Neuropsychiatric symptoms: Risk factor or disease marker? A study of structural imaging biomarkers of Alzheimer's disease and incident cognitive decline.

Neuropsychiatric symptoms (NPS) are risk factors for Alzheimer's disease (AD) but can also manifest secondary to AD pathology. Mild behavioral impairment (MBI) refers to later-life emergent and persistent NPS that may mark early-stage AD. To distinguish MBI from NPS that are transient or which represent psychiatric conditions (non-MBI NPS), we investigated the effect of applying MBI criteria on NPS associations with AD structural imaging biomarkers and incident cognitive decline. Data for participants (n = 1273) with normal cognition (NC) or mild cognitive impairment (MCI) in the National Alzheimer's Coordinating Center Uniform Data Set were analyzed. NPS status (MBI, non-MBI NPS) was derived from the Neuropsychiatric Inventory Questionnaire and psychiatric history. Normalized measures of bilateral hippocampal (HPC) and entorhinal cortex (EC) volume, and AD meta-region of interest (ROI) mean cortical thickness were acquired from T1-weighted magnetic resonance imaging scans. Multivariable linear and Cox regressions examined NPS associations with imaging biomarkers and incident cognitive decline, respectively. MBI was associated with lower volume and cortical thickness in all ROIs in both NC and MCI, except for EC volume in NC. Non-MBI NPS were only associated with lower HPC volume in NC. Although both of the NPS groups showed higher hazards for MCI/dementia than No NPS, MBI participants showed more rapid decline. Although both types of NPS were linked to HPC atrophy, only NPS that emerged and persisted in later-life, consistent with MBI criteria, were related to AD neurodegenerative patterns beyond the HPC. Moreover, MBI predicted faster progression to dementia than non-MBI NPS.

The effect of study partner characteristics on the reporting of neuropsychiatric symptoms across the neurocognitive spectrum.

OBJECTIVES: We explored the influence of study partner (SP) characteristics on SP-reported neuropsychiatric symptoms (NPS) presence across the neurocognitive spectrum and on the prognostic utility of mild behavioral impairment (MBI). DESIGN, SETTING, AND PARTICIPANTS: We performed cross-sectional (n = 26,748) and longitudinal (n = 12,794) analyses using participant-SP dyad data from the National Alzheimer's Coordinating Center. Participants were cognitively normal (CN; n = 11,951) or had mild cognitive impairment (MCI; n = 5686) or dementia (n = 9111). MEASUREMENTS: SPs rated NPS using the Neuropsychiatric Inventory Questionnaire. We used multivariable logistic regression to model the association between SP characteristics (age, sex, and relationship to participant [spouse, child, and other]) and NPS status (outcome). Cox regressions assessed SP characteristics as moderators of MBI associations with incident dementia or as predictors of incident dementia in MBI + participants only. RESULTS: Among CN persons, younger, female, and spouse SPs reported NPS more frequently. In MCI, younger SPs and those who were spouses or children of participants reported higher NPS odds. For dementia participants, NPS odds were higher in female and spouse SPs. MBI associations with incident dementia were slightly weaker when SPs were older but did not depend on SP sex or relationship to participant. Among MBI + participants with spouse or child SPs, hazard for dementia was higher when compared to MBI + participants with other SPs. CONCLUSIONS: SP age, sex, and relationship to participant influence NPS reporting across the neurocognitive spectrum, with potential implications for MBI prognosis. Considering SP characteristics may enhance the accuracy of NPS assessments, which may facilitate therapy planning and prognosis.

The mind and motion: exploring the interplay between physical activity and Mild Behavioral Impairment in dementia-free older adults.

