bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of APOE on amyloid progression in Alzheimer disease
Authors: Chen Gengsheng , Cruchaga Carlos , Su Yi , Joseph‐Mathurin Nelly , Massoumzadeh Parinaz , Liu Jingxia , Gordon Brian A. , McKay Nicole S. , Hobbs Diana A. , Morris John C , Benzinger Tammie L.S.
Published: June 2023

Background

It is well recognized that β‐amyloid (Aβ) pathology plays an important role in Alzheimer Disease (AD) pathophysiology. The amount of Aβ in the brain varies substantially within both preclinical and symptomatic AD populations. Part of this inter‐individual variability in amyloid pathology may be explained by the genotype variation of Apolipoprotein E (APOE), with the allele e4 found to be the most significant genetic risk factor for late‐onset AD. However, the impact of APOE genotype on the rate of amyloid accumulation is less clear and requires further investigation. In this study, we focus on longitudinal approaches to investigate how APOE genotype influences the trajectories of the Aβ pathology.

Method

For this project, we used longitudinal data of participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Washington University Knight Alzheimer Disease Research Center (Knight ADRC). We included 247 participants with available APOE genotype data, and longitudinal measure of Aβ burden via florbetapir (AV45) PET data, see table 1. Imaging PET data from ADNI and ADRC were harmonized using a centiloid conversion. The rate of Aβ accumulation was estimated as the slope of the random coefficient model using all available time points of longitudinal imaging data for each participant, controlling for age, sex, education and cohort. Generalized linear model was used to test the association between APOE genotype and the rate of change in amyloid.

Result

The rate of change in amyloid burden was not significantly different among all APOE genotype groups (Figure 1A; F = 1.64, p = 0.15). When looking specifically at the effect of allele count for APOE‐e4, we observed the rate of change in amyloid burden increased with e4 allele (Figure 1B; F = 4.18, P = 0.02). Pairwise comparison showed significant differences in rate of amyloid accumulation between e4e4 and e2e3 APOE genotype groups (p = 0.04), and between e4e4 and e3e3 APOE genotype groups (p = 0.04), see table 2. There was no significant difference in rate of amyloid accumulation between other genotype groups.

Conclusion

APOE e4 increases AD risk by accelerating the amyloid deposition. Future direction will include a larger sample size to investigate the effect of e2 and e3 on amyloid progression in AD.
Unique combinations of shape morphometric features improves discriminability of ftld phenotypes
Authors: Stocks Jane K , Popuri Karteek , Beg Mirza Faisal , Cobigo Yann , Rosen Howard J. , Wang Lei
Published: June 2023

Background

Frontotemporal lobar degeneration (FTLD) is associated with diverse clinical phenotypes underlain by multiple disease pathologies and genetic mutations. As such, traditional structural MRI analyses lack sensitivity and specificity for discriminating FTLD syndromes. Here, we use data‐driven methods to extract a concise set of MRI‐derived shape morphometric features and examine the discriminatory capability of their unique combinations in four FTLD clinical phenotypes.

Method

190 patients with sporadic or familial FTLD spectrum disorders (i.e., behavioral variant (bvFTD, n = 107), non‐fluent variant primary progressive aphasia (nfvPPA, n = 27), semantic variant primary progressive aphasia (svPPA, n = 12) and progressive supranuclear palsy (PSP, n = 44)) and 27 controls without pathogenic mutations from the ALLFTD cohort were evaluated. MRI data were preprocessed with FreeSurfer software and four cortical measures were extracted and indexed to a normalized surface atlas: cortical thickness (CT), surface area (SA), surface curvature (SC) and jacobian white matter surface metric distortion (JW). For all phenotypes, each shape feature was contrasted with controls using linear models adjusted for age and gender. Principal component analysis (PCA) was then applied to each individual structural measure and the discriminatory power based on individual and combined measures was assessed using logistic regression and 10‐fold cross‐validation.

Result

Figure 1 displays FDR‐corrected T‐scores of differences from controls in each morphometric feature in bvFTD. Results reveal complementary patterns of CT, SA, SC and JW for each phenotype, with greatest differences observed in CT across groups. In Figure 2, we display the features derived from the PCA, weighted by eigenvector coefficients, in bvFTD. In Figures 3‐6, receiver operating characteristic curves for individual and combined measures alongside areas under the curve (AUCs) are shown for each phenotype. In bvFTD, nfvPPA and PSP, the superior model included CT and SC at AUCs of 88.3, 87, and 78.6, respectively. For svPPA, the superior model included CT, SC and JW at an AUC of 85.6.

Conclusion

Integrating additional MRI‐derived surface morphometric features improved classification performance in all FTLD phenotypes. The principal component analysis‐based approach indicated distinct brain regions contribute to discrimination for each shape feature, suggesting they may reflect unique aspects of neurodegeneration across groups.
Classification of amyloid positivity in PET imaging using end‐to‐end deep learning: a multi‐cohort, multi‐tracer analysis
Authors: Fan Shuyang , Ha Sung Min , Chakrabarty Satrajit , Lee John , Flores Shaney , LaMontagne Pamela , Gordon Brian A. , Raji Cyrus A. , Benzinger Tammie L.S. , Morris John C , Ances Beau M. , Marcus Daniel S. , Sotiras Aristeidis
Published: June 2023

Background

Positron emission tomography (PET) imaging with amyloid‐specific tracers is the gold standard for assessing amyloid positivity in vivo. However, visual interpretation of PET images is limited by availability of clinicians and interobserver variability. Classification of amyloid status typically requires calculation of standardized uptake value ratios (SUVRs), correspondence with neuroanatomy from magnetic resonance imaging, and additional complex, computationally intensive preprocessing steps requiring specialized software. We developed a deep learning model that can automatically classify unprocessed PET images as amyloid positive or negative.

