Applying a new approach to rhesus macaque groups to realistically model individual, family, and group health across the lifespan in human populations.
Humans live in societies full of rich and complex relationships that influence our physical and mental health and well-being. In both human and nonhuman primates, social life, and its interaction with factors such as personality, influence our health in complex ways.
In order to treat and prevent illness and improve human health, we need a detailed understanding of the interplay between biological systems and social contexts that contribute to disease processes.
Dr. Brenda McCowan, Core Scientist with CNPRC Brain, Mind, and Behavior Unit and Professor with the Department of Population Health and Reproduction, School of Veterinary Medicine (PHR), heads up a research program to uncover these complex relationships. Dr. McCowan, in collaboration with co-investigators at the CNPRC, School of Veterinary Medicine, School of Medicine and College of Arts and Sciences, is conducting a series of social network studies to understand the mechanisms by which social systems influence physical and mental health and well-being in rhesus macaques (Macaca mulatta), a nonhuman primate species that shares a close evolutionary history and behavioral biology with humans. They outline, in a new invited perspective paper published in Frontiers: Psychology entitled “Connections matter: social networks and lifespan health in primate translational models”, the novel computational approach they are using to treat and understand health and well-being as a “complex system”.
The research animals are rhesus macaques, a highly social nonhuman primate species, housed outdoors in large, half-acre field corrals in a rich social environment that mimics those found in the wild.
Investigating the interplay among biological systems (for example the immune and neuroendocrine systems) and social systems across the lifespan, the research team is demonstrating that nonhuman primate systems are of sufficiently similar complexity to humans to serve as a model for the development and refinement of both analytical and theoretical frameworks linking social life to health.
A new approach
Maintaining optimal health is influenced by a wide range of factors, some specific to the individual (for example personality, genetic predispositions, or ancestry) and some specific to the social environment (for example kinship, group composition, and social stressors such as one’s social role or overall group stability).
The research team represents a cross-disciplinary collaborative effort between the School of Veterinary Medicine (i.e. Professor Brenda McCowan; Assistant Project Scientists Brianne Beisner, PhD, and Darcy Hannibal, PhD; and Professional Researcher Eliza Bliss-Moreau, PhD), the CNPRC (Postdoctoral researchers Jessica Vandeleest, PhD, and Jian Jin, PhD), and the Department of Statistics (Professor Hsieh Fushing, PhD).
The team is applying this new social systems science approach to rhesus macaque groups at the CNPRC to realistically model individual, family, and group health across the lifespan in human populations.
The McCowan Lab’s computational systems science approaches overcome prior limitations in experimental design and data analysis. Scientists had to date been unable to effectively model the extraordinarily complex dynamic nature of the social environment in concert with a full picture of what it means for an individual to “be healthy.”
Decades of research have documented the effect of social context on physical and mental health in humans and nonhuman primates. In humans, characteristics of the social environment such as socioeconomic status influence diverse health outcomes ranging from cardiovascular disease to mood disorders such as depression. Also in humans, it is well known that deleterious social relationships, such as those that occur in the context of abuse, have similar negative outcomes on physical health and mental health.
Mirroring the effect in humans, research from the CNPRC and others are demonstrating that a nonhuman primate’s absolute social rank (akin to human class), the certainty of that social rank (akin to predictably/unpredictably in relationships), and the individual’s level of sociality are key factors influencing individual-level health outcomes. Recent advances in this knowledge, such as the impact of relationship predictability, have come from advanced analytical approaches such as the computational network methods developed by the McCowan Lab.
On a biological level, social instability with rhesus macaques has been shown to alter neuroendocrine function and sympathetic innervation of lymphoid tissue, and rhesus macaques rated to be less “sociable” had elevated plasma cortisol concentrations and poorer immune responses to an HIV-like virus. Low social rank, social instability and reduced sociality all significantly reduce survival after infection with a HIV-like virus.
In contrast to these negative effects is the growing evidence that both humans and nonhuman primates that have many social connections, which include those that are direct such as “friends” but also indirect such as “friends of friends”, are buffered against stressful experiences, experience less loneliness, recover more fully from acute episodes of depression, experience less disease, and live longer.
Social life in human and nonhuman primates is multi-layered and always changing—individual relationships differ in number, quality and type that are embedded within multiple broader social contexts of family, social class, and community. Also, individuals can belong to multiple groups simultaneously which may exert differential influence on the individual at different times or in different contexts. Factors like these shape an individual’s “social role” as well as “social experience”, which is known to relate to both physical and mental health.
Yet while known, these social factors are incredibly challenging to model in humans. The investigators present a solution to these issues by using a nonhuman primate model of human social-life and health in concert with sophisticated novel computational network approaches.
Future biomedical research can address this issue directly by using socially and environmentally relevant subjects whenever possible. Indeed, with newer, more advanced and less invasive methods for collecting and analyzing biological samples in the field, wild populations of nonhuman primates may provide additional translational opportunities. Field-based biomedical research on genetically, socially, and behaviorally well-characterized nonhuman primate populations could transform our understanding of threshold, collective, and emergent effects of the social environment on health outcomes.
This work was supported by the National Institutes of Health (R01-HD068335; R24-OD024936; and CNPRC base grant NIH P51OD01107-53) and the Division of Behavioral and Social Research at the National Institute on Aging (contract No. 3438581).
McCowan B, Beisner B, Bliss-Moreau E, Vandeleest J, Jin J, Hannibal D, Hsieh F. Connections Matter: Social Networks and Lifespan Health in Primate Translational Models. Frontiers in Psychology 2016 Apr 22;7:433. PMC4841009