Physical inactivity in mid-life is a modifiable risk factor for dementia. Mild behavioral impairment (MBI) is a marker of potential neurodegenerative disease. We investigated the association between physical activity and MBI. Baseline data from the Canadian Platform for Research Online to Investigate Health, Quality of Life, Cognition, Behaviour, Function, and Caregiving in Aging (CAN-PROTECT) were used. Four categories of weekly physical activity (cardiovascular, mind-body, strength training, and physical labour) were derived from the Community Healthy Activities Model Program for Seniors questionnaire. MBI was measured using the MBI-Checklist. Multivariable negative binomial regressions modelled the association between the standardized physical activity duration and MBI severity, adjusted for age, sex, education, marital status, ethno cultural origin, occupation, hypertension, dyslipidemia, mobility, and body mass index. Every 1 SD increase in cardiovascular activity was associated with 8.42% lower MBI severity. In contrast, every 1 SD increase in physical labor duration was associated with 5.64% greater MBI severity. These associations were neither moderated by the frequency engaging in each physical activity nor by sex. Cardiovascular physical activity in older persons may reduce levels of non-cognitive dementia markers like MBI, comparable to effects seen in cognition, potentially modulating dementia risk.

Associations between white and grey matter damage and gait impairment in cerebral amyloid angiopathy.

BACKGROUND: Cerebral amyloid angiopathy (CAA) is associated with white matter damage and neurodegeneration. Gait is impaired in CAA; however, the neural basis of this impairment is unclear. RESEARCH QUESTION: Are gait impairments in patients with CAA associated with altered cerebral white matter diffusivity and/or atrophy of cortical and subcortical grey matter. METHODS: Participants with CAA (n=29), Alzheimer's disease (AD; n=16), and normal controls (n=47) were included. Gait was assessed using a 6 m walkway with parameters categorized into rhythm, pace, postural control, and variability domains. The dual-task cost (DTC) of gait speed was calculated for counting backwards, animal fluency, and serial sevens tasks. Whole-brain white matter disruption was quantified using the peak width of skeletonized mean diffusivity (PSMD), and thickness and volume of select cortical, subcortical, and cerebellar regions were quantified using FreeSurfer. RESULTS: In CAA participants, associations were found between PSMD and pace (standardized parameter estimate (ß), 95 % confidence interval (CI): 0.17, 0.03-0.32), and medial orbital frontal cortical thickness and counting backwards DTC (parameter estimate (PE), 95 % CI: -5.7 %/SD, -0.24 to -11.23). Across all groups, including CAA, associations were found between PSMD and pace, variability, counting backwards DTC, and animal fluency DTC; between frontal cortical thickness and pace, counting backwards DTC, and animal fluency DTC; between cortical regions affected by AD (inferior parietal cortex, inferior and middle temporal gyrus) and counting backwards DTC; and between thalamus volume and postural control. SIGNIFICANCE: Reduced white matter structural integrity and grey matter loss is associated with poor overall gait performance in CAA, AD, and normal controls.

Prevalence of psychotic symptoms in mild cognitive impairment: A systematic review and meta-analysis.

INTRODUCTION: Neuropsychiatric symptoms may impact prognosis in individuals with mild cognitive impairment (MCI); however, data on frequency of psychotic symptoms are sparse. METHODS: We searched MEDLINE, EMBASE, PsychoINFO from inception to June 2023. We included studies reporting patients with MCI prevalence of (delusions and/or hallucinations. Random effects model were performed to estimate the prevalence, and subgroup and meta-regression analyses were performed to explore heterogeneity. RESULTS: Of 3145 records identified, 36 studies were included, enrolling 20,426 patients. Overall prevalence of hallucinations was 1.78 % (95 % CI, 1.17 - 2.71) and delusions 3.84 % (95 % CI, 2.71 - 5.42), both with significant heterogeneity (/2 = 90 %). Prevalence of hallucinations and delusions were lower when measured by NPI scales and in population-based samples. DISCUSSION: Delusions and hallucinations occur in MCI patients at low rates. Prevalence can be partially explained by the assessment method, sample source and study heterogeneity.

Psychosis detection in dementia: a systematic review of diagnostic test accuracy studies.

