Next-generation precision medicine for suicidality prevention

Area of Science:

• Psychiatry and Genetics
• Molecular Biology
• Biomarker Discovery

Background:

• Suicidality is a significant public health concern, particularly among mental health patients.
• Current assessment and treatment efforts are hampered by a lack of objective, quantitative measures.
• Blood biomarkers offer a potential avenue for understanding the biological underpinnings of suicidality.

Purpose of the Study:

• To identify, prioritize, validate, and test blood gene expression biomarkers for suicidality in psychiatric patients.
• To expand the understanding of the biological basis of suicidality across diagnostic categories.
• To explore potential therapeutic interventions and clinical applications of identified biomarkers.

Main Methods:

• Transdiagnostic whole-genome studies in multiple independent patient cohorts.
• Cross-sectional and longitudinal analyses of blood gene expression biomarkers.
• Integration of clinical measures, social determinants, and machine learning approaches.

Main Results:

• Identification of novel and known blood biomarkers predictive of high suicidality and future hospitalizations.
• Top biomarkers include SLC6A4 (increased expression) and TINF2 (decreased expression).
• Apoptosis-related pathways were implicated, suggesting suicidality as a stress-driven aging/death process.

Conclusions:

• Biologically, suicidality may represent an extreme stress-driven form of active aging/death.
• Identified therapeutic matches include lithium, clozapine, and ketamine, with gender-specific efficacy.
• The comprehensive approach integrating biomarkers, clinical data, and machine learning holds transformative clinical utility for suicidality assessment and treatment.