Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011860 (type 2 diabetes)
 57,723 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5-5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.
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PMID:Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion. 2326 89

Objectives: The identification of the potential molecule targets for subsyndromal symptomatic depression (SSD) is critical for improving the effective clinical treatment on the mental illness. In the current study, we mined the genome-wide expression profiling and investigated the novel biological pathways associated with SSD.Methods: Expression of differentially expressed genes (DEGs) were analysed with microarrays of blood tissue cohort of eight SSD patients and eight healthy subjects. The gene co-expression is calculated by WGCNA, an R package software. The function of the genes was annotated by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.Results: We identified 11 modules from the 9,427 DEGs. Three co-expression modules (blue, cyan and red) showed striking correlation with the phenotypic trait between SSD and healthy controls. Gene ontology and KEGG pathway analysis demonstrated that the function of these three modules was enriched with the pathway of inflammatory response and type II diabetes mellitus. Finally, three hub genes, NT5DC1, SGSM2 and MYCBP, were identified from the blue module as significant genes.Conclusions: This first blood gene expression study in SSD observed distinct patterns between cases and controls which may provide novel insight into understanding the molecular mechanisms of SSD.
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PMID:Weighted gene co-expression network analysis identifies specific modules and hub genes related to subsyndromal symptomatic depression. 3048 89