The development of multiple chronic diseases in the same individual (i.e., multimorbidity) results from the loss of homeostasis across several biological systems. Identifying pathophysiological pathways common to multiple diseases, using accessible biomarkers, could increase our understanding of multimorbidity and improve its prognostication and management. We conducted a systematic review of peer-reviewed articles published till September 2024 that investigated biomarkers of multimorbidity. Due to study heterogeneity, a synthesis without meta-analysis was performed on 43 studies employing harvest plots based on direction of effect, sample size and study quality. Findings highlight how inflammatory and metabolic biomarkers, such as interleukin-6 (IL-6) and glycated haemoglobin (HbA1c) especially, but also triglycerides, low-density lipoprotein (LDL) cholesterol and kidney and liver markers, along with markers of neurodegeneration including Neurofilament Light Chain (NfL) and Phospho-Tau 217 (p-tau 217), were directly associated with multimorbidity. Nonetheless, evidence for hormonal and vascular activation markers, as well as more novel geroscience biomarkers, remains limited. These markers could have a key role in identifying individuals at high risk of developing or worsening multimorbidity. The review also highlights how methodological challenges, including heterogeneity in study design, populations, and multimorbidity definitions, impact on comparability and generalizability of findings. Addressing these gaps through standardized, longitudinal studies and multi-omics approaches is crucial to improve our understanding of the pathophysiological mechanisms of multimorbidity. In summary, this review outlines the independent association of diverse biomarkers with multimorbidity, opening to the possibility of identifying specific pathophysiological pathways for risk stratification and possible target of future personalized interventions.
Biomarkers of multimorbidity: A systematic review
Fiorillo M.;
2025-01-01
Abstract
The development of multiple chronic diseases in the same individual (i.e., multimorbidity) results from the loss of homeostasis across several biological systems. Identifying pathophysiological pathways common to multiple diseases, using accessible biomarkers, could increase our understanding of multimorbidity and improve its prognostication and management. We conducted a systematic review of peer-reviewed articles published till September 2024 that investigated biomarkers of multimorbidity. Due to study heterogeneity, a synthesis without meta-analysis was performed on 43 studies employing harvest plots based on direction of effect, sample size and study quality. Findings highlight how inflammatory and metabolic biomarkers, such as interleukin-6 (IL-6) and glycated haemoglobin (HbA1c) especially, but also triglycerides, low-density lipoprotein (LDL) cholesterol and kidney and liver markers, along with markers of neurodegeneration including Neurofilament Light Chain (NfL) and Phospho-Tau 217 (p-tau 217), were directly associated with multimorbidity. Nonetheless, evidence for hormonal and vascular activation markers, as well as more novel geroscience biomarkers, remains limited. These markers could have a key role in identifying individuals at high risk of developing or worsening multimorbidity. The review also highlights how methodological challenges, including heterogeneity in study design, populations, and multimorbidity definitions, impact on comparability and generalizability of findings. Addressing these gaps through standardized, longitudinal studies and multi-omics approaches is crucial to improve our understanding of the pathophysiological mechanisms of multimorbidity. In summary, this review outlines the independent association of diverse biomarkers with multimorbidity, opening to the possibility of identifying specific pathophysiological pathways for risk stratification and possible target of future personalized interventions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


