bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Mild cognitive impairment (MCI) in a rural Indian population and its association with hypertension, diabetes and depression
Authors: Partha Ajith , Stezin Albert , L Abhishek M , Mallikarjun Divya N , Hameed Shafeeq K Shahul , Narayanasamy Rajitha , R Meghana , Menon Meenakshi , M Amitha C , Arvind Prathima , Velavarajan Goutham , Singh Sadhana , HS Sunitha , Kommaddi Reddy Peera , Diwakar Latha , Malo Palash Kumar , Sundarakumar Jonas S. , Issac Thomas Gregor , Ravindranath Vijayalakshmi
Published: December 2023

Background

Mild cognitive impairment (MCI) is a transitional phase between normal cognitive ageing and dementia. The prevalence of MCI in rural populations is an understudied area. Risk factors such as hypertension, diabetes, and depression are more prevalent in rural areas, which can contribute to the development of MCI (Longfei et al, 2020). The purpose of this study is to find out the prevalence of MCI amongst a rural cohort and to study the relationship between MCI and hypertension, diabetes and depression.

Method

Cross sectional analysis on the subset of data taken from ongoing longitudinal study on dementia named Srinivaspura Aging, Neuro Senescence and COGnition (SANSCOG) (Sundarakumar et al, 2020), which has a target of 10000 participants. MCI was diagnosed in the subject whose Clinical Dementia Rating (CDR) score was 0.5, as per the NIA‐AA (National Institute on Aging‐Alzheimer’s Association) criteria, 2011. Presence of hypertension and diabetes were collected through a structured clinical questionnaire. Depression was assessed using the Geriatric Depression Scale 30 (GDS‐30) and a score above 9 was considered as depression. Chi‐square analysis(χ2) was used to study the association between MCI and hypertension, diabetes and depression.

Result

A total of 3789 participants were examined amongst which 293 had a CDR score of 0.5, indicating presence of MCI in 7.7% of the study group. Prevalence of depression in non‐MCI and MCI subjects was 14.91% and 30.73% respectively and depression was found to be significantly associated with MCI(χ2 =24.522, p< 0.001). Hypertension was seen in 13.83% of non‐MCI subjects and in 17.76% of subjects with MCI. Diabetes was seen in 16.93% of non‐MCI subjects and in 18.25% of subjects with MCI. Both hypertension (χ2 =2.086, p = 0.149) and diabetes (χ2=0.195, p = 0.659) were not significantly associated with MCI.

Conclusion

Depression was significantly associated with MCI. It is known that late onset depression, which is diagnosed above the age of 50, may be a predisposing factor for dementia in later life. Our results may indicate this relationship between depression and cognitive impairment. However, further longitudinal studies are necessary to evaluate causal relationship.
Cognitive Function based on Theta‐Gamma Coupling vs. Clinical Diagnosis in Older Adults with Mild Cognitive Impairment with or without Major Depressive Disorder
Authors: Brooks Heather , Wang Wei , Zomorrodi Reza , Blumberger Daniel M. , Bowie Christopher R , Daskalakis Zafiris J. , Fischer Corinne E. , Flint Alastair , Herrmann Nathan , Kumar Sanjeev , Lanctôt Krista L. , Mah Linda , Mulsant Benoit H. , Pollock Bruce G. , Voineskos Aristotle N. , Rajji Tarek K. ,   PACt‐MD Study Group
Published: December 2023

Background

Whether individuals with mild cognitive impairment (MCI) and a history of major depressive disorder (MDD) are at a higher risk for cognitive decline than those with MCI alone is still not clear. Previous work suggests that a reduction in prefrontal cortical theta phase‐gamma amplitude coupling (TGC) is an early marker of cognitive impairment. This study aimed to determine whether using a TGC cut‐off is better at separating individuals with MCI or MCI with remitted MDD (MCI+rMDD) on cognitive performance than their clinical diagnosis. Our hypothesis was that global cognition would differ more between TGC‐based groups than diagnostic groups.

Method

We analyzed data from 128 MCI (mean age: 71.8, SD: 7.3) and 85 MCI+rMDD (mean age: 70.9, SD: 4.7) participants. Participants completed a comprehensive neuropsychological battery; TGC was measured during the N‐back task. An optimal TGC cut‐off was determined during performance of the 2‐back. This TGC cut‐off was used to classify participants into low vs. high TGC groups. We then compared the Cohen’s d of the difference in global cognition between the high and low TGC groups to the Cohen’s d between the MCI and MCI+rMDD groups. We used bootstrapping to determine 95% confidence intervals for Cohen’s d values using the whole sample.

