Validating the Mild Behavioral Impairment Checklist in a Cognitive Clinic: Comparisons With the Neuropsychiatric Inventory Questionnaire.

OBJECTIVE: To compare the utility of the Mild Behavioral Impairment-Checklist (MBI-C) and Neuropsychiatric Inventory Questionnaire (NPI-Q) to capture NPS in subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia. METHODS: In this cross-sectional memory clinic study, linear regression models compared MBI-C (n = 474) and NPI-Q (n = 1040) scores in relation to Montreal Cognitive Assessment (MoCA) score. RESULTS: MBI prevalence was 37% in subjective cognitive decline, 54% in mild cognitive impairment, and 62% in dementia. Worse diagnostic status was associated with higher MBI-C and NPI-Q score (P < .001), lower MoCA (P < .001), and greater age (P < .001). Higher MBI-C (ß -.09; 95% CI -.13, -.05) and NPI-Q (ß -.17; 95% CI -.23, -.10) scores were associated with lower MoCA scores, with psychosis most strongly associated (ß -1.11; 95% CI -1.56, -.65 vs ß -1.14; 95% CI -1.55, -.73). CONCLUSIONS: The MBI-C captures global and domain-specific NPS across cognitive stages. Both the MBI-C and NPI-Q have utility in characterizing NPS.

Fall 2021: Clinician Investigator Trainee Association Of Canada (CITAC).

I hope you're taking care and found some time to relax this summer. A new semester may mean a big transition­some folks are starting their graduate studies, re-entering clerkship, starting residency or entering a fellowship. For some, there will be little or no change at all; but just a continuation of one of the many phases of the physician-scientist training pathway. Whatever stage you're at, the Clinical Investigator Trainee Association of Canada (CITAC) community is here to support and advocate for you!

Spring 2021: Clinician Investigator Trainee Association Of Canada (CITAC).

The Clinician Investigator Trainee Association of Canada (CI) trainees across the country around the common goal of improving training conditions for those pursuing a career at the junction of research and medicine. Since then, the CI training landscape has shifted dramatically. The number of Canadian CI trainees enrolled totaling 289 MD-PhD trainees and 389 Clinical Investigator Program (CIP) trainees as of 2019 [1]. Alumni outcome data have presented conclusive evidence that MD-PhD training programs are effective in producing CI careers [2-4].

Newsletter Fall 2020: Clinician Investigator Trainee Association of Canada (CITAC).

Message from the CITAC president To say that 2020 has been an unprecedented year is an understatement. The coronavirus disease 2019 (COVID-19) global pandemic and the major societal awakening on racial equity and justice have led us to reflect on our direction, goals and mission. Thanks to our talented and dedicated executive team, we were able to pivot our efforts and adapt to the changing landscape of research and advocacy. In April, we provided our members with a list of resources to help facilitate a smooth transition to working from home. In June, we published Clinician Investigator Trainee Association of Canada's (CITAC) press release on our role in combating anti-Black discrimination and racial injustice and have outlined specific advocacy efforts that we will be committing to over the next years (the full statement can be found on our website, https://www.citac-accfc.org).

Overview of the Canadian Clinician Investigator Trainees' research presented at the 2019 CSCI-CITAC Joint Meeting.

The 2019 Annual General Meeting and Young Investigators' Forum of the Canadian Society for Clinical Investigation / Société Canadienne de Recherche Clinique (CSCI/SCRC) and Clinician Investigator Trainee Association of Canada / Association des Cliniciens-Chercheurs en Formation du Canada (CITAC/ACCFC) was held in Banff, Alberta on November 8-10th, 2019. The theme was "Positioning Early Career Investigators for Success: Strategy and Resilience". Lectures and workshops provided knowledge and tools to facilitate the attendees' development as clinician investigators. Dr. Jason Berman (President of CSCI/SCRC), Elina Cook (President of CITAC/ACCFC) and Drs. Doreen Rabi and Zelma Kiss (University of Calgary Organizing Co-Chairs) gave opening presentations. The keynote speakers were Dr. William Foulkes (McGill University) (Distinguished Scientist Award winner) and Dr. Andrés Finzi (Université de Montréal) (Joe Doupe Young Investigator Award winner). Dr. Robert Bortolussi (Dalhousie University) received the Distinguished Service Award for his work as the Editor-in-Chief of Clinical and Investigative Medicine and for being instrumental in the development of the Canadian Child Health Clinician Scientist Program. This meeting was the first to host a panel discussion with Drs. Stephen Robbins and Marcello Tonelli from the Canadian Institutes of Health Research. Workshops on communication, career planning and work-life balance were hosted by André Picard and Drs. Todd Anderson, Karen Tang, William Ghali, May Lynn Quan, Alicia Polachek and Shannon Ruzycki. The AGM showcased 90 presentations from clinician investigator trainees from across Canada. Most of the abstracts are summarized in this review. Eight outstanding abstracts were selected for oral presentation at the President's Forum.

