Precision medicine for suicidality: from universality to subtypes and personalization

Area of Science:

• Genomics
• Psychiatry
• Biomarker Discovery

Background:

• Suicide is a major public health issue, particularly in individuals with psychiatric disorders.
• Current methods for identifying suicide risk and monitoring treatment response require improvement.

Purpose of the Study:

• To identify universal blood gene expression biomarkers for suicide risk across diverse populations.
• To explore subtypes of suicidality and personalized biomarker approaches.
• To investigate the biological mechanisms and potential therapeutic targets for suicide.

Main Methods:

• Utilized a multi-step approach for biomarker discovery, prioritization, and validation in large cohorts.
• Tested predictive abilities of biomarkers for suicidal ideation and future hospitalizations.
• Examined subtypes of suicidality and personalized approaches based on gender and diagnosis.
• Investigated mechanistic pathways and potential drug repurposing for identified biomarkers.

Main Results:

• Identified novel predictive biomarkers (e.g., CLN5, AK2) and validated others (e.g., SLC4A4, SKA2).
• Discovered four potential subtypes of suicidality (high anxiety, low mood, combined, non-affective).
• Demonstrated enhanced prediction precision with subtype and personalized approaches, particularly for males with depression.
• Identified biological pathways implicated in suicide, including neurogenesis, cell death, insulin signaling, and mTOR signaling.
• Achieved high predictive accuracy (90% AUC for suicidal ideation, 77% for hospitalizations).

Conclusions:

• Blood gene expression biomarkers can effectively track and predict suicide risk.
• Subtype and personalized approaches improve prediction accuracy.
• Identified biomarkers offer insights into suicide biology and potential therapeutic targets.
• APOE and IL6 emerge as key universal biomarkers suggesting an inflammatory component.