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GWAS Study

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

Sandholm N, Cole JB, Nair V et al.

35763030 PubMed ID
GWAS Study Type
22134 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

SN
Sandholm N
CJ
Cole JB
NV
Nair V
SX
Sheng X
LH
Liu H
AE
Ahlqvist E
VZ
van Zuydam N
DE
Dahlström EH
FD
Fermin D
SL
Smyth LJ
SR
Salem RM
FC
Forsblom C
VE
Valo E
HV
Harjutsalo V
BE
Brennan EP
MG
McKay GJ
AD
Andrews D
DR
Doyle R
LH
Looker HC
NR
Nelson RG
PC
Palmer C
MA
McKnight AJ
GC
Godson C
MA
Maxwell AP
GL
Groop L
MM
McCarthy MI
KM
Kretzler M
SK
Susztak K
HJ
Hirschhorn JN
FJ
Florez JC
GP
Groop PH
Chapter II

Abstract

Summary of the research findings

Aims/hypothesis: Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.

6,705 European ancestry cases, 15,430 European ancestry controls

Chapter III

Study Statistics

Key metrics and study information

22134
Total Participants
GWAS
Study Type
No
Replicated
European
Ancestry
Chapter IV

AI-Generated Summary

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