Systems analysis of multiple diabetes-helminth cohorts reveals markers of disease-disease interaction

Understanding how our immune system responds to the co-occurrence of two diseases in an individual (co-morbidity) could lead to mechanistic insights into and novel treatments for co-morbid conditions. Studies have shown that co-morbid immune responses could be more complex than the union of responses to each disease occurring separately, but a data-driven quantification of this complexity is lacking. In this study, we take a systematic approach to quantifying the interaction effect of two diseases on marker variables of interest (using a chronic inflammatory disease diabetes and parasitic infection helminth as illustrative disease pairs to identify cytokines or other immune markers that respond distinctively under a comorbid condition). To perform this systematic comorbidity analysis, we collected and preprocessed data measurements from multiple single- and double-disease cohorts, extended differential expression analysis of such data to identify disease-disease interaction (DDI) markers (such as cytokines that respond antagonistically or synergistically to the double-disease condition relative to single-disease states), and interpreted the resulting DDI markers in the context of prior cytokine/immune-cell knowledgebases. We applied this three-step DDI methodology to multiple cohorts of helminth and diabetes (specifically, helminth-infected and helminth-treated individuals in diabetic and non-diabetic conditions, and non-disease control individuals), and identified cytokines such as IFN- γ , TNF- α , and IL-2 to be DDI markers acting at the interface of both diseases in data collected prior to helminth treatment. Validating our expectations, for these cytokines and other T helper Th-2 cytokines like IL-13 and IL-4, their DDI statuses were lost after treatment for helminth infection. For instance, the relative contribution of the DDI term in explaining the individual-to-individual variation of IFN- γ and TNF- α cytokines were 67.68% and 48.88% respectively before anthelmintics treatment and dropped to 6.09% and 14.56% respectively after treatment. Furthermore, signaling pathways like IL-10 and IL-4/IL-13 were found to be significantly enriched for genes targeted by certain DDI markers, thereby suggesting mechanistic hypotheses on how these DDI markers influence both diseases. These results are promising and encourage the application of our DDI methodology ( https://github.com/BIRDSgroup/Disease-Disease-Interaction ) to dissect the interaction between any two diseases, provided multi-cohort measurements of markers are available.

Supporting Information

Please visit this URL to access Supplementary Figures, Tables and File associated with this work: https://github.com/BIRDSgroup/Disease-Disease-Interaction/tree/main/Application%20on%20helminth-diabetes%20data/Supplementary%20Figures%20and%20Tables .

Author Summary

The hygiene hypothesis, derived from epidemiological data gathered in developing and developed countries, suggests that a person’s exposure to helminth infection can lower the person’s risk of developing lifestyle diseases such as type-2 diabetes. This motivates us to study the interaction between diabetes and helminth infection. The host-pathogen interactions, specifically the host immune response to a pathogenic infection, can be quite different from a typical response when the host is suffering from another immune/inflammation-related disease such as diabetes. It is high time for a quantitative analysis of such disease-disease interactions (DDI), since not many studies have inspected DDI due to the lack of systematically collated single- and double-disease cohorts and associated statistical analysis of measurements from these cohorts. Towards this goal, we present a computational methodology for identifying and interpreting DDI markers, and apply it to systematically generated datasets from patient samples belonging to single-disease and double-disease cohorts of helminth infection and diabetes. This analysis quantified the extent of helminth-diabetes DDI exhibited by various tested markers, and thereby revealed cytokine markers such as IFN- γ (Interferon-gamma), TNF- α (Tumour Necrosis Factor-alpha), and IL-2 (Interleukin-2) to be important players in the pathogenesis of both diseases.