Jiayuan XU, MD | Tianjn Medical University General Hospital; Nana Liu, MD; Qiaojun Li, PhD; Guoshu Zhao, MD candidate; Nannan Zhang, MS candidate; Shaoying Wang, MS candidate
Competition Sponsor: Chinese Academy of Medical Sciences
Awardee Year: 2024
Geriatric depression is a common mental disorder that significantly diminishes the life quality for the aging global population. Accurately predicting those at risk is crucial, yet we confront significant challenges due to the scarcity of reliable biomarkers.
In this project, our team introduces the innovative NeuroImaging ExposoGenomics (NIEG) strategy, designed to uncover the neural mechanisms by which genetic and environmental factors influence cognition and mental health. By harnessing genetic statistics, remote-sensing, and neuroimaging technology, we aim to identify neuroimaging biomarkers based on NIEG and to develop risk prediction and stratification tools for depression leveraging machine learning.
Our team has developed a NIEGP platform, which offers personalized NIEG depression risk scores, risk genes, lifetime risk environment exposures, neuroimaging biomarkers, and predictive tools to address the unmet needs in mental disorders, including depression. Our groundbreaking findings reveal that participants with higher CRHR1 genetic risk, living in urban environments characterized by poverty, reduced greenness, and complex street networks, especially during adolescence, exhibit reduced reward-processing brain volumes and severe affective symptoms. The risk of these individuals developing depression has increased fivefold (Nat Med, 2023; Nat Hum Behav, 2022). The NIEGP application provides personalized guidance to individuals with risk genes, targeting the risk time window under specific environmental exposures, to alleviate depressive symptoms and prevent the onset of depression. Our interdisciplinary team is based at the Tianjin Key Lab of Functional Imaging (FUNI) in China.
Our lab’s flagship program, CHIMGEN, initiated in 2015, targets the neural mechanisms underlying mental disorders that affect over one billion people worldwide. Over the past decade, we have collected comprehensive genetic, environmental, neuroimaging, and behavioral data from 13,000 Chinese-Han individuals across 31 leading centers in China, creating the world’s first NIEG dataset for a non-Caucasian population. By integrating with other international datasets, CHIMGEN offers a unique opportunity to explore the cross-ancestry effects of genomics and environment on global mental health disorders.