The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here:

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Emma Ahlqvist

Emma Ahlqvist

Assistant researcher

Emma Ahlqvist

Genome-Wide association study of diabetic kidney disease highlights biology involved in glomerular basement membrane collagen


  • Rany M. Salem
  • Jennifer N. Todd
  • Niina Sandholm
  • Joanne B. Cole
  • Wei Min Chen
  • Darrell Andrews
  • Marcus G. Pezzolesi
  • Paul M.Keigue Mc
  • Linda T. Hiraki
  • Chengxiang Qiu
  • Viji Nair
  • Chen Di Liao
  • Jing Jing Cao
  • Erkka Valo
  • Suna Onengut-Gumuscu
  • Adam M. Smiles
  • Stuart J. Gurnaghan
  • Jani K. Haukka
  • Valma Harjutsalo
  • Eoin P. Brennan
  • Natalie Van Zuydam
  • Emma Ahlqvist
  • Ross Doyle
  • Tarunveer S. Ahluwalia
  • Maria Lajer
  • Maria F. Hughes
  • Jihwan Park
  • Jan Skupien
  • Athina Spiliopoulou
  • Andrew Liu
  • Rajasree Menon
  • Carine M.Kari Boustany
  • Hyun M. Kang
  • Robert G. Nelson
  • Ronald Klein
  • Barbara E. Klein
  • Kristine E. Lee
  • Xiaoyu Gao
  • Michael Mauer
  • Silvia Maestroni
  • Maria Luiza Caramori
  • Ian H.De Boer Caramori
  • Rachel G. Miller
  • Jingchuan Guo
  • Andrew P. Boright
  • David Tregouet
  • Beata Gyorgy
  • Janet K.Bergeon Snell
  • David M. Maahs
  • Leif C. Groop
  • Jose C. Florez

Summary, in English

Background Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown. Methods To identify genetic variants predisposing to diabetic kidney disease, we performed genomewide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function. Results Our GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition (BMP7) or renal biology (COLEC11 and DDR1). Conclusions The 16 diabetic kidney disease-associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.


  • Genomics, Diabetes and Endocrinology
  • EXODIAB: Excellence of Diabetes Research in Sweden

Publishing year







Journal of the American Society of Nephrology





Document type

Journal article


American Society of Nephrology


  • Endocrinology and Diabetes
  • Urology and Nephrology



Research group

  • Genomics, Diabetes and Endocrinology
  • LUDC (Lund University Diabetes Centre)


  • ISSN: 1046-6673