bluuebunny/crossref_metadata_2025_split huggingface dataset:
Daily coffee intake in midlife and enhanced late life cognition in twins
Authors: Chanti‐Ketterl Marianne , Johnson Kim , Plassman Brenda L 
Published: December 2021

AbstractBackgroundCoffee drinking has shown mixed results in its association with cognitive function in later life, likely due in part to influence from unmeasured genetic and environmental factors, leading to inconsistent findings between studies. Given that members of twin pairs share at least some of their genes and many early‐life experiences, twin studies have advantages in providing control for confounding factors, many unidentified, that affect late‐life cognition. We aimed to explore if coffee intake in midlife maintains cognitive function in late‐life.MethodA total of 7,438 members of the NAS‐NRC Twin Registry of Male World War II Veterans born from 1917–1927 were included in this study. Number of cups of coffee consumed daily was collected via mailed questionnaire in 1967. Cognitive status was measured every 3 years from 1990‐2002 using the modified Telephone Interview for Cognitive Status (TICS‐m) (range 0‐50). Daily coffee intake was categorized as tertiles (T):(T1)=1‐2 cups, (T2)=3‐4 cups, (T3)>5 cups, with reference=0 cups. Linear‐mixed‐effect regression models, controlling for age at time of initial TICS‐m, education, smoking and alcohol status and twin pair, were used to assess the association between daily intake of coffee in midlife and performance on the TICS‐m over a period of up to 12 years in later life.ResultParticipants’ mean age was 41.7 years (standard deviation (SD)=2.8) when information on coffee intake was collected and 66.9(SD=2.8) at the time of their first TICS‐m. A total of 6,665 males reported drinking coffee, and the mean number of cups was 3.6(SD=2.4) daily. Twins who consumed more than 2 cups of coffee obtained higher TICS‐m scores (T2:b=0.53; 95%CI=0.22,0.85) and (T3:b=0.50;95%CI=0.18,0.82) than non‐coffee drinkers. This equates to an average of 2.4‐2.6 TICS‐m points more for those in T2 and T3 compared to non‐coffee drinkers. However, the amount of coffee intake was not associated with the rate of cognitive decline (T1:p=0.84,T2:p=0.28,T3:p=0.09).ConclusionWe found that higher amounts of midlife coffee drinking are associated with better cognitive performance, but not reduced rate of cognitive decline in late‐life even after accounting for shared genetic and early‐life environmental factors. Future research should investigate potential mechanisms linking coffee and cognition.
Associations between sleep and Alzheimer’s disease biomarkers within the EPAD cohort
Authors: Naismith Sharon L. , Palmer Jake R. , Leng Yue , Lucey Brendan P. 
Published: December 2021

AbstractBackgroundChanges in sleep quality are common in Alzheimer’s Disease (AD) and may even play a role in the onset and accumulation of disease. However, in preclinical stages, it is unclear whether sleep quality or sleep disturbance relate to disease pathology after controlling for known covariates and AD risk factors. This study aimed to determine if self‐reported sleep quality is associated with AD biomarkers after accounting for such factors.MethodData were obtained from the European Prevention of Alzheimer’s Disease (EPAD) Longitudinal Cohort Study (LCS) data set (v1500.0). Cerebrospinal fluid (CSF) samples were collected for measurement of b‐amyloid (Ab42) and phosphorylated tau (p‐tau). Self‐reported sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). Participants with Clinical Dementia Rating (CDR) scale scores greater than 0.5, indicative of dementia, were excluded. Linear regression models were used to determine whether the p‐tau/Ab42 ratio was associated with PSQI component scores when controlling for multiple potential confounders such as demographics, ApoE4 status, depressive symptoms, body mass index, vascular risks, smoking status, use of psychotropics, white matter lesions, and hippocampal volume. PSQI component scores of 2 or 3 were combined due to small numbers of participants with component scores of 3.ResultFrom the 1500 participants in the EPAD‐LCS v1500.0 data, a total of 1239 participants were included in the regression analysis (mean age=65.30 years, SD=7.11; mean PSQI total score=5.31, SD=3.38). After adjustment for all covariates, higher p‐tau/Ab42 ratio was found to be associated with longer self‐reported sleep latency (component score of 1: b=0.16, p=0.007; component score of 2/3: b=0.12, p=0.134; R2=0.22) and better self‐reported sleep efficiency (component score of 1: b=‐0.22, p=0.04; component score of 2/3: b=‐0.31, p=0.009; R2=0.22)ConclusionWithin the EPAD cohort, longer sleep latency and greater efficiency are associated with greater AD pathology after controlling for covariates. These findings contribute to growing evidence suggesting sleep is an important early marker of underlying neurodegeneration. Longitudinal assessment of EPAD‐LCS participants will allow for the evaluation of self‐reported sleep as a predictive marker of neurodegeneration.
Preclinical amyloid‐PET SUVr in the precuneus and posterior cingulate associations with MoCA scores are driven by language domain subscores
Authors: Ali Doaa , Barber Justin M , El Khouli Riham H , Gold Brian T. , Harp Jordan , Van Eldik Linda J , Wilcock Donna M , Jicha Gregory A 
Published: December 2021

