanne E. Curran, Laura Almasy, Kousik Kundu, Albert V. Smith, Stacey Gabriel, Jerome Rotter, Myriam Fornage, Donald M Lloyd-Jones, Vasan Ramachandran, Nicholas L Smith, Kari E North, Eric Boerwinkle, Lewis C. Becker, Joshua P. Lewis, Goncalo R. Abecasis, Lifang Hou, Jeffrey R O’Connell, Alanna C. Morrison, Terri H Beaty, Robert Kaplan, Adolfo Correa, John Blangero, Eric Jorgenson, Bruce M Psaty, Charles Kooperberg, Russell T. Walton, Benjamin P. Kleinstiver, Hua Tang, Ruth Loos, Nicole Soranzo, Adam S Butterworth, Deborah A. Nickerson, Stephen Rich, Braxton D Mitchell, Andrew D. Johnson, Paul L. Auer, Yun Li, Rasika A. Mathias, Guillaume Lettre, Nathan Pankratz, Cathy C Laurie, Cecelia A Laurie, Daniel E Bauer, Matthew Conomos, Alexander P Reiner, the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium

Posted 11 Dec 2020
medRxiv DOI: 10.1101/2020.12.09.20246736

Whole genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these newly discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3bp indel p.Lys2169del (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis [OMIM 194380], associated with higher MCHC. Stepwise conditional analysis identified 12 independent red cell trait-associated variants in the chromosome 11 region spanning the beta-globin genes. In gene-based rare variant aggregated association analysis, seven genes (HBA1/HBA2, HBB, TMPRSS6, G6PD, CD36, TFRC and SLC12A7) were associated with RBC traits, independently of known single variants. Several of the variants in HBB, HBA1, TMPRSS6, and G6PD represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Together, these results demonstrate the utility of WGS in ethnically-diverse population-based samples for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

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