Shenghao Yuan

Background: The global rise in ultra-processed food (UPF) consumption and the persistent burden of mental disorders have raised growing public health concerns. Emerging evidence suggests that unfavorable dietary patterns, particularly with high UPF intake, contribute to the development of mental disorders. Objective: To assess the associations of UPF-related metabolic signatures and mental disorders. Methods: In this population-based cohort study of 30,059 participants from the UK Biobank, we first identified a plasma metabolic signature associated with UPF intake leveraging nuclear magnetic resonance metabolomics. We then applied Cox and logistic regression models to investigate the associations of both UPF consumption and its metabolic signature with incident mental disorders and specific psychological symptoms, respectively. Results: Higher UPF intake was significantly associated with increased risks of overall mental disorder (hazard ratio per 10% increment [95% confidence interval]: 1.04 [1.02, 1.06]), depressive disorder (1.14 [1.08, 1.20]), anxiety disorder (1.12 [1.06, 1.18]), and substance use disorder (1.06 [1.01, 1.11]), as well as several psychological symptoms including suicidal ideation (odds ratios [95% confidence interval]: 1.12 [1.03, 1.16]) and anxiety feeling (1.05 [1.01, 1.09]). Similarly, the UPF-related metabolic signature was independently associated with elevated risks of these mental health outcomes and partially mediated the associations between UPF intake and mental disorders. Conclusions: These findings highlighted the potential metabolic pathways underlying the neuropsychiatric risks of UPF consumption and underscored the importance of dietary quality in mental health.

Low-grade inflammation (LGI) mainly acted as the mediator of the association of obesity and inflammatory diet with numerous chronic diseases, including neuropsychiatric diseases. However, the evidence about the effect of LGI on brain structure is limited but important, especially in the context of accelerating aging. This study was then designed to close the gap, and we leveraged a total of 37,699 participants from the UK Biobank and utilized inflammation score (INFLA-score) to measure LGI. We built the longitudinal relationships of INFLA-score with brain imaging phenotypes using multiple linear regression models. We further analyzed the interactive effects of specific covariates. The results showed high level inflammation reduced the volumes of the subcortex and cortex, especially the globus pallidus (β [95% confidence interval] = −0.062 [−0.083, −0.041]), thalamus (−0.053 [−0.073, −0.033]), insula (−0.052 [−0.072, −0.032]), superior temporal gyrus (−0.049 [−0.069, −0.028]), lateral orbitofrontal cortex (−0.047 [−0.068, −0.027]), and others. Most significant effects were observed among urban residents. Furthermore, males and individuals with physical frailty were susceptive to the associations. The study provided potential insights into pathological changes during disease progression and might aid in the development of preventive and control targets in an age-friendly city to promote great health and well-being for sustainable development goals.