Effect of the dysbindin gene on antimanic agents in patients with bipolar I disorder

The role of DNA methylation in the pathophysiology and treatment of bipolar disorder

Bipolar disorder (BD) is a multifactorial illness thought to result from an interaction between genetic susceptibility and environmental stimuli. Epigenetic mechanisms, including DNA methylation, can modulate gene expression in response to the environment, and therefore might account for part of the heritability reported for BD. This paper aims to review evidence of the potential role of DNA methylation in the pathophysiology and treatment of BD. In summary, several studies suggest that alterations in DNA methylation may play an important role in the dysregulation of gene expression in BD, and some actually suggest their potential use as biomarkers to improve diagnosis, prognosis, and assessment of response to treatment. This is also supported by reports of alterations in the levels of DNA methyltransferases in patients and in the mechanism of action of classical mood stabilizers. In this sense, targeting specific alterations in DNA methylation represents exciting new treatment possibilities for BD, and the 'plastic' characteristic of DNA methylation accounts for a promising possibility of restoring environment-induced modifications in patients.

Genetics of long-term treatment outcome in bipolar disorder

Bipolar disorder (BD) shows one of the strongest genetic predispositions among psychiatric disorders and the identification of reliable genetic predictors of treatment response could significantly improve the prognosis of the disease. The present study investigated genetic predictors of long-term treatment-outcome in 723 patients with BD type I from the STEP-BD (Systematic Treatment Enhancement Program for Bipolar Disorder) genome-wide dataset. BD I patients with >6months of follow-up and without any treatment restriction (reflecting a natural setting scenario) were included. Phenotypes were the total and depressive episode rates and the occurrence of one or more (hypo)manic/mixed episodes during follow-up. Quality control of genome-wide data was performed according to standard criteria and linear/logistic regression models were used as appropriate under an additive hypothesis. Top genes were further analyzed through a pathway analysis. Genes previously involved in the susceptibility to BD (DFNB31, SORCS2, NRXN1, CNTNAP2, GRIN2A, GRM4, GRIN2B), antidepressant action (DEPTOR, CHRNA7, NRXN1), and mood stabilizer or antipsychotic action (NTRK2, CHRNA7, NRXN1) may affect long-term treatment outcome of BD. Promising findings without previous strong evidence were TRAF3IP2-AS1, NFYC, RNLS, KCNJ2, RASGRF1, NTF3 genes. Pathway analysis supported particularly the involvement of molecules mediating the positive regulation of MAPK cascade and learning/memory processes. Further studies focused on the outlined genes may be helpful to provide validated markers of BD treatment outcome.

The Genetic Intersection of Neurodevelopmental Disorders and Shared Medical Comorbidities - Relations that Translate from Bench to Bedside

Most psychiatric disorders are considered neurodevelopmental, and the associated genes often are expressed in tissues outside of the brain. This suggests a biological relatedness with medical co-occurrences that could have broad clinical implications for diagnosis and patient management over a lifetime. A qualitative integration of public data from genetic consortia of psychiatric disorders and medical comorbidities explores the question of whether genetically associated psychiatric illnesses present with co-occurring disturbances can be used to define specific mental-physical health relations. Novel patterns of gene-disorder relations appear with approximately one-third of conservatively defined, consortia-generated candidate risk genes with multiple psychiatric diagnoses. Moreover, nearly as many genes overlap with non-psychiatric phenotypes, including cardiovascular, renal, respiratory, and metabolic disturbances. While the landscape of genetic risk will change as study populations are expanded and biological confirmations accrue, the current relationships suggest that a mostly siloed perspective of gene relatedness to one categorical psychiatric diagnosis is not clinically useful. The future holds the promise that once candidates are fully validated, genome screening and mutation identification will bring more precision for predicting the risk for complex health conditions. Our view is that as genetic data are refined, continuing to decipher a shared pattern of genetic risk for brain and peripheral organ pathophysiology is not simply an academic exercise. Rather, determining relatedness will impact predictions of multifaceted health risks, patient treatment, and management.