What question did this study set out to answer?

This study aims to examine the causal relationship between metabolic syndrome traits and prostate cancer risk using genetic data.

April 5, 2026

Abstract 3605: Genetic insights into metabolic traits and prostate cancer susceptibility: A two sample Mendelian Randomization study

Key Result

Higher genetically predicted fasting glucose was associated with reduced prostate cancer risk (OR 0.82, P=0.02), while other major metabolic syndrome traits showed no causal association.

Key Points

This study aims to examine the causal relationship between metabolic syndrome traits and prostate cancer risk using genetic data.
Conducted a two-sample Mendelian randomization study using genetic instruments from large genome-wide association studies.
Utilized data from male-only cohorts in the UK Biobank to obtain metabolic syndrome trait information.
Analyzed prostate cancer risk data from the FinnGen GWAS with various statistical methods for causal estimates.
Higher genetically predicted fasting glucose was associated with a reduced prostate cancer risk (OR 0.82).
HDL-cholesterol indicated a suggestive association with prostate cancer (OR 1.52, P=0.052).
LDL-cholesterol showed a suggestive but not statistically significant effect (OR 0.87, P=0.07).
No causal associations were found for BMI, waist circumference, blood pressure, total cholesterol, or triglycerides.

Structured PICO

Do genetically predicted metabolic traits causally influence prostate cancer risk?

Population

Male participants from large genome-wide association studies (UK Biobank) and FinnGen GWAS, predominantly European ancestry

Intervention

Genetically predicted metabolic traits (BMI, waist circumference, systolic/diastolic blood pressure, fasting glucose, triglycerides, LDL-cholesterol, HDL-cholesterol, total cholesterol)

Outcome

Prostate cancer riskhard clinical

Genetically predicted higher fasting glucose is associated with a reduced risk of prostate cancer, implicating glucose metabolism pathways in prostate cancer susceptibility.

Main Result

Absolute Event Rate: 0% vs 0%

Abstract

Abstract Background: Metabolic syndrome (MetS) and its components have been implicated in prostate cancer, but observational associations remain inconsistent and vulnerable to confounding. We conducted a two-sample Mendelian randomization (MR) study to clarify whether major MetS traits causally influence prostate cancer risk. Methods: Genetic instruments for body mass index (BMI), waist circumference, systolic/diastolic blood pressure, fasting glucose, and lipid components such as triglycerides (TG), LDL-cholesterol, HDL-cholesterol, and total cholesterol were obtained from male-only large genome-wide association studies (UK Biobank) and MetS from multiple cohorts as exposure sets. Prostate cancer data set was derived from the FinnGen GWAS. Genome-wide significant variants (p5×10-8) were clumped at r20.001. Causal estimates were calculated using inverse-variance weighted (IVW), weighted median, and MR-Egger methods. Heterogeneity (Cochran’s Q), horizontal pleiotropy (MR-Egger intercept, MR-PRESSO), and sensitivity analyses were performed. Results: Higher genetically predicted fasting glucose was associated with reduced prostate cancer risk (OR 0.82, P=0.02). HDL-cholesterol (OR 1.52, P=0.052) and LDL-cholesterol (OR 0.87, P=0.07) showed suggestive effects. BMI, waist circumference, blood pressure, total cholesterol, and triglycerides showed no evidence of causal association. Conclusions: Our findings implicate glucose and lipid metabolism pathways in prostate cancer susceptibility. Given the exploratory nature and the predominantly European ancestry of the datasets, large scale studies including diverse multiple-ethnic populations are required to confirm these associations and clarify the role of metabolic traits across different ancestries in prostate cancer epidemiology. Citation Format: HWA SUN KIM, Chung-woo Lee, . Genetic insights into metabolic traits and prostate cancer susceptibility: A two sample Mendelian Randomization study abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3605.

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