AbstractBackgroundβ‐amyloid (Aβ) deposition in the brain is the earliest pathological change supporting a diagnosis of preclinical Alzheimer’s disease (pAD). Such deposition can be quantified using amyloid‐PET scans, which also enable a quantitative evaluation of the distribution of the pathology in pAD. Cognitive screening instruments such as the Montreal Cognitive Assessment (MoCA) are widely used to detect cognitive decline as one transitions from pAD to mild cognitive impairment or dementia due to AD, but have little proven utility in tracking cognitive decline during the stage of pAD. The present study sought to identify potential relationships between regional Aβ deposition and domain specific subscales and items comprising the MoCA in pAD.MethodNinety‐nine clinically normal participants with a MoCA score ≥ 23 underwent F18‐florbetapir PET/CT scanning and regional standardized uptake value ratio (SUVr) was determined using the Siemens Syngo.via® Neurology software package. Relationships between regional SUVr and MoCA test performance as well as MoCA domain scores were analyzed using linear regression models adjusted for age and education.ResultSubjects included 68 women and 31 men with a mean age of 74.2±6.3 years, education 16.7±2.6 years, and MoCA 26.6± 1.9. The adjusted linear regression analyses demonstrated that reduced global MoCA score was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p<0.05). This relationship appeared to be driven predominantly by the language domain index score rather than other subdomains of the MoCA (R2=0.122; p= 0.003).ConclusionThese data demonstrate that increased Aβ deposition in the precuneus and posterior cingulate (the earliest brain regions affected with Aβ pathology) are associated with decreased global cognitive performance, driven by language domain subscores in individuals with pAD. Further research using more sensitive domain‐specific tests in cognitively normal individuals may help determine optimal low‐cost, non‐invasive, neuropsychological predictors of pAD.
Social health and reserve in the dementia patient journey (SHARED): The role of social interactions in the clinical phase of dementia
Authors: Samtani Suraj , Stevens Ashley , Lipnicki Darren M , Sachdev Perminder S , Brodaty Henry ,   SHARED Consortium
Published: December 2021

