bluuebunny/crossref_metadata_2025 huggingface dataset:
In vivo amyloid progression in healthy middle‐aged to older people at risk of Alzheimer’s disease
Authors: Levin Fedor , Jelistratova Irina , Betthauser Tobey J. , Johnson Sterling C. , Teipel Stefan J. , Grothe Michel J.
Published: December 2020

Background

Previous studies applied in‐vivo amyloid staging to amyloid‐sensitive PET scans of healthy older people as well as patients with Alzheimer’s disease (AD) dementia or mild cognitive impairment to characterize stages of amyloid deposition. We adapted this approach to a sample of healthy middle‐aged to older participants at elevated risk for AD due to parental history of AD dementia.

Method

We analyzed 11C‐PiB‐PET scans of 220 participants enrolled in the Wisconsin Registry for Alzheimer’s Prevention (WRAP) (mean age = 61.4y, range: 46‐76y). Distribution volume ratio (DVR) maps were calculated from the dynamic PIB‐PET acquisitions and corrected for partial volume effects. DVR values were extracted from 52 cortical and subcortical regions defined in the Harvard‐Oxford atlas and were used together with global mean DVR values in two‐dimensional Gaussian Mixture Modeling to establish regional thresholds for amyloid‐positivity. Resampled regional frequencies of amyloid‐positivity across participants were used to estimate a four‐stage model of regional amyloid accumulation. We staged individual DVR maps, and assessed the associations between amyloid stage and episodic memory (delayed wordlist recall) and executive function performance (TMT‐B) with Spearman correlation.

Result

According to the amyloid progression model, stage I involved the anterior and posterior cingulate as well as lateral temporal cortex; stage II had more extensive frontal and temporo‐parietal involvement; stage III proceeded into occipito‐parietal cortical regions and the hippocampus; stage IV extended to the occipital pole, pre‐ and postcentral gyri, and subcortical structures (Figure 1). Out of 220 participants, 36 (16%) were assigned to one of the four amyloid stages, and two cases (1%) deviated from the hierarchical pattern of amyloid accumulation. Higher amyloid stages (I‐IV) correlated with lower executive function (rho = 0.35, p = 0.043), but not with lower episodic memory performance (rho = 0.13, p = 0.48).

Conclusion

The estimated 11C‐PiB‐PET‐based amyloid staging model is largely consistent with recently reported amyloid staging models for [F18]‐based amyloid‐PET scans. In this relatively young sample of healthy participants at elevated risk of AD, advanced amyloid stages were rare and not consistently linked to decreased cognitive performance. In future work we will assess whether the derived amyloid stages translate into a stage‐proportional risk of longitudinal cognitive decline in this population.
MEG detects abnormal hippocampal activity in amyloid‐positive MCI
Authors: Luppi Janne , Schoonhoven Deborah N , van Nifterick Anne M , Arjan Hillebrand , Gouw Alida A , Scheltens Philip , Stam Cornelis J , de Haan Willem
Published: December 2020

Background

Early Alzheimer’s disease (AD) is characterized by pathological hippocampal hyperactivity1,2. Non‐invasive detection of hippocampal hyperactivity is relevant for diagnostic and therapeutic purposes, but no reliable method is available. We tested magneto‐encephalographical (MEG) detection of hippocampal activity, hypothesizing that in amyloid‐positive MCI patients resting‐state hippocampal activity would be higher than in both controls and AD patients.

Method

We used resting‐state MEG data from 18 mild/moderate AD patients, 18 amyloid‐positive (CSF) amnestic MCI patients, and 18 persons with subjective cognitive decline (SCD). MEG source space signals were reconstructed for 80 AAL regions using beamforming3. We obtained 20 non‐selected, eyes‐closed, 13‐second epochs per person. Global spectral power group differences were identified for common frequency bands using ANOVA and t‐tests. Classification was tested with ROC curves.

Result

Peak frequency was similar in SCD and MCI groups, but lower in AD patients (P<0.001). In MCI and AD, hippocampal total power increased, with a significant rise in the right hippocampus in MCI (p<0.01). In MCI, this was mainly driven by high relative lower alpha (8‐10 Hz) power, significant only in the right hippocampus (P<0.01). Relative gamma (30‐45 Hz) power was lowest in the MCI patient group, hippocampal as well as overall (p<0.01). Classification between MCI and SCD was most accurate using right hippocampal gamma power (Area under the curve = 0.821).

