A feasibility randomized controlled trial of a community-level physical activity strategy for older adults with motoric cognitive risk syndrome.

The motoric cognitive risk syndrome (MCR) is a syndrome characterized by subjective memory complaints and slow walking speeds that can identify older adults at increased risk for developing Alzheimer's disease or a related dementia (ADRD). To date, the feasibility of community-based physical activity (PA) programs for improving outcomes in MCR have yet to be examined. To address this knowledge gap, we conducted a translational randomized controlled trial (RCT) comparing 24-weeks of PA to a healthy aging education (HE) control intervention delivered within the infrastructure of an urban senior center in Greater Boston (clincaltrials.gov identifier: NCT03750682). An existing senior center employee was trained to administer the multimodal group-based PA program that included moderate-intensity aerobic walking, strength, flexibility and balance training. A total of 79 older adults attended the senior center for a screening visit, of whom 29 met the MCR criteria and 25 were randomized to PA or HE (mean age: 74.4 ± 7 years; BMI: 32.4 ± 7 kg/m2; 85% female; 3MSE score: 92.4 ± 7; gait speed: 0.52 ± 0.1 m/s; SPPB score 4.8 ± 1.9). Due to the Covid-19 pandemic the study was stopped prematurely. Participants could successfully adhere to the study interventions (overall attendance rate: PA: 69% vs. HE:70% at study termination). Participants also successfully completed baseline and follow-up study assessments that included a computerized cognitive testing battery and objective tests of physical performance and functional exercise capacity. No study-related adverse events occurred. Notable trends for improved cognitive performance, gait speed and 6-min walk distance were exhibited in PA compared to HE. Our study provides important preliminary information to aid the design of larger-scale RCTs of PA that may help to preserve the independence of vulnerable older adults at high risk for ADRD in community-based settings.

Effectiveness of a Virtual Reality Open-Air Bath Program in Reducing Loneliness and Improving Brain Function for Dementia Prevention in Older Adults: Protocol for a Prospective Randomized Crossover Study.

BACKGROUND: Older adults often face loneliness due to chronic illness or loss of close ones, a situation worsened by the COVID-19 pandemic. Increased loneliness heightens the risk of diseases, especially dementia, necessitating urgent action. OBJECTIVE: This study aims to assess the impact of a virtual reality (VR)-based open-air bath program on depression and loneliness in older individuals with subjective cognitive decline/mild cognitive impairment attending the Dementia Medical Center in Kyoto, Japan. We further aim to evaluate the feasibility of the program (participant recruitment and adherence) and to measure program enjoyment and satisfaction. METHODS: The study design is a crossover trial with a 1:1 ratio, wherein 12 participants will be randomly assigned to groups 1 and 2, with group 2 serving as a waitlist control and group 1 receiving the VR program from the onset for 6 months; the VR program will be conducted 6 times (monthly). Program completion for group 1 will be followed by an observation period from months 7 to 12. Group 2 will participate in the VR program from months 7 to 12, with an observation period from months 1 to 6. Cognitive tests, psychiatric assessments, and the University of California, Los Angeles Loneliness Scale will be conducted before the study, at 6 months, and at 12 months. Results will be analyzed using repeated-measures ANOVA. Head magnetic resonance imaging and single-photon emission computed tomography scans will be performed before and after the VR program to evaluate changes and effects on brain regions. RESULTS: Recruitment began in September 2023 and data collection is expected to be completed by March 2025. Complete study results will be published by September 2025. CONCLUSIONS: This study examines the preliminary effects of VR on loneliness in older adults with predementia through open-air bath simulations. VR experiences could benefit this population, particularly those with limited outdoor activities. Quantifying VR's impact will aid in determining the size for a larger clinical trial. Qualitative results will inform participation mechanisms and guide the implementation and design of future trials. TRIAL REGISTRATION: University hospital Medical Information Network UMIN000052667; https://tinyurl.com/3yaccay5. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57101.

Essential New Complexity-Based Themes for Patient-Centered Diagnosis and Treatment of Dementia and Predementia in Older People: Multimorbidity and Multilevel Phenomenology.

