Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011854 (type 1 diabetes)
 20,749 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We have used genomic analysis to characterize a region of the central major histocompatibility complex (MHC) spanning approximately 300 kilobases (kb) between TNF and HLA-B. This region has been suggested to carry genetic factors relevant to the development of autoimmune diseases such as myasthenia gravis (MG) and insulin dependent diabetes mellitus (IDDM). Genomic sequence was analyzed for coding potential, using two neural network programs, GRAIL and GeneParser. A genomic probe, JAB, containing putative coding sequences (PERB11) located 60 kb centromeric of HLA-B, was used for northern analysis of human tissues. Multiple transcripts were detected. Southern analysis of genomic DNA and overlapping YAC clones, covering the region from BAT1 to HLA-F, indicated that there are at least five copies of PERB11, four of which are located within this region of the MHC. The partial cDNA sequence of PERB11 was obtained from poly-A RNA derived from skeletal muscle. The putative amino acid sequence of PERB11 shares approximately 30% identity to MHC class I molecules from various species, including reptiles, chickens, and frogs, as well as to other MHC class I-like molecules, such as the IgG FcR of the mouse and rat and the human Zn-alpha 2-glycoprotein. From direct comparison of amino acid sequences, it is concluded that PERB11 is a distinct molecule more closely related to nonmammalian than known mammalian MHC class I molecules. Genomic sequence analysis of PERB11 from five MHC ancestral haplotypes (AH) indicated that the gene is polymorphic at both DNA and protein level. The results suggest that we have identified a novel polymorphic gene family with multiple copies within the MHC.
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PMID:A new polymorphic and multicopy MHC gene family related to nonmammalian class I. 792 38

BAT1 (D6S81E, UAP56) lies in the central MHC between TNF and HLA-B, a region containing genes that affect susceptibility to immunopathologic disorders. BAT1 protein may be directly responsible for the genetic association, as antisense studies show it can down-regulate inflammatory cytokines. Here we investigate polymorphisms at positions -22 and -348 relative to the BAT1 transcription start site. DNA samples from healthy donors were used to confirm haplotypic associations with the type 1 diabetes-susceptible 8.1 ancestral haplotype (AH; HLA-A1,B8,BAT1-22*C,BAT1-348*C,DR3 ) and the diabetes-resistant 7.1 AH (HLA-A3,B7,BAT1-22*G,BAT1-348*T,DR15). Alleles carried at BAT1-22 and -348 were in linkage disequilibrium. Electrophoretic mobility shift assays using nuclear proteins from T-cells (Jurkat and HT2), monocytes (THP1, U937) and epithelial cells (HeLa and MDA468) demonstrated DNA : protein complexes binding oligonucleotides spanning positions -22 and -348 on the 7.1 AH only. Competition assays, supershifts and molecular weight determinations suggest the complexes include the transcription factors YY1 (at -348) and Oct1 (at -22). Promoter activity was demonstrated using 520 bp and 336 bp fragments cloned from immediately upstream of the transcription start site and carrying all combinations of -22 and -348 alleles, suggesting an unidentified non-polymorphic sequence within 336 bp of the start site drives transcription. The 520 bp fragment of the BAT1 promoter cloned from the 8.1 AH was slightly less efficient than the equivalent from the 7.1 AH, whilst the reverse was observed with 336 bp fragments. This suggests BAT1 transcription on the 7.1 AH is modified by interactions involving DNA flanking positions -22 and -348.
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PMID:Polymorphisms at positions -22 and -348 in the promoter of the BAT1 gene affect transcription and the binding of nuclear factors. 1502 69

Interactions among multiple genes across the genome may contribute to the risks of many complex human diseases. Whole-genome single nucleotide polymorphisms (SNPs) data collected for many thousands of SNP markers from thousands of individuals under the case-control design promise to shed light on our understanding of such interactions. However, nearby SNPs are highly correlated due to linkage disequilibrium (LD) and the number of possible interactions is too large for exhaustive evaluation. We propose a novel Bayesian method for simultaneously partitioning SNPs into LD-blocks and selecting SNPs within blocks that are associated with the disease, either individually or interactively with other SNPs. When applied to homogeneous population data, the method gives posterior probabilities for LD-block boundaries, which not only result in accurate block partitions of SNPs, but also provide measures of partition uncertainty. When applied to case-control data for association mapping, the method implicitly filters out SNP associations created merely by LD with disease loci within the same blocks. Simulation study showed that this approach is more powerful in detecting multi-locus associations than other methods we tested, including one of ours. When applied to the WTCCC type 1 diabetes data, the method identified many previously known T1D associated genes, including PTPN22, CTLA4, MHC, and IL2RA. The method also revealed some interesting two-way associations that are undetected by single SNP methods. Most of the significant associations are located within the MHC region. Our analysis showed that the MHC SNPs form long-distance joint associations over several known recombination hotspots. By controlling the haplotypes of the MHC class II region, we identified additional associations in both MHC class I (HLA-A, HLA-B) and class III regions (BAT1). We also observed significant interactions between genes PRSS16, ZNF184 in the extended MHC region and the MHC class II genes. The proposed method can be broadly applied to the classification problem with correlated discrete covariates.
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PMID:BLOCK-BASED BAYESIAN EPISTASIS ASSOCIATION MAPPING WITH APPLICATION TO WTCCC TYPE 1 DIABETES DATA. 2214 Apr 19