Association of DNMT3b gene variants with sporadic Parkinson's disease in a Chinese Han population.

BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disorder worldwide. Epigenetic modifications, specifically DNA methylation, have been implicated in the development of this disease. Genetic variants of DNA methyltransferase 3b (DNMT3b), one of the most important DNA methyltransferases, were shown to be associated with PD in a Brazilian population. However, it is unclear whether genetic variants of DNMT3b increase the risk of PD in the Chinese Han people. The present study aimed to investigate the association of the DNMT3b variants rs2424913, rs998382 and rs2424932 with PD in a Chinese Han population. METHODS: We studied 487 Chinese Han patients with sporadic PD and 485 healthy age-, sex- and ethnicity-matched controls. DNA was extracted from peripheral blood leukocytes and the individual genotypes were determined using the SNaPshot method. RESULTS: We found that the rs2424932 and rs998382 variants were significantly associated with an increased risk of PD compared to the controls [rs2424932: odds ratio (OR) = 1.632, 95% confidence interval (CI) = 1.108-2.406, p = 0.013; rs998382: OR = 1.612, 95% CI = 1.103-2.382, p = 0.014]. Subgroup analysis suggested that female patients carrying the rs2424932 or rs998382 variants were more likely to develop PD than female controls (rs2424932: OR = 3.863, 95% CI = 2.004-7.445, p < 0.001; rs998382: OR = 3.679, 95% CI = 1.943-6.964, p < 0.001). Haplotype analysis indicated that the three variants comprised one block and that the Trs2424913 -Crs998382 -A rs2424932 haplotype was correlated with an increased risk of PD (p = 0.0046), especially for Chinese Han females (p < 0.0001). CONCLUSIONS: The results of the present study strongly suggest that DNMT3b variants are associated with PD in the Chinese Han people, especially females.

Protocol for the development of a tool to map systemic sclerosis pain sources, patterns, and management experiences: a Scleroderma Patient-centered Intervention Network patient-researcher partnership.

INTRODUCTION: Systemic sclerosis (SSc) is a rare, complex autoimmune rheumatic disease with multiple factors that contribute to pain. People with SSc emphasize the effect pain has on their quality of life, but no studies have systematically examined the frequency and relative importance of different SSc pain sources, patterns of pain from different sources, and pain management experiences. Our objectives are to (1) develop a tool, jointly with researchers, health care providers, and patients, to map sources of pain in SSc, determine patterns of pain from different sources, and understand pain management experiences; and (2) administer the final tool version to participants in the large multinational Scleroderma Patient-centered Intervention Network (SPIN) Cohort. METHODS: First, we will use validated pain assessment tools as templates to develop an initial version of our pain assessment tool, and we will obtain input from patient advisors to adapt it for SSc. The tool will include questions on pain sources, pain patterns, pain intensity, pain management techniques, and barriers to pain management in SSc. Second, we will conduct nominal group technique sessions with people living with SSc and health care providers who care for people with SSc to further refine the tool. Third, we will conduct individual usability testing sessions with SPIN Cohort participants. Once the tool has been finalized, we will administer it to individuals in the multinational SPIN Cohort, which currently includes over 1,300 active participants from 54 sites in 7 countries. We will perform unsupervised clustering using the KAy-Means for MIxed LArge data (KAMILA) method to identify participant subgroups with similar profiles of pain sources (present or absent) and to evaluate predictors of subgroup membership. We will use latent profile analysis to identify subgroups of participants with similar profiles based on pain intensity scores for each pain source and evaluate predictors. DISCUSSION: Once completed, our pain assessment tool will allow our team and other researchers to map sources of pain in SSc and to understand pain management experiences of people living with SSc. This knowledge will provide avenues for studies on the pathophysiology of pain in SSc and studies of interventions to improve pain management.

