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Personalized psychiatry has made important gains in elucidating the neurobiological basis of many psychiatric disorders, yet heterogeneity, polygenicity and interactions with the environment and epigenetics continue to be major challenges for researchers to explore. Our September issue cover reflects this great complexity. For each person, there are potentially manifold ‘keys’ to unlocking or to personalizing diagnosis and treatment. The cover gives a nod to the fact that personalized psychiatry research is technology and tradition — an elegant incorporation of -omics and big data and a backdrop of established elements, such as self-reported measures and patient assessment.
See our Editorial for more on the potential and pitfalls of personalized psychiatry.
Personalized medicine has made substantial strides in treating cancer and rare genetic disorders by leveraging advances in genomics, yet psychiatry has lagged behind. The complexity of psychiatric disorders, owing to heterogeneity, polygenicity and environmental and epigenetic effects, calls for varied approaches in achieving personalization.
By integrating neuroimaging and multi-omics data, we established links between individual genetic variations and macro- to microscale brain circuit dysfunctions, specifically in corticocortical and corticostriatal circuits, that contribute to the diverse clinical manifestations of schizophrenia. These findings advance our understanding of the disease’s heterogeneity and offer potential treatment insights.
Using resting-state functional MRI, we revealed a dysfunction pattern in the white matter of people with four major psychiatric disorders. This pattern is distinct from structural changes and has specific molecular and genetic bases.
Using meta-analytic techniques, authors report patterns of aberrant functional brain associated with differences in neurophysiology and cognitive and behavioral regulatory mechanisms in men diagnosed with pedophilic disorder to elucidate potential mechanistic and pharmacological interventions.
In this Article, Singh and coauthors put forth a new machine-learning approach to evaluate inclusion and exclusion criteria from psychiatry abstracts to automate systematic reviews.
Using an integrated analysis on three independent large human datasets, Wang et al. map macroscale dysconnectivity in schizophrenia onto layer- and cell-type-specific microscale alterations. The authors identify different alterations of corticocortical and corticostriatal connectivity in schizophrenia and their relationship to different symptom dimensions and functional domains.
The authors use multimodal magnetic resonance imaging to investigate microstructural alterations and functional deficits in white matter in a multi-disorder sample (patients with schizophrenia, major depressive disorder, bipolar disorder or obsessive–compulsive disorder) when compared with a healthy control sample.
Catarino et al. used real-world data from the UK healthcare system to perform an economic evaluation comparing the cost-effectiveness of in-person and internet-delivered cognitive behavioral therapy for mood and anxiety disorders.
In this cross-sectional study, Blain and colleagues show that sensitivity to diverse visual, cognitive and social, putatively intrinsic rewarding stimuli is partly domain general and is linked to affective aspects of mental health unlike sensitivity to monetary rewards.