A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

Natalie R van Zuydam, Emma Ahlqvist, Niina Sandholm, Harshal Deshmukh, N William Rayner, Moustafa Abdalla, Claes Ladenvall, Daniel Ziemek, Eric Fauman, Neil R Robertson, Paul M McKeigue, Erkka Valo, Carol Forsblom, Valma Harjutsalo, Annalisa Perna, Erica Rurali, M Loredana Marcovecchio, Robert P Igo, Rany M Salem, Norberto PericoMaria Lajer, Annemari Käräjämäki, Minako Imamura, Michiaki Kubo, Atsushi Takahashi, Xueling Sim, Jianjun Liu, Rob M van Dam, Guozhi Jiang, Claudia H T Tam, Andrea O Y Luk, Heung Man Lee, Cadmon K P Lim, Cheuk Chun Szeto, Wing Yee So, Juliana C N Chan, Su Fen Ang, Rajkumar Dorajoo, Ling Wang, Tan Si Hua Clara, Amy-Jayne McKnight, Seamus Duffy, Marcus G Pezzolesi, Genie Consortium, Michel Marre, Beata Gyorgy, Samy Hadjadj, Linda T Hiraki, Tarunveer S Ahluwalia, Alexander P Maxwell, FINNDIANE Study centres

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Abstract

Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined (T1D+T2D) GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 diabetic subjects (and 18,582 DKD cases).Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, p=4.5×10-8) associated with 'microalbuminuria' in European T2D cases. However, no replication of this signal was observed in Asian subjects with T2D, or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously-reported DKD signals, except for those at UMOD and PRKAG2, both associated with 'eGFR'.We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk-variant discovery for DKD.

Original languageEnglish
Pages (from-to)1414-1427
JournalDiabetes
Volume67
Issue number7
Early online date29 Apr 2018
DOIs
Publication statusEarly online date - 29 Apr 2018

Keywords

  • diabetes
  • kidney
  • genetic
  • association
  • nephropathy
  • SNP

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    van Zuydam, N. R., Ahlqvist, E., Sandholm, N., Deshmukh, H., Rayner, N. W., Abdalla, M., Ladenvall, C., Ziemek, D., Fauman, E., Robertson, N. R., McKeigue, P. M., Valo, E., Forsblom, C., Harjutsalo, V., Perna, A., Rurali, E., Marcovecchio, M. L., Igo, R. P., Salem, R. M., ... FINNDIANE Study centres (2018). A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes. Diabetes, 67(7), 1414-1427. https://doi.org/10.2337/db17-0914