Rate of conversion from prodromal Alzheimer's disease to Alzheimer's dementia: a systematic review of the literature

Cognitive Impairment in the Primary Care Clinic

Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.

Development and validation of a risk prediction model for mild cognitive impairment in elderly patients with type 2 diabetes mellitus

BACKGROUND

The prevalence of mild cognitive impairment (MCI) is steadily increasing among elderly people with type 2 diabetes (T2DM). This study aimed to create and validate a predictive model based on a nomogram.

METHODS

This cross-sectional study collected sociodemographic characteristics, T2DM-related factors, depression, and levels of social support from 530 older adults with T2DM. We used LASSO regression and multifactorial logistic regression to determine the predictors of the model. The performance of the nomogram was evaluated using calibration curves, receiver operating characteristics (ROC), and decision curve analysis (DCA).

RESULTS

The nomogram comprised age, smoking, physical activity, social support, depression, living alone, and glycosylated hemoglobin. The AUC for the training and validation sets were 0.914 and 0.859. The DCA showed good clinical applicability.

CONCLUSIONS

This predictive nomogram has satisfactory accuracy and discrimination. Therefore, the nomogram can be intuitively and easily used to detect MCI in elderly adults with T2DM.

Diurnal cortisol, neuroinflammation, and neuroimaging visual rating scales in memory clinic patients

BACKGROUND

Neuroinflammation is a hallmark of the Alzheimer's disease (AD) pathogenic process. Cortisol dysregulation may increase AD risk and is related to brain atrophy. This cross-sectional study aims to examine interactions of cortisol patterns and neuroinflammation markers in their association with neuroimaging correlates.

METHOD

134 participants were recruited from the Karolinska University Hospital memory clinic (Stockholm, Sweden). Four visual rating scales were applied to magnetic resonance imaging or computed tomography scans: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), white matter lesions (WML), and posterior atrophy. Participants provided saliva samples for assessment of diurnal cortisol patterns, and underwent lumbar punctures for cerebrospinal fluid (CSF) sampling. Three cortisol measures were used: the cortisol awakening response, total daily output, and the ratio of awakening to bedtime levels. Nineteen CSF neuroinflammation markers were categorized into five composite scores: proinflammatory cytokines, other cytokines, angiogenesis markers, vascular injury markers, and glial activation markers. Ordinal logistic regressions were conducted to assess associations between cortisol patterns, neuroinflammation scores, and visual rating scales, and interactions between cortisol patterns and neuroinflammation scores in relation to visual rating scales.

RESULT

Higher levels of angiogenesis markers were associated with more severe WML. Some evidence was found for interactions between dysregulated diurnal cortisol patterns and greater neuroinflammation-related biomarkers in relation to more severe GCA and WML. No associations were found between cortisol patterns and visual rating scales.

CONCLUSION

This study suggests an interplay between diurnal cortisol patterns and neuroinflammation in relation to brain structure. While this cross-sectional study does not provide information on causality or temporality, these findings suggest that neuroinflammation may be involved in the relationship between HPA-axis functioning and AD.

2024 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

Neuroticism polygenic risk predicts conversion from mild cognitive impairment to Alzheimer's disease by impairing inferior parietal surface area

The high prevalence of conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) makes early prevention of AD extremely critical. Neuroticism, a heritable personality trait associated with mental health, has been considered a risk factor for conversion from aMCI to AD. However, whether the neuroticism genetic risk could predict the conversion of aMCI and its underlying neural mechanisms is unclear. Neuroticism polygenic risk score (N-PRS) was calculated in 278 aMCI patients with qualified genomic and neuroimaging data from ADNI. After 1-year follow-up, N-PRS in patients of aMCI-converted group was significantly greater than those in aMCI-stable group. Logistic and Cox survival regression revealed that N-PRS could significantly predict the early-stage conversion risk from aMCI to AD. These results were well replicated in an internal dataset and an independent external dataset of 933 aMCI patients from the UK Biobank. One sample Mendelian randomization analyses confirmed a potentially causal association from higher N-PRS to lower inferior parietal surface area to higher conversion risk of aMCI patients. These analyses indicated that neuroticism genetic risk may increase the conversion risk from aMCI to AD by impairing the inferior parietal structure.

Periodontitis: A Plausible Modifiable Risk Factor for Neurodegenerative Diseases? A Comprehensive Review

The aim of this comprehensive review is to summarize recent literature on associations between periodontitis and neurodegenerative diseases, explore the bidirectionality and provide insights into the plausible pathogenesis. For this purpose, systematic reviews and meta-analyses from PubMed, Medline and EMBASE were considered. Out of 33 retrieved papers, 6 articles complying with the inclusion criteria were selected and discussed. Additional relevant papers for bidirectionality and pathogenesis were included. Results show an association between periodontitis and Alzheimer's disease, with odds ratios of 3 to 5. A bidirectional relationship is suspected. For Parkinson's disease (PD), current evidence for an association appears to be weak, although poor oral health and PD seem to be correlated. A huge knowledge gap was identified. The plausible mechanistic link for the association between periodontitis and neurodegenerative diseases is the interplay between periodontal inflammation and neuroinflammation. Three pathways are hypothesized in the literature, i.e., humoral, neuronal and cellular, with a clear role of periodontal pathogens, such as Porphyromonas gingivalis. Age, gender, race, smoking, alcohol intake, nutrition, physical activity, socioeconomic status, stress, medical comorbidities and genetics were identified as common risk factors for periodontitis and neurodegenerative diseases. Future research with main emphasis on the collaboration between neurologists and dentists is encouraged.

A novel speech analysis algorithm to detect cognitive impairment in a Spanish population

Objective

Early detection of cognitive impairment in the elderly is crucial for diagnosis and appropriate care. Brief, cost-effective cognitive screening instruments are needed to help identify individuals who require further evaluation. This study presents preliminary data on a new screening technology using automated voice recording analysis software in a Spanish population.

Method

Data were collected from 174 Spanish-speaking individuals clinically diagnosed as cognitively normal (CN, n = 87) or impaired (mild cognitive impairment [MCI], n = 63; all-cause dementia, n = 24). Participants were recorded performing four common language tasks (Animal fluency, alternating fluency [sports and fruits], phonemic "F" fluency, and Cookie Theft Description). Recordings were processed via text-transcription and digital-signal processing techniques to capture neuropsychological variables and audio characteristics. A training sample of 122 subjects with similar demographics across groups was used to develop an algorithm to detect cognitive impairment. Speech and task features were used to develop five independent machine learning (ML) models to compute scores between 0 and 1, and a final algorithm was constructed using repeated cross-validation. A socio-demographically balanced subset of 52 participants was used to test the algorithm. Analysis of covariance (ANCOVA), covarying for demographic characteristics, was used to predict logistically-transformed algorithm scores.

Results

Mean logit algorithm scores were significantly different across groups in the testing sample (p < 0.01). Comparisons of CN with impaired (MCI + dementia) and MCI groups using the final algorithm resulted in an AUC of 0.93/0.90, with overall accuracy of 88.4%/87.5%, sensitivity of 87.5/83.3, and specificity of 89.2/89.2, respectively.

Conclusion

Findings provide initial support for the utility of this automated speech analysis algorithm as a screening tool for cognitive impairment in Spanish speakers. Additional study is needed to validate this technology in larger and more diverse clinical populations.

Multimodal Exercise and Cognitive Training Program Improves Cognitive Function in Amnestic Mild Cognitive Impairment

OBJECTIVE

To investigate the preliminary efficacy of a combined physical exercise + cognitive training intervention for older adults with amnestic mild cognitive impairment (aMCI).

DESIGN

Randomized clinical trial.

SETTING

Veteran Affairs Hospital, Palo Alto, CA.

PARTICIPANTS

Sample included 72 community-dwelling volunteers (mean age 72.4 ± 9.5) diagnosed with aMCI.

INTERVENTION

Participants were randomized to either a combined aerobic and resistance exercise + cognitive training (CARE+CT) or stretching exercise + CT (SE+CT).

MEASUREMENTS

Primary outcomes included intervention specific assessments of word list and name-face recall. Secondary cognitive outcomes included standardized composite scores that reflect cognitive domains (e.g., learning and memory, executive function, processing speed, visuospatial ability, language). Secondary physiological outcomes included VO2 max and functional capacity (e.g., distance walked 6-minute walk test). APOE and BDNF were determined from whole blood samples.

