kai-lim / UKB_selfharm

This is one of my PhD data science projects. I used UK Biobank, a huge dataset with ~250K individuals in my research to study the aetiology of self-harm using genetic causal inference methods.

Studying individual risk factors for self-harm in the UK Biobank: A polygenic scoring and Mendelian randomisation study

This is one of my PhD data science project. I used UK Biobank, a huge dataset with ~250K individuals in my research to study the aetiology of self-harm using genetic causal inference methods.

R and bash scripts used for this project can be found here.

We investigated 24 potential individual risk factors for self-harm, using their polygenic score as an index for genetic risks. Out of these 24 risk factors, major depressive disorder, attention-deficit hyperactivity disorder and schizophrenia appeared to be the most plausible causal risk factors for self-harm. No difference emerged between risk factors for non-suicidal and suicidal self-harm.

Data visualisations:

Odds ratios of polygenic scores of each risk factor in predicting self-harm.

Predicted risk for self-harm based on quantiles of polygenic scores an individual is in.

Relative risks of self-harm for depression and schizophrenia cases (medicated and non-medicated) compared to controls.