Towards a Consensus Measure of Healthspan
The measurement of life span is self-evident and obvious, but is little consensus on how to measure healthspan, the length of life spent in good health. Good health is like art, we know it when we see it, but that isn't helpful when trying to compare the effects of interventions where the studies were conducted by different researchers with different ideas as what constitutes good health in an older individual. This issue exists for both human and animal studies, and the lack of consistency makes it hard to make comparisons based on the existing literature on the topic. Researchers are starting to propose rigorous definitions of healthspan, but it seems that we stand some distance removed from any great agreement as to which of these definitions is the one to adopt as a standard.
Unlike lifespan, which has a universal definition, there is no consensus on the definition of healthspan. Previous research has suggested characterizing healthy aging in five domains: physical capability, cognitive function, physiological and musculoskeletal, endocrine, and immune functions. For practical purposes, healthspan typically refers to the period of life spent in good health, free from the chronic diseases and disabilities of aging. Studies aiming to evaluate the effects of interventions on healthspan are challenging due to the need for long follow-up lengths and large sample sizes of healthy individuals to observe the outcomes of interest. Thus, developing surrogate biomarkers that can predict healthspan is crucial for improving the feasibility of clinical trials to test interventions to prolong healthspan and lifespan.
Composite biomarkers incorporating multiple measures are more robust in predicting age-related outcomes than single biomarkers. Several composite biomarkers for predicting lifespan or mortality have been developed using clinical biomarkers or omics data. However, to date, no composite biomarker measures have been developed based on a healthspan definition. To mitigate this gap, we developed a proteomics-based healthspan biomarker (healthspan proteomic score, HPS) using chronological age and expression data of 2,920 proteins at the UK Biobank baseline/recruitment (2006-2010).
A lower HPS was associated with higher mortality risk and several age-related conditions, such as COPD, diabetes, heart failure, cancer, myocardial infarction, dementia, and stroke. HPS showed superior predictive accuracy for these outcomes compared to chronological age and biological age measures. Proteins associated with HPS were enriched in hallmark pathways such as immune response, inflammation, cellular signaling, and metabolic regulation. Our findings demonstrate the validity of HPS, making it a valuable tool for assessing healthspan and as a potential surrogate marker in geroscience-guided studies.