Method

Florbetapir (AV45), florbetaben (FBB), and Pittsburgh compound B (PiB) images from the Alzheimer’s Disease Neuroimaging Association (ADNI), AV45 and PiB images from the Open Access Series of Imaging Studies 3 (OASIS3), and FBB, flutametamol (FMT), and flutafuranol (NAV4694) images from the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) were used (Table 1). Each image was resized to isotropic 2 mm voxels, and voxel intensities between the 5th and 95th percentile were normalized to zero mean and unit variance. We trained and internally validated a convolutional neural network (CNN) on AV45 images from ADNI before testing it on images from an independent cohort and/or acquired with a different tracer.

Result

The model achieved an AUC of 0.98 [0.97, 1.0] on test AV45 images from ADNI and generalized well to AV45 images from OASIS3, achieving an AUC of 0.95 [0.92, 0.97] (Table 2). Critically, the model’s performance remained robust even when evaluating imaging from different tracers, including FBB, FMT, PiB, and NAV4694, scoring an AUC of at least 0.97 on each and demonstrating its ability to learn a tracer‐agnostic pattern of abnormality. Similar conclusions can be drawn from other performance metrics.

Conclusion

We developed a deep learning model that can classify amyloid PET scans with a high degree of accuracy. We demonstrated that the model generalizes well to unseen images acquired from an independent cohort, under a different protocol, and/or with tracers unseen during training. Our model may usefully provide concise metrics for amyloid research as well as support clinical assessment of amyloid‐specific PET when expertise or computational resources are limited.
Towards the development of a chemical probe targeting the disruption of SYK tandem SH2 domain and FCεR1γ interactions for Alzheimer’s disease
Authors: Potjewyd Frances M. , Katis Vittorio , Du Yuhong , Bradshaw William , Sikdar Arunima , Nwogbo Felix , Leisner Tina , Wang Dongxue , Hardy Brian P. , Kireev Dmitri B. , Pearce Kenneth H. , Fu Haian , Frye Stephen V. , Axtman Alison D.
Published: June 2023

Background

Spleen tyrosine kinase (SYK) and FCεR1γ were identified as targets for Alzheimer’s disease (AD) via multi‐omics human data by AMP‐AD teams. These proteins were selected for further target validation and medicinal chemistry efforts by members of the Target Enablement to Accelerate Therapy Development for Alzheimer’s Disease (TREAT‐AD) program. SYK has a reported role in AD (PMID: 31324720), and SYK activation can occur upon binding to the phospho‐ITAM region of the FCεR1γ receptor via the tandem SH2 domains (tSH2) of SYK (PMID: 29440271). Therefore, disruption of this interaction is proposed to slow AD related pathology. Through the generation of target enabling packages (TEPs) we aim to provide experimental validation of these targets for AD and develop a high‐quality chemical probe that targets this interaction.

Method

Firstly, tSH2 domains of SYK were purified, followed by crystallography of these tSH2 in the presence of phospho‐ITAM‐containing peptides. A TR‐FRET‐based assay was developed using the SYK tSH2 domain and phospho‐ITAM peptide of FCεR1γ. This assay was miniaturized for ultra‐high‐throughput screening (uHTS) of a screening library of compounds. In parallel, a DNA encoded library (DEL) screen was executed to identify compounds that bind the SYK tSH2 domain. The hits generated using these hit finding campaigns were validated in dose‐response and via orthogonal biophysical methods. Medicinal chemistry campaigns to expand upon these hits are underway.

Result

We have crystallography data of the SYK tSH2 domains bound to phospho‐ITAM peptides and have established a TR‐FRET based assay to identify inhibitors of the interaction between FCεR1γ and SYK. Hit compounds have been identified through uHTS and DEL screening methods. Further validation of these hits in orthogonal assays are underway, alongside medicinal chemistry efforts to identify more potent analogues.

Conclusion

Through the generation of a SYK/FCεR1γ TEP, we have provided the tools to allow for experimental validation of these target for AD and have begun to generate inhibitors of this interaction.
Medial temporal lobe (MTL) – default‐mode network (DMN) functional connectivity disruption in the early stages of the progression of Alzheimer’s disease in a multimodal ADNI3 MP‐RAGE and EPI‐BOLD Advanced cohort
Authors: Grajski Kamil A
Published: June 2023

Background

A cross‐sectional same‐session multi‐modal analysis of T1 structural MRI and resting‐state functional connectivity (rsfMRI) was performed to assess potential biomarkers of the progression from cognitively normal (CN) to significant memory concern (SMC) and early and late mild cognitive impairment (EMCI, LMCI).

Methods

An ADNI‐3 EPI‐BOLD Advanced protocol sub‐population (N = 49) with baseline diagnosis CN (N = 14), SMC (N = 15), EMCI (N = 11) and LMCI (N = 9), matched for age (p = 0.37), education (p = 0.65), gender (p = 0.29), and morphometric (FreeSurfer 7) and fMRI (AFNI) measurements, was processed with a hybrid a priori data‐driven method for identifying anchor‐target ROI pairs in rsfMRI [1]. Anchor‐target ROI pairwise correlations were False Detection Rate (FDR) corrected in a parallel group‐level one‐way four‐factor (CN, SMC, EMCI, LMCI) ANOVA and post hoc pairwise t tests were performed for significant tests only.

