UK Biobank Data on Depression Genetic Risk and Self-Harm Associations

A 2026 study by Eunji Jeong uses data from 91,778 UK Biobank participants of European ancestry to investigate the causal effect of major depression polygenic risk scores on self-harm. The research employs a causal forest approach to estimate average and heterogeneous treatment effects, moderated by environmental and personal factors. The dataset is available as a DOCX file under a CC-BY-4.0 license.

Use Cases

• Estimating heterogeneous treatment effects of genetic risk on self-harm based on the causal forest methodology described.
• Investigating moderation of genetic risk by environmental factors like physical violence or partner belittlement.
• Analyzing how socioeconomic factors like income or age attenuate genetic associations with self-harm.
• Replicating causal inference analyses for polygenic risk scores in a large biobank cohort.

Strengths

• Data is derived from a large cohort of 91,778 UK Biobank participants.
• Analysis focuses on a specific, high-risk genetic group (top 10% MD PRS).
• Study design explicitly examines causal relationships and effect heterogeneity.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is limited to individuals of European ancestry, which may limit generalizability.

Provenance

Source

UK Biobank

Collection Method

Likely contains derived statistical analysis results from a genetic epidemiology study.

Time Range

null

Freshness

Last updated 2026-04-13 08:40:03; freshness should be verified.

Geography

United Kingdom (UK Biobank participants)