AbstractBackgroundThe SHARED project is an international collaboration designed to investigate the role of social factors in the onset and course of dementia across the lifespan. We investigated the impact of social health on cognition throughout the clinical phase of dementia – an area that remains vastly under‐researched.MethodWe harmonised data from 12 international longitudinal studies of ageing (11 studies from the COSMIC consortium and the English Longitudinal Study of Ageing) to select participants who were had a diagnosis of mild cognitive impairment or dementia.We investigated the impact of social factors on cognitive decline across 3 groups – those who had MCI and remained stable (n = 5706), those with MCI who declined into dementia (n = 659), and those who had dementia at baseline (n = 1236). A series of multi‐level, linear mixed models were run to determine the impact of social health factors, namely loneliness, social interactions, social activities, network size, living situation, social support and relationship satisfaction on the different trajectories.ResultAfter controlling for age, sex, education, APOE e4 alleles, and physical health factors, significant differences emerged between the in the frequency of interactions. Specifically, the dementia at baseline group were less likely to engage in interactions monthly (β = ‐1.15, SE = .46, p = .01) or weekly (β = ‐1.08, SE = .42, p = .01) compared to the MCI stable group. No differences emerged in relation to network size, social support, or relationship satisfaction. Compared to the MCI decline group, the dementia at baseline group were more likely to be single (instead of married/in a relationship or separated/divorced), but this result did not emerge in studies which included APOE data.ConclusionHarmonised data from multiple longitudinal studies of ageing, demonstrated that people living with dementia were less likely to have frequent social interactions compared to people experiencing mild cognitive impairment. Further research is required to explore the trajectory of social interactions over time as individuals progress through the stages of dementia, and investigate the impact of cognitive and health factors on this trajectory.
Sex‐related differences in cognition with statin usage in a geriatric memory clinic cohort
Authors: Chan Alex K , Lo Tsz Wai Bentley , Karameh Wael K , Fornazzari Luis , Dadone Gianfranco , Golas Angela C , Barfett Joseph , Munoz David G. , Schweizer Tom A. , Fischer Corinne E. 
Published: December 2021

AbstractBackgroundRecently, there has been debate for the suitability of statins for geriatric populations and patients with dementia as there is evidence suggesting improved quality of life following discontinuation of therapy in these groups, as well as conflicting evidence surrounding its potential to both prevent and potentiate downstream cognitive deficits. Despite large scale studies being conducted in the past regarding statins and cognition, there is a paucity of literature investigating its interaction with sex, as well as possible associations with other variables such as subjective complaints, neuropsychiatric symptoms, and function.MethodsAnalysis was done on patients assessed at a Memory Disorders Clinic at St. Michael’s Hospital between 2012 and 2017, comprising a population of 348 patients divided into groups taking daily atorvastatin (N = 45), rosuvastatin (N = 40), and controls (N = 263) (Table 1). Data form the Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Behavioural Neurology Assessment‐Revised (BNA‐R), Neuropsychological Impairment Scale (NIS), The Older Americans Resources and Services (OARS) Activities of Daily Living (ADL) Scale and Neuropsychiatric Inventory Questionnaire (NPI‐Q) were analyzed.ResultsTwo‐way ANOVA demonstrated a significant interaction between sex, cognitive performance, and statin use in which female statin users scored significantly lower on multiple subdomains of the BNA‐R (p < 0.05) (Table 2). Patients taking atorvastatin additionally scored lower on CERAD delayed recall, delayed recognition, and in the cumulative recognition domain than other groups (p < 0.05). Atorvastatin and rosuvastatin were additionally associated with higher frequency of dysphoria and disinhibition, respectively (p < 0.05). No significant results were found in other measures investigated.ConclusionsIn addition to minor associations between atorvastatin usage and lower memory performance, findings from this investigation suggest a possible interaction between sex, cognition and statin use that has not been well documented in literature. Though these findings were not reflected in other measures such as subjective complaint or function, further research may be warranted to provide insight into the relationship between sex, statin usage and neurological effects.
The QuickSort: A brief cognitive screen to detect cognitive impairment in older adults
Authors: Foran Amie M , Mathias Jane L , Bowden Stephen C 
Published: December 2021