Dementia is a highly prevalent condition with devastating clinical and socioeconomic sequela. It is expected to triple in prevalence by 2050. No treatment is currently known to be effective. Symptomatic late-onset dementia and predementia (SLODP) affects 95% of patients with the syndrome. In contrast to trials of pharmacological prevention, no treatment is suggested to remediate or cure these symptomatic patients. SLODP but not young onset dementia is intensely associated with multimorbidity (MUM), including brain-perturbating conditions (BPCs). Recent studies showed that MUM/BPCs have a major role in the pathogenesis of SLODP. Fortunately, most MUM/BPCs are medically treatable, and thus, their treatment may modify and improve SLODP, relieving suffering and reducing its clinical and socioeconomic threats. Regrettably, the complex system features of SLODP impede the diagnosis and treatment of the potentially remediable conditions (PRCs) associated with them, mainly due to failure of pattern recognition and a flawed diagnostic workup. We suggest incorporating two SLODP-specific conceptual themes into the diagnostic workup: MUM/BPC and multilevel phenomenological themes. By doing so, we were able to improve the diagnostic accuracy of SLODP components and optimize detecting and favorably treating PRCs. These revolutionary concepts and their implications for remediability and other parameters are discussed in the paper.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study.

BACKGROUND: The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription. OBJECTIVES: The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity. DESIGN: Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study. SETTING: Participants from 7 retrospective cohorts (US, EU and Australia). PARTICIPANTS: This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies. MEASUREMENTS: We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats. METHODS: We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy. RESULTS: Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets. CONCLUSIONS: The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

[Diagnostic approaches to assessing mild behavioral impairment in patients with mild cognitive impairment]. / Diagnosticheskie podkhody k otsenke subklinicheskikh neiropsikhicheskikh simptomov u patsientov s myagkim kognitivnym snizheniem.

OBJECTIVE: To assess the prevalence of mild behavioral impairment (MBI ) in elderly individuals with mild cognitive impairment (MCI ), refine diagnostic criteria, and characterize the identified neuropsychiatric symptoms. MATERIAL AND METHODS: Sixty-three individuals over 50 years of age (median 72 [68; 77]) with MCI underwent psychiatric and psychometric assessments using clinical and psychopathological methods and scales. Statistical analysis was conducted to evaluate intergroup differences, ROC-analysis with calculation of the area under the curve (AUC) was performed, and sensitivity, specificity, and accuracy of MBI diagnosis were determined for MBI-C. RESULTS: The prevalence of MBI using only ISTAART research criteria was 65%. An optimal diagnostic cut point for the MBI-C scale with the highest AUC (0.793), at 10 points, was identified. Upon a comprehensive assessment of MBI using criteria and optimal cut point values from the MBI-C scale, the prevalence was 33% (median 16 [14; 20]). Patients with MBI+MCI and MCI only did not significantly differ in MMSE and MoCA test results. Significant intergroup differences were observed in the severity of symptoms such as apathy (p<0.001), depression and anxiety (p<0.001), agitation and impulsivity (p<0.001), social behavioral disturbances (p=0.009), and subsyndromal psychotic symptoms (p<0.001). The most common symptoms were related to impulse control deficits, irritability, agitation, depression, anxiety, and apathy, while less common symptoms were associated with social behavioral disturbances and subsyndromal psychotic symptoms. CONCLUSION: Novel data on the diagnostic features of MBI in elderly patients with MCI in the Russian-speaking population are presented. An optimal diagnostic cut point for the MBI-C scale in a sample of patients from specialized clinics for comprehensive use with commonly accepted criteria was determined. Further research is needed to adapt and validate the MBI-C scale and provide prognostic evaluation of MBI in the context of MCI progression to dementia.

Pseudodementia in Patients with Unipolar and Bipolar Disorders: A Case Series and Literature Review.