Result

As hypothesized, Cohen’s d for the difference in global cognition between the TGC groups was larger (0.64 [0.32,0.88]) than between the diagnostic groups (0.10 [0.004,0.37]) with a difference between these two Cohen’s d’s of 0.54[0.10, 0.80].

Conclusion

Our findings suggest that TGC is a useful marker to identify individuals at high risk for cognitive decline, beyond clinical diagnosis. This could be due to TGC being a sensitive marker of prefrontal cortical dysfunction that would lead to an accelerated cognitive decline.
Subjective Cognitive Decline And Inflammation Among The Elderly
Authors: Gonçalves Eduardo C Q , Buchain Patricia Cardoso , Ribeiz Salma Rose Imanari , Kahtalian Lais Lundstedt , Marques Fernanda Mariotti , Filho Geraldo Busatto
Published: December 2023

Background

Subjective cognitive decline (SCD) is a state of self‐perception of cognitive worsening compared to the normal state, without abnormalities on objective neuropsychological assessments. Since its definition in 2014, this condition has raised considerable interest, once those patients are at higher risk for developing objective cognitive decline, Alzheimer disease and other types of dementia (JESSEN 2020). The inflammatory cytokine network is associated with aging‐related diseases, and changes in the release of these substances may impact higher brain functions, such as mood and cognition (NG 2018).

Method

Users of basic healthcare units aged 60 years and over without dementia (MMSE≥14) and non‐depressed (CES‐D<16) from a community sample in São Paulo were assessed with a questionnaire about perceived memory problems (“have you had memory problems lately?”) and for sociodemographic data, cognitive and depression screening. Serum samples were collected for dosages of C‐reactive protein (RCP), interferon gamma (IG) and interleukines (IL) 1, 4 and 10.

Result

Out of the 529 elderly evaluated in the study, 286 were women, of which 112 (39,1%) had SCD, and 243 men, with 89 (36,6%) having SCD. The SCD group had a mean age of 69.8 years old and a mean of 8.4 years of education, contrasting with 68.3 years of age and 5.07 years of education among those without SCD. The mean age difference was statistically significant. The SCD group had a slightly lower mean dosage of IL‐1 and higher mean dosages of IL 4 and 10, IG and RCP, but only the latter reached statistical significance.

Conclusion

Our study represents a step further towards understanding the pathophysiology of SCD, as this preclinical condition could be a target of future early interventions for Alzheimer’s disease and other dementia syndromes.

References:

Jessen F, Amariglio RE et al. The characterisation of subjective cognitive decline. Lancet Neurol. 2020 Mar;19(3):271‐278. https://doi.org/10.1016/S1474-4422(19)30368-0.

Ng A et al. IL‐1β, IL‐6, TNF‐ α and CRP in Elderly Patients with Depression or Alzheimer’s disease: Systematic Review and Meta‐Analysis. Sci Rep. 2018 Aug 13;8(1):12050. https://doi.org/10.1038/s41598-018-30487-6.
Effect of APOE ε4 and its modification by sociodemographic characteristics on cognitive measures in South Asians from LASI‐DAD
Authors: Wang Yi Zhe , Zhao Wei , Dey Aparajit Ballav , Lee Jinkook , Smith Jennifer A , Kardia Sharon L R
Published: December 2023

Background

The ε4 allele of the apolipoprotein E (APOE) gene is the most significant genetic risk factor for dementia in nearly all human populations. However, the effects of APOE ε4 on late‐life cognitive function and its potential modification by sociodemographic factors have not been extensively studied in South Asians. We investigated the effects of APOE ε4 and its interaction with sociodemographic characteristics on cognitive measures in 2,607 South Asians from the Diagnostic Assessment of Dementia for the Longitudinal Aging Study of India (LASI‐DAD).

Method

We determined APOE ε4 carrier status from rs429358 and rs7412 genotypes in whole genome sequencing data. We first examined the main effects of APOE ε4 on seven cognitive measures, including five broad cognitive domain scores, a general cognitive function summary score, and the Hindi Mental State Examination (HMSE) score using linear regression models. Model 1 adjusted for age, sex, state of residence, and the first 10 genetic principal components (PCs). Model 2 additionally adjusted for education level, literacy, and urban/rural residence. We then tested for interaction between APOE ε4 and sociodemographic factors (age, sex, and education) through cross‐product terms, and further evaluated significant interactions (p<0.05) using stratified analysis.

