# Biological Risk Factors for Suicidal Behavior in Children and Adolescents: A Narrative Review

## TL;DR

This paper reviews biological factors linked to suicidal behavior in children and adolescents, highlighting how they interact with psychosocial risks.

## Contribution

The paper provides a narrative synthesis of recent biological mechanisms contributing to youth suicidality.

## Key findings

- Dysfunction in the serotonin system and impaired neuroplasticity are key neurobiological risk factors for suicidality.
- Stress-related pathways like the HPA axis and chronic inflammation are linked to biological risk factors for suicide.
- Therapeutic agents like ketamine and lithium show limited anti-suicidal efficacy in youth.

## Abstract

What are the main findings?
Biological risk factors contribute to suicidality in interaction with established psychosocial risk factors.Key neurobiological risk factors of suicidality include dysfunction in the serotonin system, impaired neuroplasticity (marked by glutamate–GABA imbalance and reduced BDNF), and dysregulation of stress-response pathways, including the HPA axis and chronic inflammation.

Biological risk factors contribute to suicidality in interaction with established psychosocial risk factors.

Key neurobiological risk factors of suicidality include dysfunction in the serotonin system, impaired neuroplasticity (marked by glutamate–GABA imbalance and reduced BDNF), and dysregulation of stress-response pathways, including the HPA axis and chronic inflammation.

What are the implications of the main findings?
A deeper understanding of these biological mechanisms is essential for the development of targeted prevention and intervention strategies tailored to the unique developmental needs of children and adolescents.Future research must prioritize longitudinal data and integrative, developmentally informed models to clarify causal mechanisms and overcome current challenges in translating biological findings into clinical practice.

A deeper understanding of these biological mechanisms is essential for the development of targeted prevention and intervention strategies tailored to the unique developmental needs of children and adolescents.

Future research must prioritize longitudinal data and integrative, developmentally informed models to clarify causal mechanisms and overcome current challenges in translating biological findings into clinical practice.

Suicidal behavior in children and adolescents is a major global public health issue, and suicide is one of the leading causes of death in this age group. While psychosocial determinants of suicidality are well established, understanding its biological risk factors is crucial for targeted prevention and treatment. This review presents a narrative synthesis of recent literature examining current evidence on the biological mechanisms that contribute to youth suicidality. Genetic liability plays a substantial role, often interacting with environmental stressors. Key neurobiological factors include dysfunction of the serotonin system and impaired neuroplasticity, characterized by a glutamate–gamma-aminobutyric acid imbalance and reduced brain-derived neurotrophic factor. Psychosocial stress appears linked to these changes through several pathways, including dysregulation of the hypothalamic–pituitary–adrenal axis, chronic low-grade inflammation, oxidative stress, and activation of the kynurenine pathway. Neurodevelopmental conditions like autism spectrum disorders and attention deficit hyperactivity disorder, as well as sleep disturbances, may further increase risk. While therapeutic agents such as ketamine and lithium target these neurobiological systems, evidence for their anti-suicidal efficacy in youth remains limited, with only a small number of randomized controlled trials conducted in pediatric populations. Biological research offers valuable insights, but the use of varied study methods and a lack of longitudinal data complicate its translation into clinical practice. Future studies should employ integrative, developmentally informed models to elucidate causal mechanisms and inform more effective interventions.