OR WAIT null SECS
For a long time, we have relied to a large extent on phenomenology and diagnosis to plan treatment strategies, but advancements in psychiatry are changing that for the better.
YEAR IN REVIEW
Dr. Amaladoss is Assistant Professor in the department of psychiatry and behavioral neurosciences at McMaster University in Hamilton, Ontario. He is a consultant psychiatrist at the Advanced Mind Clinic and Joseph Brant Hospital Burlington, Ontario. He is actively involved in medical education and has been the recipient of a number of teaching and presentation awards.
The following articles (in no particular order) add to our collective understanding of psychiatric illness. For a long time, we have relied to a large extent on phenomenology and diagnosis to plan treatment strategies. The emergence of biomarkers and connectopathies has brought us a step closer in understanding the complex world of mental illness. Future research will hopefully advance our knowledge and help us better predict therapeutic strategies.
Bipolar Spectrum Disorder
Can one reliably predict bipolar disorder? In this study, the question of whether a risk calculator can be developed to predict on an individual level the risk of bipolar spectrum disorder. The authors examined 412 offspring of parents with bipolar disorder. By using predictors in the literature, the authors developed a risk calculator to determine whether a youth will develop new-onset bipolar spectrum disorder in within 5 years. This article provides an important practical tool to inform clinical decision making and is of particular interest in future research, especially in incorporating those patients in the ultra- high-risk group.
The results presented by Moreno-Peral and colleagues suggest that prevention programs are effective regardless of an individual’s age and should be made available across the lifespan. Although the effect size is small, the importance of these findings at a population level should not be understated and has implications in further preventions policies. In a related commentary, Prevention of Anxiety Disorders Across the Lifespan, Jennifer L. Hudson, PhD, reiterates that the prevention of anxiety disorders greatly reduces the morbidity and suffering these disorders bring. While past reviews have focused on efforts to reduce anxiety in specific age groups, this review examined the efficacy of prevention strategies across the lifespan and thus provides a unique contribution.
Resting state functional connectivity (r-FMRI) is a method of evaluating brain function and is used to evaluate interaction between the regions of the brain. Evaluating results of studies are challenging to establish patterns given the variable methods used. This is an important study in that it is the first meta-analytical examination into large-scale network dysfunction in MDD and provides insight into the networks involved in regulating attention to the internal and external world as well decreased connectivity among the regulation of response to emotion. This study has helped move our understanding of MDD from the days of only the monoamine hypothesis to now thinking about this is disorder of connectopathies.
Generalized Anxiety DisorderPrediction of Error Representation in Individuals With Generalized Anxiety Disorders During Passive Avoidance (American Journal of Psychiatry)
The process of decision making is often based on a balance of our values and goals against our expectation of outcomes. In generalized anxiety disorder (GAD), there seems to be an impairment in the process of predicting outcomes, assessing feedback, and learning from experience. The authors use the heuristic of computational neuroscience to identify errors in learning from both error and reward. They found a widespread reduction in prediction error signaling in patients with GAD. As a consequence, deciding which stimulus to select in order to receive reward or avoid punishment becomes less accurate and thus suboptimal. This study provides new insights into GAD and identifies computational psychiatry as a helpful tool in this population. It can also be a helpful aid in asking clinically relevant questions.
Obesity and Bipolar Disorder
Obesity has long been recognized as an important cardiovascular risk factor. This article suggests BMI and obesity measurements are important predictors of burden of illness associated with bipolar disorder. In this retrospective analysis, Mcintyre and colleagues found that patients with bipolar disorder who were also overweight or obese exhibited greater cognitive impairments. Given the importance that attenuating cognition can have on illness course, these findings are important. This study provides rationale for directly addressing weight in individuals at elevated bipolar risk and may prevent and attenuate illness course.
DepressionFunctional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder (American Journal of Psychiatry)
Disruption of functional connectivity of subcallosal cingulate cortex (SCC) is seemingly important for depression circuitry. The study evaluated patients who had not received any treatment for major depression and who then were randomized to CBT or SSRI and SNRI treatment. The authors examined “receiver operator characteristics,” the functional MRI measure of activity in the SCC region. CBT responders showed increased connectivity in the SCC region, while antidepressant responders showed reduced activity. This study is an important contribution to the emerging field of personalized medicine, which may add to our approach to treatment today and in the future.
There are a number of complexities that surround the relationship between mood and behavior in bipolar disorder and ongoing debate continues around the core pathophysiology of the disorder. In this interesting article, Mason and colleagues describe a useful model of bipolar disorder from a neuro-computational perspective in order to predict changes and fluctuations in mood. By applying computational approaches to the study of emotion and decision making, it provides new ways to relate momentary changes in mood and behavior to well-defined neural circuits.
Models of Mental Illness
Moving From Static to Dynamic Models of the Onset of Mental Disorder. (JAMA Psychiatry)
There has been increased interest in detecting subthreshold clinical conditions and offering risk stratification and treatment options earlier in the course of illness. Given how multifactorial and complex ecosystems psychiatric illnesses manifest, the authors of this noteworthy review examine overlapping models that attempt to capture this dynamic and shifting nature and may be fruitfully applied to psychopathological research.
Is Psychoanalysis Still Relevant to Psychiatry? (Canadian Journal of Psychiatry)
Through the immense number of advances and contributions to the field, psychiatry is redefining various approaches and paradigms. With psychiatry in an era of evidence-based medicine, empiricism, and managed care, some now question the value of psychotherapy. While not as rigorously studied as neuroscience, psychotherapy remains a very important tool in understanding the mind. In this review, Joel Paris, MD examines current thinking around the field of psychotherapy as well as some recent studies in this area. Dr. Paris concludes, “It taught a generation of psychiatrists how to understand life histories and to listen attentively to what patients say. In an era dominated by neuroscience, diagnostic checklists, and psychopharmacology, we need to find a way to retain psychotherapy.”