<p>Mood disorders are highly prevalent in society, often disabling, and can lead to a reduced healthspan and lifespan, including by suicide. Depression and bipolar disorders are currently deemed to be chronic and/or treatment-refractory in up to half the patients treated. Additionally, depression and bipolar disorders need to be better distinguished, especially upon initial depressive presentations, as treatments can be quite different. Lack of widespread use of objective and/or quantitative information has hampered treatment and prevention efforts. We sought to uncover the underlying genomic and biological basis of mood disorders in a way that is reliable, comprehensive, and actionable. Blood biomarkers that track mood state can provide a window into the biology of mood, as well as could help with assessment and treatment of mood disorders. Previous studies by us were encouraging. Here we describe new studies we conducted trans-diagnostically in psychiatric patients, starting with the whole transcriptome, to expand the identification, prioritization, validation and testing of blood gene expression biomarkers for mood disorders, and their practical application. We first studied separately the two diametrical phenotypes, low mood/depression and high mood/mania. For each of the phenotypes, we carried out two separate studies, each of them on two different platforms, microarrays and RNA sequencing, using for each platform and study a multiple independent cohorts design. This was done to ensure both the biological and technical reproducibility of the final findings. We focused on biomarkers that were convergent and reproducible between the platforms in each study, for each phenotype. We found new as well as previously known biomarkers that were predictive of depression and of mania states, and of future hospitalizations related to them. We then compared and integrated the findings from the studies on the two phenotypes at the end, identifying bipolar biomarkers, that were changed in expression in opposite direction in the two phenotypes. Using a polyevidence score, the overall top gene expression blood biomarkers for depression were FKBP1A and FOSL2, for bipolar CTSB, and for mania ATP6V1C2. The top biological pathways for depression were related to immune response, for bipolar apoptosis, and for mania necroptosis. Top therapeutic matches for depression were omega-3 fatty acids, lithium, and vortioxetine; for bipolar depression lithium, valproate, and clozapine; and for mania lithium, valproate, and omega-3 fatty acids. Drug repurposing also identified the natural compounds curcumin and berberine as potential treatments for depression. We also illustrate how personalized patient reports for doctors based on gender- specific panels of top blood biomarkers would look like, which can aid with diagnosis and match patients in a personalized way to potential suggested treatments. Using such reports in <i>n</i> = 569 patients clinically diagnosed with depression or bipolar disorder, we distinguish 8 subtypes (depressive disorder, bipolar 2, bipolar 1, bipolar 3, and manic disorder, as well as the milder forms- dysthymia, cyclothymia, hyperthymia, and no mood disorder). Up to half of the patients were classified differently by our reports compared to their clinical diagnosis. Moreover, we demonstrate the clinical utility of our reports by showing that a mismatch between clinical diagnosis and biomarker- based assessment can lead to worse future hospitalizations outcomes. Specifically, patients who were (mis)diagnosed clinically as depression and were in fact on the bipolar spectrum based on biomarkers had increased future hospitalizations, not only for mood disorders exacerbation but also for suicidality and alcoholism. The converse was not true, patients who were (mis)diagnosed clinically as bipolar and were in fact on the depressive spectrum based on biomarkers fared well. Taken together, our results suggest that mood stabilizers, such as low-dose lithium, could be considered more often empirically first line in mood disorders patients, without or with the use of antidepressants, especially given the anti-suicidal properties. As mood disorders are highly prevalent, can severely affect quality of life, and lead to shortened lifespans, there is an urgent need for such insights, and for the added precision and personalization that biomarker tests can offer, to be applied to and improve clinical diagnosis, treatment, and prevention.</p>