RESULTS

Controlling for age and employment status, linear mixed effects models revealed that all participants experienced significant improvement in the delayed recall of word list, learning and memory and executive function. Only the CARE+CT condition had significant improvement in processing speed and functional capacity. APOE4 status impacted cognitive benefits of those in the SE+CT condition.

CONCLUSIONS

Results provide preliminary support for combined exercise and cognitive training interventions for older adults with aMCI. Further research is needed to understand the mechanisms involved as well as the impact of these interventions in diverse samples.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01962038.

Exploring the link between comorbidities and Alzheimer's dementia in the Australian Imaging, Biomarker & Lifestyle (AIBL) study

INTRODUCTION

Mounting evidence suggests that certain comorbidities may influence the clinical evolution of Alzheimer's dementia (AD).

METHODS

We conducted logistic regression analyses on the medical history and cognitive health diagnoses of participants in the Australian Imaging, Biomarker & Lifestyle study (n = 2443) to investigate cross-sectional associations between various comorbidities and mild cognitive impairment (MCI)/AD.

RESULTS

A mixture of associations were observed. Higher comorbidity of anxiety and other neurological disorders was associated with higher odds of AD, while arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.

DISCUSSION

This study underscores the links between specific comorbidities and MCI/AD. Further research is needed to elucidate the longitudinal comorbidity-MCI/AD associations and underlying mechanisms of these associations.

Highlights

Comorbidities that significantly increased AD odds included anxiety and other neurological disorders.Arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.Alcohol consumption had the most significant confounding effect in the study.Visual-AD association was modified by age, sex, and APOE ε4 allele status.Anxiety-AD and depression-AD associations were modified by sex.

Socially Assistive Robots for patients with Alzheimer's Disease: A scoping review

BACKGROUND

The most common form of dementia, Alzheimer's Disease (AD), is challenging for both those affected as well as for their care providers, and caregivers. Socially assistive robots (SARs) offer promising supportive care to assist in the complex management associated with AD.

OBJECTIVES

To conduct a scoping review of published articles that proposed, discussed, developed or tested SAR for interacting with AD patients.

METHODS

We performed a scoping review informed by the methodological framework of Arksey and O'Malley and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist for reporting the results. At the identification stage, an information specialist performed a comprehensive search of 8 electronic databases from the date of inception until January 2022 in eight bibliographic databases. The inclusion criteria were all populations who recive or provide care for AD, all interventions using SAR for AD and our outcomes of inteerst were any outcome related to AD patients or care providers or caregivers. All study types published in the English language were included.

RESULTS

After deduplication, 1251 articles were screened. Titles and abstracts screening resulted to 252 articles. Full-text review retained 125 included articles, with 72 focusing on daily life support, 46 on cognitive therapy, and 7 on cognitive assessment.

CONCLUSION

We conducted a comprehensive scoping review emphasizing on the interaction of SAR with AD patients, with a specific focus on daily life support, cognitive assessment, and cognitive therapy. We discussed our findings' pertinence relative to specific populations, interventions, and outcomes of human-SAR interaction on users and identified current knowledge gaps in SARs for AD patients.

Prediction of conversion from mild cognitive impairment to Alzheimer's disease and simultaneous feature selection and grouping using Medicaid claim data

BACKGROUND

Due to the heterogeneity among patients with Mild Cognitive Impairment (MCI), it is critical to predict their risk of converting to Alzheimer's disease (AD) early using routinely collected real-world data such as the electronic health record data or administrative claim data.

METHODS

The study used MarketScan Multi-State Medicaid data to construct a cohort of MCI patients. Logistic regression with tree-guided lasso regularization (TGL) was proposed to select important features and predict the risk of converting to AD. A subsampling-based technique was used to extract robust groups of predictive features. Predictive models including logistic regression, generalized random forest, and artificial neural network were trained using the extracted features.

RESULTS

The proposed TGL workflow selected feature groups that were robust, highly interpretable, and consistent with existing literature. The predictive models using TGL selected features demonstrated higher prediction accuracy than the models using all features or features selected using other methods.

CONCLUSIONS

The identified feature groups provide insights into the progression from MCI to AD and can potentially improve risk prediction in clinical practice and trial recruitment.

Chronic Non-cancer Pain and Associated Risks of Incident Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias in Middle-Aged and Older Adults

The goal of this study is to investigate the association between chronic non-cancer pain (CNCP) and mild cognitive impairment (MCI)/Alzheimer's disease and related dementias (ADRDs) development among adults aged ≥50 using administrative claims data from a national commercial health insurance company during 2007-2017. To reduce selection bias, propensity-score matching was applied to select comparable CNCP and non-CNCP patients. Time-dependent Cox proportional-hazards regressions were conducted to estimate the hazard ratios (HRs) of incident MCI/ADRDs. Of 170,900 patients with/without CNCP, 0.61% developed MCI and 2.33% had been diagnosed with ADRDs during the follow-up period. Controlling for potential confounders, CNCP patients had a 123% increase in MCI risk (HR = 2.23; 95% CI = 1.92-2.58) and a 44% increase in ADRDs risk (HR = 1.44; 95% CI = 1.34-1.54) relative to non-CNCP patients. CNCP is a risk factor for MCI/ADRDs. Promoting awareness and improving early CNCP diagnosis in middle-aged and older adults should be incorporated into cognitive impairment and dementia prevention.

Blood biomarkers in dynamic prediction of conversion to Alzheimer's disease: An application of joint modeling

OBJECTIVES

To investigate the accuracy of longitudinal trajectories of blood biomarkers for predicting future onset of AD among MCI participants as well as to demonstrate dynamic prediction of the individual conversion risk applying joint modeling.

METHODS

A total of 446 participants with MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative database were included. We introduced joint modeling to analyze the effects of the longitudinal blood biomarkers on the conversion risk to AD, and further to build individual-specific prediction risk model.

RESULTS

During the follow-up, 345 participants remained with MCI and 101 progressed to AD, and were categorized as non-progression and progression group, respectively. Longitudinally, the positive association of the concentration dynamics of plasma p-tau181 and NfL with the conversion risk to AD from MCI was also demonstrated, with Hazard Ratio (HR) = 5.83 and HR = 4.18, respectively. When incorporating plasma p-tau181 and NfL together to predict AD progression, we observed improved performance (AUC = 0.701, Brier Score = 0.119). Two participants were chosen to exemplify the individual-specific risk prediction at different follow-up time for comparative analysis.

CONCLUSIONS

Plasma p-tau181 and NfL could serve as biomarkers for the prediction of AD onset, and the individualized prediction opens up the possibility to provide clinical information at a personal level.

Potentially Modifiable Risk Factors for Dementia and Mild Cognitive Impairment: An Umbrella Review and Meta-Analysis

INTRODUCTION

The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs.

METHODS

We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia.

RESULTS

A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD.

CONCLUSION

Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management.

Psychological and neurobiological mechanisms involved in the relationship between loneliness and cognitive decline in older adults

Loneliness, among older adults, is one of the risk factors for developing dementia. Still, little is known about the neurobiological and psychological conditions that link loneliness to cognitive decline. The current study investigated several research aims: First, it sought to identify neurobiological and psychological pathways that may account for the relationship between loneliness and decline across several cognitive domains. These pathways included depressive symptoms, total gray matter volume, and conditional analyses of pro-inflammatory cytokines and brain-derived neurotrophic factor (BDNF) expression. Second, it examined loneliness as a predictor of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Third, it sought to determine whether the relationship between loneliness and cognitive decline is sex-specific in older adults. Longitudinal data were collected from 2130 Rush Memory and Aging Project participants. Participants underwent annual cognitive and psychological assessments and neuroimaging procedures every year. BDNF gene expression was measured in the dorsolateral prefrontal cortex, cytokines were measured in serum, and the final consensus clinical diagnosis was identified at the time of death. All linear mixed and multinomial logistic regression models controlled for age at baseline, education, sex, and APOE genotype. Participants were largely women (73 %), and Caucasian (93 %). The average education was 14.93 (SD = 3.34). The average age at baseline was 80.05 (SD = 7.57). Results showed that gray matter volume and depressive symptoms partially mediated the relationship between loneliness and cognitive decline. There was a significant interaction between loneliness and BDNF expression in relation to cognitive decline. Higher levels of BDNF expression was associated with slower decline in semantic memory and visuospatial ability. Finally, the current study also established that higher levels of loneliness was positively associated with the incidence of AD and other dementias. The present findings support the growing literature, which tends to show that the consequence of loneliness goes beyond the feeling of being isolated. Loneliness may induce physiological changes in our brains, leading to cognitive decline. Future research can explore a wide range of biological and psychological expressions of loneliness to clarify how loneliness relates to dementia.

