Non-Invasive Biomarkers of Musculoskeletal Health with High Discriminant Ability for Age and Gender

A novel approach to ageing studies assessed the discriminatory ability of a combination of routine physical function tests and novel measures, notably muscle mechanical properties and thigh composition (ultrasound imaging) to classify healthy individuals according to age and gender. The cross-sectional study included 138 community-dwelling, self-reported healthy males and females (65 young, mean age +/- SD = 25.7 +/- 4.8 years; 73 older, 74.9 +/- 5.9 years). Handgrip strength; quadriceps strength; respiratory peak flow; timed up and go; stair climbing time; anterior thigh tissue thickness; muscle stiffness, tone, elasticity (Myoton technology), and self-reported health related quality of life (SF36) were assessed. Stepwise feature selection using cross-validation with linear discriminant analysis was used to classify cases based on criterion variable derived from known effects of age on physical function. A model was trained and features selected using 126 cases with 0.92 accuracy (95% CI = 0.86-0.96; Kappa = 0.89). The final model included five features (peak flow, timed up and go, biceps brachii elasticity, anterior thigh muscle thickness, and percentage thigh muscle) with high sensitivity (0.82-0.96) and specificity (0.94-0.99). The most sensitive novel biomarkers require no volition, highlighting potentially useful tests for screening and monitoring effects of interventions on musculoskeletal health for vulnerable older people with pain or cognitive impairment.

Automated summary

This study utilized a novel approach to assess ageing by combining routine physical function tests with muscle mechanical properties and thigh composition. A high accuracy model was established with five features measuring the effects of age on physical function, showing high sensitivity and specificity, which could be useful for screening and monitoring musculoskeletal health in older individuals.