Subjective Cognitive Decline Research Articles

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer’s disease (DEBBIE-AD): a prospective observational multicohort study protocol

IntroductionLoss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer’s disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising...

Prevalence of depression among Egyptian male older adults with subjective cognitive decline

Prevalence of depression among Egyptian male older adults with subjective cognitive decline

Demographic and Behavioral Risk Factors Predict Functional Limitations Associated with Subjective Cognitive Decline in Americans with Chronic Obstructive Pulmonary Disease: A Secondary Analysis.

Prior research indicates that subjective cognitive decline (SCD) affects approximately one-third of older adults with Chronic Obstructive Pulmonary Disease (COPD). However, there is limited population-based research on risk factors associated with SCD-related functional limitations within this vulnerable subgroup. A secondary data analysis of 2019 Behavioral Risk Factor Surveillance System data was conducted to address this gap, focusing on Americans ≥45 years old with COPD (N = 107,204). Several sociodemographic and health-related factors were independently associated with SCD-related functional limitations. Retired and unemployed individuals were significantly more likely to require assistance with day-to-day activities due to memory loss or confusion compared to employed individuals (AOR = 3.0, 95% CI: 1.2-8.0; AOR = 5.8, 95% CI: 3.01-1.5, respectively). Additionally, unemployed individuals were over five times more likely to report confusion or memory loss affecting social activities (AOR = 5.7, 95% CI: 2.9-11.0). Disparities were also observed among different racial groups, with Black/African Americans (AOR = 4.9, 95% CI: 2.3-10.4) and Hispanics (AOR = 2.4, 95% CI: 1.2-4.7) more likely than White and non-Hispanic people, respectively, to give up daily chores due to SCD. Our findings underscore the need for culturally sensitive interventions to address functional limitations faced by retired, unemployed, and minority adults with COPD and SCD.

Can motor decline be a modifiable marker of clinical progression in subjective cognitive decline? A national prospective cohort study

ObjectivesSubjective cognitive decline represents a critical stage for preventing mild cognitive impairment and dementia, but the links between clinical progression in the subjective cognitive decline stage and various motor functions remain inconclusive. This cohort study aimed to elucidate the independent and joint associations between the clinical progression of subjective cognitive decline and motor functions. MethodsWe enrolled 4880 community-dwelling elderly participants from a national cohort and used Cox proportional hazard regression model and restricted cubic spline models to explore the longitudinal associations between motor functions (gait, strength, balance, and endurance) and the clinical progression of subjective cognitive decline. ResultsDuring 5-years follow-up, 1239 participants experienced clinical progression. After adjusting for demographics, vascular burden, body components, and polypharmacy, gait speed [hazard ratios (HRs)= 0.96, 95% confidence interval (CI) 0.94–0.99], chair stand test (HRs=1.02, 95%CI 1.01–1.03), and endurance limitation in jogging 1 kilometer (HRs=1.18, 95%CI 1.04–1.34) were significantly associated with clinical progression. Among all participants, individuals characterized by poor upper- and lower-body strength, as well as those with slow pace and reduced endurance, faced the highest risk of cognitive impairment. ConclusionsThis study emphasizes the potential of gait speed, muscle strength, and endurance as non-cognitive indicators of clinical progression in subjective cognitive decline. Understanding their combined effectiveness may reveal primary physiological mechanisms contributing to the dual decline of motor and cognition.

A network approach to subjective cognitive decline: Exploring multivariate relationships in neuropsychological test performance across Alzheimer's disease risk states

Subjective cognitive decline (SCD) is characterized by subjective concerns of cognitive change despite test performance within normal range. Although those with SCD are at higher risk for developing further cognitive decline, we still lack methods using objective cognitive measures that reliably distinguish SCD from cognitively normal aging at the group level. Network analysis may help to address this by modeling cognitive performance as a web of intertwined cognitive abilities, providing insight into the multivariate associations determining cognitive status. Following previous network studies of mild cognitive impairment (MCI) and Alzheimer's dementia (AD), the current study centered upon the novel visualization and analysis of the SCD cognitive network compared to cognitively normal (CN) older adult, MCI, and AD group networks. Cross-sectional neuropsychological data from CIMA-Q and COMPASS-ND cohorts were used to construct Gaussian graphical models for CN (n = 122), SCD (n = 207), MCI (n = 210), and AD (n = 79) groups. Group networks were explored in terms of global network structure, prominent edge weights, and strength centrality indices. CN and SCD group networks were contrasted using the Network Comparison Test. Results indicate that CN and SCD groups did not differ in univariate cognitive performance or global network structure. However, measures of strength centrality, principally in executive functioning and processing speed, showed a CN-SCD-MCI gradient where subtle differences within the SCD network suggest that SCD is an intermediary between CN and MCI stages. Additional results may indicate a distinctiveness of network structure in AD, a reversal in network influence between age and general cognitive status as clinical impairment increases, and potential evidence for cognitive reserve. Together, these results provide evidence that network-specific metrics are sensitive to cognitive performance changes across the dementia risk spectrum and can help to objectively distinguish SCD group cognitive performance from that of the CN group.

