bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive reserve: Resting‐state functional connectivity moderates the association between white matter hyperintensity and executive function in older adults with subcortical ischemic vascular cognitive impairment
Authors: Gu Yi , Hsu Chun Liang , Silva Nárlon Cássio Boa Sorte , Tam Roger , Alkeridy Walid Ahmed , Lam Kevin , Liu‐Ambrose Teresa 
Published: January 2025

AbstractBackgroundSubcortical ischemic vascular cognitive impairment (SIVCI) is the most common form of vascular cognitive impairment. White matter hyperintensities (WMH) are hallmarks of SIVCI and are associated with impaired executive function. Cognitive reserve is a property of the brain that moderates an individual’s ability to maintain cognitive performance given brain injury or pathology. The neural correlates of cognitive reserve remain elusive; however, resting‐state functional connectivity (rs‐FC) in networks such as the fronto‐executive network (FEN), fronto‐parietal network (FPN) and default mode network (DMN) have been proposed as potential candidates. The role of these networks in mitigating the impact of SIVCI‐related pathology on cognition remains unclear. Therefore, we investigated whether intra‐network rs‐FC in the FEN, FPN, and DMN moderated the negative impact of WMH on executive function in older adults living with SIVCI.MethodWe conducted a cross‐sectional study among 38 community‐dwelling older adults with SIVCI. Executive function was assessed by the Trail Making Test (B‐A). WMH volume was quantified by T2‐weighted and proton density‐weighted structural magnetic resonance imaging (MRI) using a seed‐based method and log‐transformed before analyses. The rs‐FC was computed via a 5‐min resting‐state functional MRI scan with priori‐selected region‐of‐interest masks. A moderation analysis was conducted to assess whether intra‐network rs‐FC in the FEN, FPN and DMN moderated the association between WMH volume and executive function, adjusting for age, sex, and Montreal Cognitive Assessment (MoCA) score.ResultThe participants had a mean age of 74.1 years (SD = 5.5) and 71% were female; the mean MoCA score was 21.29 (SD = 2.66). Compared with individuals with lower intra‐network rs‐FC of DMN, those with greater intra‐network rs‐FC of DMN (non‐standardized b = ‐2913.64, p = 0.000) showed better Trail Making Test performance under greater WMH load. In contrast, individuals with lower intra‐network connectivity of FEN (b = 2050.34, p = 0.007) and FPN (b = 1790.81, p = 0.005) had better Trail Making Test performance under greater WMH load.ConclusionThe strength of intra‐network connectivity in the FEN, FPN, and DMN moderates the impact of WMH on executive function in older adults with SIVCI. The results shed light on the potential neural basis of cognitive reserve against WMH.
Combining blood‐based biomarkers and accessible measures for the prognosis of cognitive decline in older primary care patients
Authors: Kleineidam Luca , Oezdemir Selçuk , Martino‐Adami Pamela , Chatterjee Madhurima , Pentzek Michael , Weyerer Siegfried , Bickel Horst , Wiese Birgitt , Riedel‐Heller Steffi G. , Scherer Martin , Zetterberg Henrik , Blennow Kaj , Jeromin Andreas , Wagner Michael , Ramirez Alfredo , Schneider Anja 
Published: January 2025

AbstractBackgroundCombining plasma phosphorylated Tau 217 (pTau217), with cognitive assessments allows for predicting incident dementia in mild cognitive impairment (MCI). However, the performance of this approach in primary care as well as the added value of other blood‐based biomarkers (BBM) in this setting is unclear.MethodsWe examined 833 older primary care patients from the AgeCoDe/AgeQualiDe study (median age=83). Plasma ALZpath pTau217 and other blood‐based biomarkers (BBM; pTau181, GFAP, NfL, Abeta‐42/40) were measured using single‐molecule arrays. Subjective cognitive decline (SCD) and the Mini‐Mental State Examination (MMSE) were assessed at baseline. We evaluated the performance of BBM, MMSE, and SCD reports for predicting the development of any cognitive impairment (MCI or dementia) or conversion to dementia at 3.5 and 7 years of follow‐up using time‐dependent ROC analysis with death as competing risk.ResultsPlasma pTau217 improved the prognosis of developing any cognitive impairment at follow‐up beyond age, sex, and renal function (base model; Figure 1) and showed a high prognostic value at 7 years of follow‐up (p<0.001, AUC=0.809; 3.5 years prognosis: p<0.001; AUC=0.767). Adding SCD and MMSE to the model provided only a small improvement in short‐term prediction (3.5 years prognosis: p=0.002; AUC=0.785) while no significant improvements were observed by considering other BBM.For predicting incident dementia, pTau217 also increased the prognostic value beyond the base model (3.5 years: p=0.044, AUC=0.689; 7 years: p=0.002; AUC=0.697). However, this increase was smaller as compared to the prognosis of any cognitive impairment since individuals developing MCI but not dementia showed similar pTau217 levels at baseline. Furthermore, considering MMSE and SCD reports resulted in a considerable increase in prognostic value beyond pTau217 (3.5 years: p<0.001, AUC=0.791; 7 years: p=0.002; AUC=0.749). Plasma pTau217 in turn improved the long‐term prediction beyond SCD reports and MMSE (p<0.001, AUC=0.749 vs 0.724). Again, other BBM did not increase the prognostic value.ConclusionsIn our sample, pTau217 showed a high ability to discriminate between older primary care patients who will stay cognitively stable over seven years from patients developing any cognitive impairment, in contrast to other BBM. Assessments of SCD and cognition can further improve the identification of patients at increased short‐term risk for dementia.