Results

MRI. FreeSurfer subcortical segmentation, but not cortical thickness, yielded significant tests in a parallel group‐level one‐way four‐factor ANOVA test (q = 0.05, p* = 2.8×10−3) for left hippocampus. rsfMRI. A 3‐mm grid of ROI (r = 6mm) seeds in left MTL yielded 1,012 ROI “anchors”. 3D (Fisher Z‐transformed) correlation maps were computed for each subject for each anchor ROI and input to a group‐level one‐way four‐factor 3D ANOVA. Cluster analysis (Nvox = 20; p = 0.02; P = 3.45) of the 3D F statistic maps yielded 3,954 target ROIs. An r = 6mm ROI was placed at the center of mass of each target cluster. ROI anchor‐target pair correlations were input to a group‐level one‐way four‐factor ANOVA FDR corrected (q = 0.005; p* = 0.0067, estimated by permutation, N = 1000) which identified 1,454 significant tests (ROI pairs). Post hoc pairwise t tests only on the significant ANOVA tests were FDR‐corrected (q = 0.005) and yielded 34 significant SMC‐CN tests (p* = 1.1×10−4); 329 EMCI‐CN tests (p* = 1.1×10−3); and 78 LMCI‐CN tests (p* = 2.6×10−4). For each pairwise contrast, the significant target ROI masks were summed which resulted in 20‐50 clusters which were bilaterally distributed in MTL and DMN‐associated regions. An independent analysis of right hemisphere yielded similar results.

Conclusions

A hybrid a priori data‐driven approach applied to anchor ROIs in MTL and multiple subcortical regions identified target ROIs that were predominantly, but not uniformly associated with DMN.

[1] Grajski, K. A., Bressler, S., and ADNI. (2019). Neuroimage Clin. 2019;23:101860.
Evaluation of a comprehensive multicomponent support program for people with dementia and their carers: Study protocol for pilot trial
Authors: D'Cunha Nathan M , Isbel Stephen , Bail Kasia , Gibson Diane
Published: June 2023

Background

A growing body of evidence demonstrates the importance of comprehensive multicomponent, person‐centred interventions, including education and support for people living with dementia and their carers following a diagnosis of dementia. However, in Australia, people with dementia and carers frequently face challenges accessing appropriate information, care and support services to support living in the community with different stages of dementia.

Method

The Sustainable Personalised Interventions for Cognition, Care, and Engagement (SPICE) program consists of evidence‐based therapeutic activities for people with dementia and carers. The project aims to recruit 24 dyads (24 people with dementia and 24 carers; four groups of six) to participate in a twelve‐week, twice per week support program using a randomised waiting‐list study design. The SPICE program intervention is delivered by allied health professionals and includes physical activity, cognitive stimulation therapy, and nutrition assessment for the person with dementia. Carers will receive support aimed to promote capacity building and self‐care, including practical strategies to manage behavioural changes. The dyad will also receive the Care of People with Dementia in their Environments (COPE) program which focuses on problem solving and goal setting in the home.

Result

The primary outcome for the intervention is quality of life of the person with dementia using the health‐related quality of life (DEMQOL) questionnaire. Secondary outcomes will assess cognition (Addenbrookes Cognitive Examination (ACE‐III)), neuropsychiatric symptoms (NPI), health and functional ability (WHODAS 2.0), physical function assessments, carer quality of life (C‐DEMQOL), and program satisfaction of the dyad. Categorical data will be summarised using frequency statistics and visualisation. Continuous and other numerical data will be visually explored and summarised using sample descriptive statistics, selected as appropriate based on apparent distributions.

Conclusion

The SPICE program has the potential to promote quality of life of people with dementia and potentially delay cognitive decline while also providing a toolkit for carers to reduce carer burden. If successful, the outcomes of the study have the potential to improve post‐diagnostic care and clinical practice for people with dementia and their carers in Australia and inform services worldwide.
Point of care measurement of blood tau in Alzheimer’s dementia
Authors: Bayoumy Sherif , Salminen Teppo , Hok‐A‐Hin Yanaika S. , van der Flier Wiesje M. , Vanbrabant Jeroen , Stoops Erik , Vanmechelen Eugeen , Verberk Inge M.W. , Teunissen Charlotte E.
Published: June 2023

Background

Several assays reliably measure cerebrospinal fluid (CSF) total tau (t‐tau) protein for Alzheimer’s diseases (AD) diagnosis. However, CSF sampling is invasive and hampers availability of biomarker testing in AD. Therefore, less invasive blood t‐tau assays are needed, preferably on different platforms to enable implementation in different clinical settings. Point‐of‐care (POC) platforms enable the development of practical and easily implemented assays. Here, we aim to develop and compare two blood t‐tau POC‐assays, (1)on the Ella microfluidics platform and (2)using upconversion‐nanoparticle based lateral flow (UCNP‐LF), for use in AD diagnosis.

Method

The prototype assays were developed with the same pair of antibodies (capture‐mAb: ADx205 and detector‐mAb: ADx204 having epitopes in respectively the regions aa 194‐204 and 1‐20) and were calibrated using a recombinant protein (2N4R tau). For the Ella‐assay, we validated the analytical sensitivity, precision (4 different runs) and parallelism. The acceptance range was set to <15% coefficient of variation (CV) for precision and 85‐115% of slope‐accuracy for parallelism. Detectability of t‐tau was assessed using 20 plasma samples, including 10 AD‐dementia patients (age: 64±9y, 60%F) and 10 controls (age: 67±8y, 50%F). For the UCNP‐LF assay, spiked buffer and serum were used for preliminary performance testing.