Targeting blood brain barrier-Remote ischemic conditioning alleviates cognitive impairment in female APP/PS1 rats

AIMS

Alzheimer's disease (AD) is a significant global health concern, and it is crucial that we find effective methods to prevent or slow down AD progression. Recent studies have highlighted the essential role of blood vessels in clearing Aβ, a protein that contributes to AD. Scientists are exploring blood biomarkers as a potential tool for future AD diagnosis. One promising method that may help prevent AD is remote ischemic conditioning (RIC). RIC involves using sub-lethal ischemic-reperfusion cycles on limbs. However, a comprehensive understanding of how RIC can prevent AD and its long-term effectiveness is still lacking. Further research is essential to fully comprehend the potential benefits of RIC in preventing AD.

METHODS

Female wild-type (WT) and APP/PS1 transgenic rats, aged 12 months, underwent ovariectomy and were subsequently assigned to WT, APP/PS1, and APP/PS1 + RIC groups. RIC was conducted five times a week for 4 weeks. The rats' depressive and cognitive behaviors were evaluated using force swimming, open-field tests, novel objective recognition, elevated plus maze, and Barnes maze tests. Evaluation of the neurovascular unit (NVU), synapses, vasculature, astrocytes, and microglia was conducted using immunofluorescence staining (IF), Western blot (WB), and transmission electron microscopy (TEM). Additionally, the cerebro-vasculature was examined using micro-CT, and cerebral blood flow (CBF) was measured using Speckle Doppler. Blood-brain barrier (BBB) permeability was determined by measuring the Evans blue leakage. Finally, Aβ levels in the rat frontal cortex were measured using WB, ELISA, or IF staining.

RESULTS

RIC enhanced memory-related protein expression and rescued depressive-like behavior and cognitive decline in APP/PS1 transgenic rats. Additionally, the intervention protected NVU in the rat frontal cortex, as evidenced by (1) increased expression of TJ (tight junction) proteins, pericyte marker PDGFRβ, and glucose transporter 1 (GLUT1), as well as decreased VCAM1; (2) mitigation of ultrastructure impairment in neuron, cerebral vascular, and astrocyte; (3) upregulation of A2 astrocyte phenotype markers and downregulation of A1 phenotype markers, indicating a shift toward a healthier phenotype. Correspondingly, RIC intervention alleviated neuroinflammation, as evidenced by the decreased Iba1 level, a microglia marker. Meanwhile, RIC intervention elevated CBF in frontal cortex of the rats. Notably, RIC intervention effectively suppressed Aβ toxicity, as demonstrated by the enhancement of α-secretase and attenuation of β-secretase (BACE1) and γ- secretase and Aβ1-42 and Aβ1-40 levels as well.

CONCLUSION

Chronic RIC intervention exerts vascular and neuroprotective roles, suggesting that RIC could be a promising therapeutic strategy targeting the BBB and NVU during AD development.

Monoclonal antibodies for treating early Alzheimer disease-a commentary on recent 'positive' trials

Recent phase 3 randomised controlled trials of amyloid-targeting monoclonal antibodies in people with pre-clinical or early Alzheimer disease have reported positive results, raising hope of finally having disease-modifying drugs. Given their far-reaching implications for clinical practice, the methods and findings of these trials, and the disease causation theory underpinning the mechanism of drug action, need to be critically appraised. Key considerations are the representativeness of trial populations; balance of prognostic factors at baseline; psychometric properties and minimal clinically important differences of the primary efficacy outcome measures; level of study fidelity; consistency of subgroup analyses; replication of findings in similar trials; sponsor role and potential conflicts of interest; consistency of results with disease causation theory; cost and resource estimates; and alternative prevention and treatment strategies. In this commentary, we show shortcomings in each of these areas and conclude that monoclonal antibody treatment for early Alzheimer disease is lacking high-quality evidence of clinically meaningful impacts at an affordable cost.

Comparison of 18F-FDG PET and arterial spin labeling MRI in evaluating Alzheimer's disease and amnestic mild cognitive impairment using integrated PET/MR

BACKGROUND

Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR.

RESULTS

Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR.

CONCLUSION

ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.

Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.

METHODS

This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.

RESULTS

The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.

CONCLUSIONS

The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

When People Facing Dementia Choose to Hasten Death: The Landscape of Current Ethical, Legal, Medical, and Social Considerations in the United States

Some individuals facing dementia contemplate hastening their own death: weighing the possibility of living longer with dementia against the alternative of dying sooner but avoiding the later stages of cognitive and functional impairment. This weighing resonates with an ethical and legal consensus in the United States that individuals can voluntarily choose to forgo life-sustaining interventions and also that medical professionals can support these choices even when they will result in an earlier death. For these reasons, whether and how a terminally ill individual can choose to control the timing of their death is a topic that cannot be avoided when considering the dementia trajectory. With a focus on the U.S. context, this landscape review considers the status of provisions that would legally permit people facing dementia to hasten death with appropriate support from medical professionals. This review can be used to plan and guide clinical and legal practitioner discussion and policy development concerning evolving questions not fully covered by existing medical decision-making provisions.

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life

Background

The increasing interest in early identification of people at risk of developing dementia, has led to the development of numerous models aimed at estimating the likelihood of progression from mild cognitive impairment (MCI) to dementia. It is important to study both the need for and possible outcomes related with such prediction models, including the impact of risk predictions on perceived quality of life (QoL).

Objective

This study aimed to quantify the impact that receiving a risk prediction on progression from MCI to dementia has on QoL.

Methods

A Discrete Choice Experiment (DCE) and Time Trade Off (TTO) study were performed. Participants completed choice tasks related to dementia prognosis while imagining having MCI. We collected DCE data by an online survey, and TTO data via videoconferencing interviews. DCE data were analyzed using a mixed multinomial logit model and were anchored to a health state utility scale using mean observed TTO valuations.

Results

296 people participated in the DCE and 42 in the TTO. Moderate and high predicted dementia risks were associated with decrements in utility (-0.05 and -0.18 respectively), compared to no prognostic information. Low predicted risk was associated with an increase in utility (0.06), as well as the availability of medication or lifestyle interventions (0.05 and 0.13 respectively).

Conclusions

This study shows a significant impact of dementia risk predictions on QoL and highlights the importance of caution when sharing information about expected MCI disease courses.

The Predictive Ability of Blood Neurofilament Light Chain in Predicting Cognitive Decline in the Alzheimer's Disease Continuum: A Systematic Review and Meta-Analysis

Background

Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset. Identifying candidate predictors to forecast AD dementia risk before disease onset is crucial for early diagnosis and treatment.

Objective

We aimed to assess the predictive ability of blood neurofilament light (NfL) chain in anticipating cognitive decline in the AD continuum.

Methods

We systematically searched PubMed, Web of Science, and Embase from inception until April 7, 2023. Longitudinal observational studies examining the association between baseline blood NfL and cognitive decline or clinical disease conversion were included based on inclusion/exclusion criteria. The final effect size was represented by adjusted hazard ratios (HR) or standardized beta (s.β) coefficients with a 95% confidence interval (CI).

Results

A total of 2,862 articles were identified, and 26 studies were included in this meta-analysis. The results indicated that baseline blood NfL could predict cognitive decline, with MMSE [s.β= -0.17, 95% CI (-0.26, -0.07)]; PACC [s.β= -0.09, 95% CI (-0.16, -0.03)]; ADAS-cog [s.β= 0.21, 95% CI (0.13, 0.29)]; CDR-SOB [s.β= 0.27, 95% CI (0.03, 0.50)]; Global cognitive composite [s.β= -0.05, 95% CI (-0.08, -0.01)]; Memory subdomain [s.β= -0.06, 95% CI (-0.09, -0.03)]; Language subdomain [s.β= -0.07, 95% CI (-0.10, -0.05)]; Executive function subdomain [s.β= -0.02, 95% CI (-0.03, -0.01)]; Visuospatial subdomain [s.β= -0.06, 95% CI (-0.08, -0.04)]. Additionally, baseline blood NfL could predict disease progression (conversion from CU/SCD/MCI to MCI/AD) in the AD continuum [Adjust HR = 1.32, 95% CI (1.12, 1.56)].

Conclusions

Baseline blood NfL demonstrated predictive capabilities for global cognition and its memory, language, executive function, visuospatial subdomains decline in the AD continuum. Moreover, it exhibited the potential to predict disease progression in non-AD dementia participants.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development

Background

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis.

