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

Conditions: Major Depressive Disorder (MDD), Anxiety Disorder, Alcohol Use Disorder (AUD)

Sex: All

Ages: 18 Years – 60 Years

Healthy volunteers: Yes

Enrollment: 680

Sponsor: Huashan Hospital

Location: Peking University Sixth Hospital Beijing

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.

Eligibility Criteria

Inclusion Criteria: 1. Diagnosis: The primary diagnosis meets the DSM-IV criteria for depressive disorder, generalized anxiety disorder, or alcohol use disorder, and comorbid conditions may be present; 2. Patients with mental disorders aged 18-60 years, with a balanced gender ratio; 3. Normal intelligence and ability to use a smartphone running the Android operating system; 4. Willingness to wear a wristband equipped with physiological monitoring functions (such as heart rate and electrodermal activity), download the study application, and upload data during the study period; 5. Participants with depression or generalized anxiety disorder who are taking medication must be on a single stable dose of a selective serotonin reuptake inhibitor (SSRI), specifically citalopram or escitalopram, and this medication regimen must have been maintained for at least 5 days. Participants with alcohol use disorder who are taking medication have no restriction on the type of drug, but the medication regimen should also have been maintained for at least 5 days. At baseline assessment, patients with depression or anxiety disorders should have a Hamilton Depression Rating Scale (HAMD-17) score \>7 or a Hamilton Anxiety Rating Scale (HAMA-14) score \>7.; 6. Voluntary participation in this study and signing of informed consent; 7. For patients with alcohol use disorder (AUD): AUD patients must have successfully completed alcohol withdrawal, confirmed by clinical standards or relevant healthcare professionals. Inclusion Criteria for Healthy Control Group 1. Healthy subjects aged 18-60 years, with a balanced gender ratio; 2. Normal intelligence and ability to use a smartphone running the Android operating system; 3. Willingness to wear a wristband equipped with physiological monitoring functions (such as heart rate and electrodermal activity), download the study application, and upload data during the study period; 4. Voluntary participation in this study and signing of informed consent. Exclusion Criteria: 1. Currently taking opioid medications; 2. Receiving any form of brain stimulation therapy within the past 1 month (including transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), or other similar treatments); 3. Skin infection or severe skin damage on the wrist or upper limbs that may affect the normal use of monitoring devices; 4. Recent use (within 30 days) of medications that may interfere with drug metabolism, such as strong CYP450 inhibitors/inducers; 5. Severe physical diseases (such as brain tumors or injuries) or special conditions (such as current pregnancy or lactation) that may affect the study protocol; 6. HAMD-17 item 3 (suicide) \>3 points (severe suicidal behavior); Exclusion Criteria for Healthy Control Group 1. Currently using benzodiazepines or opioid medications; 2. Currently receiving any form of brain stimulation therapy (including transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), or other similar treatments); 3. Skin infection or severe skin damage on the wrist or upper limbs that may affect the normal use of monitoring devices; 4. Recent use (within 30 days) of medications that may interfere with drug metabolism, such as strong CYP450 inhibitors/inducers, or not reaching steady-state drug concentration before the study; 5. Severe physical diseases (such as brain tumors or injuries) or special conditions (such as current pregnancy or lactation) that may affect the study protocol.

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Source: ClinicalTrials.gov (NCT07571226). StuddyBuddy aggregates publicly available trial information.