The role of biofluid markers in predicting near‐term cognitive impairment
Authors: Yakoub Yara , Gonzalez‐Ortiz Fernando , Ashton Nicholas J. , Karikari Thomas K , Strikwerda‐Brown Cherie , St‐Onge Frédéric , Ourry Valentin , Schöll Michael , Geddes Maiya R. , Ducharme Simon , Rosa‐Neto Pedro , Soucy Jean‐Paul , Breitner John C.S. , Zetterberg Henrik , Blennow Kaj , Poirier Judes , Villeneuve Sylvia ,   PREVENT‐AD Research Group
Published: January 2025

AbstractBackgroundPET biomarkers have proven valuable for identifying cognitively unimpaired (CU) individuals at‐risk of near‐term clinical progression. Given the increasing interest in plasma biomarkers to detect Alzheimer’s pathology, we assessed levels of amyloid (Aβ42/40) and tau (p‐tau217 and p‐tau181) biomarkers in plasma (A+T+plasma) in CU individuals as predictors of clinical progression to mild cognitive impairment (MCI). We then repeated these analyses using cerebrospinal fluid (CSF) and PET biomarkers.MethodWe studied 218 participants from the PREVENT‐AD cohort with cognitive follow‐up (mean 5.34 years, range 1–10 years) and plasma biomarkers available while CU. Cognition was assessed annually using the RBANS. Plasma biomarkers were measured using IP‐MS for Aβ42/40 and in‐house single molecular arrays for p‐tau217 and p‐tau181. An overlapping 71 participants had Aβ42/40 (Mesoscale Discovery assay) and p‐tau181 (Innotest immunoassay) CSF data available, and 135 participants had Aβ (18F‐NAV4694) and tau (18F‐florbetapir) PET data. We also performed receiver operating characteristic (ROC) curves to compare the performance of plasma (Aβ42/40 and p‐tau217; Aβ42/40 and p‐tau181), CSF (Aβ42/40 and p‐tau181) or PET (Aβ‐ and tau‐PET) biomarkers in predicting progression to MCI. We examined an additional model including only Aβ‐PET, given the importance of this technique as a stand‐alone marker for recruitment in anti‐Aβ trials.ResultThe proportion who progressed from CU to MCI was 62% in individuals with A+T+plasma217; and 41% with A+T+plasma181; 56% with A+T+CSF181 and 100% with A+T+PET (Figure 1). Cox proportional hazard models indicated a faster progression rate in all A+T+ groups compared with their matched A‐T‐ biomarker groups (Figure 2). Considering longitudinal RBANS scores, all A+T+ groups declined faster than the other groups, except for the plasma181 group. Finally, the PET (Aβ and tau‐PET) and CSF models were superior to the plasma or Aβ‐PET alone in identifying progressors, with no meaningful difference between the Aβ‐PET and the biofluid models (Figure 3).ConclusionCU individuals with A+T+ based on plasma biomarkers are at increased risk of cognitive decline and clinical progression. Nevertheless, the proportion who progressed to MCI in individuals classified with plasma was lower than that found using PET. Thus, the latter should remain the gold standard to identify presymptomatic pathological changes.
