We have investigated 11,152 SNPs for association with diabetic nephropathy in individuals with type 2 diabetes recruited in Northern Ireland. Genotyping utilised a commercial panel that has demonstrated highly accurate and reproducible results, employing strict quality control parameters. Focusing on nsSNPs is an attractive approach since less common variants that may influence the risk of disease are directly genotyped. None of the available genome-wide panels that incorporate less than a million markers are optimised to capture nsSNPs. For example, the Affymetrix 500 K chip covers only 65% of the common nsSNPs (≥5% MAF) and 24% of the rarer variants (<5% MAF) present on the HNS12 panel with an r2 > 0.8 in the CEU population (Evans et al. 2008). The Ensembl genome browser contains 97,571 nsSNPs (www.ensembl.org, accessed 08/06/09) with a recent report describing 133,505 coding SNPs in the human genome (Reumers et al. 2008), although it should be noted that many of these are not validated.
The top ranked SNPs, with respect to the adjusted P value, were located in several biological and positional candidate genes for diabetic nephropathy. rs1543547 demonstrated the most evidence for association (adjusted Pgenotype = 4 × 10−5, Pallelic = 2 × 10−5) based on comparisons of genotype and allele frequencies between cases and controls. This SNP is located at 6q25.1 in the retinoic acid early transcript 1L gene. RAET1L spans approximately 5 kb and is a member of the RAET1 family of MHC class I-related genes located within the 180 kb cluster on chromosome 6q24.2-6q25.3. Fine mapping would be complex as genes within this region are very similar; for example, RAET1L reveals approximately 97% identity with ULBP2 (Radosavljevic et al. 2002). Information is sparse regarding the precise function of this gene, however RAET1 genes encode glycoproteins that are anchored to the membrane via glycosylphosphatidylinositol linkage (Radosavljevic et al. 2002).
Within the top ranked group, two nsSNPs were clustered in the PLXND1 gene (rs2285372, rs2301572) at 3q21.3. PLXND1 is expressed in human vascular endothelial cells and is important for cardiovascular development (Gitler et al. 2004). Eight of the top ranked 32 SNPs were located at 6p21.3 with three nsSNPs clustered within the ubiquitin D (UBD) gene at 6p21.3 (rs2076487, rs2076486, rs2076484).
Several differences were observed when comparing our genotype data to the higher-throughput information recorded in dbSNP (www.ncbi.nlm.nih.gov/snp). Two SNPs recorded in dbSNP as monomorphic (rs2076486, rs2076848) were observed with minor allele frequencies of 3%. SNP rs1543547 was observed with 42% minor allele frequency in our population compared to the 7% reported for the HapMap CEU population. However, our results for rs1543547 are similar to those reported by Perlegen (ss24453248) where the T allele was observed at 46% in 24 samples from the Coriell Cell Repository that were primarily of European descent. Linkage disequilibrium (r2 > 0.8) was observed between: rs2076486, rs2076484, and rs2076487; rs2301572 and rs2285372; rs11755943 and rs10452600. These relationships were exploited by only selecting tag SNPs for further genotyping,
Ideally our results would be replicated in a larger, phenotypically similar group of individuals from the same geographical region; such a collection is not available within the British Isles. As there are shared pathophysiological mechanisms contributing to the development of diabetic kidney disease (for example, mesangial expansion and glomerular basement membrane thickening) in those with type 1 and type 2 diabetes (Caramori and Mauer 2003; Tsilibary 2003; Fioretto and Mauer 2007), we also genotyped the top ranked variants to evaluate association with type 1 diabetes. This larger case-control collection (n = 1,467) recruited individuals from Ireland in conjunction with a UK multicentre collection (Genetics Of Kidneys in Diabetes UK) that was specifically designed to investigate genetic risk factors for diabetic nephropathy (McKnight et al. 2009b). A tag SNP approach was taken where strong linkage disequilibrium was observed, resulting in 28 SNPs actually genotyped in the follow-up study. Although a strong association was not observed with nephropathy in type 1 diabetes, two SNPs in 6p21.3 (rs2076484, rs9380215, P = 0.03) warrant further investigation.
It is possible that the results from individuals with type 2 diabetes in Table 2 represent type 1 errors, or that genetic variants associated with nephropathy in type 1 diabetes may differ from those involved with nephropathy in type 2 diabetes. Robust quality control procedures were employed and several SNPs in close proximity to each other were associated with diabetic nephropathy in biologically plausible genes. Replication and fine mapping in large populations of phenotypically similar individuals are required to investigate further the top ranked variants.
Non-synonymous SNPs contribute to inter-individual differences, the variation within biological networks, genetic susceptibility to disease, and prediction of drug responsiveness (Karchin et al. 2005). We have completed a targeted genome-wide scan and revealed several novel SNPs in genes that are worthy of further investigation; validation studies are essential to confirm the importance of these findings.