Genome-wide polygenic score to predict chronic kidney disease across ancestries
Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-w...
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Published in | Nature medicine Vol. 28; no. 7; pp. 1412 - 1420 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.07.2022
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 1078-8956 1546-170X 1546-170X |
DOI | 10.1038/s41591-022-01869-1 |
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Summary: | Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining
APOL1
risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (
n
= 97,050), 6 cohorts of African ancestry (
n
= 14,544), 4 cohorts of Asian ancestry (
n
= 8,625) and 2 admixed Latinx cohorts (
n
= 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the
APOL1
risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.
A new study generated and optimized a polygenic score for chronic kidney disease with reproducible performance across 15 cohorts of different ancestries, and identified potentially clinically relevant thresholds with predicted effects comparable to having a family history of the disease. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Author Contributions Statement Conceptualization, A.K., K.K.; methodology and genetic data analysis, A.K., K.K., M.C.T., A.P., V.S., R.N., A.C.J., E.M., C.K., N.L., I.I.L, T.G., M.R.I., H.K.T., E.E.K.; e-phenotyping: N.S., C.L., G.H., C.W., G.N., eMERGE-III data contributions: O.D., I.J.K., D.J.S, E.K., J.B.M., J.W.S., C.L., D.R.C., G.P.J., P.K.B., J.N.H., P.C., L.R.T., A.G.G., W.K.C., G.H., C.W., BioMe data contributions: G.N., J.H.C., N.S.A-H., E.E.K., UAB data contributions: M.R.I., H.K.T., N.A.L; project administration A.K., A.F., overall supervision K.K., writing-original draft, A.K., K.K.; manuscript review and editing, A.K, N.S., E.M., A.G.G., T.G., J.B.M, D.R.C., J.N.H., I.I.L, G.H., M.R.I., H.K.T., E.E.K., N.A.L., and K.K. |
ISSN: | 1078-8956 1546-170X 1546-170X |
DOI: | 10.1038/s41591-022-01869-1 |