Conclusion

Resting‐state MEG detects abnormal hippocampal activity in preclinical AD patients. This may be a macroscale 'signature' of underlying neuronal hyperactivity1,4. Relevant findings in these subcortical regions and in the gamma frequency band show the added value of MEG compared to EEG and fMRI. The present approach may facilitate diagnostic and therapeutic strategies. References: (1) Canter ea. (2016). The road to restoring neural circuits for the treatment of Alzheimer's disease. Nature, 539(7628), 187; (2) Palop & Mucke (2016). Network abnormalities and interneuron dysfunction in Alzheimer disease. Nature Reviews Neuroscience, 17(12), 777; (3) López, ea. (2017). MEG beamformer‐based reconstructions of functional networks in mild cognitive impairment. Frontiers in aging neuroscience, 9, 107; (4) Busche & Konnerth (2016). Impairments of neural circuit function in Alzheimer's disease. Phil Trans Royal Soc B: Biological Sciences, 371(1700), 20150429.
Does an advanced statistical technique perform better than a simple technique for dementia prediction?
Authors: Goerdten Jantje , Carriere Isabelle , Terrera Graciela Muniz
Published: December 2020

Background

Cox regression models (CM) employ two strong assumptions: the proportional hazards (PH) and the log‐linearity (LL) of covariates. These assumptions might not hold for all predictor variables, which in turn can lead to biased results. (Abrahamowicz et al., 1997; Ritchie et al., 2016). Generalised Cox regression models (GCM) enable to independently test and relax the assumptions of CM (Abrahamowicz & MacKenzie, 2007).

Method

Data is used from the Survey of Health, Ageing and Retirement in Europe (SHARE), which includes around 140,000 individuals aged 50 or older followed over seven waves. Data from The Aging, Demographics, and Memory Study (ADAMS) is used for external validation. CM and GCM are used to estimate dementia risk.

Result

None of the predictor included in the analyses fulfils the assumptions of Cox regression. The pseudo R2 is 0.06 (95% CI: 0.047, 0.062; CM) and 0.493 (95% CI: 0.460, 0.506; GCM). The likelihood ratio test results in a p‐value of <0.001. Both models predict dementia moderately well (10‐year risk: 0.737; 95% CI: 0.695, 0.783; CM and 0.746; 95% CI: 0.711, 0.790; GCM).

Conclusion

The GCM performs significantly better than the CM in modelling dementia risk. However, this approach has also disadvantages: larger sample needed, only visual examination of effects, long computational time possible. Yet, the generalised Cox regression is an interesting extension of the Cox regression. The option to relax and independently test the assumptions is especially appealing when including continuous variables. References: (1) Abrahamowicz, M., du Berger, R., & Grover, S. A. (1997). Flexible modeling of the effects of serum cholesterol on coronary heart disease mortality. Am J Epidemiol, 145(8), 714‐729. (2) Abrahamowicz, M., & MacKenzie, T. A. (2007). Joint estimation of time‐dependent and non‐linear effects of continuous covariates on survival. Stat Med, 26(2), 392‐408. doi:10.1002/sim.2519. (3) Ritchie, K., Carrière, I., Berr, C., Amieva, H., Dartigues, J.‐F., Ancelin, M.‐L., & Ritchie, C. W. (2016). The clinical picture of Alzheimer's disease in the decade before diagnosis: clinical and biomarker trajectories. The Journal of clinical psychiatry, 77(3), e305‐311. doi:10.4088/jcp.15m09989.
Apathy and white matter integrity in amnestic mild cognitive impairment: A whole brain analysis with tract‐based spatial statistics
Authors: Setiadi Tania M , Opmeer Esther M , Martens Sander , Marsman Jan‐Bernard C , Tumati Shankar , Reesink Fransje E , De Deyn Peter Paul , Aleman André , Ćurčić‐Blake Branislava
Published: December 2020

Background

Apathy is one of the most prevalent neuropsychiatric symptoms in amnestic mild cognitive impairment (aMCI) and is associated with an increased risk for progression to Alzheimer’s Disease (AD). Previous diffusion tensor imaging (DTI) studies in AD have shown that apathy is associated with changes in the cingulum, corpus callosum and uncinate fasciculus (Hahn et al., 2013; Kim et al., 2011). However, the underlying white matter (WM) correlates of apathy in aMCI are still unclear. Therefore, we aimed to investigate the association between the severity of apathy and white matter integrity in aMCI using diffusion tensor imaging (DTI) and tract‐based spatial statistics (TBSS).