Even though pseudodementia has been historically linked to depression, other psychiatric conditions may cause reversible cognitive alterations. The purpose of this study is to improve our understanding of pseudodementia occurring throughout the entire bipolar spectrum. A systematic review was conducted according to PRISMA guidelines. PubMed, Scopus, and Web of Science databases were searched up to March 2023. Fifteen articles on patients with pseudodementia and bipolar disorder (BD), mania, hypomania, or mixed depression have been included. Moreover, seven female patients with mood disorders diagnosed with pseudodementia have been described. According to our research, pseudodementia in patients with BD mostly occurs during a depressive episode. However, pseudodementia has also been observed in the context of manic and mixed states. Psychomotor and psychotic symptoms were commonly associated. The most typical cognitive impairments were disorientation, inattention, and short-term memory deficits. Alterations in neuroimaging were frequently observed. Electroconvulsive therapy and lithium, either alone or in combination with antipsychotics, resulted in the most widely used therapies. Cognitive decline may occur in a substantial proportion of patients. Since pseudodementia can manifest along the entire mood spectrum, it should be taken into consideration as a possible diagnosis in BD patients showing cognitive deficits during manic, mixed, and depressive states.

Disease severity and mortality in Alzheimer's disease: an analysis using the U.S. National Alzheimer's Coordinating Center Uniform Data Set.

BACKGROUND: Evidence on the relative risk of death across all stages of Alzheimer's disease (AD) is lacking but greatly needed for the evaluation of new interventions. We used data from the Uniform Data Set (UDS) of the National Alzheimer's Coordinating Center (NACC) to assess the expected survival of a person progressing to a particular stage of AD and the relative risk of death for a person in a particular stage of AD compared with cognitively normal (CN) people. METHODS: This was a retrospective observational cohort study of mortality and its determinants in participants with incident mild cognitive impairment (MCI) due to AD or AD dementia compared with CN participants. Overall survival and hazard ratios of all-cause mortality in participants ≥ 50 years of age with clinically assessed or diagnosed MCI due to AD, or mild, moderate, or severe AD dementia, confirmed by Clinical Dementia Rating scores, versus CN participants were estimated, using NACC UDS data. Participants were followed until death, censoring, or until information to determine disease stage was missing. RESULTS: Aged between 50 and 104 years, 12,414 participants met the eligibility criteria for the study. Participants progressing to MCI due to AD or AD dementia survived a median of 3-12 years, with higher mortality observed in more severe stages. Risk of death increased with the severity of AD dementia, with the increase significantly higher at younger ages. Participants with MCI due to AD and CN participants had a similar risk of death after controlling for confounding factors. CONCLUSIONS: Relative all-cause mortality risk increases with AD severity, more so at younger ages. Mortality does not seem to be higher for those remaining in MCI due to AD. Findings might imply potential benefit of lower mortality if preventing or delaying the progression of AD is successful, and importantly, this potential benefit might be greater in relatively younger people. Future research should replicate our study in other samples more representative of the general US population as well as other populations around the world.

Elevated Soluble TNF-Receptor 1 in the Serum of Predementia Subjects with Cerebral Small Vessel Disease.

Tumor necrosis factor-receptor 1 (TNF-R1)-mediated signaling is critical to the regulation of inflammatory responses. TNF-R1 can be proteolytically released into systemic blood circulation in a soluble form (sTNF-R1), where it binds to circulating TNF and functions to attenuate TNF-mediated inflammation. Increases of peripheral sTNF-R1 have been reported in both Alzheimer's disease (AD) dementia and vascular dementia (VaD). However, the status of sTNF-R1 in predementia subjects (cognitive impairment, no dementia, CIND) is unknown, and putative associations with cerebral small vessel disease (CSVD), as well as with longitudinal changes in cognitive functions are unclear. We measured baseline serum sTNF-R1 in a longitudinally assessed cohort of 93 controls and 103 CIND, along with neuropsychological evaluations and neuroimaging assessments. Serum sTNF-R1 levels were increased in CIND compared with controls (p < 0.001). Higher baseline sTNF-R1 levels were specifically associated with lacunar infarcts (rate ratio = 6.91, 95% CI 3.19-14.96, p < 0.001), as well as lower rates of cognitive decline in the CIND subgroup. Our data suggest that sTNF-R1 interacts with vascular cognitive impairment in a complex manner at predementia stages, with elevated levels associated with more severe CSVD at baseline, but which may subsequently be protective against cognitive decline.

Health economic modeling for Alzheimer's disease: Expert perspectives.