Objective

To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42).

Methods

Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls.

Results

Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients.

Conclusions

Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

Mitigating cognitive impairment in aging mice: Exploring the therapeutic potential of ischelium

To deeply explore the intervention effects of ischelium on the cognitive memory decline in naturally aging mice and its potential mechanisms, we randomly divided mice into four groups: young control group (C), elderly group (M), ischelium low-dose group (L), and ischelium high-dose group (H). The experiment lasted for 12 weeks. We employed the Y-maze test, open field test, and conditioned fear test to evaluate the memory functions of each group. Through HE staining and electron microscopy, we observed morphological changes in the mouse hippocampus. RT-PCR was used to detect changes in the expression of factors related to cognitive function in the hippocampus of elderly mice. We analyzed the changes in the Nrf2/HO-1 pathway and the inflammatory factors IL-1β and TNF-α using elisa. Additionally, we examined the enzymatic activities of SOD, CAT, GSH-Px, and MDA in the hippocampus and analyzed the compositional changes of gut microbiota in mice using 16S technology. Our results indicate that ischelium effectively ameliorates cognitive impairments in elderly mice.

Protocol for the Tallaght University Hospital Institute for Memory and Cognition-Biobank for Research in Ageing and Neurodegeneration

INTRODUCTION

Alzheimer's disease and other dementias affect >50 million individuals globally and are characterised by broad clinical and biological heterogeneity. Cohort and biobank studies have played a critical role in advancing the understanding of disease pathophysiology and in identifying novel diagnostic and treatment approaches. However, further discovery and validation cohorts are required to clarify the real-world utility of new biomarkers, facilitate research into the development of novel therapies and advance our understanding of the clinical heterogeneity and pathobiology of neurodegenerative diseases.

METHODS AND ANALYSIS

The Tallaght University Hospital Institute for Memory and Cognition Biobank for Research in Ageing and Neurodegeneration (TIMC-BRAiN) will recruit 1000 individuals over 5 years. Participants, who are undergoing diagnostic workup in the TIMC Memory Assessment and Support Service (TIMC-MASS), will opt to donate clinical data and biological samples to a biobank. All participants will complete a detailed clinical, neuropsychological and dementia severity assessment (including Addenbrooke's Cognitive Assessment, Repeatable Battery for Assessment of Neuropsychological Status, Clinical Dementia Rating Scale). Participants undergoing venepuncture/lumbar puncture as part of the clinical workup will be offered the opportunity to donate additional blood (serum/plasma/whole blood) and cerebrospinal fluid samples for longitudinal storage in the TIMC-BRAiN biobank. Participants are followed at 18-month intervals for repeat clinical and cognitive assessments. Anonymised clinical data and biological samples will be stored securely in a central repository and used to facilitate future studies concerned with advancing the diagnosis and treatment of neurodegenerative diseases.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the St. James's Hospital/Tallaght University Hospital Joint Research Ethics Committee (Project ID: 2159), which operates in compliance with the European Communities (Clinical Trials on Medicinal Products for Human Use) Regulations 2004 and ICH Good Clinical Practice Guidelines. Findings using TIMC-BRAiN will be published in a timely and open-access fashion.

The age-specific comorbidity burden of mild cognitive impairment: a US claims database study

BACKGROUND

Identifying individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease and related dementia disorders (ADRD) would facilitate the development of individualized prevention plans. We investigated the association between MCI and comorbidities of ADRD. We examined the predictive potential of these comorbidities for MCI risk determination using a machine learning algorithm.

METHODS

Using a retrospective matched case-control design, 5185 MCI and 15,555 non-MCI individuals aged ≥50 years were identified from MarketScan databases. Predictive models included ADRD comorbidities, age, and sex.

RESULTS

Associations between 25 ADRD comorbidities and MCI were significant but weakened with increasing age groups. The odds ratios (MCI vs non-MCI) in 50-64, 65-79, and ≥ 80 years, respectively, for depression (4.4, 3.1, 2.9) and stroke/transient ischemic attack (6.4, 3.0, 2.1). The predictive potential decreased with older age groups, with ROC-AUCs 0.75, 0.70, and 0.66 respectively. Certain comorbidities were age-specific predictors.

CONCLUSIONS

The comorbidity burden of MCI relative to non-MCI is age-dependent. A model based on comorbidities alone predicted an MCI diagnosis with reasonable accuracy.

Nutrition risk and cognitive performance in community-living older adults without cognitive impairment: a cross-sectional analysis of the Canadian Longitudinal Study on Aging

Malnutrition is correlated with poor cognition; however, an understanding of the association between nutrition risk, which precedes malnutrition, and cognition is lacking. This study aimed to determine if nutrition risk measured with the SCREEN-8 tool is associated with cognitive performance among cognitively healthy adults aged 55+, after adjusting for demographic and lifestyle covariates. Sex- and age-stratified analyses were also explored. Baseline data from the Canadian Longitudinal Study on Aging was used. Cognition was determined using a 6-measure composite score based on four executive functions and two memory tasks, taking into account age, sex, and education. Multivariable linear regression was performed while adjusting for body mass index (BMI), lifestyle, and health covariates in the entire sample (n = 11 378) and then stratified by sex and age. Approximately half of participants were female (54.5%) aged 65+ (54.1%). Greater nutrition risk was associated with poorer cognitive performance in the entire sample (F[1, 11 368] = 5.36, p = 0.021) and among participants aged 55-64 (n = 5227; F[1, 5217] = 5.45, p = 0.020). Sex differences in lifestyle and health factors associated with cognition were apparent, but nutrition risk was not associated with cognition in sex-stratified models. Based on this analysis, there may be an association between nutrition risk and cognitive performance in older adults. When screening for either cognitive impairment or nutrition risk, complementary assessments for these conditions is warranted, as early intervention may provide benefit.

The effectiveness of dance movement interventions for older adults with mild cognitive impairment, Alzheimer's disease, and dementia: A systematic scoping review and meta-analysis

OBJECTIVES

To synthesize evidence and summarize research findings related to the effectiveness and feasibility of dance movement intervention (DMI) in older adults with mild cognitive impairment (MCI), Alzheimer's disease (AD), and dementia; to systemically map existing research gaps and research directions for future practice.

METHODS

A systematic search was conducted using six electronic databases: Web of Science, PubMed, PsycINFO, MEDLINE, ScienceDirect, and Cochrane Central Register of Controlled Trials. The methodological quality of included studies was assessed using the Cochrane Risk of Bias Tool for Randomized Trials (RoB 2) and The Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I).

RESULTS

29 dance intervention studies (13 RCT studies) were included in the scoping review: 62% of MCI, 10% of AD, and 28% of dementia; a total of 1708 participants (Female=1247; Male=461) aged from 63.8 ( ± 5.24) to 85.8 ( ± 5.27) years old. Eight RCT studies were included in the meta-analysis; results indicated that dance interventions had a significant effect on global cognition, memory, balance, and significantly decreased depression. No significant effects were found for executive function.

CONCLUSIONS

Dance is a non-pharmacological, effective, affordable, and engaging intervention that can be used as a complementary treatment for older adults with MCI, AD, and dementia.

Metallomics analysis of metal exposure and cognitive function in older adults: A combined epidemiological and bioinformatics study

Dementia is a significant cause of elderly disability and Alzheimer's disease (AD) is the most prevalent form of dementia. As an early stage of AD, the mechanism related to mild cognitive impairment (MCI) and heavy metals is still unclear. This study utilized a cross-sectional design and enrolled 514 older adults in Bejing, China. Cognitive function was assessed by the Mini-Mental State Examination (MMSE) and fourteen blood metals were measured by inductively coupled plasma mass spectrometry (ICP-MS). In the adjusted single-metal models, we observed that copper [Cu, β (95% CI): 3.73 (-6.42, -1.03)] and lead [Pb, β (95% CI): 0.79 (-1.26, -0.32)] demonstrated negative associations with cognitive function, while selenium [Se, β (95% CI): 2.97 (1.23, 4.70)] was beneficial to cognition. Our findings were robust in secondary analysis using multi-metal models, which included generalized linear models (GLM), Bayesian kernel machine regression (BKMR), and quantile g-computation (qgcomp). Moreover, the toxic metal mixture (Cu and Pb) exhibited a significant negative association with MMSE scores and the inclusion of Se in the metal mixture attenuated the neurotoxicity of Cu-Pb mixture. The in silico analysis was used to examine the potential molecular mechanisms (genes, biological processes, pathways, and illnesses) of interaction among metal mixtures. We identified 20 cognition-related genes that are associated with both Cu-Pb and Se. Among these genes, eight (APOE, APP, BAX, BDNF, CASP3, HMOX1, TF, and TPP1) exhibited opposite effects on protein activity, mRNA expression, or protein expression in response to Se and Cu/Pb exposure, which could be the key genes accounting for the anti-neurotoxic effects of Se. Our findings support that Se can attenuate the neurotoxicity of exposure to single Cu or Pb, and Cu-Pb mixture. More research is needed to confirm our findings and gain knowledge about the molecular mechanisms of combined metal exposure on cognitive function.