VAMP2 controls murine epidermal differentiation and carcinogenesis by regulation of nucleophagy.

Differentiation of murine epidermal stem/progenitor cells involves the permanent withdrawal from the cell cycle, the synthesis of various protein and lipid components for the cornified envelope, and the controlled dissolution of cellular organelles and nuclei. Deregulated epidermal differentiation contributes to the development of various skin diseases, including skin cancers. With a genome-wide shRNA screen, we identified vesicle-associated membrane protein 2 (VAMP2) as a critical factor involved in skin differentiation. Deletion of VAMP2 leads to aberrant skin stratification and enucleation in vivo. With quantitative proteomics, we further identified an autophagy protein, focal adhesion kinase family interacting protein of 200 kDa (FIP200), as a binding partner of VAMP2. Additionally, we showed that both VAMP2 and FIP200 are critical for murine keratinocyte enucleation and epidermal differentiation. Loss of VAMP2 or FIP200 enhances cutaneous carcinogenesis in vivo. Together, our findings identify important molecular mechanisms underlying epidermal differentiation and skin tumorigenesis.

Health Care Students' Perspectives on Artificial Intelligence: Countrywide Survey in Canada.

BACKGROUND: Artificial intelligence (AI) is no longer a futuristic concept; it is increasingly being integrated into health care. As studies on attitudes toward AI have primarily focused on physicians, there is a need to assess the perspectives of students across health care disciplines to inform future curriculum development. OBJECTIVE: This study aims to explore and identify gaps in the knowledge that Canadian health care students have regarding AI, capture how health care students in different fields differ in their knowledge and perspectives on AI, and present student-identified ways that AI literacy may be incorporated into the health care curriculum. METHODS: The survey was developed from a narrative literature review of topics in attitudinal surveys on AI. The final survey comprised 15 items, including multiple-choice questions, pick-group-rank questions, 11-point Likert scale items, slider scale questions, and narrative questions. We used snowball and convenience sampling methods by distributing an email with a description and a link to the web-based survey to representatives from 18 Canadian schools. RESULTS: A total of 2167 students across 10 different health professions from 18 universities across Canada responded to the survey. Overall, 78.77% (1707/2167) predicted that AI technology would affect their careers within the coming decade and 74.5% (1595/2167) reported a positive outlook toward the emerging role of AI in their respective fields. Attitudes toward AI varied by discipline. Students, even those opposed to AI, identified the need to incorporate a basic understanding of AI into their curricula. CONCLUSIONS: We performed a nationwide survey of health care students across 10 different health professions in Canada. The findings would inform student-identified topics within AI and their preferred delivery formats, which would advance education across different health care professions.

Mild Behavioral Impairment and Subjective Cognitive Decline Predict Cognitive and Functional Decline.

BACKGROUND: Mild behavioral impairment (MBI) and subjective cognitive decline (SCD) are dementia risk states, and potentially represent neurobehavioral and neurocognitive manifestations, respectively, of early stage neurodegeneration. Both MBI and SCD predict incident cognitive decline and dementia, are associated with known dementia biomarkers, and are both represented in the NIA-AA research framework for AD in Stage 2 (preclinical disease). OBJECTIVE: To assess the associations of MBI and SCD, alone and in combination, with incident cognitive and functional decline in a population of older adults. We tested the hypothesis that MBI and SCD confer additive risk for decline. METHODS: Cognitively normal participants were followed up annually at Alzheimer's Disease Centers. Logistic regression assessed the relationship between baseline classification (MBI-SCD-, MBI-SCD+, MBI+SCD-, or MBI+SCD+) and 3-year outcome. RESULTS: Of 2,769 participants (mean age=76), 1,536 were MBI-SCD-, 254 MBI-SCD+, 743 MBI+SCD-, and 236 MBI+SCD+. At 3 years, 349 (12.6%) declined to CDR >0, including 23.1% of the MBI+group, 23.5% of the SCD+group, and 30.9% of the intersection group of both MBI+and SCD+participants. Compared to SCD-MBI-, we observed an ordinal progression in risk (ORs [95% CI]): 3.61 [2.42-5.38] for MBI-SCD+ (16.5% progression), 4.76 [3.57-6.34] for MBI+SCD- (20.7%), and 8.15 [5.71-11.64] for MBI+SCD+(30.9%). CONCLUSION: MBI and SCD together were associated with the greatest risk of decline. These complementary dementia risk syndromes can be used as simple and scalable methods to identify high-risk patients for workup or for clinical trial enrichment.

Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data.

BACKGROUND: Machine learning (ML) is a promising technique for patient-specific prediction of mild cognitive impairment (MCI) and dementia development. Neuropsychiatric symptoms (NPS) might improve the accuracy of ML models but have barely been used for this purpose. OBJECTIVES: To investigate if baseline mild behavioral impairment (MBI) status used for NPS quantification along with brain morphology features are predictive of follow-up diagnosis, median 40 months later in patients with normal cognition (NC) or MCI. METHOD: Baseline neuroimaging, neuropsychiatric, and clinical data from 102 individuals with NC and 239 with MCI were extracted from the Alzheimer's Disease Neuroimaging Initiative database. Neuropsychiatric inventory questionnaire items were transformed to MBI domains using a published algorithm. Diagnosis at latest follow-up was used as the outcome variable and ground truth classification. A logistic model tree classifier combined with information gain feature selection was trained to predict follow-up diagnosis. RESULTS: In the binary classification (NC versus MCI/AD), the optimal ML model required only two features from over 200, MBI total score and left hippocampal volume. These features correctly classified participants as remaining normal or developing cognitive impairment with 84.4% accuracy (area under the receiver operating characteristics curve [ROC-AUC] = 0.86). Seven features were selected for the three-class model (NC versus MCI versus dementia) achieving an accuracy of 58.8% (ROC-AUC=0.73). CONCLUSION: Baseline NPS, categorized for MBI domain and duration, have prognostic utility in addition to brain morphology measures for predicting diagnosis change using ML. MBI total score, followed by impulse dyscontrol and affective dysregulation were most predictive of future diagnosis.

Characterizing early Canadian federal, provincial, territorial and municipal nonpharmaceutical interventions in response to COVID-19: a descriptive analysis.

BACKGROUND: Nonpharmaceutical interventions (NPIs) are the primary tools to mitigate early spread of the coronavirus disease 2019 (COVID-19) pandemic; however, such policies are implemented variably at the federal, provincial or territorial, and municipal levels without centralized documentation. We describe the development of the comprehensive open Canadian Non-Pharmaceutical Intervention (CAN-NPI) data set, which identifies and classifies all NPIs implemented in regions across Canada in response to COVID-19, and provides an accompanying description of geographic and temporal heterogeneity. METHODS: We performed an environmental scan of government websites, news media and verified government social media accounts to identify NPIs implemented in Canada between Jan. 1 and Apr. 19, 2020. The CAN-NPI data set contains information about each intervention's timing, location, type, target population and alignment with a response stringency measure. We conducted descriptive analyses to characterize the temporal and geographic variation in early NPI implementation. RESULTS: We recorded 2517 NPIs grouped in 63 distinct categories during this period. The median date of NPI implementation in Canada was Mar. 24, 2020. Most jurisdictions heightened the stringency of their response following the World Health Organization's global pandemic declaration on Mar. 11, 2020. However, there was variation among provinces or territories in the timing and stringency of NPI implementation, with 8 out of 13 provinces or territories declaring a state of emergency by Mar. 18, and all by Mar. 22, 2020. INTERPRETATION: There was substantial geographic and temporal heterogeneity in NPI implementation across Canada, highlighting the importance of a subnational lens in evaluating the COVID-19 pandemic response. Our comprehensive open-access data set will enable researchers to conduct robust interjurisdictional analyses of NPI impact in curtailing COVID-19 transmission.

Plasma Neurofilament Light: A Marker of Neurodegeneration in Mild Behavioral Impairment.