Result

For the Ella assay, we determined a limit of detection (LoD) of 3 pg/mL based on mean signal of 16 blanks plus 10x SD (figure1). The assay quantified t‐tau in the clinical samples above assay blank with an average intra‐assay CV of 5.3%. Average intra‐ and inter‐assay CV for QC plasma samples were 8% and 11.4%. The assay showed robust mean parallelism response of (95%) (figure 2). Median t‐tau concentration in AD samples was 36.9 pg/mL vs 8 pg/mL in controls. The prototype UCNP‐LF assay showed a LoD of 92 pg/mL, based upon spiked buffer with the recombinant protein, and 102 pg/mL for spiked serum (figure3). The UCNP‐LF assay has a read‐out time of 30 minutes.

Conclusion

The prototype assays showed promising preliminary performance. Next, a technology comparison using Bland‐Altman graphs on samples of at least two different clinical groups, would be measured using a reference immunoassay platform, such as Simoa.
Correlation between quantitative and qualitative assessments of white matter hyperintensities in patients from a multicentric memory clinic population
Authors: Longo Clarisse , Cavedo Enrica , Gordon Elizabeth , Samper‐Gonzales Jorge , Schwarz Adam J. ,   MEMENTO study group
Published: June 2023

Background

White matter hyperintensities (WMH) can be visualized as abnormal T2 signal in the periventricular, deep and subcortical white matter on Magnetic Resonance Imaging (MRI). WMH increase with age and are associated with stroke, cognitive decline and dementia. The most common visual rating scale used to assess WMH in the clinical setting is the Fazekas scale (Fazekas et al., 1987). The current study investigated the relationship between WMH volume (expressed as a % of intra‐cranial volume (ICV)) calculated using an automated method included in the QyScore® medical device, and Fazekas scores in a multicentric memory clinic population at baseline.

Method

1959 participants from the MEMENTO cohort (Age 71.02 +/‐ 8.61, 1218 Female, MMSE 27.95 +/‐ 1.91) had 3DT1 and T2 FLAIR MRI scans analyzed with QyScore®, an FDA‐approved and CE‐marked image analysis software. 814 had amyloid status from CSF or PET, of which 216 were Amyloid+. WMH volumes are reported in mL, corrected for %ICV. Correlation between Fazekas deep white matter (DWM) scores and quantitative WMH measurements was ascertained by Spearman’s rank correlation.

Result

There was a significant positive correlation between Fazekas DWM scores and WMH %ICV (0.76 p<0.001) for the total sample, amyloid positive (0.81 p<0.001) and negative (0.72 p<0.001) patients. The correlation was also strong when separated by clinical diagnosis: patients with Subjective Cognitive Complaint (SCC, N = 305, AGE: 69.87 +/‐ 8.03, 197 female, MMSE: 28.86 +/‐ 1.17) and MCI (N = 1638, Age: 71.2 +/‐ 8.69, 1014 Female, MMSE: 27.8 +/‐ 1.95) presented Fazekas DWM scores correlated with WMH %ICV (0.66 p<0.001 for SCC; 0.77 p<0.001 for MCI).

Conclusion

The automated quantification of ICV‐corrected WMH were well‐correlated to Fazekas DWM scores. Considering that visual rating of WMH is time consuming and suffers from intra and inter‐operator variability, the quantitative assessment of WMH load provided by QyScore® may improve the assessment of patients with cognitive impairment.
Associations between an individual’s need for cognitively stimulating activities, brain damage and cognitive functioning: Results from The Maastricht Study
Authors: Truin Lotte S. , Köhler Sebastian , Schram Miranda T. , van Boxtel Martin P.J. , Backes Walter H. , Jansen Jacobus F.A. , van Dongen Martien , de Vries Nanne , de Vries Hein , Eussen Simone J.P.M. , Stehouwer Coen D.A. , de Vugt Marjolein , Deckers Kay
Published: June 2023

Background

Dementia is a global health challenge. Currently, there is no curative treatment for dementia and therefore risk reduction through lifestyle modifications has become more prominent with high cognitive activity as a promising target. This study explored the association between an individual’s need to engage in cognitively stimulating activities, brain damage and cognitive functioning in the Dutch general population.

Method

This study used cross‐sectional data from the population‐based cohort The Maastricht Study (N = 4,209; mean age 59.06 ± 8.58 years, 50.11% women). Need For Cogntion (NFC) was measured with the Need For Cognition Scale. Cognitive functioning was tested in three domains: verbal memory, information processing speed and executive functioning and attention. Standardized volumes of white matter hyperintensities (WMH) and cerebrospinal fluid (CSF) and presence of cerebral small vessel disease (CSVD) were derived from 3 Tesla MRI. Multiple linear regression analysis was used to explore the association between NFC and cognitive functioning, NFC and WMH and NFC and CSF. Binary logistic regression analysis was used to assess the association between NFC and CSVD. Interaction between brain damage or cognitive impairment (a score of <1.5 standard deviation below the mean on any of the three cognitive domains) and NFC on cognitive functioning was tested by including interaction terms in the regression analyses.

Result

High NFC was positively associated with cognitive functioning (β: 0.21, p = <0.001) and negatively associated with CSVD (OR: 0.74, p = 0.005). These associations were independent of demographic and somatic factors. A dose‐response relationship between NFC and cognitive functioning was observed. There was no statistically significant association between NFC and WMH or CSF. No interaction between CSVD, WMH or CSF and NFC on cognitive functioning was found. Cognitive impairment did not moderate the association between NFC and cognitive functioning.

