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Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis

The “hygiene hypothesis” postulates that reduced exposure to infections favours the development of autoimmunity and childhood type 1 diabetes (T1D). But on the other side, viruses, notably enteroviruses, are suspected to trigger T1D. The assessment of the possible relationships between infections an...

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Autores principales: Bougnères, Pierre, Le Fur, Sophie, Valtat, Sophie, Kamatani, Yoichiro, Lathrop, Mark, Valleron, Alain-Jacques
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289461/
https://www.ncbi.nlm.nih.gov/pubmed/28152013
http://dx.doi.org/10.1371/journal.pone.0170658
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author Bougnères, Pierre
Le Fur, Sophie
Valtat, Sophie
Kamatani, Yoichiro
Lathrop, Mark
Valleron, Alain-Jacques
author_facet Bougnères, Pierre
Le Fur, Sophie
Valtat, Sophie
Kamatani, Yoichiro
Lathrop, Mark
Valleron, Alain-Jacques
author_sort Bougnères, Pierre
collection PubMed
description The “hygiene hypothesis” postulates that reduced exposure to infections favours the development of autoimmunity and childhood type 1 diabetes (T1D). But on the other side, viruses, notably enteroviruses, are suspected to trigger T1D. The assessment of the possible relationships between infections and T1D still defies the classical tools of epidemiology. We report the methods and results of a geographical approach that maps the addresses of patients to a communicable diseases surveillance database. We mapped the addresses of patients at birth, infancy and T1D diagnosis to the weekly estimates of the regional incidences of 5 frequent communicable diseases routinely collected since 1984 by the French Sentinel network. The pre-diagnostic infectious environment of 3548 patients with T1D diagnosed between 0.5 and 15 years was compared to those of 100 series of age-matched “virtual controls” drawn randomly on the map. Associations were classified as “suggestive” (summer diarrhea, SD, and varicella, V) when p< 0.05, or “significant” (influenza-like infections, ILI) when they passed the Bonferroni correction for FDR. Exposure to ILI and SD were associated with T1D risk, while V seemed protective. In the subset of 2521 patients for which we had genome wide data, we used a case-only approach to search for interactions between SNPs and the infectious environment as defined by the Sentinel database. Two SNPs, rs116624278 and rs77232854, showed significant interaction with exposure to V between 1 and 3 years of life. The infectious associations found should be taken as possible markers of patients’ environment, not as direct causative factors of T1D. They require replication in other populations. The increasing public availability of geographical environmental databases will expand the present approach to map thousands of environmental factors to the lifeline of patients affected by various diseases.
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spelling pubmed-52894612017-02-17 Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis Bougnères, Pierre Le Fur, Sophie Valtat, Sophie Kamatani, Yoichiro Lathrop, Mark Valleron, Alain-Jacques PLoS One Research Article The “hygiene hypothesis” postulates that reduced exposure to infections favours the development of autoimmunity and childhood type 1 diabetes (T1D). But on the other side, viruses, notably enteroviruses, are suspected to trigger T1D. The assessment of the possible relationships between infections and T1D still defies the classical tools of epidemiology. We report the methods and results of a geographical approach that maps the addresses of patients to a communicable diseases surveillance database. We mapped the addresses of patients at birth, infancy and T1D diagnosis to the weekly estimates of the regional incidences of 5 frequent communicable diseases routinely collected since 1984 by the French Sentinel network. The pre-diagnostic infectious environment of 3548 patients with T1D diagnosed between 0.5 and 15 years was compared to those of 100 series of age-matched “virtual controls” drawn randomly on the map. Associations were classified as “suggestive” (summer diarrhea, SD, and varicella, V) when p< 0.05, or “significant” (influenza-like infections, ILI) when they passed the Bonferroni correction for FDR. Exposure to ILI and SD were associated with T1D risk, while V seemed protective. In the subset of 2521 patients for which we had genome wide data, we used a case-only approach to search for interactions between SNPs and the infectious environment as defined by the Sentinel database. Two SNPs, rs116624278 and rs77232854, showed significant interaction with exposure to V between 1 and 3 years of life. The infectious associations found should be taken as possible markers of patients’ environment, not as direct causative factors of T1D. They require replication in other populations. The increasing public availability of geographical environmental databases will expand the present approach to map thousands of environmental factors to the lifeline of patients affected by various diseases. Public Library of Science 2017-02-02 /pmc/articles/PMC5289461/ /pubmed/28152013 http://dx.doi.org/10.1371/journal.pone.0170658 Text en © 2017 Bougnères et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bougnères, Pierre
Le Fur, Sophie
Valtat, Sophie
Kamatani, Yoichiro
Lathrop, Mark
Valleron, Alain-Jacques
Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title_full Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title_fullStr Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title_full_unstemmed Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title_short Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
title_sort using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289461/
https://www.ncbi.nlm.nih.gov/pubmed/28152013
http://dx.doi.org/10.1371/journal.pone.0170658
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