Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the intestine associated with genetic susceptibility and alterations in the intestinal microbiome. Multiomics data developed and analyzed over the last several decades have yielded an unprecedented amount of genetic and microbial data. But how do we pinpoint mechanistic insight into the host-microbe relationship that will ultimately enable better care for patients with IBD? In this issue of the JCI, Grasberger et al. undertook a major decoding effort to decipher this multiomic data matrix. The authors analyzed anonymized data from more than 2800 individuals to discover a link between heterozygous carriers of deleterious DUOX2 variants and high levels of plasma IL-17C. These findings provide an example of how harnessing big data can drive mechanistic discovery to define disease biomarkers that have the potential to improve clinical care in IBD.
Monica Viladomiu, Randy S. Longman
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