Causal Association of Low-density Lipoprotein Cholesterol on Blood Pressure or Diabetes in African and African American Populations: A Mendelian Randomization Study

Introduction Cardiovascular diseases, including hypertension and diabetes, disproportionately affect individuals of African descent. However, the genetic causes of these disparities are under- researched, particularly in lipid metabolism and cardiometabolic risk. Previous Mendelian Randomization (MR) studies have been primarily carried out in European populations, limiting the generalizability of genetic results to African-descendant populations. This research employs MR to ascertain whether genetically predicted low-density lipoprotein cholesterol (LDL-C) levels causally influence blood pressure and diabetes risk in Sub-Saharan African and African-American origin. We use genetic instruments to provide insight into potential causal pathways for the cardiometabolic disease disparities of these groups. Methodology We employed a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary data. Participants of Sub-Saharan African descent and African-American subjects were included in the study. Genetic tools for LDL-C were sourced from GWAS data. Fourteen independent genetic variants strongly associated with LDL cholesterol (p < 5 × 10⁻⁸) were identified in a large genome-wide significance analysis from the UK Biobank, where SNPs were selected based on genome-wide significance (p < 5 × 10⁻⁸) and linkage disequilibrium pruning (r² < 0.01). Sensitivity analyses using the simple median, weighted median, MR-Egger, and MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) were conducted, including Cochran's Q test (heterogeneity p < 0.05) and heterogeneity tests (I² > 25% indicates moderate heterogeneity), to ensure robustness and validate. Findings Our evidence established a definite causal relation between genetically controlled levels of LDL- C or blood pressure (IVW Beta = 0.21, 95% CI: 0.05–0.37, p = 0.029). The sensitivity analyses revealed minute pleiotropic bias, therefore infusing faith into the resulting estimates. Interpretation These findings suggest that genetic variants influencing levels of LDL-C contribute to blood pressure regulation in individuals of African ancestry, with possible implications for metabolic diseases such as diabetes. This has implications for ancestry-specific risk models and targeted prevention to minimize cardiometabolic risk. Larger and more heterogeneous continental African cohorts need to be investigated further to validate these findings and their clinical implications. Results of this study will inform precision medicine approaches to prevent and manage cardiovascular disease in genetically diverse populations.