bluuebunny/crossref_metadata_2025_split huggingface dataset:
The latent construct of dementia phenotype: Validation and longitudinal examination in the Sydney Memory and Ageing Study
Authors: Lam Ben CP , Crawford John D , Lipnicki Darren M , Numbers Katya T , Kochan Nicole A , Draper Brian , Trollor Julian N , Brodaty Henry , Sachdev Perminder S 
Published: December 2020

AbstractBackgroundThe latent continuous construct delta (δ) has been proposed as a novel approach to model dementia phenotype using structural equation modelling that reflects the “cognitive correlates of functional status” (Royall & Palmer, 2012. J Neuropsychiatry Clin Neurosci; Royall et al., 2012. J Alzheimers Dis). This δ factor has been demonstrated to be associated with clinically diagnosed dementia status and severity of dementia. However, thus far there are few studies validating the model longitudinally and these are in American samples. To establish the potential research and clinical utility of δ, the current research constructs and validates this latent dementia factor over a 6‐year period in a community sample of Australian older adults.MethodA community‐dwelling sample of Australian older adults without dementia (at baseline) from the Sydney Memory and Ageing Study was used (n = 1037; M
age = 78.65 years; 55% females). Biennially, participants completed a battery of neuropsychological tests measuring performance in four major cognitive domains, and informants rated their functional status on instrumental activities of daily living. Dementia status and severity were established through consensus diagnosis by an expert panel of clinicians and the Clinical Dementia Rating Scale Sum of Boxes (CDR‐SOB), respectively.ResultA latent growth curve model of δ and Spearman’s general intelligence factor (g) built on four waves of cognitive and function data revealed good fit: CFI = 0.97, RMSEA = 0.04, SRMR = 0.06. A significant increase in δ over time was observed, and this latent change in δ (Δδ) was significantly associated with CDR‐SOB at wave 4 after controlling for demographics, APOE*4, and baseline CDR‐SOB. Cox regression revealed a significant association between Δδ and incident dementia. Further, Δδ accurately discriminated diagnosed dementia cases at wave 4 (ROC area under the curve = 0.91, 95% CI [0.88, 0.95]).ConclusionThis study tests and validates the δ framework in Australian older adults by demonstrating that the change in δ over 6 years is associated with dementia risk and prospective severity of dementia. Future research should further test the model using longitudinal data from geographically and ethnoculturally diverse samples.
Spouse‐appraised memory functioning predicts memory decline better than subjective memory complaints in non‐demented older adults
Authors: Bellaali Youssef , Hanseeuw Bernard J. , Woodard John L. , Ivanoiu Adrian 
Published: December 2020

AbstractBackgroundAlzheimer's disease (AD) begins with subtle memory decline, years before dementia onset. The presence of subjective memory complaints (SMC) has been proposed as a marker of preclinical AD. However, recent evidence has demonstrated early and progressive loss of awareness of memory difficulties in non‐demented older adults harboring AD pathology. We investigated the respective contributions of SMC and spouse‐appraised memory functioning (SAM) to predict memory decline in a large cohort of non‐demented older adults.MethodThe Wisconsin Longitudinal Study collected cognitive data from a community‐based cohort of 3607 participants in both 2005 and 2011. The participant and the participant’s spouse were each asked to rate the participant’s memory functioning using a Likert scale. We predicted change in objective episodic memory performance (immediate and delayed recall of 10 words) with models including baseline SMC, baseline SAM, or both SMC and SAM, adjusting for age, sex, and education. We also evaluated an awareness index (SAM minus SMC). We then tested the interaction between APOE4 carrier status and SMC/SAM to evaluate whether the effects were driven by the individuals at‐risk for AD pathology.ResultIn separate models, SMC (Figure 1A: ‐0.081±0.036, p=0.025) and SAM (Figure 1B ‐0.084±0.028, p=0.003) were both associated with memory decline over approximately six years, but the awareness index was not (‐0.028±0.025, p=0.25). When tested in the same model, only SAM (‐0.074±0.028, p=0.009) was associated with memory decline, while SMC was not significant (‐0.061±0.037, p=0.10). The association between SAM and memory decline was stronger in the APOE4 carriers than in the non‐carriers (Figure 2B: APOE‐by‐SAM interaction: F= 6.07; p= 0.002), demonstrating that SAM was particularly predictive for individuals at‐risk for AD pathology. The association between SMC and memory decline was not driven by APOE4 carriers (Figure 2A: APOE‐by‐SMC interaction: F=2.29; p= 0.13).ConclusionSpouse‐appraised memory functioning was more predictive of memory decline than SMC or an awareness index, particularly for APOE4 carriers, who are at increased risk for AD pathology.
Genome‐wide polygenic risk scores for identification of gene therapeutic target
Authors: Kumar Atul , Shoai Maryam , Malarstig Anders , Stomrud Erik , Palmqvist Sebastian , Hardy John , Mattsson Niklas , Hansson Oskar 
Published: December 2020