Macular vessel density in the superficial plexus is not a proxy of cerebrovascular damage in non-demented individuals: data from the NORFACE cohort

IntroductionOptical coherence tomography angiography (OCT-A) is a novel tool that allows the detection of retinal vascular changes. We investigated the association of macular vessel density (VD) in the superficial plexus assessed by OCT-A with measures of cerebrovascular pathology and atrophy quantified by brain magnetic resonance imaging (MRI) in non-demented individuals.MethodsClinical, demographical, OCT-A, and brain MRI data from non-demented research participants were included. We analyzed the association of regional macular VD with brain vascular burden using the Fazekas scale assessed in a logistic regression analysis, and the volume of white matter hyperintensities (WMH) assessed in a multiple linear regression analysis. We also explored the associations of macular VD with hippocampal volume, ventricle volume and Alzheimer disease cortical signature (ADCS) thickness assessed in multiple linear regression analyses. All analyses were adjusted for age, sex, syndromic diagnosis and cardiovascular variables.ResultsThe study cohort comprised 188 participants: 89 with subjective cognitive decline and 99 with mild cognitive impairment. No significant association of regional macular VD with the Fazekas categories (all, p > 0.111) and WMH volume (all, p > 0.051) were detected. VD in the nasal quadrant was associated to hippocampal volume (p = 0.007), but no other associations of macular VD with brain atrophy measures were detected (all, p > 0.05).DiscussionRetinal vascular measures were not a proxy of cerebrovascular damage in non-demented individuals, while VD in the nasal quadrant was associated with hippocampal atrophy independently of the amyloid status.

Olfactory deficit: a potential functional marker across the Alzheimer's disease continuum.

Alzheimer's disease (AD) is a prevalent form of dementia that affects an estimated 32 million individuals globally. Identifying early indicators is vital for screening at-risk populations and implementing timely interventions. At present, there is an urgent need for early and sensitive biomarkers to screen individuals at risk of AD. Among all sensory biomarkers, olfaction is currently one of the most promising indicators for AD. Olfactory dysfunction signifies a decline in the ability to detect, identify, or remember odors. Within the spectrum of AD, impairment in olfactory identification precedes detectable cognitive impairments, including mild cognitive impairment (MCI) and even the stage of subjective cognitive decline (SCD), by several years. Olfactory impairment is closely linked to the clinical symptoms and neuropathological biomarkers of AD, accompanied by significant structural and functional abnormalities in the brain. Olfactory behavior examination can subjectively evaluate the abilities of olfactory identification, threshold, and discrimination. Olfactory functional magnetic resonance imaging (fMRI) can provide a relatively objective assessment of olfactory capabilities, with the potential to become a promising tool for exploring the neural mechanisms of olfactory damage in AD. Here, we provide a timely review of recent literature on the characteristics, neuropathology, and examination of olfactory dysfunction in the AD continuum. We focus on the early changes in olfactory indicators detected by behavioral and fMRI assessments and discuss the potential of these techniques in MCI and preclinical AD. Despite the challenges and limitations of existing research, olfactory dysfunction has demonstrated its value in assessing neurodegenerative diseases and may serve as an early indicator of AD in the future.