Method

Twenty‐nine aMCI patients and 20 cognitively healthy controls were included. Apathy severity was assessed with the Apathy Evaluation Scale Clinician version (AES‐C). Depressive symptoms were assessed using the Geriatric Depression Scale (GDS). We calculated a sub‐score of the GDS (i.e. GDS non‐apathy) which excluded apathy‐related items (Adams et al., 2004). We applied whole‐brain TBSS analyses to all DTI parameters: i.e. fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), investigating which WM areas were associated with apathy severity. Age, gender, MMSE, and GDS non‐apathy were used as covariates. Significance was set to p< .05, corrected for multiple comparisons using Threshold‐Free Cluster Enhancement (TFCE).

Result

There was no statistical difference between groups on age, gender, education level, MMSE, and AES‐C scores. Group comparison TBSS analyses showed that the aMCI group did not differ in any of the DTI parameters compared to the control group. Within the aMCI group, significant inverse associations were observed between AES‐C scores and FA values in the bilateral genu and body of the corpus callosum, anterior and superior corona radiata, anterior thalamic radiation, anterior part of inferior frontooccipital fasciculus, and the right forceps minor, superior longitudinal fasciculus/arcuate fasciculus anterior segment, corticospinal tract/internal capsule (pTFCE< .05). A similar pattern was observed in the combined group of aMCI and controls (pTFCE< .025).

Conclusion

There was no significant WM integrity difference between aMCI and control groups. Our findings point to reduced integrity in widely distributed WM pathways being related to apathy severity, regardless of aMCI diagnosis.
Comparison of the different approaches of drawing test for the detection of dementia and mild cognitive impairment: A systematic review and meta‐analysis
Authors: Chan Joyce YC , Chan Tak Kit , Tsoi Kelvin KF
Published: December 2020

Background

Drawing tests are commonly used to detect dementia and mild cognitive impairment (MCI). It is because drawing tests aim to assess visuo‐spatial ability and executive functions, and the deterioration of visuospatial abilities and executive functions is one of the common cognitive symptoms in patients with dementia and MCI. However, there are various types and administrative approaches of the drawing tests, and their diagnostic performance may vary. Thus, this study aims to evaluate the diagnostic performance of different approaches of the drawing tests for the detection dementia and MCI.

Methods

This study is a systematic review and meta‐analysis. Literature searches on each of the drawing tests were performed in OVID databases including MEDLINE, EMBASE, and PsycINFO from the earliest available dates of individual databases to September 1, 2019. Studies that were used to assess the diagnostic performance of the drawing tests to detect dementia or MCI were included. Each test’s performance was compared with the standard diagnostic criteria. Bivariate random‐effects models were used to summarize the test performance as a point estimate for sensitivity and specificity.

Results

A total of 64 studies with 15,567 participants were included to compare different approaches of the drawing tests. Most studies used clock drawing with command approach test (87%), 6 studies used clock drawing with copy approach (10%). In the detection of dementia and MCI, the sensitivity and specificity of command approach were 0.75 and 0.70, respectively, and copy approach were 0.52 and 0.85, respectively. The digital clock drawing tests showed good diagnostic accuracy, the sensitivity was 0.87 and the specificity was 0.89. The digital and traditional pentagon drawing tests were with good sensitivity but fair specificity (Table 1).

Conclusions

This study showed that the digital clock drawing tests have better diagnostic performance than the traditional clock drawing tests. In the comparison between different approaches of traditional clock drawing tests, the command approach have better diagnostic performance than the copy approach. Digital drawing tests have higher sensitivity than traditional approaches, so the development of digital drawing tests are important and useful in the aging population.
The development of a microsimulation model to predict the future burden of dementia and effects of public health interventions
Authors: Brück Chiara , Wolters Frank J , Ikram M Arfan , Kok Inge MCM de
Published: December 2020

Background

Microsimulation models can synthesise complex information, evaluate uncertainties, estimate long‐term and population wide effects of (hypothetical) interventions, and take time trends in risk factors into account. No microsimulation models have been developed so far that include all stages from cognitively healthy to severe dementia and evaluate risk factor changes and the effects of (hypothetical) interventions. We developed a microsimulation model that predicts how dementia incidence and mortality will develop over the coming decades in The Netherlands, taking into account different risk factor scenarios and interventions.

Method

Based on the well‐known Microsimulation Screening Analysis (MISCAN) model from cancer research, a dementia microsimulation model was developed. It synthesises dementia incidence data and survival probabilities from the large population‐based Rotterdam Study cohort (Ikram et al., 2017) with dementia severity stage duration estimates from the literature (Vermunt et al., 2019). The model simulates the life histories of a large number of individuals, each of whom can develop mild cognitive impairment (MCI) which can then progress to mild dementia and moderate/severe dementia and finally death. Based on these life histories, the number of dementia cases, dementia deaths, (quality adjusted) life years of both patients and caregivers, and costs can be evaluated by age and gender. Finally, the model can estimate the effect of different interventions on the life histories and subsequently the outcome measures.