AbstractBackgroundGenome‐wide association studies show that a broad polygenic architecture, estimated through polygenic risk scoring (PRS), can predict Alzheimer’s disease risk. A detailed analysis of the SNPs involved in a relevant PRS may reveal biological pathways to target for prevention or treatment of AD.MethodA generalized linear regression model (glm) was . The PRS was obtained using a threshold and pruning method, utilizing the IGAP summary statistic (Lambert et al., 2013). A protein‐protein interaction network and pathway analysis were conducted for the set of proteins encoded by the genes carrying the SNPs with the highest AUC.ResultWe fitted 14 models based on different thresholds, demographic information, and APOE genotype. The SNPs that have effect size at a p‐value threshold of 5 × 10−9 had the highest AUC when purely genetic effects were considered. The 62 SNPs involved in this PRS are located on 38 different genes, 13 of which are Long Intergenic Non‐Protein Coding RNAs (LINC). A protein‐protein interaction network of the protein‐coding genes showed a very high degree of interaction between among them (Figure 1). Pathway analysis shows the involvement of the genes in different metabolic pathways, including the immune system (Figure 2).ConclusionOur findings support the notion that a cumulative impact of large combinations of risk alleles is associated with AD. However, the diagnostic accuracy of the PRS was too low for practical diagnostic utility. The findings especially highlight the role of a few genes as contributors to AD risk. Previous studies link the genes like SORL1 and CLU to the regulation of beta‐amyloid formation and tau‐protein kinase activity. Our metabolic pathway analysis also emphasized the involvement of genes in different metabolic pathways. Further analysis of the functional connection between the immune system and the central nervous system, as well as analyses of LINC, may shed more light on druggable targets in AD.
Prevalence and factors associated with probable HIV dementia in an Africa population: A cross sectional study of an HIV/AIDS clinic population
Authors: Thiga Veronica Wanjiku 
Published: December 2020

AbstractBackgroundThe HIV/AIDS infection is common in sub‐Saharan Africa and is associated with psychological and neuro‐ cognitive impairment. These conditions, however, remain largely unrecognized. In this study we aimed to determine the prevalence of probable HIV dementia (PHD) in an HIV clinic population in Uganda and to delineate the factors associated with such impairment in these HIV positive individuals.MethodsSix hundred eighty HIV clinic attendees were surveyed in a cross sectional study. PHD was assessed using the International Dementia Scale (IHDS). Standardized measures were also used to assess clinical, psychological, social and demographic variables. Respondents were aged 18 years and above and did not have severe physical or mental health conditions. Multivariate analysis was conducted to identify associations between PHD and various factors.ResultsThe prevalence of probable HIV dementia was 64.4%. PHD was significantly associated with increasing stress scores and psychosocial impairment but not with age, BMI, CD4 count, use of HAART, or a diagnosis of depression or alcohol dependence.ConclusionThe prevalence of probable HIV dementia in an ambulatory adult HIV positive population in Uganda was 64.4%. Increasing stress scores and psychosocial impairment were significant contributing factors. Clinicians need to be aware of this and to make efforts to identify neuro‐cognitive impairment. Secondly there is need for more studies to better understand the relationship between PHD and stress in HIV populations so as to inform patient care.
Deep versus conventional machine learning for MRI‐based diagnosis and prediction of Alzheimer’s disease
Authors: Bron Esther E. , Venkatraghavan Vikram , Linders Jara , Niessen Wiro J. , Klein Stefan 
Published: December 2020

