Impact of Social Connectedness on Neuroinflammation and Brain Architecture in Non-Human Primates
Bibliographic record
Abstract
Social connectedness plays a critical role in the mental and physical health of primates, including humans.1-3 Social isolation and loneliness have been linked to a variety of negative health outcomes, such as increased risk of neurological disorders like Alzheimer’s, anxiety, and depression.2 Despite extensive research on the effects of early isolation, there is limited understanding of the neurobiological consequences of social deprivation during adulthood. This project aims to fill this gap by exploring how changes in social connectedness influence neuroinflammation and brain architecture in non-human primates (NHPs). The study utilized a longitudinal design involving 19 adult cynomolgus macaques to examine the effects of social living conditions on neuroinflammation and brain structure. The NHPs were first housed in group living conditions, transitioned to single-living conditions, and finally returned to group living. Multimodal neuroimaging was conducted to evaluate changes in cortical thickness, myelination, and brain connectivity across these phases. Blood and cerebrospinal fluid samples were collected at multiple time points to assess levels of pro-inflammatory cytokines (TNF-a, IL-1β, IL-6) and a biomarker for neuroplasticity (BDNF).4-6 Advanced biomarker detection technology, such as SIMOA, ELISA, and Luminex, could be leveraged to achieve highly sensitive measurements of these markers.7,8 Preliminary findings indicate that social deprivation leads to decreases in cortical thickness and myelination in key brain regions associated with social cognition; however, these changes may be reversible upon reintroduction to group living.9-12 This study hypothesizes that the observed structural changes correlate with increases in neuroinflammatory markers. If confirmed, these results could highlight the critical role of social connectedness in maintaining brain health and suggest potential biomarkers for loneliness and related neuropsychiatric conditions. This research could inform interventions aimed at mitigating the negative health impacts of social isolation and improve welfare standards in NHP research, enhancing the translational relevance of such models to human health. References Holt-Lunstad J, Steptoe A. Social Isolation: An underappreciated determinant of physical health. Current Opinion in Psychology. 2022;43:232-237. doi:10.1016/j.copsyc.2021.07.012 Bzdok D, Dunbar RIM. The neurobiology of social distance. Trends in Cognitive Sciences. 2020;24(9):717-733. doi:10.1016/j.tics.2020.05.016 Cacioppo JT, Cacioppo S. The growing problem of loneliness. The Lancet. 2018;391(10119):426. doi:10.1016/s0140-6736(18)30142-9 Magalhães DM, Mampay M, Sebastião AM, Sheridan GK, Valente CA. Age-related impact of social isolation in mice: Young vs middle-aged. Neurochemistry International. 2024;174:105678. doi:10.1016/j.neuint.2024.105678 Van Bogart K, Engeland CG, Sliwinski MJ, et al. The association between loneliness and inflammation: Findings from an older adult sample. Frontiers in Behavioral Neuroscience. 2022;15. doi:10.3389/fnbeh.2021.801746 Bathina S, Das UN. Brain-derived neurotrophic factor and its clinical implications. Archives of Medical Science. 2015;6:1164-1178. doi:10.5114/aoms.2015.56342 Lasseter HC, Provost AC, Chaby LE, Daskalakis NP, Haas M, Jeromin A. Cross-platform comparison of highly sensitive immunoassay technologies for cytokine markers: Platform performance in post-traumatic stress disorder and parkinson’s disease. Cytokine: X. 2020;2(2):100027. doi:10.1016/j.cytox.2020.100027 Platchek M, Lu Q, Tran H, Xie W. Comparative analysis of multiple immunoassays for cytokine profiling in drug discovery. SLAS Discovery. 2020;25(10):1197-1213. doi:10.1177/2472555220954389 Miller JG, López V, Buthmann JL, Garcia JM, Gotlib IH. A social gradient of cortical thickness in adolescence: Relationships with neighborhood socioeconomic disadvantage, family socioeconomic status, and depressive symptoms. Biological Psychiatry Global Open Science. 2022;2(3):253-262. doi:10.1016/j.bpsgos.2022.03.005 Yang Y, Cheng Z, Tang H, et al. Neonatal maternal separation impairs prefrontal cortical myelination and cognitive functions in rats through activation of Wnt Cerebral Cortex. Published online May 13, 2016. doi:10.1093/cercor/bhw121 Sallet J, Mars RB, Noonan MP, et al. Social network size affects neural circuits in macaques. Science. 2011;334(6056):697-700. doi:10.1126/science.1210027 Makinodan M, Rosen KM, Ito S, Corfas A critical period for social experience–dependent oligodendrocyte maturation and myelination. Science. 2012;337(6100):1357-1360. doi:10.1126/science.1220845
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".