The successful development of an economic model for the evaluation of future Alzheimer's disease (AD) interventions is critical to accurately inform policy makers and payers. As our understanding of AD expands, this becomes an increasingly complex and challenging goal. Advances in diagnostic techniques for AD and the prospect of disease-modifying treatments raise an urgent need to define specifications for future economic models and to ensure that the necessary data to populate them are available. This Perspective article provides expert opinions from health economists and governmental agency representatives on how future economic models for AD might be structured, validated, and reported. We aim to stimulate much-needed discussion about the detailed specification of future health economic models for AD.

Sum of boxes of the clinical dementia rating scale highly predicts conversion or reversion in predementia stages.

Background: The clinical dementia rating (CDR) scale is commonly used to diagnose dementia due to Alzheimer's disease (AD). The sum of boxes of the CDR (CDR-SB) has recently been emphasized and applied to interventional trials for tracing the progression of cognitive impairment (CI) in the early stages of AD. We aimed to study the influence of baseline CDR-SB on disease progression to dementia or reversion to normal cognition (NC). Materials and methods: The baseline CDR < 1 cohort registered from September 2015 to August 2020 with longitudinal follow-up in the History-based Artificial Intelligence Clinical Dementia Diagnostic System (HAICDDS) database was retrospectively analyzed for the rates of conversion to CDR ≥ 1. A Cox regression model was applied to study the influence of CDR-SB levels on progression, adjusting for age, education, sex, neuropsychological tests, neuropsychiatric symptoms, parkinsonism, and multiple vascular risk factors. Results: A total of 1,827 participants were analyzed, including 1,258 (68.9%) non-converters, and 569 (31.1%) converters with mean follow-up of 2.1 (range 0.4-5.5) and 1.8 (range 0.3-5.0) years, respectively. Conversion rates increased with increasing CDR-SB scores. Compared to a CDR-SB score of 0, the hazard ratios (HR) for conversion to dementia were 1.51, 1.91, 2.58, 2.13, 3.46, 3.85, 3.19, 5.12, and 5.22 for CDR-SB scores of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and ≥4.5, respectively (all p < 0.05 except for CDR-SB score = 0.5). In addition, older age, lower education, lower cognitive performance, and a history of diabetes also increased conversion rates. Furthermore, reversions to NC were 12.5, 5.6, 0.9, and 0% for CDR-SB scores of 0.5, 1.0-2.0, 2.5-3.5 and ≥4.0, respectively (p < 0.001). Conclusion: CDR-SB in predementia or very mild dementia (VMD) stages highly predicts progression to dementia or reversion to NC. Therefore, CDR-SB could be a good candidate for tracing the effectiveness of pharmacological and non-pharmacological interventions in populations without dementia.

Increased Social Support Reduces the Incidence of Motoric Cognitive Risk Syndrome.

Background and Objectives: The motoric cognitive risk syndrome (MCR) is a predementia syndrome characterized by slow gait and cognitive complaint. The relationship between MCR and social support-a potentially modifiable risk factor of dementia-is currently unknown. The current study aimed to determine whether MCR incidence varies as a function of social support in aging. Research Design and Methods: We examined MCR incidence in 506 community-dwelling older adults (M Age 76.59; 57.3% female) without MCR or dementia at baseline. We quantified perceived levels of social support with the Medical Outcomes Study Social Support Survey, incorporating four different categories of support: (a) emotional/informational support, (b) tangible support, (c) affectionate support, and (d) positive social interactions. We used Cox regression analyses, adjusted for age, sex, race/ethnicity, education, marital status, comorbidities, and global cognition, to estimate hazard ratios (aHR) with 95% confidence intervals (CIs). Results: Over a median follow-up time of 2.5 years (range = 1-7 years), 38 participants (9.8%) developed MCR. Increased tangible support decreased the risk of MCR by 30% (aHR: 0.70, 95% CI: 0.53-0.92, p = .011). Increased overall social support decreased the risk of MCR by 33% (aHR: 0.67, 95% CI: 0.46-0.98, p = .038). Other subcategories of social support were not associated with a decreased risk of MCR (p > .05). Discussion and Implications: Higher levels of tangible social support, as well as overall social support, were associated with reduced risk for MCR in older adults. Increasing social support may be a promising avenue of intervention for reducing the risk of MCR, dementia, and other forms of cognitive decline.

Plasma metabolomics and lipidomics signatures of motoric cognitive risk syndrome in community-dwelling older adults.

