The association between aging-related monocyte transcriptional networks and comorbidity burden: the Multi-Ethnic Study of Atherosclerosis (MESA).

Translating our knowledge of the biological aging from animal models to humans may give rise to novel approaches of targeting multiple aging-related diseases simultaneously and increasing health span. Here, for the first time, we use transcriptomic signatures of monocytes to identify biological aging pathways underlying multiple aging-related diseases in humans. The ordinal logistic regression was used to cross-sectionally investigate transcriptomics of the comorbidity index in 1264 community-based Multi-Ethnic Study of Atherosclerosis (MESA) adults, 47% Caucasian, 32% Hispanic, 21% African American, and 51% female, aged 55-94 years. The comorbidity index was defined as the number of prevalent aging-related diseases including cardiovascular disease, type-2 diabetes, hypertension, cancer, dementia, chronic kidney disease, chronic obstructive pulmonary disease, and hip fracture. We identified 708 gene transcripts associated with the comorbidity index (FDR < 0.05) after adjusting for age, sex, ethnicity, and study site. In a weighted gene co-expression network analysis, as postulated, aging-related declines in apoptosis/autophagy (OR = 1.21 per SD increment, p = 0.0006) and ribosome/mitochondrion (OR = 0.90 per SD increment, p = 0.05) were positively associated with the comorbidity index. After adjusting for multiple comparisons, we identified 10 comorbidity-associated modules (FDR < 0.05), including the module of apoptosis/autophagy. There were three inter-correlated modules of these 10 involved in the complement subcomponent C1q, Fc gamma receptor I, and Fc gamma receptor III of the immune system, respectively. Aging-related upregulation of these three modules was positively associated with the comorbidity index. The odds of comorbidity increased with more of these modules acting together in a dose-response fashion. In conclusion, transcriptomic analysis of human immune cells may identify biomarker panels indicative of comprehensive biological mechanisms, especially immune signaling pathways, contributing to health aging.

Duke Scholars

Author Yongmei Liu Medicine, Cardiology