Category: Suicide and Self-Injury
Presentation Type: Symposium
Objective markers would permit more precise assessment, tracking, and prediction of suicidal risk, which would enable preventive therapeutic interventions. Previous work by our group has identified blood biomarkers and phenotypic predictors for suicide risk in men (Niculescu et al. 2015), and women (Levey et al. 2016). We endeavored to answer whether the best next step of research should focus on universal predictors or more personalized predictors. First, we sought to investigate whether blood gene expression biomarkers can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using a longitudinal within-participant design. Second, we identified subtypes of suicidality based on mental state (anxiety, mood, psychosis) at the time of high suicidal ideation. Third, we examined the predictive ability of the biomarkers discovered, in a completely independent cohort, in all the participants in it, personalized by gender and diagnosis, with a focus on the highest clinical risk group. Fourth, we combined the top biomarkers with scores from a clinical information measures of suicide risk we developed in the form of an app (Convergent Functional Information for Suicidality (CFI-S), as well as an app we developed to track anxiety and mood (Simple Affective Sate Scale (SASS), to obtain a broader spectrum universal predictor (UP-Suicide) that puts the biomarkers in the context of the person and his/hers mental state. Our CFI-S scale/app captures contextual (e.g., hopelessness) information, and adds this broader context to the objective blood biomarker predictors we have uncovered. Fifth, we leveraged this list for therapeutics and drug discovery purposes, to see if some of the biomarkers we identified are modulated by existing compounds used to treat suicidality,. Lastly, we used the lists of top biomarkers we identified as a window into the biology of suicidality, by conducting biological pathways and network analyses.
Friday, November 17
1:45 PM – 3:15 PM
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