Introduction: Motoric cognitive risk syndrome (MCR) is characterized by subjective cognitive complaints (SCCs) and slow gait (SG). Metabolomics and lipidomics may potentiate disclosure of the underlying mechanisms of MCR. Methods: This was a cross-sectional study from the West China Health and Aging Trend cohort study (WCHAT). The operational definition of MCR is the presence of SCCs and SG without dementia or mobility disability. The test and analysis were based on untargeted metabolomics and lipidomics, consensus clustering, lasso regression and 10-fold cross-validation. Results: This study enrolled 6,031 individuals for clinical analysis and 577 plasma samples for omics analysis. The overall prevalence of MCR was 9.7%, and the prevalence of MCR-only, assessed cognitive impairment-only (CI-only) and MCR-CI were 7.5, 13.3, and 2.1%, respectively. By consensus clustering analysis, MCR-only was clustered into three metabolic subtypes, MCR-I, MCR-II and MCR-III. Clinically, body fat mass (OR = 0.89, CI = 0.82-0.96) was negatively correlated with MCR-I, and comorbidity (OR = 2.19, CI = 1.10-4.38) was positively correlated with MCR-III. Diabetes mellitus had the highest ORs above 1 in MCR-II and MCR-III (OR = 3.18, CI = 1.02-9.91; OR = 2.83, CI = 1.33-6.04, respectively). The risk metabolites of MCR-III showed relatively high similarity with those of cognitive impairment. Notably, L-proline, L-cystine, ADMA, and N1-acetylspermidine were significantly changed in MCR-only, and PC(40:3), SM(32:1), TG(51:3), eicosanoic acid(20:1), methyl-D-galactoside and TG(50:3) contributed most to the prediction model for MCR-III. Interpretation: Pre-dementia syndrome of MCR has distinct metabolic subtypes, and SCCs and SG may cause different metabolic changes to develop MCR.

Regional associations of white matter hyperintensities and early cortical amyloid pathology.

White matter hyperintensities (WMHs) have a heterogeneous aetiology, associated with both vascular risk factors and amyloidosis due to Alzheimer's disease. While spatial distribution of both amyloid and WM lesions carry important information for the underlying pathogenic mechanisms, the regional relationship between these two pathologies and their joint contribution to early cognitive deterioration remains largely unexplored. We included 662 non-demented participants from three Amyloid Imaging to Prevent Alzheimer's disease (AMYPAD)-affiliated cohorts: EPAD-LCS (N = 176), ALFA+ (N = 310), and EMIF-AD PreclinAD Twin60++ (N = 176). Using PET imaging, cortical amyloid burden was assessed regionally within early accumulating regions (medial orbitofrontal, precuneus, and cuneus) and globally, using the Centiloid method. Regional WMH volume was computed using Bayesian Model Selection. Global associations between WMH, amyloid, and cardiovascular risk scores (Framingham and CAIDE) were assessed using linear models. Partial least square (PLS) regression was used to identify regional associations. Models were adjusted for age, sex, and APOE-e4 status. Individual PLS scores were then related to cognitive performance in 4 domains (attention, memory, executive functioning, and language). While no significant global association was found, the PLS model yielded two components of interest. In the first PLS component, a fronto-parietal WMH pattern was associated with medial orbitofrontal-precuneal amyloid, vascular risk, and age. Component 2 showed a posterior WMH pattern associated with precuneus-cuneus amyloid, less related to age or vascular risk. Component 1 was associated with lower performance in all cognitive domains, while component 2 only with worse memory. In a large pre-dementia population, we observed two distinct patterns of regional associations between WMH and amyloid burden, and demonstrated their joint influence on cognitive processes. These two components could reflect the existence of vascular-dependent and -independent manifestations of WMH-amyloid regional association that might be related to distinct primary pathophysiology.

Timed Up and Go in People with Subjective Cognitive Decline Is Associated with Faster Cognitive Deterioration and Cortical Thickness.

