The genetic landscape of renal complications in type 1 diabetes

Niina Sandholm, Natalie Van Zuydam, Emma Ahlqvist, Thorhildur Juliusdottir, Harshal A. Deshmukh, N. William Rayner, Barbara Di Camillo, Carol Forsblom, Joao Fadista, Daniel Ziemek, Rany M. Salem, Linda T. Hiraki, Marcus Pezzolesi, David Trégouët, Emma Dahlström, Erkka Valo, Nikolay Oskolkov, Claes Ladenvall, M. Loredana Marcovecchio, Jason CooperFrancesco Sambo, Alberto Malovini, Marco Manfrini, Amy Jayne McKnight, Maria Lajer, Valma Harjutsalo, Daniel Gordin, Maija Parkkonen, The FinnDiane Study Group, Jaakko Tuomilehto, Valeriya Lyssenko, Paul M. McKeigue, Stephen S. Rich, Mary Julia Brosnan, Eric Fauman, Riccardo Bellazzi, Peter Rossing, Andrzej Krolewski, Andrew D. Paterson, The DCCT/EDIC Study Group, Jose C. Florez, Joel N. Hirschhorn, Alexander P. Maxwell, GENIE Consortium, David Dunger, Claudio Cobelli, Helen M. Colhoun, Leif Groop, Mark I. McCarthy, Per-Henrik Groop (Lead / Corresponding author), SUMMIT Consortium

    Research output: Contribution to journalArticlepeer-review

    101 Citations (Scopus)

    Abstract

    Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4×10(-3)). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associated variants. Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2×10(-5)) and the risk of type 2 diabetes (P=6.1×10(-4)) associated with the risk of diabetic kidney disease. We also found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1×10(-4)). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0×10(-6)), and pentose and glucuronate interconversions (P=3.0×10(-6)) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.

    Original languageEnglish
    Pages (from-to)557-574
    Number of pages18
    JournalJournal of the American Society of Nephrology
    Volume28
    Issue number2
    Early online date19 Sept 2016
    DOIs
    Publication statusPublished - Feb 2017

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