CKDGen Consortium Meta-Analysis Data

Gorski, van der Most, Teumer, and Chu et al., 2017

https://pubmed.ncbi.nlm.nih.gov/28452372/

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value<5×10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR<0.05) genes and 127 significantly (FDR<0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until wholegenome sequencing becomes feasible in large samples.

Data set description

• Analyses are performed among participants of European ancestry

• Within each file, the data are presented as follows:

  • rsID: rs-identifier
  • allele1: coded allele
  • allele2: noncoded allele
  • freqA1: frequency of allele1 calculated from the 1000 Genomes Phase I version 3 (all reference panel available at http://csg.sph.umich.edu/abecasis/MaCH/download/1000G.2012-03-14.html)
  • beta: effect is given with 4 digits after the dot
  • se: 2nd GC corrected standard error is given with 4 digits after the dot
  • pval: double GC corrected p-value rounded to 3 significant digits
  • N: Number of subjects in analysis

Phenotypes

• eGFRcrea overall, Nmax=110,527
• eGFRcys overall, Nmax=24,061

Citation

Reference The preferred citation is as follows:

• Gorski M, van der Most PJ, Teumer A, et al. 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function. Sci Rep 7, 45040 (2017).

Files

• CKDGen_1000Genomes_DiscoveryMeta_eGFRcrea_overall.csv.gz
• CKDGen_1000Genomes_DiscoveryMeta_eGFRcys_overall.csv.gz