INTRODUCTION: Early markers of neurodegeneration provide an opportunity to detect, monitor, and initiate interventions in individuals who have an increased risk of developing dementia. Here, we investigated whether the Timed Up and Go (TUG) test is associated with early brain neurodegeneration and whether the TUG test could be a marker of cognitive decline in people with subjective cognitive decline (SCD). METHODS: This is a longitudinal analysis of the Dementia Disease Initiation Study, a prospective, community-based, cohort study from Norway, designed to investigate early markers of cognitive impairment and dementia. Participants were classified as SCD and healthy controls (HC). The main studied variables were the TUG test and cognition as measured by the Mini-Mental State Examination and the Consortium to Establish a Registry for Alzheimer's Disease memory composite score. Additionally, we investigated the cross-sectional association of brain morphology with the TUG using 1.5T-MRI. RESULTS: The sample included 45 participants (SCD = 21, HC = 24) followed during a mean time of 1.50 ± 0.70 years. At baseline, the cognitive performance did not differ between the groups, but TUG was longer in SCD. Slower baseline TUG was associated with a faster cognitive decline in both groups and it was also associated with reduced cortical thickness especially in motor, executive, associative, and somatosensory cortical regions in people with SCD. DISCUSSION/CONCLUSION: TUG predicted cognitive change in individuals with SCD, and there was a negative association between TUG and cortical thickness. TUG is a promising cheap and noninvasive marker of early cognitive decline and may help initiate interventions in individuals who have an increased risk of dementia.

Considerations regarding a diagnosis of Alzheimer's disease before dementia: a systematic review.

BACKGROUND: The NIA-AA research framework proposes a purely biological definition of Alzheimer's disease (AD). This implies that AD can be diagnosed based on biomarker abnormalities, irrespective of clinical manifestation. While this brings opportunities, it also raises challenges. We aimed to provide an overview of considerations regarding the disclosure of AD pathology before the onset of dementia. METHODS: A systematic literature review was conducted and reported according to PRISMA guidelines. We searched PubMed, Embase, APA PsycINFO, and Web of Science Core Collection (on 10 December 2020) for references on conveying AD biomarker results to individuals without dementia. Our query combined variations on the terms Alzheimer's disease, disclosure, or diagnosis, preclinical or prodromal, and biomarkers. Two reviewers independently screened the resulting 6860 titles and abstracts for eligibility and examined 162 full-text records for relevance. We included theoretical articles in English, on communicating amyloid and/or tau results to individuals with mild cognitive impairment, subjective cognitive decline, or normal cognition. MAXQDA-software was used for inductive data analysis. RESULTS: We included 27 publications. From these, we extracted 26 unique considerations, which we grouped according to their primary relevance to a clinical, personal, or societal context. Clinical considerations included (lack of) validity, utility, and disclosure protocols. Personal considerations covered psychological and behavioral implications, as well as the right to (not) know. Finally, societal considerations comprised the risk of misconception, stigmatization, and discrimination. Overall, views were heterogeneous and often contradictory, with emphasis on harmful effects. CONCLUSIONS: We found 26 diverse and opposing considerations, related to a clinical, personal, or societal context, which are relevant to diagnosing AD before dementia. The theoretical literature tended to focus on adverse impact and rely on common morality, while the motivation for and implications of biomarker testing are deeply personal. Our findings provide a starting point for clinicians to discuss biomarker-based diagnosis with their patients, which will become even more relevant in light of the conditional approval of a first disease-modifying drug for AD.

The prevalence and associated factors of motoric cognitive risk syndrome in multiple ethnic middle-aged to older adults in west China: a cross-sectional study.

BACKGROUND AND PURPOSE: Motoric cognitive risk (MCR) syndrome characterized by subjective cognitive complaints and slow gait has been proposed and validated as a pre-dementia syndrome. The overall and specific ethnic prevalence of MCR and the associated factors are poorly understood in middle-aged to older community-dwelling residents in west China. METHODS: The present study included 6091 samples from the prospective cohort study, West China Health and Aging Trend (WCHAT). Multidimensional factors of demography, lifestyle, social support, anthropometrics and body components, and clinical status were investigated and analyzed by univariate and multivariate logistic regression models. Lasso regression and K-fold cross-validation were conducted to construct the most predictive model with fitted factors. RESULTS: The overall prevalence of MCR was 9.74%, and ethnically the prevalence was 14.25% in Tibetan, 11.03% in Yi, 10.72% in Han, 5.18% in Uighur and 4.55% in Qiang, respectively. In the adjusted models, the positively associated risk factors included diabetes mellitus (odds ratio [OR] = 1.51, p = 0.007), osteoarthritis (OR = 1.50, p = 0.002), depression (OR = 1.36, p = 0.005), poor sleep (OR = 1.21, p = 0.045), comorbidity (OR = 1.49, p = 0.001) and falls in the last 12 months (OR = 1.34, p = 0.031). Of note, every 1-unit increase of value in stroke was associated with an approximate 3-fold higher risk of having MCR, whilst in high-density lipoprotein with a 30% lower risk of MCR,respectively. CONCLUSIONS: Profiles of MCR from the aspects of ethnicity and the presenium stage need further exploration. It is a promising strategy to apply MCR as a primary prevention tool to prevent dementia.

