Websites
Colleges
Min GAO
PhD
Researcher
- MSc, DPhil supervisor
- Fellow of Wolfson College
Metabolic Health and Depression, Data Science, Health Behaviours Intervention
Min Gao is an Epidemiologist and Health Behaviour Scientist focused on understanding the link between metabolic health and depression through data science and exploring interventions that can help break this connection through modifiable behaviour strategies.
Currently, Min is leading 1) NIHR ARC-funded observational and genetic research to explore the associations and mechanisms linking obesity and cardiometabolic disorders with depression, using UK Biobank, Qresearch and CPRD datasets, 2) BRC-funded clinical trial (DIME study), a dietary intervention for individuals with treatment-resistant depression, 3) investigating the use of antidiabetic medications for depression and developing improved treatment strategies for individuals with comorbid type 2 diabetes and depression.
Min welcomes world-wide collaborations in these research areas and accepts requests for supervision of Oxford DPhil and MSc students in relevant areas.
Recent publications
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Associations between dietary patterns and incident colorectal cancer in 114,443 individuals from the UK Biobank: a prospective cohort study.
Journal article
Samuel S. et al, (2024), Cancer Epidemiology, Biomarkers and Prevention
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Data from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Other
Skulsky SL. et al, (2024)
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Figure 1 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Other
Skulsky SL. et al, (2024)
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Figure 2 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Other
Skulsky SL. et al, (2024)
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Figure 3 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Other
Skulsky SL. et al, (2024)