Aldehyde dehydrogenase 2 genotype in type 1 diabetes mellitus

FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease

Differential expressed genes are more likely to have variants associated with disease. A new tool, fitSNP, prioritizes candidate SNPs from association studies.

Background

Candidate single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWASs) were often selected for validation based on their functional annotation, which was inadequate and biased. We propose to use the more than 200,000 microarray studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs.

Results

We analyzed all human microarray studies from the Gene Expression Omnibus, and calculated the observed frequency of differential expression, which we called differential expression ratio, for every human gene. Analysis conducted in a comprehensive list of curated disease genes revealed a positive association between differential expression ratio values and the likelihood of harboring disease-associated variants. By considering highly differentially expressed genes, we were able to rediscover disease genes with 79% specificity and 37% sensitivity. We successfully distinguished true disease genes from false positives in multiple GWASs for multiple diseases. We then derived a list of functionally interpolating SNPs (fitSNPs) to analyze the top seven loci of Wellcome Trust Case Control Consortium type 1 diabetes mellitus GWASs, rediscovered all type 1 diabetes mellitus genes, and predicted a novel gene (KIAA1109) for an unexplained locus 4q27. We suggest that fitSNPs would work equally well for both Mendelian and complex diseases (being more effective for cancer) and proposed candidate genes to sequence for their association with 597 syndromes with unknown molecular basis.

Conclusions

Our study demonstrates that highly differentially expressed genes are more likely to harbor disease-associated DNA variants. FitSNPs can serve as an effective tool to systematically prioritize candidate SNPs from GWASs.

Metabolism genes are among the differentially expressed ones observed in lymphomononuclear cells of recently diagnosed type 1 diabetes mellitus patients

The large-scale differential gene expression in lymphomononuclear cells of six patients with recently diagnosed type), and six normal individuals matched to patients for sex and age were studied. Glass slides containing 4608 cDNAs from the IMAGE library were spotted using robotic technology. Statistical analysis was carried out by the SAM program, and gene function assessed by the FATIGO program. Thirty differentially expressed genes (21 induced and 9 repressed) were disclosed when DM-1 patients were compared with controls. Although presenting with distinct biological function, most of the induced or repressed genes were related with protein, phosphate, DNA, RNA, carboxylic acid, and fatty acid metabolism. Although some of these genes have been previously associated with the pathogenesis of T1DM, many other genes were identified for further studies.

Meta-analysis of three diabetes population studies: association of inactive ALDH2 genotype with maternal inheritance of diabetes

To date, there have been three population studies that examined the association of mitochondrial aldehyde dehydrogenase 2 (ALDH2) genotype with inheritance of diabetes. Here, we summarize the results by meta-analysis. The study 1 consisted of 212 type 2 diabetics who did not have renal failure. The study 2 consisted of 73 type 2 diabetics who had renal failure. The study 3 consisted of 230 type 1 diabetics. In total, 515 subjects were examined for the association of ALDH2 genotype with inheritance of diabetes. Out of 515 subjects, 307 (60%) had active ALDH2 (ALDH2*1/ALDH2*1) and 208 (40%) had inactive ALDH2 (175 had ALDH2*1/ALDH2*2 and 33 had ALDH2*2/ALDH2*2). As for family history, 25 subjects (8.1%) in the active ALDH2 group had a diabetic mother, compared with 43 (20.6%) in the inactive ALDH2 group. Twenty-nine subjects (9.4%) in the active ALDH2 group had a diabetic father, compared with 14 (6.7%) in the inactive ALDH2 group. The percentage of diabetic mother was higher in the inactive ALDH2 group, the differences were statistically significant (P < 0.0001). We hence speculate that diabetic patients with inactive ALDH2 genotype may have underlying background of mitochondria etiology, thereby showing maternal trait of diabetes inheritance. In conclusion, meta-analysis using three diabetes population studies strongly confirmed the association between ALDH2 inactivity and maternal inheritance.