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Precision Biomarkers for Mood Disorders Based on Brain Imaging

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Precision Biomarkers for Mood Disorders Based on Brain Imaging BRAIN HEALTH Precision biomarkers for mood disorders based BMJ: first published as 10.1136/bmj.m3618 on 9 October 2020. Downloaded from on brain imaging Identification of biomarkers could facilitate earlier diagnosis and better treatment, say Runsen Chen and colleagues ood disorders are a global are associated with abnormalities in both clinical symptoms, while patients with public health problem the structure and function of specific brain these diagnoses present with heterogene- because of their high prev- circuits. Interest is growing in developing ous symptoms.17 alence, chronicity, and precision biomarkers for mood disorders Clinical symptoms may be shared recurrence throughout the based on a deeper understanding of their across mood disorders or with psychiatric lifespan as well as increased risk of mor- biological bases by integrating multilevels disorders. For example, major depressive M1-3 tality. They also impose a heavy eco- of data, such as brain imaging, clinical disorder is commonly associated with nomic burden on society because of lost symptoms, and cognitive behaviours.11 12 anxiety symptoms, but these also occur in work productivity (occupational disabil- Structural and functional magnetic bipolar disorder and schizophrenia. Recent ity) and increased use of health services.4 resonance imaging (MRI) can detect subtle studies have used brain imaging and Early diagnosis and effective treatment are deficits in brain structure and function. For transdiagnostic approaches to characterise therefore essential. example, structural MRI data from more the neural basis of the shared symptoms.17-19 Mood disorders are characterised than 20 cohorts worldwide showed that, Resting state fMRI data showed that by a significant change in a person’s compared with healthy controls, patients patients with major depressive disorder, state of mood and include two main with major depressive disorder had thinner bipolar disorder, and schizophrenia had subtypes: depressive disorders (major cortical grey matter in the orbitofrontal common brain functional deficits.18 More depressive episode and dysthymia) and cortex, cingulate cortex, and insula,13 generally, recent studies proposed a general bipolar disorders (hypomania, mania, while patients with bipolar disorder had psychopathology factor (p factor) to describe or cyclothymia—that is, cycling between thinner cortical grey matter in the left a shared vulnerability to a broad range depressed and manic states). In 2015, pars opercularis, left fusiform gyrus, and of symptoms across mental disorders,20 over 300 million people were living with left rostral middle frontal cortex (fig 1).14 and a higher p factor was associated with http://www.bmj.com/ major depressive disorder worldwide, Using resting state functional MRI (fMRI), diminished activation of the frontal pole, representing 4.4% of the global Satterthwaite and colleagues found that the anterior cingulate cortex, and anterior insula population.5 A world mental health survey severity of major depressive disorder was during executive tasks.19 The imbalance in reported that the lifetime and 12 month associated with diminished connectivity these brain circuits is believed to confer prevalences of bipolar disorders in the between the amygdala and frontal areas, vulnerability to mood disorders as well as general population were 2.4% and 1.5%, including both the dorsolateral prefrontal other mental disorders, which could be 6 15 respectively. cortices and anterior cingulate cortex. the underlying mechanism of the shared on 1 October 2021 by guest. Protected copyright. Mood disorders are associated with Studies using task based fMRI showed that symptoms. Other specific brain circuits a widespread cognitive dysfunction, patients with mood disorders exhibited related to factors such as anhedonia may involving higher-order executive function,7 atypical neural responses to emotional therefore give rise to specific diagnoses such reward processing,8 and emotional processing in the medial prefrontal cortex, as major depressive disorder. regulation (fig 1, box 1).10 These deficits amygdala, and insula, as well as decreased Heterogeneity is also a problem in the neural responses to emotional regulation current diagnostic system. Mood disorders in the dorsolateral prefrontal cortex.16 are increasingly viewed not as a unitary KEY MESSAGES Multimodal brain imaging therefore disease but as a heterogeneous clinical offers the potential to identify biomarkers syndrome that encompasses multiple • Mood disorders are among the lead- for mood disorders that could improve subtypes with distinct pathophysiological ing causes of disability across all age diagnosis and treatment. deficits. Interest is therefore growing in groups parsing the neurobiological heterogeneity of • High quality brain imaging data is Diagnostic confusion mood disorders.17 Drysdale and colleagues providing a better understanding of Current diagnostic systems, including the subdivided major depressive disorder into brain mechanisms underlying shared Diagnostic and Statistical Manual of Men- four discrete biotypes using a clustering symptoms, heterogeneity, and atypi- tal Disorder and International Classifica- approach, each type defined by distinct cal development of mood disorders tion of Diseases, were developed based on patterns of dysfunctional connectivity in the • Such data could allow development clinical symptoms and signs. The acquired limbic and frontostriatal systems.21 Rather of precision biomarkers for mood dis- diagnostic categories do not align with the than dividing mood disorders into discrete orders underlying psychopathology or predict categories, dimensional approaches are • The benefits of a cognitive neuropsy- treatment response. The diagnostic cat- able to parse them into several dimensions chological model could be harnessed egories of major depressive disorder and using brain imaging, with each dimension to predict treatment outcomes bipolar disorder, for example, share many representing loadings onto symptoms.17 the bmj | BMJ 2020;371:m3618 | doi: 10.1136/bmj.m3618 1 BRAIN HEALTH disorder had a greater grey matter Striatum volume contraction and less white matter BMJ: first published as 10.1136/bmj.m3618 on 9 October 2020. Downloaded from expansion in the prefrontal cortex during Thalamus development.24 Xia and colleagues found Prefrontal that mood symptoms were related to cortex dysconnectivity within the frontoparietal system and the pattern of dysconnectivity was strengthened from childhood to adulthood.25 Based on these findings, scientists increasingly conceptualise mood disorders as neurodevelopmental disorders.26 An understanding of the atypical brain development in patients with Anterior mood disorders could allow identification cingulate cortex of a biologically informed time of onset for Amygdala mood disorders, which might be earlier than the onset of clinical symptoms. Dense sampling shows particular Executive function Hippocampus Emotional regulation promise for precise characterisation of the Reward processing atypical development of brain functional organisation in patients with mood disorders. Typical fMRI acquisitions last Fig 1 | Brain regions underlying executive function, emotional regulation, and reward 5-10 minutes, and may be adequate for processing. The figure was made with reference from Wang and Olson9 characterising group average functional organisation. However, such short acquisitions have limited reliability for Dimensional approaches can account Accurate identification of the time of onset describing an individual’s brain functional for the continuous spectrum from health of a disorder is essential for achieving this 27 28 organisation in detail. Recent studies to disease by including people at risk of goal. Clinical symptoms of mood disorders have shown individual variations in the illness and considering diagnosable cases usually begin in youth, with the mean age topography of brain organisation that are as an extreme phenotype. Consistent with of onset being 14.9 years for major depres- 22 obscured in group level organisation and these efforts, the US National Institute of sive disorder and 20.2 years for bipolar http://www.bmj.com/ 11 12 23 can only be reliably detected using dense Mental Health research domain criteria disorders. Therefore, youth—defined 27 29 30 fMRI scanning data. Dense fMRI framework invited the scientific and clinical as ranging from childhood to early adult- protocols acquire a much longer time series communities to integrate brain imaging, hood—is a critical period for diagnosis and of fMRI data on one person, which can be cognition, and clinical symptoms to develop implementation of suitable interventions. acquired by repeated scanning in multiple a novel biologically informed nosology and Youth is also a period of considerable sessions. Such protocols reveal specific precision biomarkers for mood disorders. brain development, and atypical brain topography details for individuals that are developmental trajectories are related on 1 October 2021 by guest. Protected copyright. both reliable and reproducible and could be High quality imaging data for early to clinical symptoms and cognitive useful in identifying precision biomarkers identification dysfunction in patients with mood for mood disorders.31 Precision biomarkers need to be detected disorders.26 For example, longitudinal Recently, Cui and colleagues used 27 at an early stage in the progression of mood high resolution MRI showed that relative
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