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Article Dans Une Revue PLoS ONE Année : 2017

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

Résumé

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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cea-04516178 , version 1 (22-03-2024)

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Pierre Bougneres, Sophie Le Fur, Isis-Diap Collaborative,, Sophie Valtat, Yoichiro Kamatani, et al.. Using spatio-temporal surveillance data to test the infectious environment of children before type 1 diabetes diagnosis. PLoS ONE, 2017, 12 (2), pp.e0170658. ⟨10.1371/journal.pone.0170658⟩. ⟨cea-04516178⟩
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