|Title||Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.|
|Publication Type||Journal Article|
|Year of Publication||2021|
|Authors||Lin BM, Grinde KE, Brody JA, Breeze CE, Raffield LM, Mychaleckyj JC, Thornton TA, Perry JA, Baier LJ, Fuentes Lde Las, Guo X, Heavner BD, Hanson RL, Hung Y-J, Qian H, Hsiung CA, Hwang S-J, Irvin MR, Jain D, Kelly TN, Kobes S, Lange L, Lash JP, Li Y, Liu X, Mi X, Musani SK, Papanicolaou GJ, Parsa A, Reiner AP, Salimi S, Sheu WH-H, Shuldiner AR, Taylor KD, Smith AV, Smith JA, Tin A, Vaidya D, Wallace RB, Yamamoto K, Sakaue S, Matsuda K, Kamatani Y, Momozawa Y, Yanek LR, Young BA, Zhao W, Okada Y, Abecasis G, Psaty BM, Arnett DK, Boerwinkle E, Cai J, Der Chen IYii-, Correa A, L Cupples A, He J, Kardia SLr, Kooperberg C, Mathias RA, Mitchell BD, Nickerson DA, Turner ST, Vasan RS, Rotter JI, Levy D, Kramer HJ, Köttgen A, Rich SS, Lin D-Y, Browning SR, Franceschini N|
|Date Published||2021 Jan|
BACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.
METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.
FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.
INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
|PubMed Central ID||PMC7804602|
|Grant List||R01 HL120393 / HL / NHLBI NIH HHS / United States |
R01 DK117445 / DK / NIDDK NIH HHS / United States
HHSN268201800001C / HL / NHLBI NIH HHS / United States
R21 HL123677 / HL / NHLBI NIH HHS / United States
R01 MD012765 / MD / NIMHD NIH HHS / United States
R01 HL117626 / HL / NHLBI NIH HHS / United States
R01 HL149683 / HL / NHLBI NIH HHS / United States
K01 AG059898 / AG / NIA NIH HHS / United States
R01 HL131136 / HL / NHLBI NIH HHS / United States
R01 HG009974 / HG / NHGRI NIH HHS / United States
R21 HL140385 / HL / NHLBI NIH HHS / United States