Hang Zhou, PhD
Assistant Professor of Psychiatry, and of Biomedical Informatics and Data ScienceCards
About
Titles
Assistant Professor of Psychiatry, and of Biomedical Informatics and Data Science
Biography
Hang Zhou, PhD, is Assistant Professor of Psychiatry and of Biomedical Informatics and Data Science, Yale School of Medicine. Dr. Zhou has a broad background in computational biology and psychiatric genetics with rich experience in genomic data analyses and inferences. The main research interest is to identify novel genetic risks and explore the biological etiology for alcohol use disorder, substance use disorders and the relationship with comorbidities. Dr. Zhou’s lab will continue research on addiction, sex differences and relationship between alcohol and cancers using large-scale human genetic data (SNP array, WES and whole genome sequencing), exploring Machine Learning and leveraging brain imaging data to investigate the mechanisms through broad collaborations.
Appointments
Psychiatry
Assistant ProfessorPrimaryBiomedical Informatics & Data Science
Assistant ProfessorSecondary
Other Departments & Organizations
- Biomedical Informatics & Data Science
- Center for Brain & Mind Health
- Lab - Psychiatry - Zhou, Hang
- Psychiatry
Education & Training
- Associate Research Scientist
- Yale School of Medicine (2021)
- Postdoctoral Associate
- Yale School of Medicine (2018)
- PhD
- CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences (2015)
- BSc
- Shanghai Jiao Tong University (2009)
Research
Overview
The central goal of my graduate and postdoctoral work is to understand the human genome and how it affects human traits and diseases. To reach this goal, I completed training in population genetics during PhD and psychiatric genetics as postdoc. I performed a series of genetic studies on natural selection in the human genome and genome-wide studies on substance use disorders (SUDs) and comorbid psychiatric diseases. We were the first to study the shared genetic mechanism for SUDs and major depression comorbidity using genome-wide methods, identified a risk variant (SEMA3A) which specifically contributed to comorbid alcohol use disorder (AUD) and depression (Zhou et al., JAMA Psychiatry, 2017; highlighted by an Editorial paper in JAMA Psychiatry), and a risk variant in GRIA4 gene associated with comorbid nicotine dependence and depression (Zhou et al., Translational Psychiatry, 2018).
I was promoted to Associate Research Scientist in July 2018. During this period, I lead the analytic effort for several projects in the Million Veteran Program (MVP). We conducted the largest multi-ancestry genome-wide association study (GWAS) on alcohol consumption and AUD (Kranzler*, Zhou*, Kember* et al., Nature Communications, 2019), all five major US ancestry groups were included (African Americans, European Americans, Latino Americans, East Asian and South Asian Americans). This study delivered a key message that changed this field: AUD differs from alcohol consumption genetically. We accomplished, to our knowledge, the largest meta-analysis for problematic alcohol use (PAU) in European samples (N=435,563), tripled the number of risk variants associated with PAU (Zhou et al., Nature Neuroscience, 2020). In particular, we found that PAU is genetically correlated with many traits; phenome-wide polygenic risk score (PRS) analysis in an independent biobank (Vanderbilt University Biobank) confirmed the genetic correlations between PAU and substance use and psychiatric disorders; Mendelian randomization (MR) suggested that the liability to PAU was attributable in part to substance use, psychiatric status, risk-taking behavior and cognitive performance; and the genetic heritability of PAU was enriched in certain brain regions. We also conducted the largest-to-date genetic study of opioid use disorder (OUD) and identified functional coding variant Asn40Asp in OPRM1 associated with OUD (Zhou et al., JAMA Psychiatry, 2020). These studies made a noteworthy contribution to this field.
Currently, I am working on multiple projects in MVP, include comorbid AUD and mental disorders, and others. MVP has released the genotype data release 4 containing over 650,000 unique samples, which is presently the world’s largest genomic cohort connected to electronic health record data. I am also working on the whole exome sequencing (WES) data in Yale-Penn cohort (over 4,400 samples) for PAU and comorbid diseases (Brain Behavior Research Foundation 2018 NARSAD Young Investigator Award).
Future research plans
Based on my previous work, my future research will focus on three topics related to alcohol: 1) the genetic causality of alcohol intake and PAU on cancer risk; 2) genetics of sex differences in alcohol use and PAU; 3) advanced genetic study of PAU by incorporating WES, whole genome sequencing (WGS), functional magnetic resonance imaging (fMRI) data, and machine learning methodologies.
Medical Research Interests
Academic Achievements & Community Involvement
News & Links
Media
- GWAS of AUD and AUDIT-C in 274,424 individuals from MVP. EA: European American, AA: African American, LA: Hispanic or Latino, EAA: East Asian American, SAA: South Asian American.
- AUD differs from AUDIT-C genetically.
- Outliers were removed in MVP after 2nd round of PCA.
- More data is needed, especially in non-European populations.
News
- August 15, 2024
Human Genetics and Epigenetics of Alcohol Use Disorder
- June 12, 2024
YSM, VA Researchers Complete First Genome-Wide Association Study of Epiretinal Membrane
- April 05, 2024Source: Molecular Psychiatry
Genetic Influences and Causal Pathways Shared Between Cannabis Use Disorder and Other Substance Use Traits
- December 07, 2023
VA/Yale Researchers Lead Multi-ancestry Study of Genetics of Problematic Alcohol Use