Causal Association Between Genetically Predicted Ankle Spacing Width and Risk of Age-Related Bone Mineral Density

Abstract

While observational studies suggest associations between ankle spacing width (ASW, defined as the horizontal distance between the medial malleoli under weight-bearing conditions) and osteoporosis (OP), fractures, and falls, causal evidence remains limited. This gap hinders the translation of ASW measurements into clinical risk stratification tools. This study aimed to investigate the causal relationships between ASW indicators and site-/age-specific bone mineral density (BMD), bone fracture and fall risks. Genetic exposure data for ASW indicators were retrieved from the MRC-IEU datasets, and the outcome data were all derived from the Genetic Factors for Osteoporosis Consortium (GEFO). Genome-wide associations of single nucleotides polymorphisms (SNPs) were served as instrumental variables (IVs) to infer causal effects using two-sample mendelian randomization (TSMR) and multivariable mendelian randomization (MVMR) analyses. The results of sites-specific TSMR analysis revealed that per unit increase in ASW (including left and right) were causally associated with lower estimated from quantitative heel ultrasounds BMD (eBMD, reflecting calcaneal bone density) and total-body BMD (TB-BMD, assessed via DEXA scans), with pronounced effects in individuals aged over 60 years. Age-stratified analyses revealed no significant associations between ASW and TB-BMD in younger age groups (age ≤ 15, 15 < age ≤ 30, 30 < age ≤ 45, 45 < age ≤ 60) or site-specific fractures/falls. MVMR adjustment for BMI, smoking, and alcohol consumption confirmed persistent causal associations between ASW and reduced eBMD and TB-BMD, particularly for TB-BMD in individuals aged over 60 years. Our study provides evidence that genetically predicted ASW is associated with reduced eBMD and TB-BMD, and a causal association between ASW and TB-BMD (aged over 60), suggesting ASW as a potential auxiliary biomarker for monitoring age-dependent bone loss.

Keywords: Ankle spacing width; Bone mineral density; Mendelian randomization; Osteoporosis.

Fig. 1

The flow chart of MR study design. MR Mendelian Randomization, IVs instrumental variables, LD linkage disequilibrium, MAF minor allele frequency, MR-PRESSO Mendelian Randomization Pleiotropy RESidual Sum and Outlier, TSMR Two-Sample Mendelian Randomization.

Fig. 2

Forest plot of causal associations of ASW on sites-specific BMD with IVW method. ASW ankle spacing width, CI confidence interval, BMD bone mineral density, FA forearm, FN femoral neck, LS lumbar spine, eBMD estimated from quantitative heel ultrasounds BMD, TB-BMD total-body BMD, N. SNPs number of single-nucleotide polymorphisms, IVW inverse-variance weighted.

Fig. 3

Forest plot of causal associations of ASW on age-specific BMD with IVW method. ASW ankle spacing width, BMD bone mineral density, CI confidence interval, N. SNPs number of single-nucleotide polymorphisms, IVW inverse-variance weighted.

Fig. 4

Forest plot of causal associations of ASW on the risk of bone fractures and falls with IVW method. ASW ankle spacing width, BMD bone mineral density, CI confidence interval, N. SNPs number of single-nucleotide polymorphisms, OR odds ratio, IVW inverse-variance weighted.

Fig. 5

FDR-adjusted P-values for causal associations with ASW on BMD, fractures and falls. ASW ankle spacing width, BMD bone mineral density, FA forearm, FN femoral neck, LS lumbar spine, eBMD estimated from quantitative heel ultrasounds BMD, TB-BMD totalbody BMD.

Fig. 6

Causal effects of ASW on the risk of eBMD and TB-BMD after adjustment for BMI, smoking and drinking alcohol. ASW ankle spacing width, BMI body mass index, eBMD estimated from quantitative heel ultrasounds BMD, TB-BMD totalbody BMD.