Contextual modifiers of healthspan, lifespan, and epigenome in mice under chronic social stress

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 120; no. 16; p. e2211755120
• Main Authors: Razzoli, Maria, Nyuyki-Dufe, Kewir, Chen, Brian H., Bartolomucci, Alessandro
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 18.04.2023
• Subjects: Age related diseases; Aggression; Aging; Aging - genetics; Animal models; Animals; Biological Sciences; Discriminant analysis; Epigenetics; Epigenome; Fat-free body mass; Humans; Life expectancy; Life span; Longevity - genetics; Machine learning; Male; Mice; Mice, Inbred C57BL; Population studies; Psychological stress; Ranking; Rodents; Social determinants of health; Social interactions; Social rank; Socioeconomics; Stress, Psychological - genetics; social status; social determinants of health; aging; epigenetic; strain differences
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.2211755120

Sustained life stress and low socioeconomic status are among the major causes of aging-related diseases and decreased life expectancy. Experimental rodent models can help to identify the underlying mechanisms, yet very few studies address the long-term consequences of social stress on aging. We conducted a randomized study involving more than 300 male mice of commonly used laboratory strains (C57BL/6J, CD1, and Sv129Ev) chosen for the spontaneous aggression gradient and stress-vulnerability. Mice were exposed to a lifelong chronic psychosocial stress protocol to model social gradients in aging and disease vulnerability. Low social rank, inferred based on a discretized aggression index, was found to negatively impact lifespan in our study population. However, social rank interacted with genetic background in that low-ranking C57BL/6J, high-ranking Sv129Ev, and middle-ranking CD1 mice had lower survival, respectively, implying a cost of maintaining a given social rank that varies across strains. Machine learning linear discriminant analysis identified baseline fat-free mass as the most important predictor of mouse genetic background and social rank in the present dataset. Finally, strain and social rank differences were significantly associated with epigenetic changes, most significantly in Sv129Ev mice and in high-ranking compared to lower ranking subjects. Overall, we identified genetic background and social rank as critical contextual modifiers of aging and lifespan in an ethologically relevant rodent model of social stress, thereby providing a preclinical experimental paradigm to study the impact of social determinants of health disparities and accelerated aging.