Inherited Predisposition to Increased Systemic Inflammation Predicts a Broad Class of Disease Phenotypes

Chronic, low-grade systemic inflammation is a polygenic trait captured with the INFLA-score, a composite of C-reactive protein, platelet count, leukocyte count, and granulocyte-to-lymphocyte ratio. We derived a polygenic risk score from the INFLA-score (iPRS) in a multi-ancestry population from the UK Biobank (n=421,368), then evaluated and used it in a phenome-wide association study among participants in the All of Us Research Program (AoU). The multi-ancestry iPRS was tested for association with the INFLA-score in AoU (N=4,833 with biomarker data) via linear regression, adjusting for age, sex, and genetically-determined principal components (PCs) and with 2,821 phecodeX-defined phenotypes in AoU (N=265,068) via logistic regression, adjusting for sex, age, EHR length, race, ethnicity and PCs. The iPRS predicted the INFLA-score (R-squared=0.026, beta=0.980, p<2x10^-16) and was associated with 47 phenotypes (Bonferroni-corrected p<0.05). The strongest associations were with blood-related phenotypes: elevated white blood cell count (OR=1.19, p=3.85x10^-66), thrombocytopenia (OR=0.86, p=5.70x10^-44), platelet defects (OR=0.86, p=2.47x10^-43), neutropenia (OR= 0.86, p=5.52x10^-18), myeloproliferative disorder (OR= 1.2, p=2.77x10^-15). Others included celiac disease (OR=0.713, p=2.98x10^-46), ankylosing spondylitis (OR=1.4, p=1.33 x 10^-17), hypertension (OR=1.04, p=4.56x10^-15), rheumatoid arthritis (OR=1.09, p=1.02x10^-13), hematuria (OR=1.05, p=1.96x10^-10). Removing major-histocompatibility-complex SNPs abolished associations with known autoimmune diseases, while all other associations remained. We replicated 17 (42.5%) of 40 significant phenotypes available in the Vanderbilt University Medical Center's BioVU. Our findings demonstrate that systemic inflammation can be predicted using the iPRS across multiple ancestries, and the iPRS is associated with numerous clinical endpoints. This multi-ancestry iPRS may have future utility in stratifying risk for inflammation-driven conditions across diverse populations.