T1DBase, a community web-based resource for type 1 diabetes research

Smink, Luc J.; Helton, Erin; Healy, Barry; Cavnor, Christopher C.; Lam, Adam; Flamez, Daisy; Burren, Oliver S.; Wang, Yan; Dolman, Geoffrey E.; Burdick, David B.; Everett, Vincent H.; Glusman, Gustavo; Laneri, Davide; Rowen, Lee; Schuilenburg, Helen; Walker, Neil M.; Mychaleckyj, Josyf C.; Wicker, Linda S.; Eizirik, Décio L.; Todd, John A.; Goodman, Nathan

doi:10.1093/nar/gki095

Cited by 45 publications

(36 citation statements)

References 27 publications

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“…MPSS data sets obtained in control and cytokine (IL1-β+ IFN-γ)-exposed human islets [21] were compared with LICR MPSS data sets obtained in 32 human tissues [22], including total pancreas. Microarray data (included in the Beta Cell Gene Bank [30]) obtained in INS-1E cells, primary rat beta cells or human islets either in the control condition or exposed to cytokines were compared with data sets available on the Internet (Symatlas, GEO Omnibus). After this step, 950 islet-specific genes were selected and were further tested for membrane localisation using the TMHMM and IPA programs; this resulted in the selection of 114 plasma membrane proteins.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore we compared the MPSS and microarray data with previous microarray data sets posted in the Beta Cell Gene Bank [30], including comparisons between cytokine-treated and control human islets [31], primary rat beta cells [26,27] and INS-1E cells [32]. Based on these data, and following the selection procedure described in Fig.…”

Section: Tissue Samplesmentioning

confidence: 99%

“…5. Expression levels of the selected markers should not be modified to any major extent by inflammation, as evaluated by our microarray data sets obtained in purified primary rat beta cells [26,28,30,32] and in human islets [31].…”

Section: Mpssmentioning

confidence: 99%

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A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)γa as a pancreatic beta cell-specific biomarker

et al. 2010

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Aims/hypothesis Non-invasive imaging of the pancreatic beta cell mass (BCM) requires the identification of novel and specific beta cell biomarkers. We have developed a systems biology approach to the identification of promising beta cell markers. Methods We followed a functional genomics strategy based on massive parallel signal sequencing (MPSS) and microarray data obtained in human islets, purified primary rat beta cells, non-beta cells and INS-1E cells to identify promising beta cell markers. Candidate biomarkers were validated and screened using established human and macaque (Macacus cynomolgus) tissue microarrays.Results After a series of filtering steps, 12 beta cell-specific membrane proteins were identified. For four of the proteins we selected or produced antibodies targeting specifically the human proteins and their splice variants; all four candidates were confirmed as islet-specific in human D. Flamez and I. Roland contributed equally to this study. Electronic supplementary materialThe online version of this article

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Section: Resultsmentioning

confidence: 99%

Section: Tissue Samplesmentioning

confidence: 99%

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A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)γa as a pancreatic beta cell-specific biomarker

et al. 2010

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“…db = snp). The expression profile for GluK1 mRNA in human tissues was obtained from T1Dbase [23] database that uses data from Gene Novartis Foundation (GNF) database [3]. Data pertaining to murine brain region-specific expression of GluK1 was also obtained from the GNF database [3].…”

Section: Bio-informatics Proceduresmentioning

confidence: 99%

“…Robust expression of GluK1 mR-NA is observed in cortical layers II, III and IV, with a transient peak during the period of greatest developmental plasticity in the somatosensory cortex of rat brain [6,28]. A search of human (T1Dbase) [3,23] and murine (Gene Novartis Foundation) [3] databases reveals region-specific expression of GluK1 mRNA in the cerebellum, striatum, caudate nucleus, hippocampus, amygdala and the cortex.…”

Section: Introductionmentioning

confidence: 99%

A Study of GluK1 Kainate Receptor Polymorphisms in Down Syndrome Reveals Allelic Non-Disjunction at 1173(C/T)

et al. 2009

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Abstract. Mechanisms underlying Down syndrome (DS)-related mental retardation (MR) remain poorly understood. In trisomic offspring, non-disjunction may result in the reduction to homozygosity of a susceptibility allele inherited from a heterozygous parent. Accordingly, we sought evidence for allelic non-disjunction in the GluK1 gene that encodes the critical kainite-binding glutamate receptor subunit-5, maps to chromosome 21q22.1 in the DS critical region and is expressed in brain regions responsible for learning and memory. Three polymorphisms of GluK1 [522(A/C) rs363538; 1173(C/T) rs363430 and 2705(T/C) rs363504] were genotyped in 86 DS patient families by means of PCR-coupled RFLP assays and evaluated with respect to allele frequency, heterozygosity, linkage disequilibrium, stage and parental origin of allelic non-disjunction. We report that the distribution of allele frequencies is in Hardy-Weinberg equilibrium. Moderate heterozygosity (0.339) and a major allele frequency of 0.

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Immunology and genetics of type 1 diabetes

Morran

Omenn

Pietropaolo

2008

Mount Sinai J Medicine

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Type 1 diabetes is one of the most well-characterized autoimmune diseases. Type 1 diabetes compromises an individual's insulin production through the autoimmune destruction of pancreatic beta-cells. Although much is understood about the mechanisms of this disease, multiple potential contributing factors are thought to play distinct parts in triggering type 1 diabetes. The immunological diagnosis of type 1 diabetes relies primarily on the detection of autoantibodies against islet antigens in the serum of type 1 diabetes mellitus patients. Genetic analyses of type 1 diabetes have linked human leukocyte antigen, specifically class II alleles, to susceptibility to disease onset. Environmental catalysts include various possible factors, such as viral infections, although the evidence linking infections with type 1 diabetes remains inconclusive. Imbalances within the immune system's system of checks and balances may promote immune activation, while undermining immune regulation. A lack of proper regulation and overactive pathogenic responses provide a framework for the development of autoimmune abnormalities. Type 1 diabetes is a predictable and potentially treatable disease that still requires much research to fully understand and pinpoint the exact triggering events leading to autoimmune activation. In silico research can aid the comprehension of the etiology of complex disease pathways, including Type I diabetes, in order to and help predict the outcome of therapeutic strategies aimed at preserving beta-cell function.

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T1DBase, a community web-based resource for type 1 diabetes research

Cited by 45 publications

References 27 publications

A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)γa as a pancreatic beta cell-specific biomarker

A genomic-based approach identifies FXYD domain containing ion transport regulator 2 (FXYD2)γa as a pancreatic beta cell-specific biomarker

A Study of GluK1 Kainate Receptor Polymorphisms in Down Syndrome Reveals Allelic Non-Disjunction at 1173(C/T)

Immunology and genetics of type 1 diabetes

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