Introduction: Symptoms of psychosis, characterized by delusions and hallucinations, are commonly experienced by persons living with dementia. A systematic review was completed to identify tools to evaluate symptoms of psychosis compared to a reference standard in persons with dementia. Articles reporting correlation values between psychosis tools were also identified. Methods: The search concepts psychosis, dementia, and diagnostic accuracy were used to search MEDLINE, PsycINFO, and Embase. Included articles meeting the primary objective described a tool to assess symptoms of psychosis, delusions, or hallucinations in persons with dementia, a reference standard form of diagnostic assessment for psychosis, and diagnostic accuracy outcomes for the psychosis tool. Secondary objective articles reported correlation values between two or more psychosis tools in persons with dementia. Results: One study met the primary objective and described the sensitivity and specificity of the Neuropsychiatric Inventory (NPI) and Columbia University Scale for Psychopathology in Alzheimer's Disease (CUSPAD) in identifying symptoms of psychosis, hallucinations, and delusions. The sensitivity of the NPI and CUSPAD in identifying symptoms of psychosis was 83 and 90%, respectively. Nine studies meeting the secondary objective described eleven unique tools and examined the degree to which tools used to assess psychotic symptoms in persons with dementia were related. Discussion: The NPI and CUSPAD were identified in a single study as psychosis tools that have been evaluated against a reference standard of psychosis assessment in persons with dementia. Various tools to assess the burden of psychotic symptoms in persons with dementia exist, but the diagnostic accuracy of existing tools remains understudied. Further research on the comparative utility and diagnostic accuracy is required for all psychosis tools used with persons with dementia.

Detection of anxiety symptoms and disorders in older adults: a diagnostic accuracy systematic review.

BACKGROUND: Anxiety symptoms and disorders are common in older adults and often go undetected. A systematic review was completed to identify tools that can be used to detect anxiety symptoms and disorders in community-dwelling older adults. METHODS: MEDLINE, Embase and PsycINFO were searched using the search concepts anxiety, older adults and diagnostic accuracy in March 2023. Included articles assessed anxiety in community-dwelling older adults using an index anxiety tool and a gold standard form of anxiety assessment and reported resulting diagnostic accuracy outcomes. Estimates of pooled diagnostic accuracy outcomes were completed. RESULTS: Twenty-three anxiety tools were identified from the 32 included articles. Pooled diagnostic accuracy outcomes were estimated for the Geriatric Anxiety Inventory (GAI)-20 [n = 3, sensitivity = 0.89, 95% confidence interval (CI) = 0.70-0.97, specificity = 0.80, 95% CI = 0.67-0.89] to detect generalized anxiety disorder (GAD) and for the GAI-20 (n = 3, cut off ≥ 9, sensitivity = 0.74, 95% CI = 0.62-0.83, specificity = 0.96, 95% CI = 0.74-1.00), Beck Anxiety Inventory (n = 3, sensitivity = 0.70, 95% CI = 0.58-0.79, specificity = 0.60, 95% CI = 0.51-0.68) and Hospital Anxiety and Depression Scale (HADS-A) (n = 3, sensitivity = 0.78, 95% CI = 0.60-0.89, specificity = 0.76, 95% CI = 0.60-0.87) to detect anxiety disorders in clinical samples. CONCLUSION: The GAI-20 was the most studied tool and had adequate sensitivity while maintaining acceptable specificity when identifying GAD and anxiety disorders. The GAI-20, GAI-Short Form and HADS-A tools are supported for use in detecting anxiety in community-dwelling older adults. Brief, self-rated and easy-to-use tools may be the best options for anxiety detection in community-dwelling older adults given resource limitations. Clinicians may consider factors including patient comorbidities and anxiety prevalence when selecting a tool and cut off.

Detecting agitation and aggression in persons living with dementia: a systematic review of diagnostic accuracy.