AbstractBackgroundAccurate diagnosis and prediction of Alzheimer's disease (AD) is important for care planning and clinical trials. Machine learning based on MRI showed promising results for these tasks. While in many medical imaging applications deep neural networks have outperformed conventional approaches, this has not been shown for AD classification. Therefore, this work presents a direct comparison of conventional and deep AD classification.MethodsWe included participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI): 334 AD patients, 520 cognitively normals (CN), 231 mild cognitive impaired (MCI) patients who converted to AD within 3 years (MCIc) and 628 MCI patients who did not convert (MCInc). As input features we considered two MRI‐based images in MNI‐space: raw T1‐weighted images and preprocessed modulated GM maps that encode gray matter density. As conventional classifier, we used a linear support vector machine (SVM). The c‐parameter was optimized with 5‐fold crossvalidation on the training set. The deep classifier was an all convolutional neural network (all‐CNN) that consisted of 7 convolutional blocks and a final softmax classification layer (Fig. 1). A validation set (10%) was used for regularization by early stopping. Classifiers were trained for AD‐CN classification using 20 repetitions of random split (10% test). Confidence intervals (95%CI) on performance measures were computed with the corrected resampled t‐test. Based on AD‐CN results, we selected the best input feature and retrained classifiers on the full AD/CN dataset to evaluate predictive performance (MCIc‐MCInc).ResultsFor AD‐CN classification based on modulated GM maps, the AUC for SVM (0.940; 95%CI: 0.924‐0.955) was similar to that of all‐CNN (0.933; 95%CI: 0.918‐0.948) (Fig. 2). Both with SVM and all‐CNN, classification based on modulated GM maps outperformed classification based on T1w‐images, especially in the case of SVM. Application to MCI conversion prediction (Fig. 3) yielded slightly higher performance for SVM (AUC=0.765) than for all‐CNN (AUC=0.742) (p=0.01 for McNemar’s test).ConclusionDeep and conventional classifiers performed equally well in AD detection. For AD prediction, the conventional classifier yielded slightly higher performance. Both approaches benefitted from the use of modulated GM maps instead of raw T1‐weighted images, while this effect is stronger for the conventional method.
Role of speech therapist in palliative care
Authors: Olivares Claudia A , Tapia Sara E 
Published: December 2020

AbstractBackgroundIn many cases, older adults reach the end of their lives suffering from different health conditions that interfere with their communication, limiting their opportunities to express wishes or wills. The role of the speech therapist in the palliative care team, and how to include them in palliative care health team could optimize the patient's communication with his environment, has not been investigated in Depth. The aim of this research is describe how the speech therapist can contribute to the care of patients in palliative care by optimizing communication skills for greater comfort at the end of life.MethodA bibliographic review was made, without restriction of date, in the Spanish and English languages. There were no restrictions regarding the type of study. All sources included approaches to speech therapy performance in palliative care.ResultsThe evidence related to the role of language and speech therapy in palliative care is not consistent, it establishes certain guidelines to focus attention on maintaining the quality of life, taking into consideration some skills of the discipline that would help optimize communication at the end of life.ConclusionsThe increase of the geriatric population in the country requires professionals better prepared to attend their demands and needs, this implies modifying the task and enhancing the disciplinary skills for the benefit of those who require it. This review gives the first orientations to the language and speech therapist role in palliative care.
Comparing different approaches for operationalizing subjective cognitive decline: Impact on syndromic and biomarker profiles
Authors: Diaz‐Galvan Patricia , Ferreira Daniel , Barroso Jose , Westman Eric 
Published: December 2020