Subjective Memory and its Association with Cognitive Performance among Older Adults: Findings from a Cohort Study in Lebanon
Authors: Chaaya Monique , Abdulrahim Sawsan , Elbejjani Martine , McCall Stephen , Sammak Aya El , Nassif Alexandra Abi , Ngwa CH Henry , de Leon Carlos Mendes 
Published: January 2025

AbstractBackgroundRapid aging in low‐to‐middle income countries (LMICs) is expected to lead to exponential growth in dementia. As standard cognitive tools can be time‐consuming and cause fatigue for older adults, health professionals in primary care settings can utilize efficient measures to assess their cognitive performance. To date, there are still inconsistencies in the correlation between subjective memory complaints and cognitive impairment. Moreover, the validity of using a single‐item subjective memory is still not established. The aim of this study is to assess whether a one‐item measure of subjective memory is correlated with objective measures of cognitive performance among older adults in LMICs.MethodLebanon Study on Aging and Health (LSAHA) is an ongoing population‐based cohort study of older adults aged 60 years or older, where 1,502 older adults were recruited from a rural district in Lebanon between October to December 2023. Cognitive performance was assessed using four tools: the Cognitive Domain in the ‘Community Screening Instrument for Dementia (CSI‐D)’ the ‘CERAD 10‐word’ immediate and delayed recall and the Informant Questionnaire on Cognitive Decline among the Elderly (IQCODE). Subjective memory was assessed by a single item and responses were categorized as: “good/very good/excellent” and “fair/poor.” Baseline data was analyzed using adjusted linear and logistic regression models to assess the association between subjective memory and cognitive performance measures.ResultOf the participants that responded to subjective memory and cognitive tools (n = 1,245), more than half (56.3%) reported fair/poor subjective memory. Adjusting for age, gender, and educational level, subjective fair/poor memory recall was significantly associated with higher odds of cognitive impairment based on CSID (OR:1.82 95%CI:1.42‐2.34) and IQCODE (OR:1.78 95%CI:1.33‐2.37) and a lower number of immediate (β:‐1.70 95%CI:‐2.19‐ ‐1.20) or delayed (β:‐0.65 95%CI:‐0.85‐ ‐0.44) word recall.ConclusionThis study’s findings suggest that a single‐item subjective memory assessment could be used by healthcare providers to identify older adults who may require further evaluation for cognitive impairment, similar to how self‐rated health has been a good marker for mortality and other health conditions. The results of this study warrant further research on this measure across different populations, comparing it with other validated screening tools.
Modifiable and non‐modifiable disparity‐related predictors of cognitive scores in a population‐based cohort: the ELSI‐Brazil
Authors: Borelli Wyllians Vendramini , Da Ros Lucas Uglione , Aguzzoli Cristiano Schaffer , de Bastiani Marco Antônio , Suemoto Claudia Kimie , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundSocial and health‐related disparity factors are important predictors of brain health in low and middle‐income countries (LMIC). Social predictors of cognition have a higher impact on brain health among LMICs than classic demographic factors, such as age and sex. This study aimed to evaluate the impact of modifiable and non‐modifiable social and health‐related factors on cognition in a Brazilian population‐based cohort.MethodWe selected 9,412 individuals from the ELSI‐Brazil cohort, which is a population‐based study conducted with a similar design as the Health and Retirement Study. Complex sample design stratified and clustered distinct geographical regions according to their representation nationally. We included health‐related disparity factors (hypertension, diabetes, cardiovascular disease, and falls), as well as social determinants of health (piped water, access to healthcare, private health coverage, income, food insecurity, and education). Non‐modifiable factors were also retrieved (age, sex, race and region). We evaluated cognition using a global composite of orientation, animal fluency, and memory recall scores. A linear regression model was conducted to identify and stratify predictors of global cognitive scores (R2 adjusted = 0.336).ResultWe included 5,432 individuals above 60 years of age in this analysis (mean age 70.3±7.97 yo). The regression model identified that the most important modifiable predictor of cognition was depression (ß = ‐0.14±0.06, p < 0.001), followed by physical activity (ß = 0.12±0.03, p < 0.001), and private health coverage (ß = 0.09±0.06, p = 0.001). Among non‐modifiable predictors of cognition, northeast region dwelling was the most important predictor (ß = ‐0.16±0.05, p < 0.001), following residing in the north region (ß = ‐0.14±0.10, p = 0.006), and brown race (ß = ‐0.1±0.05, p < 0.001). No health‐related factor reached significance.ConclusionOverall, modifiable and non‐modifiable social‐related disparity factors had a significant impact on cognition in this study. Modifiable factors should be addressed in public health policies, while non‐modifiable risk factors may provide insights on compensatory strategies to overcome their negative effects on brain health. Further studies may expand this investigation to other LMIC.
