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Research / Funded grants

2022 Pilot Research Grant

Investigation of the Neural Correlates of the Acquired Capability for Suicide in Child and Adult Brains

2 research findings from this AFSP-funded study.

Research finding · December 2025

Certain changes in brain development during early adolescence may be related to suicidal behavior

As children move into early adolescence, their brains and behavior undergo rapid changes that shape how they respond to emotions, stress, and reward. For most youth, this is simply part of growing up, but for some, these shifts may play a role in the emergence of suicidal thoughts or behaviors. Understanding which developmental patterns signal vulnerability is an important step toward earlier, more supportive interventions. Large longitudinal studies that follow children over several years offer a unique window into how brain development and emotional health interact over time. By examining these patterns before a crisis occurs, researchers can begin identifying early indicators in young people might need extra support during this sensitive transitional period.

Using data from more than 11,000 participants in the Adolescent Brain Cognitive Development (ABCD) Study, Dr. Yi Zhou tracked changes in brain structure and behavior over two years from ages 10 to 12, comparing three groups of youth: those who later developed suicidal behaviors, those who experienced suicidal thoughts only, and those with no suicide-related experiences. The youth who went on to engage in suicidal behavior showed the fastest reductions in cortical gray matter volume, a sign that their brains were maturing at a different pace than their peers. They also showed the largest increases in depression symptoms over time. One behavioral pattern stood out as well: while most children show a natural decline in reward-seeking behavior (e.g., desire for novelty, impulsivity, spontaneity) as they move through early adolescence, the group that later engaged in suicidal behavior did not show this decline. When Dr. Zhou looked across the broader sample, he also found that lower gray matter volume at baseline predicted higher reward-seeking behavior two years later, suggesting a meaningful link between early brain development and later behavioral tendencies. Taken together, the findings point to a combination of factors that may help identify youth on a pathway toward suicidal behavior before those behaviors begin.

Citation: Zhou, Y., & Neale, M. C. (2025). Adolescent suicide behaviors associate with accelerated reductions in cortical gray matter volume and slower decay of behavioral activation Fun-Seeking scores. Scientific reports, 15(1), 32886. https://doi.org/10.1038/s41598-025-16856-y

This finding comes from an AFSP-funded study — see the grant below ↓

Research finding · May 2025

Brain structure may relate to suicidal attempts in adulthood and late adolescence

Suicide prevention efforts have long sought reliable, objective markers that could help identify individuals at elevated risk before a crisis occurs. Brain structure has emerged as a promising area of investigation, with research increasingly linking certain neurobiological features to suicidal behavior. If differences in cortical (brain) surface area or thickness are found to play a causal role in suicide risk, this could open the door to early detection strategies and biologically informed interventions. This is particularly relevant for youth, where early changes in brain development may signal emerging vulnerability, and understanding these mechanisms could guide age-appropriate preventive efforts that interrupt the trajectory toward suicidality.

Yi Zhou used his AFSP Pilot Grant to analyze genetic and brain imaging data from both adults and children in order to assess whether differences in brain structure can play a role in increasing the likelihood of suicide attempt. In adults, he found that smaller total cortical surface area was consistently associated with a higher likelihood of suicide attempts. In contrast, the same relationship was not found in children. However, in youth, thinner average cortical thickness was linked to higher levels of depression and internalizing symptoms, both of which are well-established precursors to suicidal behavior. Together, the findings suggest that structural brain differences may influence risk for suicidal behavior differently depending on age, emerging more apparently in adulthood. Understanding these patterns could help identify high-risk individuals earlier and tailor prevention strategies across developmental stages.

Citation: Zhou Y, Castro-de-Araujo LFS, Singh M, Neale MC, Causal Analyses of Associations Between Brain Structure and Suicide Attempt in Adulthood and Late Childhood, JAACAP Open (2025), doi: https://doi.org/10.1016/j.jaacop.2025.02.005

This finding comes from an AFSP-funded study — see the grant below ↓

The grant behind this work · 2022 Pilot Research Grant

Investigation of the Neural Correlates of the Acquired Capability for Suicide in Child and Adult Brains

Yi Zhou, MSc

Yi Zhou, M.Sc.

Virginia Commonwealth University

Amount awarded
$30,000 Focus area
Neurobiological

Inside the Research

Most people who think about suicide do not make an attempt. It is unclear whether there are differences in the brain between these individuals. Identifying any differences in the brain may increase our understanding of the development of suicide behaviors. Using brain scans from children and young adolescents, we will study how the brain changes in individuals who go on to make a suicide attempt as compared with those who do not.

Full scientific abstract

Project Title: Investigation of the Neural Correlates of the Acquired Capability for Suicide in Child and Adult Brains.

Abstract:

Few studies have investigated the potential neural correlates underlying the acquired capability for suicide (ACS) as part of the Interpersonal Theory of Suicide (ITP) and other related theoretical models. While there have been many neuroimaging studies of suicidality, most have been cross-sectional and none have explored how transitioning from suicide ideation (SI) to suicide attempt (SA) is related to changes in brain structure and function associated with the ACS directly in individuals with suicidal thoughts and behaviors (STBs), to our knowledge.

Research Aims: In this project, we propose to 1) in children from the ABCD study who develop SA at 2-year follow-up, quantify the changes in the functional connectivity of brain networks, including those specifically associated with the ACS and 2) using a genetic epidemiological method called mendelian randomization (MR) to evaluate the evidence for the causal relationships between brain structure and function associated with the ACS and SA.

Sample: In total, there are 71 individuals who go on to develop SA at 2-year follow-up who previously did not report SA at baseline. These consist of individuals who previously did not endorse any STBs (STB naïve) and those who only endorsed SI at baseline. Furthermore, we will include a group of 290 individuals who develop suicide ideation at 2-year follow-up who were STB naive at baseline. Finally, we will also include 5995 individuals who remain STB naive at 2-year follow-up.

Measures: In the ABCD study, there are in total, 443 resting state functional MRI (rsfMRI) connectivity measures that we will use in our longitudinal analyses. Additionally, we will use pre-processed rsfMRI temporal variance measures from 19 brain regions previously identified to be associated with the ACS. For our MR analyses, we will be using genome wide association study (GWAS) summary statistics from brain imaging measures obtained from the UK Biobank, which were analyzed using brain scans from around 43,000 healthy adults.  As well, we will be using GWAS summary statistics from a recent study of suicide attempt that utilized 29,782 suicide attempt cases and 519,961 controls

Procedures: For each of the pre-processed major rsfMRI connectivity measures, we will use mixed effects modeling to analyze the changes in rsfMRI connectivity from baseline to 2-year follow-up, while controlling for the random effects of subjects. Additionally, we will perform longitudinal factor analysis using 19 rsfMRI measures from brain regions previously associated with the ACS. Finally, we will perform 2-step MR analyses with brain imaging measures as our exposure/risk factor and SA as our outcome measure.

Potential Impact: Findings from our study may help us understand and identify biomarkers of the transition from SI to SA and provide specific targets for intervention to prevent SA.

Next Steps: Our next seps are to begin data preparation to carry out the analyses outlined in our specific aims.

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