Identification and Molecular Characterisation of Urban-environmental Stress Patterns Affecting Mental Illness

Brief Summary

Mental disorders have become a major contributor to the global burden of non-communicable diseases, with disability-adjusted life years (DALYs) attributable to these conditions continuing to rise. Although evidence suggests that environmental factors may account for up to 40% of the attributable risk for mental disorders such as major depressive disorder, anxiety disorders, and alcohol use disorder, the underlying mechanisms remain unclear, particularly regarding how dynamic environmental stress influences disease onset, progression, and relapse. Traditional research has primarily focused on individual-level psychosocial factors, including socioeconomic status and life events, while lacking real-time, multidimensional assessments of objective urban environmental stressors such as air pollution, noise exposure, and reduced green space. This study proposes a prospective longitudinal cohort design based in real-world environments, enrolling both patients with mental disorders and healthy controls. Using wearable devices integrated with the "'StreetMind'" mobile application and wear the visible watch, we will continuously and dynamically collect multimodal data on environmental exposures and physiological responses in urban settings. These include photoplethysmography (PPG)-derived heart rate, oxygen saturation, physical activity, and gait parameters, as well as objective environmental indicators such as temperature, humidity, light intensity, and noise levels. At baseline, all participants will undergo standardized psychiatric assessments to characterize depressive, anxiety, and addictive conditions. Peripheral blood and urine samples will also be collected for subsequent molecular and multi-omics analyses. The study aims to systematically evaluate the associations between urban environmental factors-including air pollution, noise exposure, and green space availability-and the risk of mental disorder relapse. Furthermore, it seeks to elucidate the potential mechanisms by which environmental stress affects mental health through neuroinflammation and alterations in brain circuitry. The findings are expected to provide novel insights for risk prediction, early intervention, and precision management of mental disorders.