Result

APOE ε4 was inversely associated with all cognitive measures except visuospatial function in the full sample in Model 1 after Bonferroni correction (p<0.007), all of which remained nominally significant in Model 2 (p<0.05). For example, APOE ε4 carrier status was associated with a decrease in the HMSE score of 0.77 points (p = 1.6×10−4) and a decrease in general cognitive function score of 0.09 standard deviations (p = 0.001) in Model 2. Furthermore, interaction tests showed that the effect of APOE ε4 was stronger in females than males for memory (ßAPOE ε4_male = ‐0.121, βAPOE ε4_female = ‐0.177) and language/fluency (βAPOE ε4_male = 0.075, βAPOE ε4_female = ‐0.125), and stratified analysis indicated that the APOE ε4 effects were significant only in females (p<0.05).

Conclusion

APOE ε4 is associated with lower cognitive function in older South Asians from India. For memory and language/fluency, this association is stronger in females than males.
Effect of age, sex, cognitive status and Apolipoprotein E genotype on plasma biomarkers of amyloid pathology
Authors: Hortsch Sayuri , Carboni Margherita , Kurka Hedwig , Kollmorgen Gwendlyn , Jethwa Alexander , Blennow Kaj , Fowler Christopher J , Laws Simon M , Doecke James D , Masters Colin L
Published: December 2023

Background

Plasma biomarkers of amyloid pathology may streamline the diagnostic pathway for patients with subjective cognitive decline, MCI, AD . The influence of age, sex, cognitive status, body mass index (BMI) and apolipoprotein E (APOE ε) genotype on phosphorylated‐tau‐181 (phospho‐tau‐181) and apolipoprotein E4 plasma biomarkers was explored.

Method

597 plasma samples (from the Australian Imaging, Biomarkers and Lifestyle cohort) were retrospectively analysed using the fully automated Elecsys® prototype plasma immunoassays for phospho‐tau‐181 and apolipoprotein E4 on the cobas e 601 and e 411 analysers (Roche Diagnostics International Ltd). A composite score was derived by combining phospho‐tau‐181 and apolipoprotein E4 results. Amyloid‐positron emission tomography (PET) visual read was the reference standard for defining amyloid status. The relationship between biomarker levels and potential influencing factors was assessed.

Result

Phospho‐tau‐181 and composite score were increased in samples from amyloid‐positive versus amyloid‐negative subjects and in dependence of cognitive status. The dependence of phospho‐tau‐181 and composite score on APOE ε genotype could largely be explained by the increased prevalence of amyloid positivity in APOE ε4 carriers compared with non‐carriers. A potential confounding relationship between sex and age and phospho‐tau‐181 or composite score was detected, which could not be fully explained by the increasing incidence of amyloid positivity with age. Apolipoprotein E4 was highest in APOE ε4 homozygotes, lower in heterozygotes and undetectable in non‐carriers.

Conclusion

A single cut‐off value for phospho‐tau‐181 and composite score may be used in clinical routine to determine amyloid pathology in the intended use population, regardless of age, sex and APOE ε genotype. Further evaluation is required in more diverse populations (comorbidities) and using additional biomarkers (β‐amyloid).
How does amyloid beta alter levels of ınflammation parameters in human astrocyte culture?
Authors: Şengül Büşra , Keskin Ebru , Dursun Erdinc , Gezen‐Ak Duygu
Published: December 2023

Background

In neurodegenerative diseases, specific neuron types and glial cells undergo degeneration leading to the appearance of specific disease symptoms (1). Neurodegenerative diseases in the central nervous system (CNS) are also highly effective on cells that support neuron life. Astrocytes are dynamic support cells that maintain brain balance, regulate the neurotransmitter system, process synaptic information, energy metabolism, antioxidant system, and inflammatory response (2). The blood‐brain barrier (BBB) may lose its permeability in pathological conditions. Both endothelial cells and astrocytes undergo phenotypic changes and become reactive (3). In Alzheimer’s disease (AD), amyloid beta (Aβ) is suggested to induce a pathological pathway that leads to neurodegeneration and dementia (4). A limited number of studies in the literature reveal a general profile of the neuroinflammatory mediators induced by Aβ, one of the main pathological elements of AD in human astrocytes.

