By analyzing blood biomarkers from older adults, researchers have identified signals that may explain why multiple chronic diseases tend to cluster as people age. The study, published in Nature Medicine, links routine and advanced blood markers to disease patterns and progression across aging populations.
Researchers used data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), which followed over 2,200 adults aged 60 or older for up to 15 years. Participants' health was tracked through clinical interviews, physical exams, lab tests, medication records, and registry data. Diagnoses were coded according to international standards.
The team measured a range of blood biomarkers using both standard clinical assays and research-grade platforms. They then applied statistical learning methods such as LASSO regression and principal component analysis to identify connections between these markers and patterns of multimorbidity—the presence of two or more chronic conditions.
Analysis revealed five main multimorbidity patterns: Unspecific; Neuropsychiatric; Psychiatric and Respiratory; Sensory Impairment and Anemia; and Cardiometabolic. These groupings are based on statistical associations rather than discrete diagnoses.
Several biomarkers—including cystatin C, hemoglobin A1c (HbA1c), growth differentiation factor 15 (GDF15), leptin, insulin, neurofilament light chain (NfL), creatinine, and C-peptide—were associated with higher counts of chronic diseases. Hemoglobin was inversely associated overall but showed a positive link within one pattern.
Shared associations across all multimorbidity types included C-peptide, creatinine, cystatin C, GDF15, folic acid, HbA1c, insulin, leptin, and total cholesterol. Pattern-specific relationships were also observed: for example, GDF15 had stronger links with Neuropsychiatric and Cardiometabolic patterns.
Faster rates of disease accumulation correlated with higher levels of GDF15, HbA1c, cystatin C, leptin, gamma-glutamyl transferase (GGT), and insulin. Albumin was linked with slower disease accumulation.
Validation in an independent cohort from the Baltimore Longitudinal Study of Aging confirmed the biomarker associations found in the Swedish sample.
"These findings are observational and do not establish causality," researchers note in their report. "Overall, the results suggest that age-related metabolic and systemic stress reflects biological vulnerability common to multiple chronic diseases."
Long-term outcomes matched these biomarker-defined patterns: those in the Neuropsychiatric group experienced more dementia and depression cases over time; those in the Cardiometabolic group had higher rates of heart disease events. Mortality over fifteen years was greater among people with any multimorbidity pattern compared to those without multiple chronic conditions.
The study suggests that monitoring specific blood markers could help characterize biological vulnerability to multimorbidity as people age. However, translating these insights into preventive strategies remains a challenge for future research.
