Blacker, Caren J.

Objectives: Prior studies demonstrate elevated cortical glutamate (Glu) in patients with bipolar disorder (BD). Studies assessing neurochemistry in early stages of bipolar illness before the emergence of manic symptoms are lacking. This study aimed to examine neurochemical correlates measured by proton magnetic resonance spectroscopy ( 1 H-MRS) and a dimensional measure of bipolarity in a sample of depressed adolescents. Methods: Adolescent participants (aged 13–21 years) underwent a semistructured diagnostic interview and clinical assessment, which included the General Behavior Inventory Parent Version (P-GBI), a 73-item, parent-rated assessment of symptoms and behaviors. 1 H-MRS scans of a left dorsolateral prefrontal cortex (L-DLPFC) voxel (8 cm 3 ) were collected using a two-dimensional J -averaged sequence to assess N -acetylaspartate (NAA), Glu, Glx (glutamate + glutamine), and NAA/Glx concentrations. We used generalized linear models to assess the relationships between P-GBI scores and metabolite levels in L-DLPFC. Results: Thirty-six participants (17 healthy controls, 19 depressed) underwent 1 H-MRS scans and clinical evaluation with the P-GBI. There was a significant negative relationship between P-GBI score and L-DLPFC NAA/Glx in the whole sample. However, the magnitude of the effect was small and statistical significance was lost after correcting for multiple comparisons. Conclusions: These preliminary results suggest that NAA/Glx may have utility as a marker of bipolar traits in healthy and depressed adolescents. If replicated, 1 H-MRS measures of glutamatergic metabolism anomalies might have a role in identifying depressed adolescents at risk for mixed symptom presentations or BD. Identifying bipolarity in the early stages of the disease would have a significant impact on treatment planning and prognosis. Further longitudinal studies should examine neurochemical correlates of mood state during the developmental emergence of BD.

Major depressive disorder (MDD) is the leading cause of disability worldwide and is associated with high rates of suicide and medical comorbidities. Current antidepressant medications are suboptimal, as most MDD patients fail to achieve complete remission from symptoms. At present, clinicians are unable to predict which antidepressant is most effective for a particular patient, exposing patients to multiple medication trials and side effects. Since MDD’s etiology includes interactions between genes and environment, the epigenome is of interest for predictive utility and treatment monitoring. Epigenetic mechanisms of antidepressant medications are incompletely understood. Differences in epigenetic profiles may impact treatment response. A systematic literature search yielded 24 studies reporting the interaction between antidepressants and eight genes (BDNF, MAOA, SLC6A2, SLC6A4, HTR1A, HTR1B, IL6, IL11) and whole genome methylation. Methylation of certain sites within BDNF, SLC6A4, HTR1A, HTR1B, IL11, and the whole genome was predictive of antidepressant response. Comparing DNA methylation in patients during depressive episodes, during treatment, in remission, and after antidepressant cessation would help clarify the influence of antidepressant medications on DNA methylation. Individuals’ unique methylation profiles may be used clinically for personalization of antidepressant choice in the future.

Post-traumatic stress disorder (PTSD) is an acquired psychiatric disorder with functionally impairing physiological and psychological symptoms following a traumatic exposure. Genetic, epigenetic, and environmental factors act together to determine both an individual’s susceptibility to PTSD and its clinical phenotype. In this literature review, we briefly review the candidate genes that have been implicated in the development and severity of the PTSD phenotype. We discuss the importance of the epigenetic regulation of these candidate genes. We review the general epigenetic mechanisms that are currently understood, with examples of each in the PTSD phenotype. Our focus then turns to studies that have examined PTSD in the context of comorbid psychiatric disorders or associated social and behavioral stressors. We examine the epigenetic variation in cases or models of PTSD with comorbid depressive disorders, anxiety disorders, psychotic disorders, and substance use disorders. We reviewed the literature that has explored epigenetic regulation in PTSD in adverse childhood experiences and suicide phenotypes. Finally, we review some of the information available from studies of the transgenerational transmission of epigenetic variation in maternal cases of PTSD. We discuss areas pertinent for future study to further elucidate the complex interactions between epigenetic modifications and this complex psychiatric disorder.

Purpose Physician suicide rates are reportedly higher than those of the general population, but medical student suicide rates are not well studied. It is difficult to determine whether physician suicide rates can be predicted by medical student risk factors for suicide and difficult to identify those risk factors without knowing medical student suicide rates. The authors systematically reviewed the literature to collate data on medical student suicide rates. Method The authors searched the PubMed, Web of Science, and Library of Congress databases for papers published in any language before November 11, 2017. They identified 3,429 papers; after the initial screening process, they assessed 82 full-text articles for eligibility. Twelve ultimately met the full inclusion criteria; meta-analysis was not possible. Data regarding medical student suicide numbers and rates were extracted and compared with contemporaneous general population suicide rates using public epidemiological data, when available. Results Medical student suicide rates were infrequently reported in the historical and international literature, and data collection techniques were inconsistent. Generally, U.S. medical student suicide rates were lower than those of the contemporaneous general population. Proportionate mortality of medical students (number of deaths by a particular cause such as suicide divided by total number of deaths) was not reported in the literature. Conclusions Gaps exist in knowledge of medical student suicide rates, risk factors, and targets for intervention. Significant barriers have impeded information collection. Yet, more comprehensive data collection is needed to understand suicide risk in this population and to implement and improve effective intervention strategies.