AbstractBackgroundA framework for research on subjective cognitive decline (SCD) was published in 2014, but different SCD operationalization approaches still need to be compared. We compared two hypotheses‐driven and two data‐driven approaches in the same sample of individuals.MethodsNine cognitive complaints were assessed on 399 cognitively healthy individuals from a community‐based cohort. Four SCD operationalization approaches were applied and the resulting groups were characterized using multivariate methods on comprehensive demographic, clinical, cognitive, and neuroimaging data.ResultsTwo main phenotypes were identified: first, an amnestic form associated with an Alzheimer’s Disease (AD) signature pattern of brain atrophy; second, an anomic form mainly related to cerebrovascular pathology. Complaints on other language components also allowed further identifying a subgroup with subclinical impairment in cognition and activities of daily living, as well as with an AD signature pattern of atrophy.ConclusionsThe phenotype of SCD, including syndromic and biomarker profiles, varies depending on the operationalization approach. We discuss how these findings may be used in clinical practice and research.
Investigating associations of an MRI‐based measure of Alzheimer’s disease neuroanatomic risk with incident cognitive impairment and β‐amyloid burden across race and sex in the ARIC cohort
Authors: Casanova Ramon , Hayden Kathleen M. , Barnard Ryan , Anderson Andrea , Hsu Fang‐Chi , Talluri Rajesh , Whitlow Christopher T. , Griswold Michael E , Hughes Timothy M. , Gottesman Rebecca F , Wagenknecht Lynne E. 
Published: December 2020

AbstractBackgroundMRI based biomarkers are of increasing interest due to availability, low cost, and low patient burden compared to other biomarkers. Alzheimer’s disease pattern similarity (AD‐PS) scores, an MRI‐based AD risk measure, have been previously investigated in predominantly white cohorts. The Atherosclerosis Risk in Communities (ARIC) study provides an opportunity to further evaluate the AD‐PS score in a diverse setting.MethodThe ARIC study has collected cognitive data and MRI scans at visit 5 (2011‐2013) and visit 6 (2015‐2017). Participants were aged 76.0 (5.3) yrs at visit 5 and included both blacks and whites. MRI scans from the ARIC and Alzheimer's Disease Neuroimaging Initiative (ADNI) studies were aligned and segmented using the Advanced Normalization Toolbox software. A high‐dimensional classifier was trained using gray matter images (N = 598) from the ADNI study. Then ARIC MRI images were provided as input to the classifier to obtain the scores. Incident cognitive impairment (ICI) analyses were based on individuals diagnosed as cognitively normal (CN) (N = 868) at visit 5. Logistic regression considered ICI (either a diagnosis of mild cognitive impairment or dementia at visit 6) as the outcome. In PET analyses logistic regression was used to investigate associations of the AD‐PS scores with cross‐sectional β‐amyloid lesion burden (global cortical standardized uptake value ratio dichotomized at 1.2) derived from F18‐Florbetapir PET images available in a subset (N = 330, MCI=89). All analyses were adjusted for age, race, sex, education, site, and intracranial volume. The relevant variables were standardized. Analyses were further stratified by race and sex.ResultAmong participants who were CN at visit 5, 125 were diagnosed with MCI and 28 with dementia at visit 6. The AD‐PS scores were significantly associated with ICI in: the full sample, whites, blacks, males and females (Table 1). The scores were also significantly associated with β‐amyloid burden in: the full sample, blacks and males.ConclusionAD‐PS scores, an MRI based biomarker of AD, were associated with ICI and β‐amyloid burden derived from PET in the ARIC study. Significant associations were found in the overall sample, as well as by race and sex.
Association of plasma EFEMP1 with brain aging and dementia
Authors: McGrath Emer R , Himali Jayandra J , Levy Daniel , Yang Qiong , DeCarli Charles , Courchesne Paul , Satizabal Claudia L , Finney Rebecca , Vasan Ramachandran S , Beiser Alexa S , Seshadri Sudha 
Published: December 2020