AbstractBackgroundSorting tests are amongst the most sensitive cognitive tests for detecting brain injury, but are rarely used to screen older adults for cognitive impairment. A recent meta‐analysis (Foran, Mathias & Bowden) found that sorting ability deteriorates in older adults who have been diagnosed with one of a number of common neurodegenerative disorders, suggesting that sorting tests may provide an alternative to cognitive screens. The QuickSort is a new test that improves on existing sorting tasks, with the manual and test stimuli freely accessible to users (Foran, Mathias & Bowden, 2020). It is quicker to administer and score, and better suited for use with older adults whose cognitive ability may be compromised.MethodA consecutive cohort of older (≥60 years) community‐dwelling adults (n=187) and hospital inpatients who were referred for a neuropsychological assessment (n=73) were administered the Mini‐Mental Status Examination (MMSE), Frontal Assessment Battery (FAB) and QuickSort (9‐stimuli, which must be sorted by color, shape & number; Total score range = 0‐18; higher scores indicate better cognition). A Cognitively‐Healthy normative subsample (n=115), screened for cognitive and psychological disorders, was formed from the community sample.ResultsThe Cognitively‐Healthy subsample completed the QuickSort within 2‐minutes, 50% had errorless performance, and 95% scored 10 or more. The likelihood of community‐dwelling older adults and inpatients (n=260) being impaired on either the MMSE or FAB, or both, increased by a factor of 3.52 for QuickSort Total scores <10 and reduced by a factor of 0.23 for scores ≥10.ConclusionMost healthy older adults complete the QuickSort quickly and easily. The QuickSort performance of a patient can be compared to their cognitively‐healthy peers in order to estimate the likelihood that they will be impaired on either the MMSE or FAB, or both. The QuickSort can also be customized for use in specific settings. The QuickSort may provide an alternative to lengthier cognitive screens (MMSE and FAB) in settings that have very limited clinical resources.
Applicability of deep neural networks and local binary pattern for the classification of MCI‐C and MCI‐NC
Authors: Bhasin Harsh , Deshwal Vishal 
Published: December 2021

AbstractBackgroundThe classification of Mild Cognitive Impairment (MCI) patients, who convert to Alzheimer’s (MCI‐C) and do not convert to Alzheimer’s (MCI‐NC) is important to understand the progression of the disease. The imaging data, particularly s‐MRI helps to understand the disease by capturing the variation in the gray matter.MethodWe developed a Deep Learning based method to classify MCI‐C and MCI‐NC. For each MRI volume Local Binary Pattern (LBP) was applied on each slice and the features so obtained were concatenated to get the feature vector of the volume. The features were obtained using three methods: creating a histogram having 256 bins, by using the Uniform LBP, and using the Uniform‐Rotation Invariant LBP. This feature set was fed to a Deep Neural Network having two hidden layers and a Softmax layer. Experiments were conducted to find the optimal architecture of the DNN, which gives the best accuracy. Also, a dropout layer was added to prevent overfitting. The results were also compared with the Support Vector Machine. The data used in the experiment was obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI).ResultWe evaluated the model performance using accuracy. It was found that amongst the three variants of LBP, that having 256 bins produced the best results. Also, DNN performed far better as compared to SVM. Amongst the various DNN’s the one having 100 units in the first hidden layer, 50 in the next, and having a dropout of 0.1, gave the best results. The model used Adam optimizer and categorical cross‐entropy. It was also noted that the results obtained using raw volumes were inferior as compared to that obtained using LBP. Table 1 shows the results.ConclusionWe propose a Deep Learning model for classifying MCI‐C and MCI‐NC. The proposed method is capable of finding discriminating features to classify the two sets. It may be the case that LBP is able to infer the difference in the distribution of microstructures in the two classes which helped the DNN to obtain better accuracy as compared to the state of the art.
Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry
Authors: Albright Jack , Ashford Miriam T. , Jin Chengshi , Neuhaus John , Camacho Monica R. , Rabinovici Gil D. , Truran‐Sacrey Diana , Maruff Paul T , Mackin R. Scott , Nosheny Rachel L. , Weiner Mike W. 
Published: December 2021