Examining the relationship between brain activation and proxies of disease severity using quantile regression in individuals at risk of Alzheimer's disease

Previous studies have reported a pattern of hyperactivation in the pre-dementia phase of Alzheimer's disease (AD), followed by hypoactivation in later stages of the disease. This pattern was modeled as an inverse U-shape function between activation and markers of disease severity. In this study, we used quantile regression to model the association between task-related brain activation in AD signature regions and three markers of disease severity (hippocampal volume, cortical thickness, and associative memory). This approach offers distinct advantages over standard regression models as it analyzes the relationship between brain activation and disease severity across various levels of brain activation. Participants were 54 older adults with subjective cognitive decline+ (SCD+) or mild cognitive impairment (MCI) from the CIMA-Q cohort. The analysis revealed an inverse U-shape quadratic function depicting the relationship between disease severity markers and the activation of the left superior parietal region, while a linear relationship was observed for activation of the hippocampal and temporal regions. Quantile differences were observed for temporal and parietal activation, with more pronounced effects observed in the higher quantiles of activation. When comparing quantiles, we found that higher quantile of activation featured a greater number of individuals with SCD+ compared to mild cognitive impairment (MCI). Results are globally consistent with the presence of an inverse-U shape function of activation in relation to disease severity. They study also underscores the utility of employing quantile regression modeling as the modeling approach revealed the presence of non-homogeneous effects across various quantiles.

Cognitive and immunological effects of yoga compared to memory training in older women at risk for alzheimer’s disease

Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) accompanied by cerebrovascular risk factors (CVRFs) are known to increase the risk of developing dementia. Mind-body practices such as yoga and meditation, have been recognized as safe techniques with beneficial effects on cognitive functions in older adults at risk for cognitive decline. We conducted a randomized, controlled trial to assess the efficacy of Kundalini yoga training (KY) compared to memory enhancement training (MET) on mood and cognitive functioning in a group of older women with CVRFs and SCD (clinicaltrials.gov = NCT03503669). The KY intervention consisted of weekly, 60-min in-person classes with a certified instructor for 12 weeks, with a 12-min guided recording for daily homework practice at home. MET involved 12 weekly in-person group classes with 12-min daily homework exercises. Objective and subjective memory performance were the primary outcomes. Peripheral whole blood samples were collected at baseline, 12-weeks, and 24-weeks follow-up for RNA sequencing and cytokine/chemokine assays. A total of 79 patients (KY = 40; MET = 39) were randomized, and 63 completed the 24-week follow-up (KY = 65% completion rate; MET = 95%; χ2(1) = 10.9, p < 0.001). At 24-weeks follow-up, KY yielded a significant, large effect size improvement in subjective cognitive impairment measures compared to MET. KYOn a transcriptional level, at 12- and 24-week follow-up, KY uniquely altered aging-associated signatures, including interferon gamma and other psycho-neuro-immune pathways. Levels of chemokine eotaxin-1, an aging marker, increased over time in MET but not KY participants. These results suggest clinical and biological benefits to KY for SCD, linking changes in cognition to the anti-inflammatory effects of yoga.

Everyday functioning among older adults with subjective cognitive decline: a scoping review

Purpose Older adults with subjective cognitive decline (SCD) experience cognitive difficulties without objectively measurable cognitive impairments but which may affect their everyday functioning. However, everyday functioning in this population has not yet been characterized. We sought to describe the empirical literature on the everyday functioning of community-dwelling older adults with SCD, their recruitment methods, and the measurements used. Methods A scoping review was conducted for primary research articles including at least one measure of everyday functioning. Retrieved records were independently screened. Data were extracted then analyzed using descriptive statistics and summative content analysis. Results 6544 studies were screened; 21 studies were included. All were observational analytic studies. Most compared an SCD group with a group of healthy control (47.6%), mild cognitive impairment (71.5%), and/or dementia (33.3%). Subjective cognition was measured via interview (28.6%) or clinical question(s) (14.3%). Normal cognition was determined by a wide variety of cognitive tests. The most studied everyday functioning domain was instrumental activities of daily living (90.5%). Most studies used questionnaires (81.0%), and measured ability to do an everyday life task (76.2%). Conclusions More research is needed on everyday functioning other than IADL, with greater focus on measures that consider an individual’s real-life participation.

Exploring the Remediation of Behavioral Disturbances of Spatial Cognition in Community-Dwelling Senior Citizens with Mild Cognitive Impairment via Innovative Technological Apparatus (BDSC-MCI Project): Protocol for a Prospective, Multi-Center Observational Study.