OBJECTIVE: 40-60% of persons living with dementia (PLWD) experience agitation and/or aggression symptoms. There is a need to understand the best method to detect agitation and/or aggression in PLWD. We aimed to identify agitation and/or aggression tools that are validated against a reference standard within the context of PLWD. METHODS: Our study was registered on PROSPERO (CRD42020156708). We searched MEDLINE, Embase, and PsycINFO up to April 22, 2024. There were no language or date restrictions. Studies were included if they used any tools or questionnaires for detecting either agitation or aggression compared to a reference standard among PLWD, or any studies that compared two or more agitation and/or aggression tools in the population. All screening and data extraction were done in duplicates. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Data extraction was completed in duplicates by two independent authors. We extracted demographic information, prevalence of agitation and/or aggression, and diagnostic accuracy measures. We also reported studies comparing the correlation between two or more agitation and/or aggression tools. RESULTS: 6961 articles were screened across databases. Six articles reporting diagnostic accuracy measures compared to a reference standard and 30 articles reporting correlation measurements between tools were included. The agitation domain of the Spanish NPI demonstrated the highest sensitivity (100%) against the agitation subsection of the Spanish CAMDEX. Single-study evidence was found for the diagnostic accuracy of commonly used agitation scales (BEHAVE-AD, NPI and CMAI). CONCLUSIONS: The agitation domain of the Spanish NPI, the NBRS, and the PAS demonstrated high sensitivities, and may be reasonable for clinical implementation. However, a limitation to this finding is that despite an extensive search, few studies with diagnostic accuracy measurements were identified. Ultimately, more research is needed to understand the diagnostic accuracy of agitation and/or aggression detection tools among PLWD.

Mild behavioral impairment domains are longitudinally associated with pTAU and metabolic biomarkers in dementia-free older adults.

BACKGROUND: The mechanisms linking mild behavioral impairment (MBI) and Alzheimer's disease (AD) have been insufficiently explored, with conflicting results regarding tau protein and few data on other metabolic markers. We aimed to evaluate the longitudinal association of the MBI domains and a spectrum of plasma biomarkers. METHODS: Our study is a secondary analysis of data from NOLAN. The longitudinal association of the MBI domains with plasma biomarkers, including pTau181, was tested using adjusted linear mixed-effects models. RESULTS: The sample comprised 359 participants (60% female, mean age: 78.3, standard deviation: 0.3 years). After 1 year, the MBI domain of abnormal perception was associated with steeper increases in plasma pTau181. Abnormal perception, decreased motivation, and impulse dyscontrol were associated with homocysteine or insulin dysregulation. DISCUSSION: Apart from the association with plasma pTau181, our results suggest that MBI might also represent metabolic dysregulation, probably contributing to dementia transition among older adults with subjective cognitive decline or mild cognitive impairment. HIGHLIGHTS: Mild behavioral impairment (MBI) psychosis was associated with steeper increases in plasma p. pTau could be a pharmacological target to treat agitation and psychosis symptoms. MBI domains were linked to metabolic dysregulation involving insulin and homocysteine.

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 : Mise à jour des lignes directrices cliniques pour la prise en charge du trouble dépressif majeur chez les adultes.

BACKGROUND: The Canadian Network for Mood and Anxiety Treatments (CANMAT) last published clinical guidelines for the management of major depressive disorder (MDD) in 2016. Owing to advances in the field, an update was needed to incorporate new evidence and provide new and revised recommendations for the assessment and management of MDD in adults. METHODS: CANMAT convened a guidelines editorial group comprised of academic clinicians and patient partners. A systematic literature review was conducted, focusing on systematic reviews and meta-analyses published since the 2016 guidelines. Recommendations were organized by lines of treatment, which were informed by CANMAT-defined levels of evidence and supplemented by clinical support (consisting of expert consensus on safety, tolerability, and feasibility). Drafts were revised based on review by patient partners, expert peer review, and a defined expert consensus process. RESULTS: The updated guidelines comprise eight primary topics, in a question-and-answer format, that map a patient care journey from assessment to selection of evidence-based treatments, prevention of recurrence, and strategies for inadequate response. The guidelines adopt a personalized care approach that emphasizes shared decision-making that reflects the values, preferences, and treatment history of the patient with MDD. Tables provide new and updated recommendations for psychological, pharmacological, lifestyle, complementary and alternative medicine, digital health, and neuromodulation treatments. Caveats and limitations of the evidence are highlighted. CONCLUSIONS: The CANMAT 2023 updated guidelines provide evidence-informed recommendations for the management of MDD, in a clinician-friendly format. These updated guidelines emphasize a collaborative, personalized, and systematic management approach that will help optimize outcomes for adults with MDD.

