Alterations in brain network organization in adults with obesity as compared to healthy-weight individuals and seniors.

OBJECTIVE Life expectancy and obesity rates have drastically increased in recent years. An unhealthy weight is related to long-lasting medical disorders that might compromise the normal course of aging. The aim of the current study of brain connectivity patterns was to examine whether adults with obesity would show signs of premature aging, such as lower segregation, in large-scale networks. METHODS Participants with obesity (N = 30, mean age 32.8± 5.68) were compared to healthy-weight controls (N = 33, mean age 30.9± 6.24) and senior participants who were stroke-free and without dementia (N = 30, mean age 67.1± 6.65 years) using resting-state MRI and graph theory metrics (i.e., small-world index, clustering coefficient, characteristic path length, and degree). RESULTS Contrary to our hypothesis, participants with obesity exhibited a higher clustering coefficient compared to senior participants (t = 5.06, p < 0.001, d= 1.23, CIbca 95% [0.64, 1.88]). Participants with obesity also showed lower global degree relative to seniors (t = -2.98, p = 0.014, d= -0.77, CIbca 95%[-1.26, -0.26]) and healthy-weight controls (t = -2.92, p = 0.019, d= -0.72, CIbca 95% [-1.19, -0.25]). Regional degree alterations in this group were present in several functional networks. CONCLUSIONS Participants with obesity displayed greater network clustering than seniors and also had lower degree compared to seniors and individuals with normal weight, which is not consistent with the notion that obesity is associated with premature aging of the brain. Although the cross-sectional nature of the study precludes causal inference, the overly clustered network patterns in obese participants could be relevant to age-related changes in brain function because regular networks might be less resilient and metabolically inefficient.