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images

Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This study aimed to develop a dual-stream attention neural network to classify individuals with MCI based on multi-modal retinal images. Our approach incorporated a cross-modality fusion technique, a variable scale dense residual model, and a multi-classifier mechanism within the dual-stream network. The model utilized a residual module to extract image features and employed a multi-level feature aggregation method to capture complex context information. Self-attention and cross-attention modules were utilized at each convolutional layer to fuse features from optical coherence tomography (OCT) and fundus modalities, resulting in multiple output losses. The neural network was applied to classify individuals with MCI, Alzheimer's disease, and control participants with normal cognition. Through fine-tuning the pre-trained model, we classified community-dwelling participants into two groups based on cognitive impairment test scores. To identify retinal imaging biomarkers associated with accurate prediction, we used the Gradient-weighted Class Activation Mapping technique. The proposed method achieved high precision rates of 84.96% and 80.90% in classifying MCI and positive test scores for cognitive impairment, respectively. Notably, changes in the optic nerve head on fundus photographs or OCT images among patients with MCI were not used to discriminate patients from the control group. These findings demonstrate the potential of our approach in identifying individuals with MCI and emphasize the significance of retinal imaging for early detection of cognitive impairment.

Effects of home-based computerized cognitive training and tai chi exercise on cognitive functions in older adults with mild cognitive impairment

BACKGROUND

A randomized trial was conducted to investigate the effects of computerized cognitive training (CCT) and tai chi exercise (TCE) vs. health education (HE) on cognitive functions in 189 older adults with mild cognitive impairment (MCI).

METHODS

Cognitive functions were assessed by the five-domain Mattis Dementia Rating Scale (MDRS) (attention, initiation/perseveration, construction, conceptualization, and memory) and the modified Telephone Interview of Cognitive Status (TICS-M), while the timed up and go (TUG), Tinetti's balance, activities of daily living (ADLs), and Activities-specific Balance Confidence (ABC) were also evaluated. Each intervention was delivered once a week for 6 months. All outcomes were followed up at 6 and 12 months of the study.

RESULTS

Compared to HE, CCT increased scores on the MDRS's total, initiation/perseveration, construction, and conceptualization domains and on the TICS-M at 6 months and those on the MDRS's total, attention, construction, conceptualization, and memory domains and on the TICS-M at 12 months; TCE increased scores on the MDRS's total and construction domains and on the TICS-M at 6 months and those on the MDRS's total, attention, initiation/perseveration, and conceptualization domains and on the TICS-M at 12 months. Moreover, CCT improved the TUG at 6 and 12 months and Tinetti's balance at 12 months, and TCE improved the TUG at 6 and 12 months, Tinetti's balance, and ABC at 6 and 12 months, and ADLs at 12 months.

CONCLUSIONS

The effects of CCT and TCE on improving global cognition and certain cognitive domains for older MCI adults may have been small but they lasted for at least 12 months.

MyCOACH (COnnected Advice for Cognitive Health): a digitally delivered multidomain intervention for cognitive decline and risk of dementia in adults with mild cognitive impairment or subjective cognitive decline-study protocol for a randomised controlled trial

INTRODUCTION

Digital health interventions are cost-effective and easily accessible, but there is currently a lack of effective online options for dementia prevention especially for people at risk due to mild cognitive impairment (MCI) or subjective cognitive decline (SCD).

METHODS AND ANALYSIS

MyCOACH (COnnected Advice for Cognitive Health) is a tailored online dementia risk reduction programme for adults aged ≥65 living with MCI or SCD. The MyCOACH trial aims to evaluate the programme's effectiveness in reducing dementia risk compared with an active control over a 64-week period (N=326). Eligible participants are randomly allocated to one of two intervention arms for 12 weeks: (1) the MyCOACH intervention programme or (2) email bulletins with general healthy ageing information (active control). The MyCOACH intervention programme provides participants with information about memory impairments and dementia, memory strategies and different lifestyle factors associated with brain ageing as well as practical support including goal setting, motivational interviewing, brain training, dietary and exercise consultations, and a 26-week post-intervention booster session. Follow-up assessments are conducted for all participants at 13, 39 and 65 weeks from baseline, with the primary outcome being exposure to dementia risk factors measured using the Australian National University-Alzheimer's Disease Risk Index. Secondary measures include cognitive function, quality of life, functional impairment, motivation to change behaviour, self-efficacy, morale and dementia literacy.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the University of New South Wales Human Research Ethics Committee (HC210012, 19 February 2021). The results of the study will be disseminated in peer-reviewed journals and research conferences.

TRIAL REGISTRATION NUMBER

ACTRN12621000977875.

An interpretable Alzheimer's disease oligogenic risk score informed by neuroimaging biomarkers improves risk prediction and stratification

Introduction

Stratification of Alzheimer's disease (AD) patients into risk subgroups using Polygenic Risk Scores (PRS) presents novel opportunities for the development of clinical trials and disease-modifying therapies. However, the heterogeneous nature of AD continues to pose significant challenges for the clinical broadscale use of PRS. PRS remains unfit in demonstrating sufficient accuracy in risk prediction, particularly for individuals with mild cognitive impairment (MCI), and in allowing feasible interpretation of specific genes or SNPs contributing to disease risk. We propose adORS, a novel oligogenic risk score for AD, to better predict risk of disease by using an optimized list of relevant genetic risk factors.

Methods

Using whole genome sequencing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n  =  1,545), we selected 20 genes that exhibited the strongest correlations with FDG-PET and AV45-PET, recognized neuroimaging biomarkers that detect functional brain changes in AD. This subset of genes was incorporated into adORS to assess, in comparison to PRS, the prediction accuracy of CN vs. AD classification and MCI conversion prediction, risk stratification of the ADNI cohort, and interpretability of the genetic information included in the scores.

Results

adORS improved AUC scores over PRS in both CN vs. AD classification and MCI conversion prediction. The oligogenic model also refined risk-based stratification, even without the assistance of APOE, thus reflecting the true prevalence rate of the ADNI cohort compared to PRS. Interpretation analysis shows that genes included in adORS, such as ATF6, EFCAB11, ING5, SIK3, and CD46, have been observed in similar neurodegenerative disorders and/or are supported by AD-related literature.

Discussion

Compared to conventional PRS, adORS may prove to be a more appropriate choice of differentiating patients into high or low genetic risk of AD in clinical studies or settings. Additionally, the ability to interpret specific genetic information allows the focus to be shifted from general relative risk based on a given population to the information that adORS can provide for a single individual, thus permitting the possibility of personalized treatments for AD.

Understanding the role of psychiatrists in the diagnosis and management of mild cognitive impairment and mild Alzheimer's disease dementia: a cross-sectional survey

BACKGROUND

Alzheimer's disease (AD) is a progressive neurological disorder and the most common cause of dementia. The clinical continuum of AD ranges from asymptomatic disease to mild cognitive impairment (MCI), followed by AD dementia, categorized as mild, moderate, or severe. Almost one-third of patients suspected of having MCI or mild AD dementia are referred to specialists including psychiatrists. We sought to better understand the role that psychiatrists play in the diagnosis, treatment, and management of patients with all-cause MCI or mild AD dementia.

METHODS

We conducted an anonymous, online survey among physicians in the United States between February 4, 2021, and March 1, 2021. We surveyed psychiatrists, primary care physicians (PCPs), geriatricians, and neurologists who treat patients with all-cause MCI or mild AD dementia.