Spatial navigation (SN) has been reported to be one of the first cognitive domains to be affected in Alzheimer's disease (AD), which occurs as a result of progressive neuropathology involving specific brain areas. Moreover, the epsilon 4 isoform of apolipoprotein-E (APOE-ε4) has been associated with both sporadic and familial late-onset AD, and patients with mild cognitive impairment (MCI) due to AD are more likely to progressively deteriorate. Spatial navigation performance will be examined on a sample of 76 community-dwelling senior citizens (25 healthy controls; 25 individuals with subjective cognitive decline (SCD); and 26 patients with MCI due to AD) via a virtual computer-based task (i.e., the AppleGame) and a naturalistic task (i.e., the Detour Navigation Test-modified version) for which a wearable device with sensors will be used for recording gait data and revealing physiological parameters that may be associated with spatial disorientation. We expect that patients with MCI due to AD and APOE-ε4 carriers will show altered SN performances compared to individuals with SCD and healthy controls in the experimental tasks, and that VR testing may predict ecological performance. Impaired SN performances in people at increased risk of developing AD may inform future cognitive rehabilitation protocols for counteracting spatial disorientation that may occur during elders' traveling to unfamiliar locations. The research protocol has been approved by the Ethics Committee of the Istituto Auxologico Italiano. Findings will be published in peer-reviewed medical journals and discussed in national and international congresses.

Modelling the Distribution of Cognitive Outcomes for Early-Stage Neurocognitive Disorders: A Model Comparison Approach.

Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools. These cognitive scores are usually left-skewed and the results of the association analysis might not be robust. This study aims to study the distribution of the cognitive outcomes and to discuss potential solutions. Materials and Methods: In this retrospective cohort study of individuals with subjective cognitive decline or mild cognitive impairment, the inverse-transformed cognitive outcomes are modelled using different statistical distributions. The robustness of the proposed models are checked under different scenarios: with intercept-only, models with covariates, and with and without bootstrapping. Results: The main results were based on the VCAT score and validated via the MoCA score. The findings suggested that the inverse transformation method improved the modelling the cognitive scores compared to the conventional methods using the original cognitive scores. The association of the baseline characteristics (age, gender, and years of education) and the cognitive outcomes were reported as estimates and 95% confidence intervals. Bootstrap methods improved the estimate precision and the bootstrapped standard errors of the estimates were more robust. Cognitive outcomes were widely analysed using linear regression models with the default normal distribution as a conventional method. We compared the results of our suggested models with the normal distribution under various scenarios. Goodness-of-fit measurements were compared between the proposed models and conventional methods. Conclusions: The findings support the use of the inverse transformation method to model the cognitive outcomes instead of the original cognitive scores for early-stage neurocognitive disorders where the cognitive outcomes are left-skewed.

Long-term follow-up of brain regional changes and the association with cognitive impairment in quarantined COVID-19 survivors.

This study aimed to evaluate the neuropsychiatric symptoms of quarantined COVID-19 survivors 15months after discharge and explore its potential association with structural and functional brain changes and inflammation. A total of 51 quarantined COVID-19 survivors and 74 healthy controls were included in this study. Cognitive function was assessed using the THINC-integrated tool. Structural brain changes were examined through both surface- and volume-based analyses, and functional changes were assessed using resting-state amplitude low-frequency fluctuation (ALFF). Serum inflammatory markers were measured by a multiplexed flow cytometric assay. COVID-19 survivors exhibited subjective cognitive decline compared to healthy controls, despite no significant differences in objective cognitive tasks. Structural analysis revealed significantly increased gray matter volume and cortical surface area in the left transverse temporal gyrus (Heschl's gyrus) in quarantined COVID-19 survivors. This enlargement was negatively correlated with cognitive impairment. The ALFF analysis showed decreased neural activity in multiple brain regions. Elevated levels of serum inflammatory markers were also found in COVID-19 survivors, including MIP-1a, MIP-1b, TNF-a, and IL-8, which correlated with functional abnormalities. Our findings indicate a subjective cognitive decline in quarantined COVID-19 survivors 15months after discharge, which is associated with brain structural alterations in the left Heschl's gyrus. The observed elevation of inflammatory markers suggests a potential mechanism involving inflammation-induced neurogenesis. These results contribute to our understanding of the possible mechanisms underlying long-term neuropsychiatric consequences of COVID-19 and highlight the need for further research to develop targeted interventions.

Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease.

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

Predicting progression of cognitive decline to dementia using dyadic patterns of subjective reporting: evidence from the CompAS longitudinal study.