AbstractBackgroundThis study investigated the extent to which subjective and objective data from an online registry can be analyzed using machine learning methodologies to provide an accurate prediction of the brain amyloid beta (Aß) status of registry participants.MethodWe developed and optimized machine learning models using data from up to 664 participants in the Brain Health Registry. Models were assessed on their ability to predict Aß positivity using the results of positron emission tomography as ground truth.ResultThe optimal feature set included gender, study partner‐assessed Everyday Cognition score, and the Cogstate Brief Battery’s One Card Learning test and resulted in a cross‐validated AUC score of 0.75.ConclusionInclusion of study partner assessments and certain Cogstate Brief Battery scores increases the ability of machine learning models to predict Aß positivity.
Effects of lifestyle on the health, depression, and quality of life of middle‐aged and elderly before and after COVID‐19: Structural equation modeling
Authors: Yang Min Ah , Park Ji‐Hyuk 
Published: December 2021

AbstractBackgroundThe purpose of this study is to identify the effects of the lifestyle (physical activity, activity participation, and nutrition) of middle‐aged and elderly people on health, depression, and quality of life, and to identify changes before and after COVID‐19. In addition, it is intended to establish a structural equation model to confirm the influence coefficients for each path.MethodAmong those aged 55 and older, the study measured lifestyle, subjective health, depression, and quality of life for a total of 327 people. We used SPSS 25 for general characteristics of subjects, descriptive statistical analysis of variables, and AMOS 20 for validation of variables, affirmative factor analysis, and effectiveness analysis on paths.ResultIn the case of physical activity, there were significant differences between the two groups in moderate exercise (p<0.001) and walking (p<0.01) before and after COVID‐19. The results of participation in activities showed significant differences between leisure activities, social activities and education before and after COVID‐19 (p<0.001). For eating habits, significant differences were found in the two observations: carbohydrate (p<0.05) and protein (p<0.05). Comparing the overall mean, there were significant differences between health (p<0.05), depression (p<0.001), and quality of life (p<0.001) before and after COVID‐19. The final model was built through normality test and confirmatory factor analysis, and the fit of the final study model was x²=3.306, GFI=0.902, RMR=0.049, RMSEA=0.059, IFI=0.928, TLI=0.917, CFI=0.928, which was appropriate compared to each criterion, showed significance for each path.ConclusionThrough this research, it was confirmed that lifestyle affects health, depression, and quality of life for middle‐aged elderly people, which is in the same context as prevention‐oriented policies currently in place worldwide. In addition, the results of this study show the importance of a healthy lifestyle, suggesting that lifestyle education for middle and high‐aged people and customized lifestyle interventions for individual lives are needed. Comparisons between the two periods before and after COVID‐19 show that the social isolation caused by COVID‐19 has a negative impact on each factor. Through these results, health care is essential for middle‐aged and elderly people, and measures should be taken to resolve restrictions on participation in activities caused by social isolation.
Gender difference of cerebrospinal fluid ceruloplasmin in mild cognitive impairment
Authors: Wang Lijun , Liu Jun 
Published: December 2021

AbstractBackgroundThe underlying mechanisms of brain oxidative stress and neuroinflammation, an invariant neurodegenerative features that correlate with cognitive function and the progression of Alzheimer’s disease (AD), remains elusive. Ceruloplasmin (Cp) is a protein that intersects these pathways. The role of Cp in AD and its potential use as a biomarker has not been identified. The purpose of the study is to explore the impact of gender on cerebrospinal fluid (CSF) ceruloplasmin concentrations in patients with mild cognitive impairment (MCI).MethodSeventy‐one males and 33 females with MCI from the AD Neuroimaging Initiative (ADNI) were included in the study. We explored the gender discrepancies in CSF ceruloplasmin levels, volumes of hippocampus, entorhinal cortex (EC), fusiform and medial temporal lobe (MTA).ResultThe results showed that CSF ceruloplasmin levels were significantly higher in males compare to females in MCI patients (P = 0.011). No gender differences were found in CSF Aβ42, CSF Tau and CSF P‐tau (P = 0.496, P = 0.096, P = 0.070). Females showed reduced volumes of the EC, fusiform and MTA (P = 0.010, P < 0.001, P < 0.001) than males. However, volumes of the hippocampus between the males and females in MCI did not differ (P = 0.099).ConclusionThese findings suggest that gender discrepancies should be considered in the interpretation of CSF ceruloplasmin when evaluating MCI.