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dc.contributor.authorPierce, Brian G.
dc.contributor.authorEberwine, Ryan
dc.contributor.authorNoble, Janelle A.
dc.contributor.authorHabib, Michael
dc.contributor.authorShulha, Hennady P.
dc.contributor.authorWeng, Zhiping
dc.contributor.authorBlankenhorn, Elizabeth P.
dc.contributor.authorMordes, John P.
dc.date2022-08-11T08:08:29.000
dc.date.accessioned2022-08-23T15:56:32Z
dc.date.available2022-08-23T15:56:32Z
dc.date.issued2013-02-13
dc.date.submitted2013-07-26
dc.identifier.citationBrian G. Pierce, Ryan Eberwine, Janelle A. Noble, et al., “The Missing Heritability in T1D and Potential New Targets for Prevention,” Journal of Diabetes Research, vol. 2013, Article ID 737485, 10 pages, 2013. doi:10.1155/2013/737485. <a href="http://dx.doi.org/10.1155/2013/737485">Link to article on publisher's site</a>
dc.identifier.issn2314-6745 (Print)
dc.identifier.doi10.1155/2013/737485
dc.identifier.pmid23691517
dc.identifier.urihttp://hdl.handle.net/20.500.14038/29991
dc.description.abstractType 1 diabetes (T1D) is a T cell-mediated disease. It is strongly associated with susceptibility haplotypes within the major histocompatibility complex, but this association accounts for an estimated 50% of susceptibility. Other studies have identified as many as 50 additional susceptibility loci, but the effect of most is very modest (odds ratio (OR) 5) and that deletion of V beta 13+ T cells prevents diabetes. A role for the TCR is also suspected in NOD mice, but TCR regions have not been associated with human T1D. To investigate this disparity, we tested the hypothesis in silico that previous studies of human T1D genetics were underpowered to detect MHC-contingent TCR susceptibility. We show that stratifying by MHC markedly increases statistical power to detect potential TCR susceptibility alleles. We suggest that the TCR regions are viable candidates for T1D susceptibility genes, could account for "missing heritability," and could be targets for prevention.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=23691517&dopt=Abstract">Link to Article in PubMed</a>
dc.rightsCopyright 2013 Brian G. Pierce et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.subjectBioinformatics
dc.subjectEndocrinology, Diabetes, and Metabolism
dc.subjectImmunoprophylaxis and Therapy
dc.titleThe Missing Heritability in T1D and Potential New Targets for Prevention
dc.typeJournal Article
dc.source.journaltitleJournal of diabetes research
dc.source.volume2013
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1220&amp;context=faculty_pubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/221
dc.identifier.contextkey4352232
refterms.dateFOA2022-08-23T15:56:33Z
html.description.abstract<p>Type 1 diabetes (T1D) is a T cell-mediated disease. It is strongly associated with susceptibility haplotypes within the major histocompatibility complex, but this association accounts for an estimated 50% of susceptibility. Other studies have identified as many as 50 additional susceptibility loci, but the effect of most is very modest (odds ratio (OR) 5) and that deletion of V beta 13+ T cells prevents diabetes. A role for the TCR is also suspected in NOD mice, but TCR regions have not been associated with human T1D. To investigate this disparity, we tested the hypothesis in silico that previous studies of human T1D genetics were underpowered to detect MHC-contingent TCR susceptibility. We show that stratifying by MHC markedly increases statistical power to detect potential TCR susceptibility alleles. We suggest that the TCR regions are viable candidates for T1D susceptibility genes, could account for "missing heritability," and could be targets for prevention.</p>
dc.identifier.submissionpathfaculty_pubs/221
dc.contributor.departmentDepartment of Medicine, Division of Endocrinology and Metabolism
dc.contributor.departmentProgram in Bioinformatics and Integrative Biology
dc.source.pages737485


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