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Background: Age is the strongest risk factor for most chronic diseases, and yet individuals may age at different rates biologically. A biological age formed from biomarkers may be a stronger risk factor than chronological age and understanding what factors contribute to it could provide insight into new opportunities for disease prevention. Methods and findings: Among 480,019 UK Biobank participants aged 40-70 recruited in 2006-2010 and followed up for 6-12 years via linked death registry and secondary care records, a subpopulation of 141,254 (29.4%) non-smoking adults in good health and with no medication use or disease history at baseline were identified. Independent components of 72 biomarkers measured at baseline were characterised by principal component analysis. The Klemera Doubal method (KDM), which derived a weighted sum of biomarker principal components based on the strengths of their linear associations with chronological age, was used to derive sex-specific biological ages in this healthy subpopulation. The proportions of the overall biological and chronological age effects on mortality, coronary heart disease and age-related non-fatal hospital admissions (based on a hospital frailty index) that were explained by biological age were assessed using log-likelihoods of proportional hazards models. Reduced lung function, reduced kidney function, slower reaction time, lower insulin-like-growth factor 1, lower hand grip strength and higher blood pressure were key contributors to biological age (explaining the highest percentages of its variance) in both men and women, while lower albumin, higher sex hormone-binding globulin and lower muscle mass in men, and higher liver enzymes, blood lipids and HbA1c in women were also important. Across both sexes, a 51-principal component biological age explained 66%, 80% and 63% of the age effects on mortality, coronary heart disease and hospital admissions, respectively. Restricting the biological age to the 12-13 key biomarkers corresponding to the 10 most importantly contributing principal components resulted in little change in these proportions for women, but a reduction to 53%, 63% and 50%, respectively, for men. Conclusions: This study identified that markers of impaired function in a range of organs account for a substantial proportion of the apparent effect of age on disease and hospital admissions. It supports a broader, multi-system approach to research and prevention of diseases of ageing.

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