Aims:Current research has found that conventional lifestyle factors (such as diet, physical activity, smoking and alcohol, electronic devices use), adverse life experience, other individual behaviors (such as social media exposure), and health and medical history have been associated with mental illnesses including psychiatric disorders and cognitive dysfunction. Whether these environmental risk factors play a synergistic role in the genetic mechanism of mental illnesses warrants further investigation. Although abdundant neuroimaging studies have been conducted to look for unique brain structural and functional changes related to mental illnesses, large-sample studies are highly encouraged to estabilish replicatable and solid neuroimaging phenotypes. To sum up, we plan to utilize UK Biobank data to quantify environmental, genetic, and neuroimaging contribution to mental illnesses and establish artificial intelligence-based representation model by means of imaging genetics.
In the time span of 36 months, the aims of this research are: (1) to investigate environmental factors (such as adverse life experience, lifestyle, and psychosocial factors) of mental illnesses including psychiatric disorders and cognitive dysfunction; (2) to identify genetic endotypes of mental illnesses and resultant metabolic disturbances (such as endocrine disorders and cardiovascular diseases); (3) to study gene-environmental interaction of the above-mentioned illnesses; (4) to identify distinct brain structural features by measuring T1 structural brain MRI, T2-weighted brain MRI and diffusion brain MRI, and functional features via resting-state fMRI or arterial spin labelling brain MRI of common mental illnesses; (5) to identify how genetic and environmental risk, through transcriptome regulation, is linked to neural dysconnectivity and how their connection in turn contributes to clinical deficits in mental illnesses; (6) with machine learning methods to establish classification and prognosis prediction models with genetic, environmental, and neuroimaging markers.
We hope the results of this study could help us better understand the onset and development of mental illnesses in a biopsychosocial way and learn more about how genetic and environmental factors contribute to clinical deficits thourgh neural activities.