Method

Based on this information, AD‐like pathology was created in our study with Aβ1‐42 treatment in human astrocyte cultures. The inflammatory response of these pathologies in human astrocytes was compared with the profile that emerges differently from a healthy astrocyte population. Alterations in the levels of released inflammatory proteins and their receptors were detected with the chemiluminescence‐based Western/dot blot method by using the human inflammation antibody array (Ray Biotech C‐Series Human Antibody Inflammation Array C4).

Result

Our data show that Aβ1‐42 treatment predominantly releases IL‐6, MCP‐1, and TIMP‐2 proteins into the culture supernatant in human astrocyte cells. On the other hand, whether reactive astrogliosis was triggered in the presence of Aβ in human astrocytes was followed by immunofluorescent labeling (IF).

Conclusion

This is the first study that investigated the general profile of released inflammatory factors in human astrocytes and how this profile is altered by Aβ1‐42 treatment.

(The present work was supported by the Research Fund of Istanbul University, Project no: 30666)
Microglia transcriptional heterogeneity across human and experimental models
Authors: Garg Anjali , Novotny Brenna C , D'Oliveira Albanus Ricardo , Brase Logan , Karch Celeste M. , Morris John C , Perrin Richard J. , Sutherland Greg T , Benitez Bruno A. , Harari Oscar
Published: December 2023

Background

The molecular data from multiple brain regions, cohorts, experimental models are seldom integrated comprehensively, although it provides a unique opportunity to study the cellular heterogeneity and molecular changes across AD etiology and progression. We have developed a new reference model to bridge across datasets.

Method

We leveraged single‐nuclei transcriptomic profiles (snRNA‐seq) of human microglia (parietal cortex from 67 donors from the Knight ADRC and DIAN brain banks; N = 15,726; Dataset1) [1], iPSC‐MLC CRISPRi/a‐based genetic screens in human iPSC‐derived microglia (N = 15,350; Dataset2) [2], and WT and R47H TREM2 xenografted microglia (xMGs), isolated from chimeric AD mice (N = 25,407; Dataset3) [3] to build a comprehensive atlas of microglia heterogeneity, that captures transcriptional states fairly well represented in each dataset. We employed Seurat v4 [4] to integrate the data, and scArches [5] to build classifiers.

Result

We identified homeostatic, activated, interferon (IFN), and IL1B clusters across datasets present in all data we had integrated. In addition, we identified MHCII. We observed that some of the clusters of original states were combined into single clusters. For example, CXCL10‐IFN and INF. We also observed that the integrated data shows a more distinctive expression profile of Type I+II IFN. Furthermore, we build a multiclassifier to label novel microglia generated from hundreds of samples, and data from various experimental models. The cross‐validation analyses indicate that the overall accuracy of the classifier (scArchers) is 0.85 (Fig. 1), although it changes for the distinct datasets [5]. For human microglia in Dataset1 the accuracy was 0.79, while for iPSC‐MLC was 0.73 and 0.96 for Dataset 3. Our results indicate that this multi‐model reference can capture subtle differences better that study‐centric analyses of the data.

Conclusion

We are repurposing microglia transcriptomic single‐cell data to build a cross‐species and experimental iPSC‐MLC to bridge across cohorts, species, and experiments. Our results, indicate that this new resource allows to simultaneously interrogate gene expression across different experiments and transcriptional states, and providing the foundation to integrate additional single‐cell molecular data from model organism, ATAC‐seq, and spatially resolved transcriptomics.

References: [1 https://doi.org/10.1101/2021.11.30.21267072; [2] PMID: 34301296; [3] PMID: 35953545; [4] PMID: 34062119; [5] PMID: 34462589
Determination of molecular chaperone levels in cerebrospinal fluids of Alzheimer’s patients
Authors: Sordu Pelin , Alaylıoğlu Merve , Samancı Bedia , Bilgiç Başar , Hanagasi Hasmet , Gurvit Hakan , Ulutin Turgut , Dursun Erdinc , Gezen‐Ak Duygu
Published: December 2023

Background

Molecular chaperones are a component of the protein homeostasis network and regulate the biogenesis, folding, and trafficking of proteins, protecting the proteome against misfolding, aggregation, and proteotoxicity [1]. Therefore, they serve as the first line of defense against toxicity caused by misfolded proteins such as Aβ and tau [2]. Amyloid precursor protein (APP) interacts with chaperones from the moments of microtubule‐associated protein tau (MAPT) production. These properties keep the molecular chaperones in close contact with many proteins within the cell, including proteins associated with Alzheimer’s disease (AD), such as APP and tau [3]. According to the data we obtained using the web‐based FpClass protein‐protein association (PPI) prediction program, which investigates protein‐protein interactions, we determined that the AD‐related proteins MAPT and APP strongly interact with the chaperone proteins HSP90AA1, CHIP (STUB1) and HSPA4. In light of this information, we thought these chaperone proteins could interact with Aβ and tau and exit the CSF together, and these chaperones could be used as a biomarker.