To analyze the validity of self and informant reports, depressive symptomatology, and some sociodemographic variables to predict the risk of cognitive decline at different follow-up times. A total of 337 participants over 50 years of age included in the CompAS and classified as Cognitively Unimpaired (CU), Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) groups were assessed at baseline and three follow-ups. A short version of the QAM was administered to assess the severity of subjective cognitive complaints (SCCs), and the GDS-15 was used to evaluate the depressive symptoms. At each follow-up assessment, participants were reclassified according to the stability, regression or progression of their conditions. Logistic regression analysis was used to predict which CU, SCD and MCI participants would remain stable, regress or progress at a 3rd follow-up by using self- and informant-reported complaints, depressive symptomatology, age and education at baseline and 2nd follow-ups as the predictive variables. Overall, self-reported complaints predicted progression between the asymptomatic and presymptomatic stages. As the objective deterioration increased, i.e., when SCD progressed to MCI or dementia, the SCCs reported by informants proved the best predictors of progression. Depressive symptomatology was also a predictor of progression from CU to SCD and from SCD to MCI. A late increase in self-reported complaints make valid estimates to predict subjective decline at asymptomatic stages. However, an early increase in complaints reported by informants was more accurate in predicting objective decline from asymptomatic stages. Both, early and late decrease in self-reported complaints successfully predict dementia from prodromic stage. Only late decrease in self-reported complaints predict reversion from prodromic and pre-symptomatic stages.

Unveiling the sound of the cognitive status: Machine Learning-based speech analysis in the Alzheimer's disease spectrum.

Advancement in screening tools accessible to the general population for the early detection of Alzheimer's disease (AD) and prediction of its progression is essential for achieving timely therapeutic interventions and conducting decentralized clinical trials. This study delves into the application of Machine Learning (ML) techniques by leveraging paralinguistic features extracted directly from a brief spontaneous speech (SS) protocol. We aimed to explore the capability of ML techniques to discriminate between different degrees of cognitive impairment based on SS. Furthermore, for the first time, this study investigates the relationship between paralinguistic features from SS and cognitive function within the AD spectrum. Physical-acoustic features were extracted from voice recordings of patients evaluated in a memory unit who underwent a SS protocol. We implemented several ML models evaluated via cross-validation to identify individuals without cognitive impairment (subjective cognitive decline, SCD), with mild cognitive impairment (MCI), and with dementia due to AD (ADD). In addition, we established models capable of predicting cognitive domain performance based on a comprehensive neuropsychological battery from Fundació Ace (NBACE) using SS-derived information. The results of this study showed that, based on a paralinguistic analysis of sound, it is possible to identify individuals with ADD (F1 = 0.92) and MCI (F1 = 0.84). Furthermore, our models, based on physical acoustic information, exhibited correlations greater than 0.5 for predicting the cognitive domains of attention, memory, executive functions, language, and visuospatial ability. In this study, we show the potential of a brief and cost-effective SS protocol in distinguishing between different degrees of cognitive impairment and forecasting performance in cognitive domains commonly affected within the AD spectrum. Our results demonstrate a high correspondence with protocols traditionally used to assess cognitive function. Overall, it opens up novel prospects for developing screening tools and remote disease monitoring.

Analysis of the prevalence of anticoagulant therapy in patients with cognitive disorders and cerebral amyloid angiopathy (CAA)

To investigate the prevalence of coincident anticoagulation in patients with cognitive disorders and possible or probable cerebral amyloid angiopathy (CAA) as well as the relationship between the presence of oral anticoagulation and CAA-specific lesion load. Patients with subjective cognitive decline (SCD), amnestic and non-amnestic mild cognitive impairment (aMCI/naMCI), Alzheimer's disease (AD), mixed dementia (MD) and vascular dementia (VD) who presented to our outpatient dementia clinic between February 2016 and October 2020 were included in this retrospective analysis. Patients underwent cranial magnetic resonance imaging (MRI). MRI data sets were analyzed regarding the presence of CAA-related MRI biomarkers to determine CAA prevalence. Presence of anticoagulant therapy was determined by chart review. Within the study period, 458 patients (209 male, 249 female, mean age 73.2 ± 9.9years) with SCD (n = 44), naMCI (n = 40), aMCI (n = 182), AD (n = 120), MD (n = 68) and VD (n = 4) were analyzed. Atotal of 109 patients (23.8%) were diagnosed with possible or probable CAA. CAA prevalence was highest in aMCI (39.4%) and MD (28.4%). Of patients with possible or probable CAA, 30.3% were under platelet aggregation inhibition, 12.8% were treated with novel oral anticoagulants and 3.7% received phenprocoumon treatment. Regarding the whole study cohort, patients under oral anticoagulation showed more cerebral microbleeds (p = 0.047). There was no relationship between oral anticoagulation therapy and the frequency of cortical superficial siderosis (p = 0.634). CAA is afrequent phenomenon in older patients with cognitive disorders. Almost half of CAA patients receive anticoagulant therapy. Oral anticoagulation is associated with ahigher number of cortical and subcortical microbleeds.

