Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.

<h4>Background</h4>Determining genetic risk is a fundamental prerequisite for the implementation of primary prevention trials for type 1 diabetes (T1D). The aim of this study was to assess the risk conferred by HLA-DRB1, INS-VNTR and PTPN22 single genes on the onset of T1D and the joint...

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Autores principales:	Rosalba Portuesi, Paolo Pozzilli, Bernhard Boehm, Raffaella Buzzetti, Simonetta Filippi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f45aba6aeced43929912b64771026ad6
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spelling	oai:doaj.org-article:f45aba6aeced43929912b64771026ad62021-11-18T08:45:54ZAssessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.1932-620310.1371/journal.pone.0079506https://doaj.org/article/f45aba6aeced43929912b64771026ad62013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24260237/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Determining genetic risk is a fundamental prerequisite for the implementation of primary prevention trials for type 1 diabetes (T1D). The aim of this study was to assess the risk conferred by HLA-DRB1, INS-VNTR and PTPN22 single genes on the onset of T1D and the joint risk conferred by all these three susceptibility loci using the Bayesian Network (BN) approach in both population-based case-control and family clustering data sets.<h4>Methodology/principal findings</h4>A case-control French cohort, consisting of 868 T1D patients and 73 French control subjects, a French family data set consisting of 1694 T1D patients and 2340 controls were analysed. We studied both samples separately applying the BN probabilistic approach, that is a graphical model that encodes probabilistic relationships among variables of interest. As expected HLA-DRB1 is the most relevant susceptibility gene. We proved that INS and PTPN22 genes marginally influence T1D risk in all risk HLA-DRB1 genotype categories. The absolute risk conferred by carrying simultaneously high, moderate or low risk HLA-DRB1 genotypes together with at risk INS and PTPN22 genotypes, was 11.5%, 1.7% and 0.1% in the case-control sample and 19.8%, 6.6% and 2.2% in the family cohort, respectively.<h4>Conclusions/significance</h4>This work represents, to the best of our knowledge, the first study based on both case-control and family data sets, showing the joint effect of HLA, INS and PTPN22 in a T1D Caucasian population with a wide range of age at T1D onset, adding new insights to previous findings regarding data sets consisting of patients and controls <15 years at onset.Rosalba PortuesiPaolo PozzilliBernhard BoehmRaffaella BuzzettiSimonetta FilippiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 11, p e79506 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rosalba Portuesi Paolo Pozzilli Bernhard Boehm Raffaella Buzzetti Simonetta Filippi Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
description	<h4>Background</h4>Determining genetic risk is a fundamental prerequisite for the implementation of primary prevention trials for type 1 diabetes (T1D). The aim of this study was to assess the risk conferred by HLA-DRB1, INS-VNTR and PTPN22 single genes on the onset of T1D and the joint risk conferred by all these three susceptibility loci using the Bayesian Network (BN) approach in both population-based case-control and family clustering data sets.<h4>Methodology/principal findings</h4>A case-control French cohort, consisting of 868 T1D patients and 73 French control subjects, a French family data set consisting of 1694 T1D patients and 2340 controls were analysed. We studied both samples separately applying the BN probabilistic approach, that is a graphical model that encodes probabilistic relationships among variables of interest. As expected HLA-DRB1 is the most relevant susceptibility gene. We proved that INS and PTPN22 genes marginally influence T1D risk in all risk HLA-DRB1 genotype categories. The absolute risk conferred by carrying simultaneously high, moderate or low risk HLA-DRB1 genotypes together with at risk INS and PTPN22 genotypes, was 11.5%, 1.7% and 0.1% in the case-control sample and 19.8%, 6.6% and 2.2% in the family cohort, respectively.<h4>Conclusions/significance</h4>This work represents, to the best of our knowledge, the first study based on both case-control and family data sets, showing the joint effect of HLA, INS and PTPN22 in a T1D Caucasian population with a wide range of age at T1D onset, adding new insights to previous findings regarding data sets consisting of patients and controls <15 years at onset.
format	article
author	Rosalba Portuesi Paolo Pozzilli Bernhard Boehm Raffaella Buzzetti Simonetta Filippi
author_facet	Rosalba Portuesi Paolo Pozzilli Bernhard Boehm Raffaella Buzzetti Simonetta Filippi
author_sort	Rosalba Portuesi
title	Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
title_short	Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
title_full	Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
title_fullStr	Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
title_full_unstemmed	Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.
title_sort	assessment of type 1 diabetes risk conferred by hla-drb1, ins-vntr and ptpn22 genes using the bayesian network approach.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/f45aba6aeced43929912b64771026ad6
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Assessment of type 1 diabetes risk conferred by HLA-DRB1, INS-VNTR and PTPN22 genes using the Bayesian network approach.

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