Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.

Erkka Valo Joanne B ColeViji NairXin Sheng Hongbo Liu Emma Ahlqvist Natalie R van Zuydam Erika B ParenteDamian FerminLaura Jane Smyth Rany M Salem Carol M Forsblom Erkka Valo Joanne B Cole Eoin P Brennan Gareth J McKay Darrell Andrews Ross DoyleHelen C LookerRobert G Nelson Colin Neil Alexander Palmer Amy Jayne McKnight Catherine Godson Alexander Peter Maxwell Leif C GroopMark I McCarthyMatthias Kretzler Katalin SusztákJoel N HirschhornJose C Florez Per-Henrik Groopnull null

Published in: Diabetologia (2022)

The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).

Keyphrases

systematic review
genome wide
type diabetes
meta analyses
dna methylation
healthcare
case control
randomized controlled trial
glycemic control
copy number
skeletal muscle