Association between social capital and quality of life in older adults with subjective cognitive decline: A cross-sectional study

BackgroundSubjective cognitive decline (SCD) is increasingly recognized as a clinical and medical risk factor for mild cognitive impairment (MCI) and dementia. Currently, there is little evidence regarding the quality of life (QoL) in older adults with SCD and the impact of social capital on their QoL. AimsTo examine the perceptions of social capital and QoL among older adults with SCD. MethodsA total of 325 participants (92.9 % response rate) with a self-reported diagnosis of SCD completed the Chinese version of the 36-item Short-Form Health Survey, the Chinese Shortened Social Capital Scale and the Generalized Anxiety Disorder Scale. A t-test was used to compare the QoL score of our sample with the Chinese norm. Pearson correlation analysis and multivariate linear regression analysis were used to assess the association of social capital with QoL. ResultsSocial capital were strongly correlated with the total QoL, as well as its physical component summary and mental component summary. The QoL score of older adults with SCD was significantly lower than the Chinese norm (P < 0.001). Multivariate analysis showed that social capital, physical activity, nutrition and anxiety symptoms were factors associated with QoL among older SCD population (P < 0.05). ConclusionThe findings of the current study suggest that older adults with SCD may experience lower QoL. Social capital is associated with the QoL in older adults with SCD. These findings have implications for clinicians who work with older adults with SCD.

Effect of dairy consumption on cognition in older adults: A population-based cohort study.

We aimed to assess the effect on cognitive function of adding dairy (total, fermented, non-fermented, full fat, low fat, and sugary) to the diet and of substituting some food groups for dairy. Secondary analysis of a prospective population-based cohort study. We analyzed data from 1334 cognitively healthy participants (median age 67 years at baseline) with a mean follow-up of 5.6 years from the CoLaus|PsyColaus cohort in Lausanne, Switzerland. The participants completed a food frequency questionnaire at baseline and cognitive tests at baseline and at follow-up. Clinical dementia rating was the primary outcome. Subjective cognitive decline, memory, verbal fluency, executive and motor functions were secondary outcomes. Our exposure was the consumption of total and 5 sub-types of dairy products (g/d). We used marginal structural models to compute average causal effects of 1) increasing dairy consumption by 100 g/d and 2) substituting 100 g/d of meat, fish, eggs, fruits and vegetables with dairy on the outcomes. We used inverse probability of the treatment and lost to follow-up weighting to account for measured confounding and non-random loss to follow-up. Overall, the effects of adding dairy products to the diet on cognition were negligible and imprecise. No substitution had a substantial and consistent effect on clinical dementia rating. The substitution of fish [11.7% (-3% to 26.5%)] and eggs [18% (2.3%-33.7%)] for dairy products could negatively impact verbal memory and neurolinguistic processes. We found no effect of adding dairy to the diet or substituting meat, vegetables or fruit for dairy on cognitive function in this cohort of older adults. The substitution of fish and eggs for dairy could have a negative effect on some secondary outcomes, but more studies modeling food substitutions are needed to confirm these results.

Predicting progression to Alzheimer's disease dementia using cognitive measures.

It is important to determine if cognitive measures identified as being prognostic in dementia research cohorts also have utility in memory clinics. We aimed to identify measures with the greatest power to predict future Alzheimer's disease (AD) dementia in a clinical setting where expensive biomarkers are not widely available. This study utilized routine Memory Clinic data collected over 18years. From 2214 patients assessed in the clinic, we selected 328 patients with an initial diagnosis of subjective cognitive decline or mild cognitive impairment. We compared two types of statistical model for the prediction of AD dementia. The first model included baseline cognitive test scores only, while the second model also included change scores between baseline and the first follow-up. Baseline scores on tests of global cognitive function (Mini-mental state examination and Cambridge Cognitive Examination-Revised), verbal episodic memory and psychomotor speed were the best predictors of conversion to AD dementia. The inclusion of cognitive change scores over 1year of follow-up improved predictive accuracy versus baseline scores alone. We found that the best cognitive predictors of AD dementia in a clinical setting were similar to those previously identified using research cohorts. Taking change in cognitive function into account enabled the onset of AD dementia to be predicted with greater accuracy.