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

Date Published: February 2, 2017

Publisher: Public Library of Science

Author(s): Pierre Bougnères, Sophie Le Fur, Sophie Valtat, Yoichiro Kamatani, Mark Lathrop, Alain-Jacques Valleron, Marc S. Horwitz.

http://doi.org/10.1371/journal.pone.0170658

Abstract

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.

Partial Text

The natural history of T1D makes the search for environmental markers difficult. Indeed, it takes a silent period lasting several months up to several years for the autoimmune reaction to achieve the near-complete destruction of ß-cells, as indicated by the appearance of autoantibodies in a child’s serum long before T1D is diagnosed [1–3]. The rate of ß-cell destruction varies across patients for unknown reasons, but seems accelerated in young children [4]. Environmental factors can affect susceptibility, triggering of autoimmunity, and possibly preclinical course of T1D. The limited concordance of T1D (30–40%) across monozygotic twin pairs is the main proof of major non-genetic risk factors [5–8] that are thought to interact with the genetic background of predisposed children. The genetic background that predisposes to childhood T1D nowadays may not be the same as 30 years ago [9].

This study detected differences in infectious exposures between future T1D patients and control children that occurred at the location of residence, while social environment was comparable. This observation supports the existence of a relationship between infections and T1D occurrence. A weakness of our study is that it is exclusively based on addresses of residence and brings no proof that the child living in the area of residence of infected individuals has actually developed the infection reported by the sentinel surveillance network, or even has been exposed to infected individuals. This is why in this manuscript said “exposures” shoud be understood as “potential exposures”.

 

Source:

http://doi.org/10.1371/journal.pone.0170658

 

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