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Research / Funded grants

2022 Focus Grant

Saving Lives: Constructing a Nationwide Cohort With Multi-modal Data to Improve Precision in Prediction and Prevention of Suicide

1 research finding from this AFSP-funded study.

Research finding · January 2026

Commonly reported suicide risk and warning signs differ by sex and age

Suicide does not look the same across the lifespan, nor does it present in the same way for women and men. While suicide rates are higher among men and increase with age, some of the warning signs clinicians and researchers rely on (e.g., mental health diagnoses or recent contact with psychiatric services) are actually more common in women and younger people. This mismatch creates a challenge for prevention: the very indicators we tend to watch for may be less visible in groups at the highest risk for suicide. Understanding how patterns of distress differ by sex and age, especially in the period leading up to suicide, can help refine how we identify risk and support people more effectively.

Dr. Christian Rück used nationwide health and social registry data from Sweden to study nearly 20,000 people who died by suicide and compare them with more than 190,000 similar living individuals who matched on age and sex. They examined whether people had any of 25 commonly cited risk indicators in the year before death, including mental health diagnoses, self-harm, psychiatric care, medication use, serious physical illness, bereavement, unemployment, or financial stress. What Dr. Rück found was not that these indicators were unimportant, but that they appeared unevenly across groups. Women and younger people who died by suicide were more likely to have had these warning signs documented beforehand. In contrast, men and older adults who died by suicide were less likely to have had these indicators recorded at all. This means that many men and older adults may be at risk without ever appearing on clinicians’ or systems’ “radar.” At the same time, because men have higher overall suicide rates, men who did show these indicators were often at particularly high risk, though this may reflect a potential bias of not asking or recording risk factors for men. Overall, the findings suggest that suicide prevention efforts relying mainly on documented mental health or social warning signs may miss many at-risk men and older adults, pointing to the need for broader, more tailored approaches to identifying and supporting people in distress.

Citation: Johansson, F., Gunnarsson, L., Grossmann, L., Mataix-Cols, D., Fernández de la Cruz, L., Fazel, S., Gardner, R. M., Dalman, C., Wallert, J., & Rück, C. (2025). Patterns of sex-specific and age-specific risk indicators of suicide: a population-nested case-control study. BMJ mental health, 28(1), e301959. https://doi.org/10.1136/bmjment-2025-301959

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

The grant behind this work · 2022 Focus Grant

Saving Lives: Constructing a Nationwide Cohort With Multi-modal Data to Improve Precision in Prediction and Prevention of Suicide

Christian Ruck, MD, PhD

Christian Ruck, M.D., Ph.D.

Karolinska Institutet (Sweden)

Amount awarded
$1,494,898
Focus area
Neurobiological, Genetic

Inside the Research

Suicide is difficult to predict and prevent. The goal of this research program is to utilize Sweden’s unique national databases to improve prediction of suicide by integrating the many environmental factors captured by national registers and genetic information using multi-modal modeling. We will create a large national suicide biobank and aim to create useful predictive models combining different types of data and using new analytic approaches to best make use of those data. The goal is to increase our understanding of suicidal behavior.

Full scientific abstract

Suicide is a major public health issue, causing severe impact on individuals and families, as well as relevant societal costs. In Sweden alone, ~70,000 years of potential life are lost each year due to suicide. Despite dedicated research efforts and prevention strategies, suicide-related outcomes are still difficult to predict and prevent. The goal of this research program is to utilize unique resources in Sweden to improve prediction of suicide by integrating environmental factors captured by national registers and genetic information using multi-modal modelling. In aim 1, we will create a large suicide biobank by collecting neonatal blood spots stored at the Swedish PKU biobank from all individuals who died by suicide, i.e., total coverage of all suicides in Sweden from individuals born 1975 and onwards (n=5000). DNA will be extracted from each of these blood spots. Data from the national registers will be added, covering major risk factors across the lifetime (socioeconomic, demographic, and medical). Further, blood spots and register data from 10,000 matched controls with no suicidal outcomes will be available through collaboration. In aim 2, we will identify register-based risk factors and genetic variants associated with suicide by genotyping all DNA samples from cases and matched controls and performing a case-control genome-wide association study meta-analysis. In aim 3, we will combine hundreds of candidate suicide predictors from the national registers (covering demographics, socioeconomic status, electronic medical records, criminality) with genetic predictors (polygenic risk scores for suicide, depression, impulsivity, and substance misuse) using both established quantitative modelling and newer machine learning approaches. This study should help provide a refined understanding of factors influencing suicide and an increased ability to identify those at risk.

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