Conclusion

A high need for engaging in cognitively stimulating activities is associated with better cognitive functioning and less brain damage. This is in line with previous research. These results indicate that, in middle‐aged populations, stimulating cognitive activity may be an opportunity for risk reduction of cognitive decline and dementia.
Characterizing oldest‐old SuperAgers based on cognitive domains and demographic factors: The Life After 90 study
Authors: Biswas Roshni , Kawas Claudia H. , Gilsanz Paola , Whitmer Rachel A. , Mungas Dan M. , Decarli Charles , Glymour M. Maria , Corrada María M. M.
Published: June 2023

Background

SuperAgers are individuals who maintain superior cognitive performance despite advanced age. Most studies define SuperAgers as superior performers only in episodic memory. Our aim was to assess in a diverse oldest‐old cohort if superior performance in one domain indicates superior performance in other domains and explore demographic characteristics.

Methods

The LifeAfter90 study is a multi‐ethnic cohort of members of Kaiser Permanente Northern California aged 90 or older. Baseline verbal episodic memory (VEM), semantic memory (SM), and executive function (EF) were evaluated using the Spanish and English Neuropsychological Assessment Scale (SENAS). SuperAgers were individuals who scored above the mean of domain and race‐specific SENAS scores from a reference cohort aged 65‐70 years. The reference group were similar participants from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study. To assess the association between age, sex, education, and being a SuperAger, odds ratios (OR) and 95% confidence interval (CI) were calculated using multiple logistic regression.

Results

The 617 study participants (236 men and 381 women) had a mean age of 92.9 years (Table1). 53.6% of individuals were SuperAgers in one domain, 22.8% in any two domains, and 7.7% in all three domains. 7.0% of individuals were SuperAgers in SM and EF, 4.5% in VEM and EF, and 3.5% in VEM and SM (Figure1). SuperAgers were younger than non‐SuperAgers. Women were more likely to be SuperAgers in VEM (OR = 2.13; 95%CI: 1.43,3.18) and EF (OR = 2.18; 95%CI: 1.44,3.30) and less likely in SM (OR = 0.49; 95%CI: 0.34,0.71) compared to men. Higher education was related to being a SuperAger in SM (OR = 1.85; 95%CI: 1.28,2.67) and EF (OR = 2.56; 95%CI: 1.74,3.78) but not VEM (Table2).

Conclusion

In this diverse cohort of oldest‐old SuperAgers we found that exceptional episodic memory performance does not indicate exceptional performance in other cognitive domains. Education was not a predictor of exceptional performance in all domains. Future work should investigate predictors of exceptional cognitive aging after age 90.
Regional cerebral atrophy correlates with amyloid accumulation in preclinical Alzheimer’s disease
Authors: Imabayashi Etsuko , Ishii Kenji , Toyohara Jun , Kojima Narumi , Tago Tetsuro , Sakata Muneyuki , Wagatsuma Kei , Ishibashi Kenji , Tokumaru Aya M. , Kim Hunkyung
Published: June 2023

Background

This study was aimed to evaluate the regional hierarchical brain atrophy among the preclinical to mild cognitive impairment (MCI) stages of Alzheimer’s disease associated with amyloid deposition using [18F]flutemetamol positron emission tomography and volumetric magnetic resonance imaging.

Method

This was a prospective, single‐cohort study of volunteers who were living independently in Itabashi‐ku (Tokyo, Japan). One hundred thirty‐six participants (female/male = 96/40, mean age/standard deviation = 79.2/4.0 years) were recruited. Two subjects, one with meningeal thickening and another with sequelae in the brain, and 17 visually amyloid‐negative MCI subjects who possibly had neurodegenerative disease other than Alzheimer’s disease were excluded from the further analysis. We applied voxel‐based regression slope analysis between composite voxel of interest values calculated with Cortex ID Suite (GE Healthcare) on [18F]flutemetamol positron emission tomography and volumetric magnetic resonance images in three groups: 70 amyloid‐negative cognitively normal (CN) participants, 29 amyloid‐positive cognitively normal (PreC) participants, and 18 amyloid‐positive MCI (MCI+) participants. Statistical Parametric Mapping 12 software was used for analysis.

Result

Even in the cognitively normal stage, the PreC group showed a larger slope of atrophy in the basal forebrain and middle frontal gyri than the CN group. In the MCI+ group, the slopes were larger in the lateral and medial parietal lobes, uncus, and right lateral temporal areas.

Conclusion

The speed of amyloid‐related atrophy in the basal forebrain and middle frontal gyri was quick even in the preclinical stage of Alzheimer’s disease. As no significant slope changes were observed among the three groups in the medial temporal area, except for the uncus, the well‐known medial temporal atrophy in early Alzheimer’s disease might not be related to the accumulation of amyloid.
Mediterranean diet and longitudinal change of white matter hyperintensity in cognitively intact young and older adults
Authors: Song Suhang , Gaynor Alexandra M. , Cruz Emily , Lee Seonjoo , Gazes Yunglin , Habeck Christian , Stern Yaakov , Gu Yian
Published: June 2023

Background

A healthy dietary pattern, Mediterranean diet (MeDi), has been reported to be associated with better brain and cognition. White matter hyperintensities (WMHs), seen in brain magnetic resonance imaging, are considered to be due to cerebral small vessel diseases and have been shown to predict faster cognitive decline in older adults. However, current evidence on the association between MeDi and WMH is inconsistent and longitudinal data are scarce. This study aims to examine whether better adherence to MeDi is associated with less accumulation of WMH over time.