Assessing and disclosing test results for 'mild cognitive impairment': the perspective of old age psychiatrists in Scotland.

BACKGROUND: Mild cognitive impairment (MCI) is a condition that exists between normal healthy ageing and dementia with an uncertain aetiology and prognosis. This uncertainty creates a complex dynamic between the clinicians' conception of MCI, what is communicated to the individual about their condition, and how the individual responds to the information conveyed to them. The aim of this study was to explore clinicians' views around the assessment and communication of MCI in memory clinics. METHOD: As part of a larger longitudinal study looking at patients' adjustment to MCI disclosure, we interviewed Old Age Psychiatrists at the five participating sites across Scotland. The study obtained ethics approvals and the interviews (carried out between Nov 2020-Jan 2021) followed a semi-structured schedule focusing on [1] how likely clinicians are to use the term MCI with patients; [2] what tests clinicians rely on and how much utility they see in them; and [3] how clinicians communicate risk of progression to dementia. The interviews were voice recorded and were analysed using reflective thematic analysis. RESULTS: Initial results show that most clinicians interviewed (Total N = 19) considered MCI to have significant limitations as a diagnostic term. Nevertheless, most clinicians reported using the term MCI (n = 15/19). Clinical history was commonly described as the primary aid in the diagnostic process and also to rule out functional impairment (which was sometimes corroborated by Occupational Therapy assessment). All clinicians reported using the Addenbrooke's Cognitive Examination-III as a primary assessment tool. Neuroimaging was frequently found to have minimal usefulness due to the neuroradiological reports being non-specific. CONCLUSION: Our study revealed a mixture of approaches to assessing and disclosing test results for MCI. Some clinicians consider the condition as a separate entity among neurodegenerative disorders whereas others find the term unhelpful due to its uncertain prognosis. Clinicians report a lack of specific and sensitive assessment methods for identifying the aetiology of MCI in clinical practice. Our study demonstrates a broad range of views and therefore variability in MCI risk disclosure in memory assessment services which may impact the management of individuals with MCI.

Association of Motoric Cognitive Risk Syndrome with Cardiovascular and Noncardiovascular Factors: A Systematic Review and Meta-Analysis.

