Metabolic abnormalities are closely tied to the development of ovarian cancer (OC), yet the relationship between anthropometric indicators as risk indicators for metabolic abnormalities and OC lacks consistency.
The Mendelian randomization (MR) approach is a widely used methodology for determining causal relationships. Our study employed summary statistics from the genome-wide association studies (GWAS), and we used inverse variance weighting (IVW) together with MR-Egger and weighted median (WM) supplementary analyses to assess causal relationships between exposure and outcome. Furthermore, additional sensitivity studies, such as leave-one-out analyses and MR-PRESSO were used to assess the stability of the associations.
The IVW findings demonstrated a causal associations between 10 metabolic factors and an increased risk of OC. Including “Basal metabolic rate” (OR= 1.24,
Several metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC.