Markers of positive affect and brain state synchrony discriminate melancholic from non-melancholic depression using naturalistic stimuli.

Melancholia has been proposed as a qualitatively distinct depressive subtype associated with a characteristic symptom profile (psychomotor retardation, profound anhedonia) and a better response to biological therapies. Existing work has suggested that individuals with melancholia are blunted in their display of positive emotions and differ in their neural response to emotionally evocative stimuli. Here, we unify these brain and behavioural findings amongst a carefully phenotyped group of seventy depressed participants, drawn from an established Australian database (the Australian Genetics of Depression Study) and further enriched for melancholia (high ratings of psychomotor retardation and anhedonia). Melancholic (n = 30) or non-melancholic status (n = 40) was defined using a semi-structured interview (the Sydney Melancholia Prototype Index). Complex facial expressions were captured whilst participants watched a movie clip of a comedian and classified using a machine learning algorithm. Subsequently, the dynamics of sequential changes in brain activity were modelled during the viewing of an emotionally evocative movie in the MRI scanner. We found a quantitative reduction in positive facial expressivity amongst participants with melancholia, combined with differences in the synchronous expression of brain states during positive epochs of the movie. In non-melancholic depression, the display of positive affect was inversely related to the activity of cerebellar regions implicated in the processing of affect. However, this relationship was reduced in those with a melancholic phenotype. Our multimodal findings show differences in evaluative and motoric domains between melancholic and non-melancholic depression through engagement in ecologically valid tasks that evoke positive emotion. These findings provide new markers to stratify depression and an opportunity to support the development of targeted interventions.

Caregiver Burden in Parkinson Disease: A Scoping Review of the Literature from 2017-2022.

Caregiver burden is a term that refers to the adverse effect of caregiving on the physical, emotional, social, spiritual, and financial well-being of the caregiver. Caregiver burden is associated with providing care to an individual with a chronic illness or disability, and the unique symptoms of Parkinson disease (PD) can amplify a patient's needs and reliance on others, leading to adverse outcomes for patients and their caregivers. In this scoping review of the literature from January 2017 through April 2022 that included 114 studies, we provide an updated, evidence-based summary of patient and caregiver-related factors that contribute to caregiver burden in PD. We also describe the impact of caregiver stress and burden on caregivers based on qualitative research studies and review recent interventions to mitigate burden. By providing clinical updates for practitioners, this review is designed to improve recognition of caregiver burden in the post-pandemic era and foster the development of targeted interventions to reduce caregiver burden in PD.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study.

BACKGROUND: Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated. OBJECTIVE: To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group. METHODS: Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated. RESULTS: Overall, people with PD had a regionally smaller posterior lobe (dmax = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17). CONCLUSIONS: We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders.

Importance: Physical health and chronic medical comorbidities are underestimated, inadequately treated, and often overlooked in psychiatry. A multiorgan, systemwide characterization of brain and body health in neuropsychiatric disorders may enable systematic evaluation of brain-body health status in patients and potentially identify new therapeutic targets. Objective: To evaluate the health status of the brain and 7 body systems across common neuropsychiatric disorders. Design, Setting, and Participants: Brain imaging phenotypes, physiological measures, and blood- and urine-based markers were harmonized across multiple population-based neuroimaging biobanks in the US, UK, and Australia, including UK Biobank; Australian Schizophrenia Research Bank; Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative; Prospective Imaging Study of Ageing; Human Connectome Project-Young Adult; and Human Connectome Project-Aging. Cross-sectional data acquired between March 2006 and December 2020 were used to study organ health. Data were analyzed from October 18, 2021, to July 21, 2022. Adults aged 18 to 95 years with a lifetime diagnosis of 1 or more common neuropsychiatric disorders, including schizophrenia, bipolar disorder, depression, generalized anxiety disorder, and a healthy comparison group were included. Main Outcomes and Measures: Deviations from normative reference ranges for composite health scores indexing the health and function of the brain and 7 body systems. Secondary outcomes included accuracy of classifying diagnoses (disease vs control) and differentiating between diagnoses (disease vs disease), measured using the area under the receiver operating characteristic curve (AUC). Results: There were 85 748 participants with preselected neuropsychiatric disorders (36 324 male) and 87 420 healthy control individuals (40 560 male) included in this study. Body health, especially scores indexing metabolic, hepatic, and immune health, deviated from normative reference ranges for all 4 neuropsychiatric disorders studied. Poor body health was a more pronounced illness manifestation compared to brain changes in schizophrenia (AUC for body = 0.81 [95% CI, 0.79-0.82]; AUC for brain = 0.79 [95% CI, 0.79-0.79]), bipolar disorder (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.57-0.58]), depression (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.58-0.58]), and anxiety (AUC for body = 0.63 [95% CI, 0.63-0.63]; AUC for brain = 0.57 [95% CI, 0.57-0.58]). However, brain health enabled more accurate differentiation between distinct neuropsychiatric diagnoses than body health (schizophrenia-other: mean AUC for body = 0.70 [95% CI, 0.70-0.71] and mean AUC for brain = 0.79 [95% CI, 0.79-0.80]; bipolar disorder-other: mean AUC for body = 0.60 [95% CI, 0.59-0.60] and mean AUC for brain = 0.65 [95% CI, 0.65-0.65]; depression-other: mean AUC for body = 0.61 [95% CI, 0.60-0.63] and mean AUC for brain = 0.65 [95% CI, 0.65-0.66]; anxiety-other: mean AUC for body = 0.63 [95% CI, 0.62-0.63] and mean AUC for brain = 0.66 [95% CI, 0.65-0.66). Conclusions and Relevance: In this cross-sectional study, neuropsychiatric disorders shared a substantial and largely overlapping imprint of poor body health. Routinely monitoring body health and integrated physical and mental health care may help reduce the adverse effect of physical comorbidity in people with mental illness.

Tetrahydrocannabinol and Cannabidiol in Tourette Syndrome.

BACKGROUND: Tourette syndrome is characterized by chronic motor and vocal tics. There is preliminary evidence of benefit from cannabis products containing Δ9-tetrahydrocannabinol (THC) and that coadministration of cannabidiol (CBD) improves the side-effect profile and safety. METHODS: In this double-blind, crossover trial, participants with severe Tourette syndrome were randomly assigned to a 6-week treatment period with escalating doses of an oral oil containing 5 mg/ml of THC and 5 mg/ml of CBD, followed by a 6-week course of placebo, or vice versa, separated by a 4-week washout period. The primary outcome was the total tic score on the Yale Global Tic Severity Scale (YGTSS; range, 0 to 50 [higher scores indicate greater severity of symptoms]). Secondary outcomes included video-based assessment of tics, global impairment, anxiety, depression, and obsessive-compulsive symptoms. Outcomes were correlated with plasma levels of cannabinoid metabolites. A computerized cognitive battery was administered at the beginning and the end of each treatment period. RESULTS: Overall, 22 participants (eight female participants) were enrolled. Reduction in total tic score (at week 6 relative to baseline) as measured by the YGTSS was 8.9 (±7.6) in the active group and 2.5 (±8.5) in the placebo group. In a linear mixed-effects model, there was a significant interaction of treatment (active/placebo) and visit number on tic score (coefficient = −2.28; 95% confidence interval, −3.96 to −0.60; P=0.008), indicating a greater decrease (improvement) in tics under active treatment. There was a correlation between plasma 11-carboxy-tetrahydrocannabinol levels and the primary outcome, which was attenuated after exclusion of an outlier. The most common adverse effect in the placebo period was headache (n=7); in the active treatment period, it was cognitive difficulties, including slowed mentation, memory lapses, and poor concentration (n=8). CONCLUSIONS: In severe Tourette syndrome, treatment with THC and CBD reduced tics and may reduce impairment due to tics, anxiety, and obsessive-compulsive disorder; although in some participants this was associated with slowed mentation, memory lapses, and poor concentration. (Funded by the Wesley Medical Research Institute, Brisbane, and the Lambert Initiative for Cannabinoid Therapeutics, a philanthropically-funded research organization at the University of Sydney, Australia; Australian and New Zealand Clinical Trials Registry number, ACTRN12618000545268.)

Clinical recommendations for the care of people with treatment-refractory obsessive-compulsive disorder when undergoing deep brain stimulation.

Deep brain stimulation is an emerging therapy for treatment-refractory obsessive-compulsive disorder patients. Yet, accessibility is limited, treatment protocols are heterogeneous and there is no guideline or consensus on the best practices. Here, we combine evidence from scientific investigations, expert opinions and our clinical expertise to propose several clinical recommendations from the pre-operative, surgical and post-operative phases of deep brain stimulation care for treatment-refractory obsessive-compulsive disorder patients. A person-centered and biopsychosocial approach is adopted. Briefly, we discuss clinical characteristics associated with response, the use of improved educational materials, an evaluative consent process, comprehensive programming by an expert clinician, a more global assessment of treatment efficacy, multi-disciplinary adjunct psychotherapy and the importance of peer support programs. Furthermore, where gaps are identified, future research suggestions are made, including connectome surgical targeting, scientific evaluation of hardware models and health economic data. In addition, we encourage collaborative groups of data and knowledge sharing by way of a clinical registry and a peer group of programming clinicians. We aim to commence a discussion on the determinants of deep brain stimulation efficacy for treatment-refractory obsessive-compulsive disorder patients, a rare and severe patient group, and contribute to more standardized and evidence-based practices.