OBJECTIVES: Motoric cognitive risk syndrome (MCR) is a recently proposed predementia syndrome characterized by subjective cognitive impairment and slow gait. We aim to assess the cardiovascular and noncardiovascular factors associated with MCR. DESIGN: Systematic review and meta-analysis. SETTING AND PARTICIPANTS: Studies comparing patients with MCR to those without MCR, and identifying the factors associated with MCR. METHODS: We used databases, including PubMed, Cochrane CENTRAL, and Embase, to identify studies evaluating the factors associated with MCR. Mean differences, odds ratios (ORs), risk ratios (RRs), and hazard ratios (HRs) with 95% CIs were calculated using Review Manager. RESULTS: Meta-analysis revealed that all cardiovascular factors, including diabetes (21 studies; OR 1.50, 95% CI 1.37, 1.64), hypertension (21 studies; OR 1.20, 95% CI 1.08, 1.33), stroke (16 studies; OR 2.03, 95% CI 1.70, 2.42), heart disease (7 studies; OR 1.45, 95% CI 1.13, 1.86), coronary artery disease (5 studies; OR 1.49, 95% CI 1.16, 1.91), smoking (13 studies; OR 1.28, 95% CI 1.04, 1.58), and obesity (12 studies; OR 1.34, 95% CI 1.13, 1.59) were significantly higher in the MCR than the non-MCR group. Noncardiovascular factors, including age (22 studies; MD = 1.08, 95% CI 0.55, 1.61), education (8 studies; OR 2.04, 95% CI 1.28, 3.25), depression (17 studies; OR 2.19, 95% CI 1.65, 2.91), prior falls (9 studies; OR 1.45, 95% CI 1.17, 1.80), arthritis (6 studies; OR 1.35, 95% CI 1.07, 1.70), polypharmacy (5 studies; OR 1.65, 95% CI 1.07, 2.54), and sedentary lifestyle (11 studies; OR 2.00, 95% CI 1.59, 2.52), were significantly higher in the MCR than in the non-MCR group. Alcohol consumption (6 studies; OR 0.84, 95% CI 0.72, 0.98), however, favored the MCR over the non-MCR group. Additionally, there was no significant association of MCR with gender (22 studies; OR 1.04, 95% CI 0.94, 1.15) and cancer (3 studies; OR 2.39, 95% CI 0.69, 8.28). MCR was also significantly associated with an increased likelihood of incident dementia (5 studies; HR 2.84, 95% CI 1.77, 4.56; P < .001), incident cognitive impairment [2 studies; adjusted hazard ratio (aHR) 1.76, 95% CI 1.44, 2.15], incident falls (4 studies; RR 1.37, 95% CI 1.17, 1.60), and mortality (2 studies; aHR 1.58, 95% CI 1.35, 1.85). CONCLUSIONS AND IMPLICATIONS: MCR syndrome was significantly associated with diabetes, hypertension, stroke, obesity, smoking, low education, sedentary lifestyle, and depression. Moreover, MCR significantly increased the risk of incident dementia, cognitive impairment, falls, and mortality.

Apathy as a Treatment Target in Alzheimer's Disease: Implications for Clinical Trials.

Apathy is one of the most prevalent, stable and persistent neuropsychiatric symptom across the neurocognitive disorders spectrum. Recent advances in understanding of phenomenology, neurobiology and intervention trials highlight apathy as an important target for clinical intervention. We conducted a comprehensive review and critical evaluation of recent advances to determine the evidence-based suggestions for future trial designs. This review focused on 4 key areas: 1) pre-dementia states; 2) assessment; 3) mechanisms/biomarkers and 4) treatment/intervention efficacy. Considerable progress has been made in understanding apathy as a treatment target and appreciating pharmacological and non-pharmacological apathy treatment interventions. Areas requiring greater investigation include: diagnostic procedures, symptom measurement, understanding the biological mechanisms/biomarkers of apathy, and a well-formed approach to the development of treatment strategies. A better understanding of the subdomains and biological mechanisms of apathy will advance apathy as a treatment target for clinical trials.

Machine Learning to Predict Brain Amyloid Pathology in Pre-dementia Alzheimer's Disease Using QEEG Features and Genetic Algorithm Heuristic.

The use of positron emission tomography (PET) as the initial or sole biomarker of ß-amyloid (Aß) brain pathology may inhibit Alzheimer's disease (AD) drug development and clinical use due to cost, access, and tolerability. We developed a qEEG-ML algorithm to predict Aß pathology among subjective cognitive decline (SCD) and mild cognitive impairment (MCI) patients, and validated it using Aß PET. We compared QEEG data between patients with MCI and those with SCD with and without PET-confirmed beta-amyloid plaque. We compared resting-state eyes-closed electroencephalograms (EEG) patterns between the amyloid positive and negative groups using relative power measures from 19 channels (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), divided into eight frequency bands, delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz) calculated by FFT and denoised by iSyncBrain®. The resulting 152 features were analyzed using a genetic algorithm strategy to identify optimal feature combinations and maximize classification accuracy. Guided by gene modeling methods, we treated each channel and frequency band of EEG power as a gene and modeled it with every possible combination within a given dimension. We then collected the models that showed the best performance and identified the genes that appeared most frequently in the superior models. By repeating this process, we converged on a model that approximates the optimum. We found that the average performance increased as this iterative development of the genetic algorithm progressed. We ultimately achieved 85.7% sensitivity, 89.3% specificity, and 88.6% accuracy in SCD amyloid positive/negative classification, and 83.3% sensitivity, 85.7% specificity, and 84.6% accuracy in MCI amyloid positive/negative classification.