The influence of amyloid on tau deposition in clinically obese participants
Authors: Yu Yang Yang , Nowell Joseph , Edison Paul 
Published: January 2025

AbstractBackgroundObesity is a prevalent comorbid condition that doubles the risk of Alzheimer’s disease. The proposed mechanisms underlying neuronal damage involve chronic low‐grade inflammation, the production of reactive oxidative species, and altered brain glucose metabolism. In Alzheimer’s disease, amyloid is thought to influence tau deposition and glucose metabolism. We explore the impact of amyloid on tau pathology in individuals with obesity.MethodWe processed 267 PET scans (18F‐flortaucipir) from 267 participants with a BMI ≥30 (n=116) and those without obesity (n=151) in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset to compare tau pathology. Amyloid status was determined from the ADNI database using predefined cerebellum positivity thresholds (SUVR of 1.08 for 18Florbetaben and 1.11 for 18florbetapir). Independent t‐tests and multivariate analysis were employed in subjects with obesity versus those without, in global cortex and specific regions of interests in relation to Alzheimer’s. Amyloid positive and negative subjects were evaluated separately within different cognitive subgroups, namely those with mild cognitive impaired and those who were cognitively normal.ResultIndependent t‐tests were conducted in the obese group with normal cognition and negative amyloid status, revealing higher tau uptake in the parietal lobe and anterior cingulate compared to non‐obese subjects. Multivariate analysis, controlling for age and APOE‐ε4, further confirmed the significance of these findings in these brain regions. This pattern was absent in obese subjects with positive amyloid status and in those with mild cognitive impairment, regardless of amyloid status being positive or negative.ConclusionTauopathy manifests in the obese brain independently of amyloid deposition, even preceding cognitive impairment. These findings suggest that amyloid‐targeting therapies may be less effective in obese patients.
Audiometric hearing level in individuals with SCD, MCI and mild dementia
Authors: Rattanabannakit Chatchawan , Sirikuntharamas Poramad , Suwanwech Triphoom , Prakairungthong Sarun , Nanthasi Witsarut , Senanarong Vorapun 
Published: January 2025

AbstractBackgroundHearing impairment is identified as a risk factor for dementia. This study aimed to investigate audiometric hearing level in individuals across the clinical spectrum of cognitive impairment, from normal cognition (NC) to mild dementia, encompassing subjective cognitive decline (SCD) and mild cognitive impairment (MCI).Method135 participants were included in this study. There were 33 NC participants, 36 participants with SCD, 34 participants with MCI, and 33 participants with mild dementia. Demographic data was collected, along with the Montreal Cognitive Assessment (MoCA), and the Cognitive Change Index to capture subjective cognitive complaints from patients themselves (CCI‐S) and their informants (CCI‐I). All participants underwent tonal audiometry to measure the best air‐conduction and bone‐conduction hearing threshold, speech recognition test (SRT) and word recognition score (WRS). Association of audiometric data and cognitive function and their differences between diagnostic groups were analyzed.ResultThe median age of all participants was 61.5 (IQR = 19) years, 77.2% were female, median years of education was 14.5 (IQR = 7) years. There were significant differences in age, education, and visual acuity among groups (all p<0.001) (Table). Air‐conduction and bone‐conduction hearing thresholds demonstrated significant differences between groups (all p<0.001), which the worst performance observed in the mild dementia group (p<0.001), even after controlling for age and education (p = 0.013). 63.2% of all participants were defined as having hearing impairment according to WHO criteria, peaking at 93.94% in mild dementia patients. Individuals with moderate hearing impairment demonstrated lower MoCA score and higher CCI‐I scores, compared to those with mild or no hearing impairment. The higher air‐conduction, bone‐conduction hearing threshold, SRT, WRS were significantly correlated with the lower score of MoCA (r = ‐0.47 to ‐0.36, all p<0.001) and a higher score of CCI‐I (r = 0.31 to 0.39, all p<0.001), but not the CCI‐S. However, these associations became insignificant after controlling for age (all p>0.05).ConclusionOur study indicates a link between diminishing audiometric hearing levels and a higher degree of objective cognitive decline, along with an increased level of informant perception regarding individuals' cognitive deficits. Not related to age or education, individuals with mild dementia display significantly worse hearing than those without.
