Abstract
Age is the leading risk factor for non-communicable diseases. Identifying biomarkers able to discriminate individuals on different health trajectories at an earlier stage in life is crucial for timely prevention measures and maintenance of health. We implemented a multi-omics approach to investigate potential metabolite and protein markers of healthy ageing.
Using cross-sectional data from the Cooperative Health Research in South Tirol (CHRIS) study, we assessed overall health status using the Cumulative Illness Rating Scale (CIRS) index, which measures morbidity in 14 specific organ domains. Our analysis included 991 participants aged≥55 years for which 175 metabolites and 148 proteins were quantified in fasting serum and plasma samples, respectively. Participants were categorized in being healthy or having any morbidity condition in at least one CIRS domain. We used random forest classification to identify omics markers able to predict health status. Multivariable linear regression models were fitted to investigate directionality of relevant signatures, as well as omics-markers related to CIRS domain specific morbidity. The analyses were repeated for individuals of any age (n=3,198).
We identified 10 omics signatures predictive of health status in the group with age>=55 years, which were serotonin, a set of acylcarnitines and sphingolipids and the proteins IGLV1, CP and APOC1. In the any ages sample we identified 34 signatures, which were serotonin and other four biogenic amines, four amino acids, seven acylcarnitines, one sugar and 17 proteins. Moreover, several omics markers were jointly related to endocrine-metabolic, cardiovascular and renal morbidity.
Notably, serotonin was consistently part of any signature and lower levels generally reflected a poorer health status overall and across CIRS domains. Future studies are needed to investigate the mediating role of these signatures in relation to lifestyle and the environment to promote healthy ageing.