One person dies by suicide every 40 seconds worldwide. Having a psychiatric disorder increases risk. Self-report of an individual or clinical impression of a healthcare professional are not always reliable. Developing and validating quantitative and objective ways for predicting and preventing suicidality (ideation, attempts, completions) is urgently needed. Recent work by our group has identified blood gene expression biomarkers that track suicidality using longitudinal within-subject designs, validated them in suicide completers, and tested them in independent cohorts for ability to assess state (suicidal ideation), and ability to predict trait (future hospitalizations for suicidality). These studies were conducted in males with psychiatric disorders (Le-Niculescu et al. Molecular Psychiatry 2013, Niculescu et al. Molecular Psychiatry 2015) and in females with psychiatric disorders (Levey et al. Molecular Psychiatry 2016). The studies pointed to some similarities as well as to important gender differences. A fundamental question remains to be answered: is a quest for more universal predictors that work across genders and are trans-diagnostic, or a quest for more personalized predictors by gender and diagnosis going to be more productive, for ultimate translation to clinical practice? We endeavored to answer this fundamental question with a recent series of studies (Niculescu et al. Molecular Psychiatry 2017), and would like to extend and solidify that with the work proposed in this grant application. First, we will solidify findings for blood gene expression biomarkers for suicidality that are more universal in nature, working across genders and various psychiatric diagnoses, and are predictive in independent cohorts. Second, a more personalized discovery and testing approach, by gender and psychiatric diagnosis, will be undertaken. We will compare the results of the personalized approach to the universal approach, to determine which approach identifies better predictors in independent cohorts. Third, the top biomarkers will also be used to understand the biological pathways involved, co-morbidity with other disorders, as well as generate leads on pharmacogenomics and repurposed drugs. This work will permit us to establish generalizability, discriminatory power, and potential personalization of biomarkers and panels of biomarkers, of high relevance to developing this area towards full clinical applicability as precision medicine. Given the fact that suicide is a potentially preventable cause of death, the need for efforts such as ours cannot be overstated.