BACKGROUND: Assessing neuropsychiatric symptoms (NPS) in older adults is important for determining dementia risk. Mild behavioral impairment (MBI) is an at-risk state for cognitive decline and dementia, characterized by emergent NPS in later life. MBI has significantly higher dementia incidence than late life psychiatric conditions. However, its utility as a proxy for neurodegeneration has not been demonstrated. Plasma neurofilament light (NfL) is a validated biomarker of axonal damage, and has been shown to associate with hallmarks of neurodegeneration. OBJECTIVE: The purpose of this investigation was to identify associations between NfL rate of change and the presence of MBI symptomatology. METHODS: We evaluated the association of MBI with changes in NfL in a cohort (n = 584; MBI + n = 190, MBI- n = 394) of non-demented participants from the Alzheimer's Disease Neuroimaging Initiative. MBI was determined by transforming Neuropsychiatric Inventory Questionnaire items using a published algorithm. Change in NfL was calculated over 2 years. RESULTS: Time*MBI status was the only significant interaction to predict change in NfL concentrations (F(1,574) = 4.59, p = 0.032), even after controlling for age, mild cognitive impairment, and demographics. Analyses reclassifying 64 participants with new onset MBI over 2 years similarly demonstrated greater increases in NfL (F(1,574) = 5.82, p = 0.016). CONCLUSION: These findings suggest MBI is a clinical proxy of early phase neurodegeneration with putative utility in identifying those at dementia risk. MBI can be used as a case ascertainment approach to capture those at high risk for cognitive decline and dementia, and is an important construct for clinicians dealing with cognitive and neuropsychiatric symptomatology in older adults.

Agitation and impulsivity in mid and late life as possible risk markers for incident dementia.

To identify knowledge gaps regarding new-onset agitation and impulsivity prior to onset of cognitive impairment or dementia the International Society to Advance Alzheimer's Research and Treatment Neuropsychiatric Syndromes (NPS) Professional Interest Area conducted a scoping review. Extending a series of reviews exploring the pre-dementia risk syndrome Mild Behavioral Impairment (MBI), we focused on late-onset agitation and impulsivity (the MBI impulse dyscontrol domain) and risk of incident cognitive decline and dementia. This scoping review of agitation and impulsivity pre-dementia syndromes summarizes the current biomedical literature in terms of epidemiology, diagnosis and measurement, neurobiology, neuroimaging, biomarkers, course and prognosis, treatment, and ongoing clinical trials. Validations for pre-dementia scales such as the MBI Checklist, and incorporation into longitudinal and intervention trials, are needed to better understand impulse dyscontrol as a risk factor for mild cognitive impairment and dementia.

G2019S LRRK2 Increases Stress Susceptibility Through Inhibition of DAF-16 Nuclear Translocation in a 14-3-3 Associated-Manner in Caenorhabditis elegans.

Mutations in leucine-rich repeat kinase 2 (LRRK2) are common causes of familial Parkinson's disease (PD). Oxidative stress plays a key role in the pathogenesis of PD. Mutations in LRRK2 have been shown to increase susceptibility to oxidative stress. To explore mechanisms underlying susceptibility to oxidative stress in LRRK2 mutants, we generated stable Caenorhabditis elegans (C. elegans) strains in which human LRRK2 proteins including wild type LRRK2 (WT), G2019S LRRK2 (G2019S), and G2019S-D1994A kinase-dead LRRK2 (KD) were expressed in all neurons. Human 14-3-3 ß was injected into LRRK2 transgenic worms to allow co-expression of 14-3-3 ß and LRRK2 proteins. We found that G2019S transgenic worms had increased sensitivity to stress (heat and juglone treatment) and impaired stress-induced nuclear translocation of DAF-16. In addition, G2019S inhibited ftt2 (a 14-3-3 gene homolog in C. elegans) knockdown-associated nuclear translocation of DAF-16. Comparably, overexpression of human 14-3-3 ß could attenuate G2019S-associated toxicity in response to stress and rescued G2019S-mediated inhibition of sod-3 and dod-3 expression. Taken together, our study provides evidence suggesting that 14-3-3-associated inhibition of DAF-16 nuclear translocation could be a mechanism for G2019S LRRK2-induced oxidative stress and cellular toxicity. Our findings may give a hint that the potential of 14-3-3 proteins as neuroprotective targets in PD patients carrying LRRK2 mutations.