This observational study focuses on elucidating the causal relationships between commonly prescribed antihypertensive drugs (ACEIs and ARBs) and lipid-lowering drugs (HMG-CoA reductase inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors) with various inflammatory cytokines, including IL-1β, TNF-α, CRP, MCP-1, and IFN-γ, using a drug-targeted Mendelian randomization (MR) framework. The study employs large-scale genetic data from European populations, drawing from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) datasets, to construct instrumental variables that mimic the effects of drug exposure.
The primary aim is to explore how these pharmaceutical interventions influence inflammatory pathways at the molecular level. The use of MR methods enables causal inference by utilizing genetic variants within or near drug-target genes, allowing for the estimation of downstream effects similar to those produced by actual drug interventions. Key statistical methods, including inverse variance weighting and sensitivity analyses, are applied to ensure robustness and validity of the results.
This research provides critical evidence for the selection of antihypertensive and lipid-lowering therapies that not only manage cardiovascular risk factors but also modulate inflammation, contributing to personalized medicine strategies for patients with chronic inflammatory conditions. Furthermore, the findings have broader implications for drug repurposing and the development of new therapeutic targets aimed at mitigating inflammatory processes that underlie various chronic diseases.