Assessing a Digital Lifestyle Intervention to Reduce Dementia Risk in Older Adults
Authors: Bunyan Maria , Irving Jessica , Barnett Jennifer H , Kawadler Jamie , Bauermeister Sarah , Vassilev Philip , Gallacher John , Koychev Ivan 
Published: January 2025

AbstractBackgroundAn estimated ∼40% of dementia cases are due to modifiable risk factors which can be targeted in lifestyle interventions. Effective interventions employ face‐to‐face delivery, making them resource‐intensive and burdensome. Digital interventions offer scalability, accessibility and cost‐effectiveness. Engagement and efficacy of digital interventions are unknown, as is whether the ‘human component’ of these interventions must be retained.MethodThe Five Lives app is a digital health solution that combines a CE‐marked dementia risk assessment with a digital coaching programme (DC) to facilitate behaviour changes which could lead to eventual reduced dementia risk. Three groups were compared: DC‐only, DC and access to brief 1‐to‐1 virtual clinician services (DC+VC) and no intervention (control). The study spanned 12 weeks and participants (n = 154) were aged 50‐69 with normal cognition. A lifestyle score was conducted at baseline and exit, which scores participants on behaviour relating to sleep, physical activity, diet, stress & mood and mental stimulation. Engagement was measured as the total number of app activities (brain games, articles, quizzes and lifestyle log) completed during the intervention period.ResultParticipant engagement was high (mean participant activities = 35/week). There was a significantly greater change in lifestyle score between intervention group (DC‐only and DC+VC pooled) and control (F(1,81) = 3.10, p = 0.049), and a trend for significance for a greater change in DC‐only versus control (F(1,24) = 3.96, p = 0.058). The change in lifestyle score between DC‐only and DC+VC was not significant, nor was the difference in app engagement. Total engagement was not predictive of lifestyle score change.ConclusionParticipant engagement indicates the intervention is feasible in older adults. Results suggest the Five Lives app is a promising tool to facilitate behaviour change to potentially reduce dementia risk, and the VC does not provide significant additional benefits. This study provides initial data to warrant further development of DC interventions to reduce dementia risk. Future analyses should investigate which participants respond best to the intervention, barriers to change, and how engagement interplays with sustained dementia‐targeted lifestyle change.
‘Diet’ deep canonical correlation analysis for high‐dimensional genetics study of brain imaging phenotypes in Alzheimer’s disease
Authors: Yang Shu , Wang Austin , Bao Jingxuan , Mu Shizhuo , Feng Yanbo , Wen Zixuan , Baik Jae Young , Wen Junhao , Hou Bojian , Wang Rongguang , Huang Heng , Saykin Andrew J. , Thompson Paul M. , Davatzikos Christos , Shen Li ,   for the ADNI and AI4AD
Published: January 2025

AbstractBackgroundUnderstanding the relationship between genetic variations and brain imaging phenotypes is an important issue in Alzheimer's disease (AD) research. As an alternative to GWAS univariate analyses, canonical correlation analysis (CCA) and its deep learning extension (DCCA) are widely used to identify associations between multiple genetic variants such as SNPs and multiple imaging traits such as brain ROIs from PET/MRI. However, with the recent availability of numerous genetic variants from genotyping and whole genome sequencing data for AD, these approaches often suffer from severe overfitting when dealing with ‘fat’ genetics data, e.g. large numbers of SNPs with much smaller numbers of samples.MethodsHere, we propose to tackle the challenge by integrating an efficient model parameterization approach from Mila’s Diet Network architecture into DCCA to handle high dimensional SNP data in AD imaging‐genetics study (Figure 1). The new method, DietDCCA, was applied to nine datasets derived from 955 subjects in the ADNI data. Each dataset contains 68 FreeSurfer cortical ROIs from the florbetapir (AV45) PET imaging and varied numbers of SNPs from 810 to 11,938 based on different significance thresholds derived from previous studies.ResultsFirstly, we compared our DietDCCA with DCCA on each of the nine datasets to demonstrate the improvement on test correlations (Figure 2). DietDCCA outperformed DCCA by a large margin on all datasets even when the SNPs are as many as ∼10k. Next, we sought to verify if the detected correlations were contributed by meaningful SNPs and extracted the SNP feature that has the largest weight in each neuron of the diet net layer (Figure 3). DietDCCA successfully selected the APOE4 SNP (rs429358) for most cases and also picked out SNPs in other genes (ABCA7, APOC2, CLPTM1, NECTIN2) that were previously reported to associate with AD.ConclusionsWe introduced a novel method, DietDCCA, to handle high‐dimensional SNP features in AD imaging‐genetics study. The initial investigation of DietDCCA on the ADNI data showed promises in detecting correlation signals with AV45 ROIs from biologically meaningful SNPs. The study supplies a novel and effective tool to study the genetic basis of AD imaging phenotypes for future analyses.