A computational approach to chemical etiologies of diabetes

Abstract

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals, and offers thus promising guidance for future research in regard to the etiology and pathogenesis of complex diseases.

Figure 1. Workflow of the meta-analysis approach for identifying chemicals connected to Type II diabetes (T2D).

Three data sources represent evidence layers (1–3), which allow ranking chemicals to prioritize chemicals likelihood to be involved in T2D.

Figure 2. Disease layer: Disease-chemical associations.

Green nodes are the eight diseases, which have common genes to T2D (from the human diseasome). Chemicals (grey nodes) are connected to at least one of these diseases (data from CTD, only score > 5). The edges between a chemical and a disease represent the evidence e.g. blue edge is literature-based, red edge is therapeutic and green edge is marker/mechanism. The six clusters show the chemicals the most connected to diseases. The green cluster contains only one chemical linked to six diseases. The purple cluster group the chemicals having associations to five diseases. The orange cluster shows association between chemicals and four diseases, and the blue ones between chemicals and three diseases. All other chemicals are connected to one or two diseases only.