Method

This longitudinal study was conducted among 183 cognitively intact adults aged 20‐80 years. MeDi was calculated from dietary data assessed by a self‐reported food frequency questionnaire, ranging from 0‐55, with a higher score indicating better adherence. WMH was assessed by 3T MRI, and log‐transformed prior to analyses. A one‐sample T‐test was used to examine if WMH burden increased from baseline to follow‐up over an average of five years. Multivariable linear regression was used to estimate the effect of MeDi on the change in WMH. Covariates included age, gender, race/ethnicity, education, IQ, follow‐up interval, caloric intake, baseline WMH, baseline total gray matter volume, and baseline mean cortical thickness. Moderation effects by age (young: <43, middle‐aged: 43‐65, and older: ≥65 years), sex, and race/ethnicity (non‐Hispanic White and other, non‐Hispanic Black, and Hispanic) were examined, followed by stratification analyses.

Result

Among all participants, WMH increased from baseline to follow‐up (mean difference [follow‐up‐baseline][standard error(SE)] = 0.31[0.04], p<0.001). A higher MeDi was associated with less increase of WMH (β[SE] = ‐0.014[0.006], p = 0.034), adjusting by all covariates. The association between MeDi and WMH change was moderated by age group (young group as the reference, p‐interaction[middle‐aged*MeDi] = 0.024, p‐interaction[older*MeDi] = 0.017), adjusting by follow‐up interval: the association was observed among the young group (β[SE] = ‐0.038[0.010], p<0.001), but not among the middle‐aged ((β[SE] = ‐0.002[0.013, p = 0.872]) or the older group ((β[SE] = ‐0.002[0.009], p = 0.836). No significant moderation effects by sex or race/ethnicity were found, adjusting by age and follow‐up interval.

Conclusion

Better adherence to MeDi was associated with reduced increase of WMH over time. Following a healthy diet, especially at an early age, may help maintain a healthy brain.
Validation of a new cognitive screening tool, the Brain Health Test‐7, for identification of mild cognitive impairment and early dementia
Authors: Hwang Tzung‐Jeng , Wang Pei‐Ning , Chen Cheng‐Sheng , Chen Jiahn‐Jyh , Hsu Chih‐Cheng
Published: June 2023

Background

The Brain Health Test‐7 (BHT‐7) was developed to identify patients with mild cognitive impairment (MCI) and early dementia. Here we report the validity of the BHT‐7 versus the Mini‐Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) in subjects of different psychiatry or neurology clinics.

Method

Patients with the chief complaint of memory decline were recruited in this study from the outpatient clinic of psychiatry or neurology in 3 different kinds of hospitals between November 2017 to December 2020. All patients underwent the evaluation of the BHT‐7, MMSE, MoCA, and CDR by trained research assistants or board‐certified psychologists. The final clinical diagnosis (normal, MCI, dementia) was made by consensus meeting, taking into account all available data, including clinical history and symptoms, brain image, cognitive tests, and CDR. Demographic data (age, gender, and education level) and the scores of the MMSE, MoCA, and BHT‐7 between groups were compared. Logistic regression was adopted for analysis of optimal cutoff values, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the ROC curve.

Result

We enrolled a total of 1090 subjects (normal 402, MCI 317, dementia 371); of them, 705 (64.7%) were female. There was a statistically significant difference in age, years of education, and 3 cognitive test scores among the 3 groups of subjects. Compared with the MMSE and MoCA, the BHT‐7 performed slightly better in differentiating MCI and dementia. In sub‐group analysis (divided based on 6 years of education), the BHT‐7 still performed slightly better than MMSE and MoCA. The testing time for the BHT‐7 was about 5‐7 minutes, shorter than that of the MMSE and MoCA. For BHT‐7, the cutoff point was 17 between normal and MCI, and 14 between normal and dementia. These cutoff points of BHT‐7 were consistent through 3 different settings (medical center’s psychiatry and neurology clinics, and outpatient clinic of a psychiatry center). In contrast, the cutoff points were inconsistent for MMSE and MoCA in different settings.

Conclusion

The results support that BHT‐7 may be a useful cognitive screening tool for MCI or early dementia in various clinic settings.
Sleep quality and memory performance in a lifespan sample of racially/ethnically diverse adults
Authors: Hokett Emily , Lao Patrick J. , Turney Indira C , Martinez‐Amezcua Pablo , Starks Tiara M. , Brickman Adam M. , Palta Priya , Manly Jennifer J.
Published: June 2023

Background

While studies have shown that Non‐Latinx Black and Latinx adults sleep less and more poorly than Non‐Latinx White adults, the cognitive consequences of poor sleep in Non‐Latinx Black and Latinx adults are understudied. Moreover, it is unclear if negative factors that disproportionately affect racial/ethnic minorities, including discrimination, may result in racial/ethnic differences in the relationship between sleep and cognition. We hypothesized that poorer quality sleep and inadequate sleep duration (e.g., short or long sleep) is associated with poorer memory performance, and the strength of these associations would differ by racial/ethnic group.

Method

Our analysis included non‐Latinx Black, non‐Latinx White, and Latinx participants across the adult lifespan recruited from the community of Northern Manhattan as a part of the Offspring study. Participants self‐reported their sleep duration and quality over the past month using the Pittsburgh Sleep Quality Index, which we used to calculate global sleep quality. We evaluated memory with the Buschke Selective Reminding Task. We used general linear models to estimate mean differences in sleep duration and quality for racial/ethnic groups. We used multivariable regression to estimate relationships of sleep duration and quality with delayed recall in the total sample and stratified by racial/ethnic group. Models were adjusted for age, sex, and years of education.

