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Approved research

Identify biomarkers for distinguishing different mental disorders using brain images and their associations with genetic risk

Principal Investigator: Dr Yuhui Du
Approved Research ID: 34175
Approval date: February 4th 2019

Lay summary

We aim to investigate neuroimage-based biomarkers and disease-specific genetic variants for distinguishing different brain disorders since some mental disorders currently diagnosed using clinical symptoms have similar symptoms and shared risk genes. We will work on data of T1 and T2 brain MRI, resting and task functional brain MRI, diffusion brain MRI as well as genetic data from patients with schizophrenia (SZ), bipolar disorder (BP), schizoaffective disorder (SAD), autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC). We expect to reveal shared brain abnormalities across these disorders and identify disease-specific brain alterations and genetic variants for each disorder. Our goal is to improve the diagnosis, prediction, prevention and treatment of brain disorders by using measures from brain images and genes. Therefore, our project accords with the aims of UK Biobank project. In our project, biologically meaningful measures obtained from brain functional and structural imaging data as well as genetics are expected to provide biological markers for distinguishing different mental disorders. We will compute voxel-based morphometry using structure MRI, functional networks using functional MRI and PET, white-matter mapping using diffusion images, genetic association, as well as the fusion of the above measures. Based on these measures, we will identify markers and classify brain disorders, which will in turn help to understand the mechanism of disorders and diagnose the brain disease. In the project, we expect to include all the subjects with imaging data in BioBank as it becomes available, although we may primarily focus on patients with mental disorders. We want to include the full imaged cohort of all available data. In addition, we would get both self-report and medical record data if we can. The timeline is as follows. Month 1: Download, organize and preprocess all the imaging and genetic data. Month 2-3: Extract measures from the structural, diffusion, functional MRI data and genetic variants. Month 4-5: Identify markers, investigate associations, and classify individual subjects.

Scope extension:

We aim to investigate neuroimage-based biomarkers for distinguishing different mental disorders and their associates with genetic risk, since many mental disorders currently diagnosed using clinical symptoms have overlapping symptoms and shared risk genes. We will work on data including T1 and T2 brain MRI, resting and task functional brain MRI, diffusion brain MRI as well as genetic data from patients with schizophrenia (SZ), bipolar disorder (BP), schizoaffective disorder (SAD), autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC). We expect to reveal shared brain abnormalities among these disorders and identify disease-specific brain alterations and genetic risk for each disorder.

In addition to the current scope of research, we are going to explore aging-related brain alteration, since aging of the population becomes a serious problem. Besides, as the COVID-19 pandemic is an ongoing global pandemic of coronavirus disease, we also hope to explore the impact of the disease on brain. Regarding the goals, we will work on a large amount of data including T1 and T2 brain MRI, resting and task functional brain MRI, diffusion brain MRI, genetic data, demographics, population characteristics, as well as cognitive behavioral data.

Scope extension:

We aim to investigate neuroimage-based biomarkers for distinguishing different mental disorders and their associates with genetic risk, since many mental disorders currently diagnosed using clinical symptoms have overlapping symptoms and shared risk genes. We will work on data including T1 and T2 brain MRI, resting and task functional brain MRI, diffusion brain MRI as well as genetic data from patients with schizophrenia (SZ), bipolar disorder (BP), schizoaffective disorder (SAD), autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC). We expect to reveal shared brain abnormalities among these disorders and identify disease-specific brain alterations and genetic risk for each disorder.

In addition to the current scope of research, we are going to explore aging-related brain alteration, since aging of the population becomes a serious problem. Besides, as the COVID-19 pandemic is an ongoing global pandemic of coronavirus disease, we also hope to explore the impact of the disease on brain. Regarding the goals, we will work on a large amount of data including T1 and T2 brain MRI, resting and task functional brain MRI, diffusion brain MRI, genetic data, demographics, population characteristics, as well as cognitive behavioral data.

In addition to the current scope of research, we are going to investigate the impact of macro-environmental factors, such as climate and temperature, on brain structure, function, and mental well-being. To do this, we need to map the approximate address of the participants to a location on a spatial map which is sampled at 100m resolution. As such, we would like to request the data with the field IDs 22700, 22701, 22702, 22703, and 22704.