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research.

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease.

BACKGROUND: Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood. OBJECTIVE: The aim was to explore the changes in white matter microstructure linked to MBI and mild cognitive impairment (MCI) in early- to mid-stage PD using diffusion magnetic resonance imaging (dMRI). METHODS: A total of 91 PD patients and 36 healthy participants were recruited and underwent anatomical MRI and dMRI, a comprehensive neuropsychological battery, and the completion of the Mild Behavioral Impairment-Checklist. Metrics of white matter integrity included tissue fractional anisotropy (FAt) and radial diffusivity (RDt), free water (FW), and fixel-based apparent fiber density (AFD). RESULTS: The connection between the left amygdala and the putamen was disrupted when comparing PD patients with MBI (PD-MBI) to PD-non-MBI, as evidenced by increased RDt (η2 = 0.09, P = 0.004) and both decreased AFD (η2 = 0.05, P = 0.048) and FAt (η2 = 0.12, P = 0.014). Compared to controls, PD patients with both MBI and MCI demonstrated increased FW for the connection between the left orbitofrontal gyrus (OrG) and the hippocampus (η2 = 0.22, P = 0.008), augmented RDt between the right OrG and the amygdala (η2 = 0.14, P = 0.008), and increased RDt (η2 = 0.25, P = 0.028) with decreased AFD (η2 = 0.10, P = 0.046) between the right OrG and the caudate nucleus. CONCLUSION: MBI is associated with abnormal microstructure of connections involving the orbitofrontal cortex, putamen, and amygdala. To our knowledge, this is the first assessment of the white matter microstructure in PD-MBI using dMRI. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Guideline Recommendations on Behavioral and Psychological Symptoms of Dementia: A Systematic Review.

OBJECTIVE: To synthesize recommendations on assessing and managing behavioral and psychological symptoms of dementia (BPSDs) in existing clinical practice guidelines on dementia care to learn from and adapt recommendations to a Canadian context and language for describing BPSDs. DESIGN: Systematic review. SETTING AND PARTICIPANTS: Moderate to high-quality clinical practice guidelines on dementia care that made 1 or more recommendations on BPSD assessment or management. METHODS: We searched MEDLINE, Embase, JBI EBM, PsycINFO, AgeLine, and gray literature for clinical practice guidelines on dementia care making recommendations on BPSD, published between January 1, 2011, and October 13, 2022. Two independent reviewers conducted study screening and data abstraction. Four independent reviewers completed quality appraisal using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool; included guidelines had a mean overall AGREE II score ≥4. RESULTS: Our systematic review identified 23 moderate to high-quality clinical practice guidelines (264 recommendations). The mean overall quality score on the AGREE II tool ranged from 4 to 6.5. Recommendations were clearly presented (mean clarity of presentation score 73.5%), but guideline applicability was not consistently addressed (mean applicability score 39.3%). BPSD was the most prevalent term describing neuropsychiatric symptoms (number of guidelines [n] = 14). People with lived experience contributed to 6 guidelines (26.1%). Ten guidelines (43.5%) described 1 or more health equity considerations. Guidelines made recommendations for assessing and managing agitation (n = 12), aggression (n = 10), psychosis (n = 11), depression (n = 9), anxiety (n = 5), apathy (n = 6), inappropriate sexual behavior (n = 3), nighttime behavior (n = 5), and eating disturbances (n = 3). There was substantial variability in recommendation statements, evidence quality assigned to each statement, and strength of recommendations. CONCLUSIONS AND IMPLICATIONS: There are several moderate to high-quality clinical practice guidelines making recommendations on BPSD assessment and management, but variability in recommendation statements across guidelines and insufficient consideration of guideline applicability may hamper guideline dissemination and implementation in clinical practice.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease.

Background: While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain. Objective: To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum. Methods: Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations. Results: MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aß1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers. Conclusions: Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Barriers and facilitators to care for agitation and/or aggression among persons living with dementia in long-term care.