Result

Black and Latinx adults reported lower sleep duration and poorer quality sleep than Non‐Latinx White adults. In the overall sample, higher quality sleep was associated with better delayed recall performance. We also found linear and quadratic relationships between sleep duration and delayed recall. Taken together, high quality sleep and adequate sleep duration was linked with better delayed recall. Stratified analyses revealed that these effects were strongest in the Latinx group and were not present among non‐Latinx Black and non‐Latinx White participants.

Conclusion

Non‐Latinx Black and Latinx adults report lower sleep duration and poorer sleep quality compared to Non‐Latinx White adults. We observed stronger associations between poor sleep quality and sleep duration and memory performance in Latinx adults. Future work will determine which psychosocial factors (e.g., social support, discrimination) underlie racial/ethnic sleep disparities and mediate racial/ethnic differences in the cognitive consequences of poor sleep.
Prediction of cognitive impairment in morphologically‐ and immunohistochemically‐stained whole slide images reveals white matter alterations
Authors: McKenzie Andrew T , Marx Gabriel A. , Koenigsberg Daniel , Sawyer Mary , Iida Megan A , Walker Jamie M. , Richardson Timothy E. , Campanella Gabriele , Attems Johannes , McKee Ann C. , Stein Thor D. , Fuchs Thomas J , III Charles White , Farrell Kurt W. , Crary John F.
Published: June 2023

Background

Age‐related cognitive impairment is complex and multifactorial, with numerous underlying and frequently co‐morbid pathological correlates. Given that conventional measures are imperfect predictors of cognitive impairment, improved approaches are urgently needed to identify correlated histopathological changes in an unbiased way.

Methods

We used a weakly supervised deep learning algorithm, clustering‐constrained‐attention multiple‐instance learning (CLAM), on digitized whole slide images of human brain tissue sections from a group of elderly individuals without significant amyloid‐beta deposition to predict the presence or absence of cognitive impairment. The brain tissue sections were from the hippocampus and frontal cortex and were either morphologically stained with LH&E or immunohistochemically stained for hyper‐phosphorylated tau. We used attention analysis to pinpoint the underlying architectural and cellular features that the top‐performing models used for the predictions.

Results

Despite noisy labels of cognition, our trained models were able to predict the presence of cognitive impairment with an accuracy that significantly beat chance, in both the morphologically stained and immunohistochemically stained whole slide images. Attention‐based analysis of the features most associated with cognitive impairment in both types of whole slide images analyzed suggests that the models identified white matter alterations in donors with cognitive impairment.

Conclusions

The deep learning method for the prediction of cognitive impairment that we present, which appears to be minimally influenced by the human‐identified visually salient aspects of whole slide images, may help to discover unexpected aspects of the pathophysiology associated with cognitive impairment in the elderly.
Risk and protective factors for cognitive decline in lower educated older adults with 15‐year follow‐up
Authors: Ribeiro Fabiana , Leist Anja K.
Published: June 2023

Background

Studies have identified modifiable risk factors for both prevalence and incidence of cognitive impairment in lower educated older adults. However, patterns of cognitive change, and risk and protective factors for declining versus stable cognitive trajectories have rarely been described in this population. Our goal was to explore the long‐term trajectories of cognitive function and identify modifiable risk and protective factors for cognitive decline beyond education.

Method

We applied group‐based trajectory modelling and multinomial logistic regressions to explore possible trajectories and associated baseline factors on data from a population‐based Health, Welfare and Aging (SABE) survey collected in 2000, 2006, 2010, and 2015 in Sao Paulo, Brazil. Cognitive functioning was assessed using the abbreviated Mini‐Mental State Exam. A total of 354 respondents aged 60 + participating in all follow‐ups were included in the statistical analyses.

Result

Group‐based trajectory modelling identified three different cognitive trajectories, specifically groups with stable (37.4%), declining (53.8%), and strongly declining (8.8%) trajectories, with the last one reaching the threshold for cognitive impairment (Figure 1). Socioeconomic status, specifically living in rural areas during childhood and no schooling or primary education, as well as self‐identified race was systematically different between the groups (Table 1). Moreover, respondents in the stable trajectory were more likely to report living in urban areas, more than primary education, to be white, to earn more than four times the minimum wage/month, to practice manual work, craft or artistic activity at least once a week, and less likely to have had stroke or be widowed. On the other hand, those in the strongly declining trajectory were more likely to be black or mixed and smoke at baseline.

Conclusion

Our findings suggest substantial potential for modification of risk of cognitive decline even in lower educated older individuals at risk for cognitive impairment. Risk factors related to self‐identified race/ethnicity and socioeconomic status suggest systematic inequalities in brain health potential, with risk for later‐life cognitive impairment. Sample attrition suggests conservative estimates of the magnitude of the risk factors for cognitive decline. Health and social policies should address inequalities to improve later‐life cognitive function of at‐risk individuals.
Effects of ApoE in the Panama aging research initiative: A community‐dwelling older adults’ cohort in Panama
Authors: Villarreal Alcibiades E , Britton Gabrielle B , Oviedo Diana C , O'Bryant Sid E. , Edwards Melissa , Carreira Maria B , Rangel Giselle
Published: June 2023

Background

The Panama Aging Research Initiative (PARI) is a longitudinal study of more than 800 adults aged 60 years and older. The objective of this analysis consists of identifying the effects of Apolipoprotein E (ApoE) gene as a risk factor for sporadic Alzheimer’s disease (AD), with elevated risk for ε4‐carriers and reduced risk for ε2‐carriers.

