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. 2010 Aug;128(2):195-204.
doi: 10.1007/s00439-010-0842-3. Epub 2010 Jun 8.

Candidate genes for non-diabetic ESRD in African Americans: a genome-wide association study using pooled DNA

Affiliations

Candidate genes for non-diabetic ESRD in African Americans: a genome-wide association study using pooled DNA

Meredith A Bostrom et al. Hum Genet. 2010 Aug.

Abstract

African Americans have increased susceptibility to non-diabetic (non-DM) forms of end-stage renal disease (ESRD) and extensive evidence supports a genetic contribution. A genome-wide association study (GWAS) using pooled DNA was performed in 1,000 African Americans to detect associated genes. DNA from 500 non-DM ESRD cases and 500 non-nephropathy controls was quantified using gel electrophoresis and spectrophotometric analysis and pools of 50 case and 50 control DNA samples were created. DNA pools were genotyped in duplicate on the Illumina HumanHap550-Duo BeadChip. Normalization methods were developed and applied to array intensity values to reduce inter-array variance. Allele frequencies were calculated from normalized channel intensities and compared between case and control pools. Three SNPs had p values of <1.0E-6: rs4462445 (ch 13), rs4821469 (ch 22) and rs8077346 (ch 17). After normalization, top scoring SNPs (n = 65) were genotyped individually in 464 of the original cases and 478 of the controls, with replication in 336 non-DM ESRD cases and 363 non-nephropathy controls. Sixteen SNPs were associated with non-DM ESRD (p < 7.7E-4, Bonferroni corrected). Twelve of these SNPs are in or near the MYH9 gene. The four non-MYH9 SNPs that were associated with non-DM ESRD in the pooled samples were not associated in the replication set. Five SNPs that were modestly associated in the pooled samples were more strongly associated in the replication and/or combined samples. This is the first GWAS for non-DM ESRD in African Americans using pooled DNA. We demonstrate strong association between non-DM ESRD in African Americans with MYH9, and have identified additional candidate loci.

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Figures

Fig. 1
Fig. 1
Scheme for the normalization of Illumina BeadArray intensity data
Fig. 2
Fig. 2
Q–Q plots of the t test p value data quartiles compared to a normal distribution. Plots and corresponding inflation values are shown for both normalization methods
Fig. 3
Fig. 3
Comparison of relative allele frequency (RAF) between individual genotyping and pooling of samples from one control pool of 50 individuals using 166,033 SNPs
Fig. 4
Fig. 4
Log10(1/p) of the top 5,000 SNPs from the two sample t test with equal and unequal variance using the “log array mean” dataset

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