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Next-generation precision medicine for suicidality prevention.

R Bhagar1, S S Gill1,2, H Le-Niculescu1,3

  • 1Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA.

Translational Psychiatry
|September 6, 2024
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Summary
This summary is machine-generated.

New blood biomarkers for suicidality risk have been identified in psychiatric patients. These biomarkers, including SLC6A4 and TINF2, offer objective insights into the biology of suicidality and potential therapeutic targets.

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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.