RESULTS

A total of 301 physicians participated in the survey, 50 of whom were psychiatrists. Of their patients with all-cause MCI or mild AD dementia, psychiatrists reported personally diagnosing two-thirds (67%). Psychiatrists used various methods to diagnose MCI or mild AD dementia including mental status testing (94%), review of patient medical history (86%), and neurological exams (61%). Upon diagnosis, psychiatrists reported most commonly discussing treatments (86%), management strategies (80%), disease progression (72%), and etiology of MCI or mild AD dementia (72%) with their patients. Most psychiatrists surveyed (82%) reported receiving advanced formal training in MCI and AD dementia care, primarily via residency training (38%), continuing medical education (22%) or fellowship (18%). Additionally, almost all psychiatrists (92%) reported receiving referrals for ongoing management of patients with MCI or mild AD dementia, primarily from PCPs or neurologists. However, only 46% of psychiatrists viewed themselves as the coordinator of care for their patients with MCI or mild AD dementia.

CONCLUSIONS

Many psychiatrists indicated that they were well-informed about MCI and AD dementia and have a strong interest in providing care for these patients. They can provide timely and accurate diagnosis of clinical MCI and mild AD dementia and develop optimal treatment plans for patients. Although many psychiatrists consider other physicians to be the care coordinators for patients with MCI and mild AD dementia, psychiatrists can play a key role in diagnosing and managing patients with MCI and mild AD dementia.

Stress, depression, and risk of dementia - a cohort study in the total population between 18 and 65 years old in Region Stockholm

BACKGROUND

Chronic stress and depression are potential risk factors for mild cognitive impairment and dementia, including Alzheimer disease. The aim was to investigate whether any such risk is additive.

METHODS

Cohort study including 1 362 548 people (665 997 women, 696 551 men) with records in the Region Stockholm administrative healthcare database (VAL). Exposure was a recorded ICD-10 diagnosis of chronic stress, depression, or both, recorded in 2012 or 2013. Outcome was a diagnosis of Alzheimer disease, other dementia, or mild cognitive impairment recorded from 2014 through 2022. Odds ratios with 99% confidence intervals (CI) adjusted for age, sex, neighborhood socioeconomic status, diabetes, and cardiovascular disorders were calculated.

RESULTS

During the exposure period, 4 346 patients were diagnosed with chronic stress, 40 101 with depression, and 1 898 with both. The average age at baseline was around 40 years in all groups. In the fully adjusted model, the odds ratio of Alzheimer disease was 2.45 (99% CI 1.22-4.91) in patients with chronic stress, 2.32 (99% CI 1.85-2.90) in patients with depression, and 4.00 (99% CI 1.67-9.58) in patients with chronic stress and depression. The odds ratio of mild cognitive impairment was 1.87 (99% CI 1.20-2.91) in patients with chronic stress, 2.85 (99% CI 2.53-3.22) in patients with depression, and 3.87 (99% CI 2.39-6.27) in patients with both. When other dementia was analyzed, the odds ratio was significant only in patients with depression, 2.39 (99% CI 1.92-2.96).

CONCLUSIONS

Documented chronic stress increased the risk of mild cognitive impairment and Alzheimer disease. The same was seen with depression. The novel finding is the potential additive effect of chronic stress to depression, on risk of MCI and AD.

Would You Screen This Patient for Cognitive Impairment? : Grand Rounds Discussion From Beth Israel Deaconess Medical Center

Dementia, according to the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, is defined by a significant decline in 1 or more cognitive domains that interferes with a person's independence in daily activities. Mild cognitive impairment (MCI) differs from dementia in that the impairment is not sufficient to interfere with independence. For the purposes of this discussion, cognitive impairment (CI) includes both dementia and MCI. Various screening tests are available for CI. These tests ask patients to perform a series of tasks that assess 1 or more domains of cognitive function or ask a caregiver to report on the patient's abilities. A positive result on a screening test does not equate to a diagnosis of CI; rather, it should lead to additional testing to confirm the diagnosis. On review of the evidence, the U.S. Preventive Services Task Force (USPSTF) concluded in 2020 that the evidence was insufficient to assess the balance of benefits and harms of screening for CI in older adults ("I statement"). The USPSTF did clarify that although there is insufficient evidence, there may be important reasons to identify CI. In this article, 2 experts review the available evidence to answer the following questions: What screening tools are available, and how effective are they in identifying patients with CI? What interventions are available for patients found to have CI, to what extent do they improve patient outcomes, and what, if any, negative effects occur? And, would they recommend screening for CI, and why or why not?

Paving the Way for Predicting the Progression of Cognitive Decline: The Potential Role of Machine Learning Algorithms in the Clinical Management of Neurodegenerative Disorders

Alzheimer's disease (AD) is the most common form of neurodegenerative disorder. The prodromal phase of AD is mild cognitive impairment (MCI). The capacity to predict the transitional phase from MCI to AD represents a challenge for the scientific community. The adoption of artificial intelligence (AI) is useful for diagnostic, predictive analysis starting from the clinical epidemiology of neurodegenerative disorders. We propose a Machine Learning Model (MLM) where the algorithms were trained on a set of neuropsychological, neurophysiological, and clinical data to predict the diagnosis of cognitive decline in both MCI and AD patients.

METHODS

We built a dataset with clinical and neuropsychological data of 4848 patients, of which 2156 had a diagnosis of AD, and 2684 of MCI, for the Machine Learning Model, and 60 patients were enrolled for the test dataset. We trained an ML algorithm using RoboMate software based on the training dataset, and then calculated its accuracy using the test dataset.

RESULTS

The Receiver Operating Characteristic (ROC) analysis revealed that diagnostic accuracy was 86%, with an appropriate cutoff value of 1.5; sensitivity was 72%; and specificity reached a value of 91% for clinical data prediction with MMSE.

CONCLUSION

This method may support clinicians to provide a second opinion concerning high prognostic power in the progression of cognitive impairment. The MLM used in this study is based on big data that were confirmed in enrolled patients and given a credibility about the presence of determinant risk factors also supported by a cognitive test score.

Effectiveness of an enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) in older adults with mild cognitive impairment

The aim of this study was to provide a dual-task program that included cognitive and physical training to older adults with mild cognitive impairment (MCI) and evaluate its effects. A single-group pretest-posttest design was performed using 15 older adults with MCI. A 12-week enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) program was conducted from September 2019 to December 2019. Participants were assessed using the Korean version of the Montreal Cognitive Assessment, electroencephalography (EEG), muscle strength, flexibility, agility, memory self-efficacy questionnaire, physical self-efficacy scale, and quality of life before and after 6 and 12 weeks of the intervention. The ESCARF program significantly improved cognitive function, physical function, self-efficacy, and quality of life in older adults with MCI. These findings will provide insights into the development and implementation of customized cognitive interventions to prevent or delay the onset of cognitive decline in older adults with MCI.

The Association of Selected GWAS Reported AD Risk Loci with CSF Biomarker Levels and Cognitive Decline in Slovenian Patients

Alzheimer's disease (AD) is the most common neurodegenerative disease, with a complex genetic background. Apart from rare, familial cases, a combination of multiple risk loci contributes to the susceptibility of the disease. Genome-wide association studies (GWAS) have identified numerous AD risk loci. Changes in cerebrospinal fluid (CSF) biomarkers and imaging techniques can detect AD-related brain changes before the onset of clinical symptoms, even in the presence of preclinical mild cognitive impairment. In this study, we aimed to assess the associations between SNPs in well-established GWAS AD risk loci and CSF biomarker levels or cognitive test results in Slovenian patients with cognitive decline. The study included 82 AD patients, 28 MCI patients with pathological CSF biomarker levels and 35 MCI patients with normal CSF biomarker levels. Carriers of at least one polymorphic TOMM40 rs157581 C allele had lower Aβ42 (p = 0.033) and higher total tau (p = 0.032) and p-tau181 levels (p = 0.034). Carriers of at least one polymorphic T allele in SORCS1 rs1358030 had lower total tau (p = 0.019), while polymorphic SORCS1 rs1416406 allele was associated with lower total tau (p = 0.013) and p-tau181 (p = 0.036). In addition, carriers of at least one polymorphic T allele in BCHE rs1803274 had lower cognitive test scores (p = 0.029). The study findings may contribute to the identification of genetic markers associated with AD and MCI and provide insights into early disease diagnostics.

Effects of Tai Chi combined with tDCS on cognitive function in patients with MCI: a randomized controlled trial

Background

Mild cognitive impairment (MCI) is a critical stage of dementia. Previous reviews have suggested that physical exercise combined with non-invasive brain stimulation is more beneficial for improving cognitive function. However, no targeted studies have confirmed the effect of Tai Chi combined with transcranial direct current stimulation (tDCS) on the improvement of cognitive function in patients with MCI. Thus, this randomized trial was conducted to assess the effect of Tai Chi combined with tDCS on the cognitive performance of patients with MCI.

