Genome-wide polygenic score to predict chronic kidney disease across ancestries

Khan, A., Turchin, M. C., Patki, A., Srinivasasainagendra, V., Shang, N., Nadukuru, R., Jones, A. C., Malolepsza, E., Dikilitas, O., Kullo, I. J., Schaid, D. J., Karlson, E., Ge, T., Meigs, J. B., Smoller, J. W., Lange, C., Crosslin, D. R., Jarvik, G. P., Bhatraju, P. K., … Kiryluk, K. (2022). Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nature Medicine, 28(7), 1412–1420. https://doi.org/10.1038/s41591-022-01869-1
Authors:
Atlas Khan
Michael C. Turchin
Amit Patki
Vinodh Srinivasasainagendra
Ning Shang
Rajiv Nadukuru
Alana C. Jones
Edyta Malolepsza
Ozan Dikilitas
Iftikhar J. Kullo
Daniel J. Schaid
Elizabeth Karlson
Tian Ge
James B. Meigs
Jordan W. Smoller
Christoph Lange
David R. Crosslin
Gail P. Jarvik
Pavan K. Bhatraju
Jacklyn N. Hellwege
Paulette Chandler
Laura Rasmussen Torvik
Alex Fedotov
Cong Liu
Christopher Kachulis
Niall Lennon
Noura S. Abul-Husn
Judy H. Cho
Iuliana Ionita-Laza
Ali G. Gharavi
Wendy K. Chung
George Hripcsak
Chunhua Weng
Girish Nadkarni
Marguerite R. Irvin
Hemant K. Tiwari
Eimear E. Kenny
Nita A. Limdi
Krzysztof Kiryluk
Affiliated Authors:
Atlas Khan
Ning Shang
Alex Fedotov
Cong Liu
Iuliana Ionita-Laza
Ali G. Gharavi
Wendy K. Chung
George Hripcsak
Chunhua Weng
Krzysztof Kiryluk
Columbia Affiliation:
Subjects:
Apolipoprotein L1 (MeSH)
Renal Insufficiency, Chronic (MeSH)
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Publication Type:
Article
Unique ID:
10.1038/s41591-022-01869-1
PMID:
35710995
DOI:
10.1038/s41591-022-01869-1
Journal:
Nature Medicine
Publication Date:
Data Source:
Scopus
Source Link:
View Scopus Record
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