Method

Our ongoing community‐based cohort (n = 400) has undergone clinical interviews, neuropsychological testing, and assessments of frailty at two time points (14‐29 months apart). Fasting blood draws were obtained for measurements of genetic and blood‐based biological markers. DNA was extracted from whole blood and (ApoE) genotyping (n = 330) was conducted according to standardized PCR procedures. We will examine whether ε2 and ε4 are associated with differential rates of normal cognitive aging, and whether associations of ε4 with cognitive decline are modified by sex, education or other health conditions common among older adults in Panama, including chronic illnesses, polypharmacy and frailty.

Result

Our study evaluate whether ApoE ε2, ε3 and ε4 allele frequency is a significant factor associated with cognition and daily function in elderly individuals. Specifically, we focus on evaluating the frequency of ApoE ε4 expression as a risk for cognitive impairment. Together these results contribute to our understanding of the risk factors of cognitive outcomes among Hispanic populations outside the US.

Conclusion

Little is known about the factors associated to cognitive health at old age in Central American populations. Genetic biomarkers could be used as a tool for diagnostic testing. It is expected that ApoE‐ε4 polymorphism will correlate with cognitive deficit among the elderly population and those at risk for cognitive impairment.
Unbiased deep learning assessment of APOE4 risk for sporadic Alzheimer’s disease
Authors: Bae Jinhyeong , Nho Kwangsik , Saykin Andrew J. , Penchev Valentin , Apostolova Liana G.
Published: June 2023

Background

Genome wide association study (GWAS) presented that a cohort having one or two copies of APOE4 show about 2.84 or 8.07 times, respectively, higher risk of having Alzheimer’s disease (AD) than who do not. However, it is unclear how much impact does APOE4 have in progressing AD for an individual. We implemented a deep learning model to identify the APOE4’s risk impact at the individual level.

Method

We applied a novel deep learning model to the 266,161 SNP chromosome 19 data of 313 AD and 457 cognitively unimpaired (CU) ADNI patients. The whole dataset was divided into train, validation, and test set with a ratio of 60%, 20%, and 20% for model development. In the test set, 63.93% of AD participants were APOE4 carriers as opposed to 30.11% of CU participants. Therefore, APOE4 alone has a 67.5% diagnostic accuracy.

Result

The model achieved 68.18% in classifying CU vs. AD and recognized SNPs in APOC1 (rs12721051, rs56131196, rs12721046, and rs4420638) as strong AD risk factors. On the other hand, SNPs in APOE did not show a risk impact such that removal or replacement of the SNPs of the APOE haplotype (rs429358 and rs7412) did neither increase nor decrease the likelihood of AD for any of the 154 test set participants. Furthermore, rs429358 and rs7412 did not show any interaction effects with other SNPs in chromosome 19. Further closer examination of these results confirmed that the APOE haplotype (rs429358 and rs7412) and the APOC1 SNPs (rs12721051, rs56131196, rs12721046, and rs4420638) are in strong linkage disequilibrium (normalized correlation coefficients range 0.685‐0.844) which explains why only one of the two genes was selected by our model. These results were reproduced by 5‐fold cross validation as well as with the implementation of a different deep learning model architecture.

Conclusion

APOC1 variants were ranked higher and selected by our deep learning algorithm over the APOE haplotype that has been established as the strongest sporadic AD risk factor to date. APOC1 might be a major AD risk gene that needs further exploration.
Severity and symptoms of depression in older adults presenting to mental health services during COVID‐19 lockdown – an experience from south London region
Authors: Velayudhan Latha , Cheung Wai Yan , Perera Gayan , Broadbent Matthew , Stewart Robert , Mueller Christoph
Published: June 2023

Background

Social restrictive measures during COVID‐19 pandemic has influenced people’s mental health conditions across different countries. Global studies indicated an increased prevalence of anxiety disorder and depression with varied impacts among different age groups. Most studies in the elderly have been done via surveys or internet medias missing out on people with no access to digital technology tools. We aimed to investigate the prevalence of depression among elderly people aged 65 years and above who attended mental health service for older adults (MHOA).

Methods

Retrospective data was collected from the South London and Maudsley NHS Foundation Trust (SLaM) Biomedical Research Centre (BRC) Case Register for MHOA. Using this large mental health care database in South London, United Kingdom, we identified referrals to MHOA during the first UK lockdown (March ‐ July 2020) and compared those to a corresponding pre‐COVID period (February ‐ July 2019). Logistic regression analysis adjusted for age, gender, ethnicity, diagnosis and living conditions were done to examine association between COVID‐19 lockdown and severity and symptoms of depression.

Results

536 patients were referred and seen within the MHOA during the first UK COVID‐19 lockdown period compared to 1,455 patients during the pre‐COVID‐19 corresponding period. We found presence of COVID‐19 lockdown had no effect on overall severity of depression but significantly associated with depressive symptoms such as anhedonia (1.64, 95% CI 1.14‐2.37, p = 0.008), lack of energy (1.65. 95% CI 1.65 (1.25‐2.16), p<0.001), tearfulness (1.43, CI% 1.15‐1.78, p = 0.001), agitation (1.32, CI% 1.07‐1.63, p = 0.009), disturbed sleep (1.37, CI% 1.11‐1.70, p = 0.003) and guilt feelings (1.45, CI% 1.04‐2.03, p = 0.030)

Conclusions

There was an increased prevalence of certain depressive symptoms among older adults within MHOA during first COVID‐19 lockdown which implies impact of isolation and possibly physical ill‐health on mental well‐being. This needs to be explored further for potential prevention and managements.