Estimating causal effects of C-reactive protein on disease and health outcomes using multivariable Mendelian randomization adjusting for heritable confounding

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Estimating causal effects of C-reactive protein on disease and health outcomes using multivariable Mendelian randomization adjusting for heritable confounding 2026

Background
C-reactive protein (CRP) is a marker of inflammation associated with autoimmune, cardiovascular, and neuropsychiatric disorders. However, it remains unclear whether CRP causally affects these traits or if observed associations result from reverse causation or confounding.
Results
Univariable MR suggests evidence of potential causal effects of CRP on coronary artery disease, high-density lipoprotein (HDL) cholesterol, LDL cholesterol, triglycerides, type 2 diabetes, glycated hemoglobin (HbA1c), rheumatoid arthritis (RA), SCZ and OA at the nominal P < .05 significance level. However, after adjusting for computationally selected heritable confounders, only effects on HDL cholesterol (negative), HbA1c (positive), RA (risk increasing), and SCZ (risk decreasing) remain nominally significant. Using confounder-adjusted MVMR additionally reveals evidence of a protective effect of CRP on bipolar disorder not observed in the univariable analysis.
Conclusion
These results suggest that univariable MR analyses of CRP may be biased by high levels of heritable confounding, though CRP may indeed play a causal role in development of some diseases, potentially mediated by its role in innate immunity. These results also highlight the potential for automatic confounder selection to improve the robustness of MR analyses.

So CRP-lowering intervention might not do much by themselves then?

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Personally I think CRP is an indicator of a high level of senescent cells (if you measure it sufficiently frequently to get the back ground level). Hence anything driven by senescence is more likely to occur, but not causally.