Result

We were able to develop the MISCAN‐Dementia model, as depicted in Figure 1. MISCAN‐Dementia consists of three modules: a demography module, a natural history module, and a screening module. Given this structure, the model can be used to evaluate long‐term benefits and harms of important interventions at different disease stages: 1) changes in risk factors (i.e. onset of cognitive decline); 2) earlier detection and treatment by population screening (i.e. early, pre‐dementia stage); and 3) care and cure (i.e. dementia stage).

Conclusion

The dementia microsimulation model developed in this study predicts how the burden of dementia will develop over the coming decades, including incidence, mortality, quality of life, and costs. In addition, modelling the effect of interventions on a population level will provide essential information for researchers and policy makers.
Identifying patient‐relevant endpoints in the progression of Alzheimer’s disease
Authors: Mank Arenda , van Maurik Ingrid S. , Bakker Els D. , van de Glind Esther M.M. , van Der Flier Wiesje , Visser Leonie N.C.
Published: December 2020

Background

Alzheimer’s disease (AD) is characterized by a long predementia stage and high symptom variability. Prediction of disease progression is important in clinical decision‐making and care planning. Prognostic studies mainly attempted to predict progression to dementia, but it is questionable whether from a patient’s perspective, this is most relevant. We aimed to identify endpoints of relevance to patients and caregivers in AD progression, as part of the European ADDITION project.

Method

We used a two‐step approach. First, we conducted four focus groups with in total 12 patients and 14 care partners between July and October 2019 (Table 1). Participants were recruited through two Dutch memory clinics, and purposefully selected to compose heterogeneous groups in terms of gender, age, and disease stage and setting. Transcripts of the audiotaped focus groups were independently coded by two researchers using thematic content analysis. The resulting list of endpoints then served as input for an online survey. Patients and caregivers were asked to potentially add endpoints, rate their importance, and rank them in order of relevance.

Result

Eight major categories of endpoints were: 1) Cognition (e.g. How long do I still recognize others?); 2) Functioning and dependency (e.g. How long can I still perform hobbies?); 3) Behavioral and neuropsychiatric (e.g. When can I expect behavioral problems?); 4) Social environment (e.g. When should I tell others?); 5) Psychical health (e.g. Which physical symptoms can I expect?); 6) Patient quality of life; 7) Time to death; 8) Caregiver‐oriented outcomes (e.g. How is caregiver quality of life impacted?). In the preliminary analysis of the survey (data collection ongoing; available now N=34 patients; N=36 caregivers), we found that both patients and caregivers considered the cognition‐related endpoints as most important (Table 2). We are currently extending data collection to other European countries for cross‐cultural validation.

Conclusion

We identified patient and caregiver‐relevant outcomes, and will incorporate these in a large‐scale, online data‐collection. The ultimate goal is to predict these endpoints in individualized prediction modeling, that will help to provide patients and care partners with personalized information on the expected disease course.
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

Background

The 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.

Method

A 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.

Result

A 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]).

Conclusion

This 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

Background

Alzheimer'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.

Method

The 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.

Result

In 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).

Conclusion

Spouse‐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

Background

Genome‐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.

Method

A 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.

Result

We 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).

Conclusion

Our 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

Background

The 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.

Methods

Six 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.

Results

The 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.

Conclusion

The 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

Background

Accurate 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.

Methods

We 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).

Results

For 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).

Conclusion

Deep 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

Background

In 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.

Method

A 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.

Results

The 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.

Conclusions

The 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

Background

A 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.

Methods

Nine 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.

Results

Two 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.

Conclusions

The 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

Background

MRI 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.

Method

The 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.

Result

Among 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.

Conclusion

AD‐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

Background

Biological 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.

Method

Plasma 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.

Result

During 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).

Conclusion

Elevated 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

Background

Despite 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.

Methods

In 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.

Results

At 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.

Conclusions

Uncontrolled diabetes increases the risk of cognitive impairment and accelerates its progression to dementia, particularly in older adults with comorbid CVD.
A longitudinal structural brain MRI template for non‐demented older adults
Authors: Ridwan Abdur Raquib , Niaz Mohammad Rakeen , Wu Yingjuan , Qi Xiaoxiao , Bennett David A , Arfanakis Konstantinos
Published: December 2020

Background

One of the major challenges in constructing a longitudinal structural template of the older adult brain is to ensure spatio‐temporal consistency. Here, a new method was introduced to construct a spatio‐temporally consistent longitudinal template of the older adult brain using high‐quality cross‐sectional older adult data from a large cohort. The new template was compared to templates generated with previously published methods in terms of spatio‐temporal consistency and image quality and showed superior performance.

