Detecting causal relationship between metabolic traits and osteoporosis using multivariable Mendelian randomization.

Area of Science:

• Genetics and Epidemiology
• Metabolic Diseases
• Skeletal Biology

Background:

• Osteoporosis (OP) is a prevalent metabolic skeletal disease marked by decreased bone mineral density (BMD).
• Current genetic markers (SNPs) explain only about 10% of BMD variability, with few causal factors identified.
• There is a need to identify more causal risk factors for effective intervention.

Purpose of the Study:

• To identify and prioritize potential causal risk factors for bone mineral density (BMD) traits.
• To utilize advanced Mendelian randomization (MR) methods for causal inference.
• To provide novel insights for the treatment and intervention of bone-related diseases.

Main Methods:

• Employed extension approaches of Mendelian randomization (MR), including multivariable MR (mvMR) and MR-Bayesian Model Averaging (MR-BMA).
• Assessed the causal relationship between fifteen metabolic risk factors and BMD.
• Utilized genetic instrumental variables (IVs) to evaluate potential causal effects.

Main Results:

• Identified causal risk factors for different BMD sites: FN BMD (T2D, FG, HCadjBMI), FA BMD (FI, T2D, HCadjBMI, WCadjBMI), and LS BMD (FI, T2D, HDL cholesterol).
• Confirmed causal associations for most identified risk factors with heel BMD, excluding triglycerides and WCadjBMI.
• MR-BMA results corroborated the findings from mvMR, confirming top risk factors for each BMD trait.

Conclusions:

• Combined MR approaches successfully identified and prioritized causal risk factors for various BMD traits (FN, FA, LS, heel).
• The findings offer novel insights into the causal pathways influencing BMD.
• These insights can guide future treatment and intervention strategies for bone-related complex traits and diseases like osteoporosis.