AbstractBackgroundBiological pathways underlying the association between white matter hyperintensities (WMH) and Alzheimer’s disease (AD) dementia remain poorly understood. Epidermal growth factor containing fibulin extracellular matrix protein‐1 (EFEMP1) has been associated with increased WMH burden and disorders of premature aging. However, it is unknown if elevated circulating EFEMP1 is associated with clinical dementia. We determined the association between plasma EFEMP1 levels and incident dementia and Alzheimer’s disease (AD) dementia in a community‐based sample of cognitively healthy individuals.MethodPlasma EFEMP1 levels were measured in 1597 [53% women, mean age 68.7 (SD 5.7) yr] Framingham Heart Study Offspring cohort participants who were free of dementia at examination cycle seven (1998‐2001). We related plasma EFEMP1 levels to risk of incident dementia and Alzheimer’s disease (AD) dementia. Structural MRI brain measures and neurocognitive test performance were included as secondary outcomes.ResultDuring a median 11.8 [Q1, Q3: 7.1, 13.3] year follow‐up, 131 participants developed dementia and 98 were diagnosed with AD dementia. On Cox proportional‐hazards analysis adjusting for vascular risk factors and ApoE4 carrier status, the highest quintile of plasma EFEMP1, compared to the bottom four quintiles, was associated with an almost 80% increased risk of time to incident all‐cause dementia (HR 1.77, 95% CI 1.18‐2.64) and AD dementia (HR 1.76, 95% CI 1.11‐2.81). The highest quintile of EFEMP1, compared to the bottom four quintiles, was also associated with lower total brain volume (SE, ‐0.28±0.11, p=0.01) and hippocampal volume (‐0.006±0.003, p=0.04) but not WMH burden. Higher circulating EFEMP1 concentrations were associated with impairment in abstract reasoning (Similarities test, ‐0.18±0.08, p=0.018 per standard deviation increment in EFEMP1).ConclusionElevated circulating EFEMP1 levels are associated with an increased risk of incident dementia and AD dementia as well as lower brain volumes and impaired cognitive performance. EFEMP1 may play an important biological role in the development of AD and all‐cause dementia mediated through nonvascular pathways (e.g. microglial activation or via regulatory effects on metalloproteases), although additional studies are warranted to replicate our findings.
Type 2 diabetes and cardiovascular disease increase the risk of cognitive impairment and accelerate the progression to dementia in Swedish older adults
Authors: Dove Abigail , Shang Ying , Grande Giulia , Laukka Erika J , Fratiglioni Laura , Xu Weili , Marseglia Anna 
Published: December 2020

AbstractBackgroundDespite the well‐established link between type 2 diabetes and dementia, its impact on the prodromal dementia phase remains controversial, as does the impact of comorbid cardiovascular disease (CVD). In this study, we assessed the impact of diabetes and CVD on the development of cognitive impairment no dementia (CIND) and its progression to dementia.MethodsIn the Swedish National Study on Aging and Care‐Kungsholmen (SNAC‐K), a cohort of cognitively‐intact individuals (n=1840) and a cohort of individuals with CIND (n=682) aged ≥60 years were followed over 15 years. At baseline and each follow‐up (every 3 or 6 years), a neuropsychological test battery was administered to assess five cognitive domains (episodic memory, processing speed, executive function, verbal fluency, visuospatial abilities). CIND was defined as having no dementia and cognitive performance ≥1.5 SDs below age group‐specific means in at least one domain. Dementia was diagnosed according to international criteria. Diabetes (controlled and uncontrolled: HbA1c <7.5% vs. ≥7.5%) was assessed based on medical history, clinical records, and glycated hemoglobin. CVD (atrial fibrillation, heart failure, ischemic heart disease, cardiac valve diseases, and bradycardias) was ascertained through medical examinations and medical records. Data were analyzed with multivariable Cox regression models.ResultsAt baseline, 135 (7%) participants in the cognitively‐intact cohort and 85 (12%) in the CIND cohort had diabetes. During follow‐up (mean 9.2 ± 3.1 years [2.2–15.6 years]), 544 (30%) participants in the cognitively‐intact cohort developed CIND. Diabetes was associated with a 35% higher risk of CIND (HR 1.35, 95% CI: 0.98‐1.88) compared to the diabetes‐free group. This risk rose to 75% in people with comorbid diabetes and CVD (HR 1.75, 95% CI: 1.01‐3.04) and was doubled in people with uncontrolled diabetes (HR 1.97, 95% CI: 1.12‐3.49). In the CIND cohort, 151 (22%) individuals progressed to dementia during follow‐up. Participants with uncontrolled diabetes had triple the risk of progressing to dementia (HR 3.00, 95% CI: 1.26‐7.13) vs. the diabetes‐free group, and the HR of dementia was 4.36 (95% CI: 1.51‐12.59) in individuals with uncontrolled diabetes and comorbid CVD.ConclusionsUncontrolled diabetes increases the risk of cognitive impairment and accelerates its progression to dementia, particularly in older adults with comorbid CVD.