Method

T1‐weighted MPRAGE brain data collected on a 3T MRI scanner from 222 non‐demented older adults (65‐95 age‐range, male: female=1:1) participating in the Memory and Aging Project were used for longitudinal template construction. In Method 1, 10 years wide kernel with constant weight was moved to cover eight age‐ranges (65‐75,68‐78,71‐81,74‐84,77‐87,80‐90,86‐95), each including 58 participants with male:female=1:1. Each age‐ranged data were normalized (SyGN) and averaged, resulting into a longitudinal template with eight time‐points:Rage‐range(Fig.1 steps 1,2,3). Method 2 was a variant of Method 1 and included an initial affine‐registration of individual datasets to the same initial template to limit group biases. This method resulted into a second longitudinal template:Aage‐range
. The proposed method first builds a common population template using data from all participants(65‐95 age‐range) using SyGN registration(Fig.1 steps 1,2,3). Next, the inverse of the non‐linear deformations and the inverse of the shape‐update deformation for participants in each age‐range were concatenated and averaged separately. Each resulting deformation was applied to data from corresponding sub‐group and were averaged, resulting into the proposed longitudinal template:Lage‐range. The three longitudinal templates were compared in terms of spatio‐temporal consistency and image quality.

Result

The longitudinal template constructed using the proposed method resulted in the highest spatio‐temporal consistency as illustrated both visually (Figs.2,3) and quantitatively for gray matter, white matter and the lateral ventricles (Fig. 4). Image sharpness was similar across methods (Fig.3). No image artifacts were detected.

Conclusion

We introduced a new method for the development of a longitudinal structural template of the older adult brain that exhibited higher spatio‐temporal consistency compared to two previously published methods and was characterized by high image sharpness and no image artifacts. The new longitudinal template is part of the MIITRA atlas (www.nitrc.org/projects/miitra).
Visual impairment and dementia risk in two population‐based prospective cohorts
Authors: Littlejohns Thomas J , Hayat Shabina , Luben Robert , Conroy Megan , Foster Paul J , Kuzma Elzbieta , Khawaja Anthony P
Published: December 2020

Background

Visual impairment (VI) has been associated with an increased risk of cognitive decline and dementia, however studies using objective measures of visual function are lacking. Therefore, we investigated the association between objectively‐measured VI and risk of incident all‐cause dementia in two large population‐based prospective cohorts.

Method

Cox‐proportional hazards models were used to assess the association between VI and incident all‐cause dementia in 62,311 UK Biobank (UKB) and 7,506 EPIC‐Norfolk participants aged ≥60 years and dementia free at baseline. In both cohorts, visual acuity was measured with habitual correction (glasses or contact lenses) using a logarithm of the minimum angle of resolution (LogMAR) chart with the participant sitting 4 metres away. VI was defined as a score of ≥0.24 LogMAR, which is the threshold used to meet UK driving standards. In both cohorts, incident dementia was ascertained through cohort‐wide linkage to longitudinal hospital inpatient and death registry records, and, additionally, mental health data in EPIC‐Norfolk.

Result

In UKB and EPIC‐Norfolk, respectively, 3,918 (6.3%) and 470 (6.2%) participants were visually impaired at baseline, and over 8 years (mean=6.5) and 14.5 years (mean=9.6) of follow‐up, 373 and 535 participants developed all‐cause dementia. In UKB, VI was associated with double the risk of developing all‐cause dementia when adjusting for age, sex, ethnicity, socioeconomic status, education, alcohol consumption, smoking, body mass index, self‐reported diabetes and cardiovascular disease (Hazard Ratio (HR)=2.06, 95% Confidence Interval (CI) 1.54‐2.75). In EPIC‐Norfolk, VI was associated with almost a 50% increased risk of developing all‐cause dementia when adjusting for the same covariates (HR=1.49, 95% CI 1.16‐1.92). After excluding participants who were diagnosed with all‐cause dementia within the first three years of follow‐up to account for reverse causation, the HRs were 1.86 (95% CI 1.32‐2.61) and 1.44 (95% CI 1.10‐1.88) in UKB and EPIC‐Norfolk, respectively.

Conclusion

In two large, independent, cohorts of healthy, late middle‐ to older‐aged adults, VI was associated with an increased risk of developing all‐cause dementia. These findings suggest that VI could potentially be a modifiable risk factor for dementia or target for identifying those at high risk of the condition.