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Distinguishing clinical and genetic risk factors for suicidal ideation and behavior in a diverse hospital population

  • Sarah M.C. Colbert
  • , Lauren Lepow
  • , Brian Fennessy
  • , Nakao Iwata
  • , Masashi Ikeda
  • , Takeo Saito
  • , Chikashi Terao
  • , Michael Preuss
  • , Jyotishman Pathak
  • , J. John Mann
  • , Hilary Coon
  • , Niamh Mullins

Research output: Contribution to journal › Article › peer-review

Abstract

Suicidal ideation (SI) and behavior (SB) are major public health concerns, but risk factors for their development and progression are poorly understood. We used ICD codes and a natural language processing algorithm to identify individuals in a hospital biobank with SI-only, SB, and controls without either. We compared the profiles of SB and SI-only patients to controls, and each other, using phenome-wide association studies (PheWAS) and polygenic risk scores (PRS). PheWAS identified many risk factors for SB and SI-only, plus specific psychiatric disorders which may be involved in progression from SI-only to SB. PRS for suicide attempt were only associated with SB, and even after accounting for psychiatric disorder PRS. SI PRS were only associated with SI-only, although not after accounting for psychiatric disorder PRS. These findings advance understanding of distinct genetic and clinical risk factors for SB and SI-only, which will aid in early detection and intervention efforts.

Original languageEnglish
Article number63
JournalTranslational psychiatry
Volume15
Issue number1
DOIs
Publication statusPublished - 12-2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Biological Psychiatry

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