BACKGROUND: Agitation and/or aggression affect up to 60% of persons living with dementia in long-term care (LTC). It can be treated via non-pharmacological and pharmacological interventions, but the former are underused in clinical practice. In the literature, there is currently a lack of understanding of the challenges to caring for agitation and/or aggression among persons living with dementia in LTC. This study assesses what barriers and facilitators across the spectrum of care exist for agitation and/or aggression among people with dementia in LTC across stakeholder groups. METHODS: This was a qualitative study that used semi-structured interviews among persons involved in the care and/or planning of care for people with dementia in LTC. Participants were recruited via purposive and snowball sampling, with the assistance of four owner-operator models. Interviews were guided by the Theoretical Domains Framework and transcribed and analyzed using Framework Analysis. RESULTS: Eighteen interviews were conducted across 5 stakeholder groups. Key identified barriers were a lack of agitation and/or aggression diagnostic measures, limited training for managing agitation and/or aggression in LTC, an overuse of physical and chemical restraints, and an underuse of non-pharmacological interventions. Facilitators included using an interdisciplinary team to deliver care and having competent and trained healthcare providers to administer non-pharmacological interventions. CONCLUSIONS: This study advances care for persons living with dementia in LTC by drawing attention to unique and systemic barriers present across local and national Canadian LTC facilities. Findings will support future implementation research endeavours to eliminate these identified barriers across the spectrum of care, thus improving care outcomes among people with dementia in LTC.

Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study.

OBJECTIVES: Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses. METHODS: The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits. RESULTS: Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively. CONCLUSIONS: The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Adjunctive Brexpiprazole for Patient Life Engagement in Major Depressive Disorder: A Canadian, Phase 4, Open-Label, Interventional Study: Brexpiprazole d'appoint pour l'engagement dans la vie des patients souffrant de trouble dépressif majeur: une étude interventionnelle canadienne ouverte de phase 4.

OBJECTIVES: To characterize the effects of adjunctive brexpiprazole on patient life engagement and depressive symptoms in patients with major depressive disorder (MDD) using patient-reported outcomes. METHODS: An 8-week, Phase 4, open-label, interventional study was conducted at 15 Canadian trial sites between April 2021 and May 2022. Adult outpatients with MDD (at least moderately severe) and inadequate response to 1-2 antidepressants continued their current antidepressant and received oral adjunctive brexpiprazole 0.5-2 mg/day. Co-primary endpoints were change from baseline to Week 8 in Inventory of Depressive Symptomatology Self-Report (IDS-SR) 10-item Life Engagement subscale score, and IDS-SR 30-item total score. Safety was assessed by standard variables. RESULTS: Of 122 enrolled patients, 120 (98.4%) were treated (mean [SD] dose: 1.2 [0.4] mg/day) and analyzed, and 111 (91.0%) completed the study. Statistically significant least squares mean improvements to Week 8 were observed on IDS-SR10 Life Engagement subscale score (baseline mean [SD]: 16.1 [4.7]; change [95% confidence interval]: -8.11 [-9.34, -6.88]; p < 0.001) and IDS-SR total score (baseline mean [SD]: 41.3 [9.8]; change [95% confidence interval]: -17.38 [-20.08, -14.68]; p < 0.001). Improvements were observed from Week 2, onwards. Treatment-emergent adverse events with incidence ≥5% were fatigue (n = 13, 10.8%), headache (n = 13, 10.8%), insomnia (n = 12, 10.0%), nausea (n = 9, 7.5%), tremor (n = 8, 6.7%), and weight increase (n = 7, 5.8%). Six patients (5.0%) discontinued due to adverse events. Mean (SD) change in body weight from baseline to last visit was +1.9 (3.4) kg. CONCLUSIONS: Using an exploratory patient-reported outcome measure, patients with MDD and inadequate response to antidepressants who received open-label adjunctive brexpiprazole showed early and clinically meaningful improvement in patient life engagement, which should be further assessed in a prospective randomized controlled trial. Patient-rated depressive symptoms (on the validated 30-item IDS-SR) also improved. Adjunctive brexpiprazole was well tolerated, and no new safety signals were observed. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04830215.