Methods

From April 2018 to February 2020, a randomized, single-blind clinical trial was conducted, involving 180 participants with MCI who were divided into four intervention groups: Tai Chi combined with tDCS (TCT), Tai Chi combined with sham tDCS (TCS), walking combined with tDCS (WAT), and walking combined with sham tDCS (WAS). All participants were assessed at baseline and 12 weeks for global cognitive function, memory, attention, and executive function.

Results

At baseline, there were no significant differences in age, gender, education duration, body mass index, or the Baker Depression Inventory among the four groups (P ≥ 0.05). After 12 weeks of intervention, the TCT group showed greater improvements in MOCA scores, memory quotient scores, and digit-symbol coding task reaction time compared to the TCS, WAS, and WAT groups (P < 0.05). The TCT group also had a shorter Stroop test color reaction time compared to the WAS and WAT groups (P < 0.05), a higher increase in Auditory Verbal Learning Test-immediate recall than the TCS and WAT groups (P < 0.05), a shorter visual reaction time than the TCS group (P < 0.05), and a shorter sustained attention time compared to the WAT group (P < 0.05).

Conclusion

Tai Chi combined with tDCS effectively improves global cognitive performance, memory, execution function, and attention in patients with MCI. These findings suggest the potential clinical use of Tai Chi combined with tDCS as a physical exercise combined with a non-invasive brain stimulation intervention to improve cognitive function in older adults with MCI.

Clinical trial registration

ChiCTR1800015629.

Baseline Profiles of Drug Prescriptions Prior to Diagnosis of Mild Cognitive Impairment (MCI) Obtained by Latent Class Analysis (LCA), and Assessment of Their Association with Conversion to Dementia

Polypharmacy has been linked to cognitive decline. However, interventions targeting modifiable risk factors, some of which are targets of the most commonly used drugs, could reduce the prevalence of dementia. Our aim was to determine the drug prescription regimen at baseline, prior to the diagnosis of mild cognitive impairment (MCI), and its possible association with progression to dementia. Data were collected from the electronic medical records of 342 MCI outpatients diagnosed during 2006-2017 at their first neurology consultation. We followed the classical three-step method of statistical analysis, starting with a Latent Class Analysis (LCA) to discover subgroups of drug prescription probability. Half of the patients were under polypharmacy (≥5 drugs), 17.5% had no recorded medication, 33.3% progressed to dementia (94.7% in ≤5 years), and 84.1% of them to Alzheimer's disease (AD). According to the LCA and based on 20 therapeutic indicators obtained from 240 substances and regrouped according the Anatomical Therapeutic Chemical Classification, we identified a four-profile model: (1) low (35.7% of patients); (2) mixed (28.7%); (3) cardio-metabolic (19.3%); and (4) psychotropic (16.4%). The binomial regression logistic model showed that profiles 2 and 3 (and 4 for AD), with a higher drug prescription conditioned probability against classic risk factors, were protective than profile 1 (OR = 0.421, p = 0.004; OR = 0.278, p = 0.000; OR = 0.457, p = 0.040, respectively), despite polypharmacy being significant in profiles 2 and 3 (mean > 7 drugs) vs. profile 1 (1.4 ± 1.6) (p = 0.000). Patients in the latter group were not significantly older, although being aged 65-79 years old quadrupled (OR = 4.217, p = 000) and being >79 tripled (OR = 2.945, p = 0.010) the conversion risk compared to patients <65 years old. According to the proposed analytical model, profiling the heterogeneous association of risk factors, which were taken prior to diagnosis, could be explored as an indicator of prior care and a predictor of conversion to dementia.

Olfactory function reflects episodic memory performance and atrophy in the medial temporal lobe in individuals at risk for Alzheimer's disease

We examined cognitive domains and brain regions associated with olfactory performance in cognitively unimpaired older adults (CU-OAs) and individuals with or at risk for Alzheimer's Disease (AD). We compared CU-OAs (N = 55), individuals with subjective cognitive decline (SCD, N = 55), mild cognitive impairment (MCI, N = 101), and AD (N = 45) on measures of olfactory function (Brief Smell Identification Test), cognition (episodic and semantic memory), and medial temporal lobe thickness and volume. Analyses controlled for age, sex, education, and total intracranial volume. Olfactory function decreased from SCD to MCI to AD. CU-OAs outperformed all groups except SCDs on tests of cognition and olfaction. Although these measures did not differ between the CU-OAs and SCDs, olfactory function correlated with episodic memory tests and with entorhinal cortex atrophy only in the SCD group. Olfactory function also correlated with hippocampal volume and right-hemisphere entorhinal cortex thickness in the MCI group. Olfactory dysfunction reflects medial temporal lobe integrity and memory performance in a group at risk for AD with normal cognition and olfaction.

Procedural learning, declarative learning, and working memory as predictors of learning the use of a memory compensation tool in persons with amnestic mild cognitive impairment

Persons with amnestic Mild Cognitive Impairment (aMCI) are at risk for experiencing changes in their daily functioning due to their memory impairment. The Memory Support System (MSS), a compensatory calendaring system, was developed to support functional independence in persons with aMCI (pwaMCI). This cross-sectional study examined procedural learning, declarative learning, and working memory as predictors of MSS learning efficiency in pwaMCI. Sixty pwaMCI participated in MSS training. The Serial Reaction Time Test and Mirror Tracing Test were used to assess procedural learning. The Rey Auditory Verbal Learning Test and CogState One Card Learning were used to assess declarative learning and the CogState One Back task was used to assess working memory. Multiple regression analyses were conducted to assess if procedural learning, declarative learning, and working memory predicted MSS learning efficiency. This study showed that declarative learning predicted MSS learning efficiency in pwaMCI, with less consistent results for procedural learning and non-significant results for working memory. Findings suggest that success in teaching compensatory tools is greater when training is offered in early aMCI before declarative learning skill is fully lost. Future studies should assess additional strategies to facilitate MSS learning in advanced aMCI.

Shared Decision Making for Elective Surgical Procedures in Older Adults with and without Cognitive Insufficiencies

PURPOSE

Older adults are prone to cognitive impairment, which may affect their ability to engage in aspects of shared decision making (SDM) and their ability to complete surveys about the SDM process. This study examined the surgical decision-making processes of older adults with and without cognitive insufficiencies and evaluated the psychometric properties of the SDM Process scale.

METHODS

Eligible patients were 65 y or older and scheduled for a preoperative appointment before elective surgery (e.g., arthroplasty). One week before the visit, staff contacted patients via phone to administer the baseline survey, including the SDM Process scale (range 0-4), SURE scale (top scored), and the Montreal Cognitive Assessment Test version 8.1 BLIND English (MoCA-blind; score range 0-22; scores < 19 indicate cognitive insufficiency). Patients completed a follow-up survey 3 mo after their visit to assess decision regret (top scored) and retest reliability for the SDM Process scale.

RESULTS

Twenty-six percent (127/488) of eligible patients completed the survey; 121 were included in the analytic data set, and 85 provided sufficient follow-up data. Forty percent of patients (n = 49/121) had MoCA-blind scores indicating cognitive insufficiencies. Overall SDM Process scores did not differ by cognitive status (intact cognition x ¯  = 2.5, s = 1.0 v. cognitive insufficiencies x ¯  = 2.5, s = 1.0; P = 0.80). SURE top scores were similar across groups (83% intact cognition v. 90% cognitive insufficiencies; P = 0.43). While patients with intact cognition had less regret, the difference was not statistically significant (92% intact cognition v. 79% cognitive insufficiencies; P = 0.10). SDM Process scores had low missing data and good retest reliability (intraclass correlation coefficient = 0.7).

CONCLUSIONS

Reported SDM, decisional conflict, and decision regret did not differ significantly for patients with and without cognitive insufficiencies. The SDM Process scale was an acceptable, reliable, and valid measure of SDM in patients with and without cognitive insufficiencies.

HIGHLIGHTS

Forty percent of patients 65 y or older who were scheduled for elective surgery had scores indicative of cognitive insufficiencies.Patient-reported shared decision making, decisional conflict, and decision regret did not differ significantly for patients with and without cognitive insufficiencies.The Shared Decision Making Process scale was an acceptable, reliable, and valid measure of shared decision making in patients with and without cognitive insufficiencies.

Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review

Mild cognitive impairment (MCI), representing the 'transitional zone' between normal cognition and dementia, has become a novel topic in clinical research. Although early detection is crucial, it remains logistically challenging at the same time. While traditional pen-and-paper tests require in-depth training to ensure standardized administration and accurate interpretation of findings, significant technological advancements are leading to the development of procedures for the early detection of Alzheimer's disease (AD) and facilitating the diagnostic process. Some of the diagnostic protocols, however, show significant limitations that hamper their widespread adoption. Concerns about the social and economic implications of the increasing incidence of AD underline the need for reliable, non-invasive, cost-effective, and timely cognitive scoring methodologies. For instance, modern clinical studies report significant oculomotor impairments among patients with MCI, who perform poorly in visual paired-comparison tasks by ascribing less attentional resources to novel stimuli. To accelerate the Global Action Plan on the Public Health Response to Dementia 2017-2025, this work provides an overview of research on saccadic and exploratory eye-movement deficits among older adults with MCI. The review protocol was drafted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Electronic databases were systematically searched to identify peer-reviewed articles published between 2017 and 2022 that examined visual processing in older adults with MCI and reported gaze parameters as potential biomarkers. Moreover, following the contemporary trend for remote healthcare technologies, we reviewed studies that implemented non-commercial eye-tracking instrumentation in order to detect information processing impairments among the MCI population. Based on the gathered literature, eye-tracking-based paradigms may ameliorate the screening limitations of traditional cognitive assessments and contribute to early AD detection. However, in order to translate the findings pertaining to abnormal gaze behavior into clinical applications, it is imperative to conduct longitudinal investigations in both laboratory-based and ecologically valid settings.

Cognitive assessment in primary care: Practical recommendations

ABSTRACT

Primary care clinicians play a critical role in both the identification and management of cognitive impairment due to common diseases. Primary care practices should incorporate feasible, reliable, and helpful tools into existing workflow to recognize and support people living with dementia and their care partners.

Tooth Loss, Periodontal Disease, and Mild Cognitive Impairment Among Hispanic/Latino Immigrants: The Moderating Effects of Age at Immigration

BACKGROUND

The objectives were to assess (a) the association between poor oral health and mild cognitive impairment (MCI) in Hispanic/Latino immigrants and (b) potential modification effects on this association by age at immigration.

METHODS

Data were from the Hispanic Community Health Study/Study of Latinos and its ancillary study-the Study of Latinos-Investigation of Neurocognitive Aging. MCI, a binary outcome variable, defined by the National Institute on Aging-Alzheimer's Association criteria. The main exposure was significant tooth loss (STL), defined as a loss of 8 or more teeth, and periodontitis, classified using the Centers for Disease Control and Prevention and American Academy of Periodontology case classification. Multiple logistic regression was used to assess the association between STL/periodontitis and MCI and test moderation effects of age at immigration. The analytical sample comprised 5 709 Hispanic/Latino adult immigrants.

RESULTS

Hispanic/Latino immigrants with STL (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI]: 1.01-1.85) were more likely to have MCI than those with greater tooth retention. Overall, migration to the United States after age 18 was associated with greater odds of MCI than migration at a younger age. A significant interaction effect between STL and age at immigration revealed that the effect of STL on MCI is even higher in those who immigrated to the United States at ages 35-49 years.

CONCLUSIONS

STL is a significant risk factor for MCI and age at immigration had a modification effect on the association between STL and MCI. Better access to dental care, health education on risk factors of MCI, and promotion of good oral health may mitigate the burden of cognitive impairment in Hispanics/Latinos.

Proteostatic modulation in brain aging without associated Alzheimer's disease-and age-related neuropathological changes

AIMS

(Phospho)proteomics of old-aged subjects without cognitive or behavioral symptoms, and without AD-neuropathological changes and lacking any other neurodegenerative alteration will increase understanding about the physiological state of human brain aging without associate neurological deficits and neuropathological lesions.

METHODS

(Phospho)proteomics using conventional label-free- and SWATH-MS (Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) has been assessed in the frontal cortex (FC) of individuals without NFTs, senile plaques (SPs) and age-related co-morbidities classified by age (years) in four groups; group 1 (young, 30-44); group 2 (middle-aged: MA, 45-52); group 3 (early-elderly, 64-70); and group 4 (late-elderly, 75-85).

RESULTS

Protein levels and deregulated protein phosphorylation linked to similar biological terms/functions, but involving different individual proteins, are found in FC with age. The modified expression occurs in cytoskeleton proteins, membranes, synapses, vesicles, myelin, membrane transport and ion channels, DNA and RNA metabolism, ubiquitin-proteasome-system (UPS), kinases and phosphatases, fatty acid metabolism, and mitochondria. Dysregulated phosphoproteins are associated with the cytoskeleton, including microfilaments, actin-binding proteins, intermediate filaments of neurons and glial cells, and microtubules; membrane proteins, synapses, and dense core vesicles; kinases and phosphatases; proteins linked to DNA and RNA; members of the UPS; GTPase regulation; inflammation; and lipid metabolism. Noteworthy, protein levels of large clusters of hierarchically-related protein expression levels are stable until 70. However, protein levels of components of cell membranes, vesicles and synapses, RNA modulation, and cellular structures (including tau and tubulin filaments) are markedly altered from the age of 75. Similarly, marked modifications occur in the larger phosphoprotein clusters involving cytoskeleton and neuronal structures, membrane stabilization, and kinase regulation in the late elderly.

CONCLUSIONS

Present findings may increase understanding of human brain proteostasis modifications in the elderly in the subpopulation of individuals not having AD neuropathological change and any other neurodegenerative change in any telencephalon region.

Eye Movement Latency Coefficient of Variation as a Predictor of Cognitive Impairment: An Eye Tracking Study of Cognitive Impairment

Studies demonstrated impairment in the control of saccadic eye movements in Alzheimer's disease (AD) and people with mild cognitive impairment (MCI) when conducting the pro-saccade and antisaccade tasks. Research showed that changes in the pro and antisaccade latencies may be particularly sensitive to dementia and general executive functioning. These tasks show potential for diagnostic use, as they provide a rich set of potential eye tracking markers. One such marker, the coefficient of variation (CV), is so far overlooked. For biological markers to be reliable, they must be able to detect abnormalities in preclinical stages. MCI is often viewed as a predecessor to AD, with certain classifications of MCI more likely than others to progress to AD. The current study examined the potential of CV scores on pro and antisaccade tasks to distinguish participants with AD, amnestic MCI (aMCI), non-amnesiac MCI (naMCI), and older controls. The analyses revealed no significant differences in CV scores across the groups using the pro or antisaccade task. Antisaccade mean latencies were able to distinguish participants with AD and the MCI subgroups. Future research is needed on CV measures and attentional fluctuations in AD and MCI individuals to fully assess this measure's potential to robustly distinguish clinical groups with high sensitivity and specificity.

Serum cystatin C and mild cognitive impairment: The mediating role of glucose homeostasis

Background

This study explored the mediating role of glucose homeostasis indicators in the relationship between serum cystatin C and mild cognitive impairment (MCI).

Methods

The present study used a cross-sectional design and included 514 participants aged ≥50 years in Beijing, China. The Mini-Mental State Examination was used to assess cognitive function. Serum cystatin C and a comprehensive set of glucose homeostasis indicators were detected, including fasting blood glucose (FBG), glycosylated albumin percentage (GAP), glycated hemoglobin (HbAlc), insulin, and homeostatic model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β). Generalized linear models were used to investigate the associations among cystatin C, glucose homeostasis indicators, and cognitive function. Mediation analysis was conducted to explore potential mediator variables.

Results

In this study of 514 participants, 76 (14.8%) had MCI. Those with cystatin C levels ≥1.09 mg/L had a 1.98-fold higher risk of MCI than those with levels &lt;1.09 mg/L (95% CI, 1.05–3.69). FBG, GAP, and HbA1c increased the risk of MCI, while HOMA-β decreased the risk. Notably, the associations between MCI risk and cystatin C or glucose homeostasis were only founded in diabetes patients. Serum cystatin C was found to be positively associated with HOMA-β (beta (95% CI): 0.20 [0.06, 0.34]), HOMA-IR (0.23 [0.09, 0.36]), and insulin (0.22 [0.09, 0.34]) levels. Moreover, HOMA-β was identified as playing a negative mediating role (proportion mediated: −16%) in the relationship between cystatin C and MCI.

Conclusion

Elevated levels of cystatin C are associated with an increased risk of MCI. The glucose homeostasis indicator, HOMA-β, plays a negative mediating role in the relationship between cystatin C and MCI risk.