Tau-PET in early cortical Alzheimer brain regions in relation to mild behavioral impairment in older adults with either normal cognition or mild cognitive impairment.

Mild Behavioral Impairment (MBI) leverages later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a high-risk group for incident dementia. Phosphorylated tau (p-tau) is a hallmark biological manifestation of Alzheimer disease (AD). We investigated associations between MBI and tau accumulation in early-stage AD cortical regions. In 442 Alzheimer's Disease Neuroimaging Initiative participants with normal cognition or mild cognitive impairment, MBI status was determined alongside corresponding p-tau and Aß. Two meta-regions of interest were generated to represent Braak I and III neuropathological stages. Multivariable linear regression modelled the association between MBI as independent variable and tau tracer uptake as dependent variable. Among Aß positive individuals, MBI was associated with tau uptake in Braak I (ß=0.45(0.15), p<.01) and Braak III (ß=0.24(0.07), p<.01) regions. In Aß negative individuals, MBI was not associated with tau in the Braak I region (p=0.11) with a negative association in Braak III (p=.01). These findings suggest MBI may be a sequela of neurodegeneration, and can be implemented as a cost-effective framework to help improve screening efficiency for AD.

A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm.

Distributed learning is a promising alternative to central learning for machine learning (ML) model training, overcoming data-sharing problems in healthcare. Previous studies exploring federated learning (FL) or the traveling model (TM) setup for medical image-based disease classification often relied on large databases with a limited number of centers or simulated artificial centers, raising doubts about real-world applicability. This study develops and evaluates a convolution neural network (CNN) for Parkinson's disease classification using data acquired by 83 diverse real centers around the world, mostly contributing small training samples. Our approach specifically makes use of the TM setup, which has proven effective in scenarios with limited data availability but has never been used for image-based disease classification. Our findings reveal that TM is effective for training CNN models, even in complex real-world scenarios with variable data distributions. After sufficient training cycles, the TM-trained CNN matches or slightly surpasses the performance of the centrally trained counterpart (AUROC of 83% vs. 80%). Our study highlights, for the first time, the effectiveness of TM in 3D medical image classification, especially in scenarios with limited training samples and heterogeneous distributed data. These insights are relevant for situations where ML models are supposed to be trained using data from small or remote medical centers, and rare diseases with sparse cases. The simplicity of this approach enables a broad application to many deep learning tasks, enhancing its clinical utility across various contexts and medical facilities.

Exploiting macro- and micro-structural brain changes for improved Parkinson's disease classification from MRI data.

Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop and evaluate an explainable deep learning model for PD classification from multimodal neuroimaging data. The model was trained using one of the largest collections of T1-weighted and diffusion-tensor magnetic resonance imaging (MRI) datasets. A total of 1264 datasets from eight different studies were collected, including 611 PD patients and 653 healthy controls (HC). These datasets were pre-processed and non-linearly registered to the MNI PD25 atlas. Six imaging maps describing the macro- and micro-structural integrity of brain tissues complemented with age and sex parameters were used to train a convolutional neural network (CNN) to classify PD/HC subjects. Explainability of the model's decision-making was achieved using SmoothGrad saliency maps, highlighting important brain regions. The CNN was trained using a 75%/10%/15% train/validation/test split stratified by diagnosis, sex, age, and study, achieving a ROC-AUC of 0.89, accuracy of 80.8%, specificity of 82.4%, and sensitivity of 79.1% on the test set. Saliency maps revealed that diffusion tensor imaging data, especially fractional anisotropy, was more important for the classification than T1-weighted data, highlighting subcortical regions such as the brainstem, thalamus, amygdala, hippocampus, and cortical areas. The proposed model, trained on a large multimodal MRI database, can classify PD patients and HC subjects with high accuracy and clinically reasonable explanations, suggesting that micro-structural brain changes play an essential role in the disease course.