Method

Following this purpose, we determined the levels of HSP90AA1, STUB1, and HSPA4 chaperone proteins in CSF samples of AD, MCI, and FTD patients and individuals diagnosed with SCI using the ELISA method. Depending on the distribution of ApoE, any changes in CSF chaperone levels and co‐localization of these chaperones with MAPT and Aβ1‐42 were demonstrated by double‐immunofluorescence labeling in neuron‐differentiated human SH‐SY5Y cells. Within the scope of the study, these parameters included to be biomarkers that were investigated.

Result

CSF HSP90AA1 protein levels were increased in sporadic AD and FTD patients compared to controls, CSF HSPA4 protein levels were increased in sporadic AD patients compared to family history of AD patients, and CSF STUB1 protein levels were decreased in AD, MCI, and FTD patients compared to controls.

Conclusion

Considering the findings of our study, the presence of these chaperone proteins in CSF suggests that they may have an important place in the neuropathological processes of neurodegenerative diseases such as Alzheimer’s disease.

The present work was supported by the Research Fund of Istanbul University‐Cerrahpasa. Project No. 33638
Multimodal Neuromarkers Predict Successful Physical Activity Engagement in Older Adults with Vascular Disease
Authors: Thovinakere Nagashree , Lin Sue‐Jin , Baumeister Robert , Medina Yasser Iturria , Geddes Maiya R.
Published: December 2023

Background

Physical inactivity is a significant risk factor for cognitive decline, particularly in vulnerable populations including those with cardiovascular risk‐factors1. To better understand the mechanisms that support positive physical activity engagement, the current study aimed to evaluate whether neuromarkers can predict future change in physical activity among older adults with a newly diagnosed cardiovascular risk‐factor.

Method

We analyzed baseline resting‐state functional and structural magnetic resonance imaging (MRI) data from the UK‐Biobank, a large population longitudinal cohort (n = 365; mean age = 62.10 years ± 6.5; cognitively normal). Brain imaging was obtained at baseline, and physical activity data was obtained at baseline and follow‐up after 5 years. Inclusion criteria were a new diagnosis of a cardiovascular risk factor (hypertension, type‐II diabetes‐mellitus, dyslipidemia, cardiac angina or myocardial infarction) between baseline and follow‐up; and did not meet the World Health Organization recommended 150 minutes/week of moderate or 75 minutes/week of vigorous physical activity at baseline. Demographic variables including age, sex, and education were included as covariates of non‐interest.

To assess whether baseline resting‐state brain imaging predicts future change in physical activity behaviour, we performed a kernel‐ridge‐regression model with 5‐fold nested‐cross‐validation. Preprocessed neuroimaging data was used as input for the analysis, and the machine‐learning pipeline included feature reduction using grid‐search, hyperparameter selection, and model‐building: the model predicts whether test subject successfully increased physical activity engagement at follow up (reported above 150 min/week moderate or 75 min/week vigorous physical activity). Permutation‐testing (100 times) was performed before evaluating prediction metrics using accuracy and Receiver Operating Characteristic curves.

Result

Our prediction model delivered an accurate performance with average accuracy of 0.861 ± 3.8, and 0.883 ± 4.2 area under the curve (AUC) in predicting future behaviour change from physically inactive at baseline to physically active in follow up.

Conclusion

These results show baseline brain imaging can accurately predict physical activity behavior change in older adults with new cardiovascular disease. Leveraging machine‐learning methods to predict future lifestyle engagement will help characterize the neural mechanisms that support successful lifestyle change after a new cardiovascular diagnosis.

1. Gallen et al. Trends in Cog Sci. 2019
Blood‐based markers of neurodegeneration linked with brain atrophy and cognition in aging
Authors: Kalpouzos Grégoria , Magnusson Filip , Gustavsson Jonatan , Falahati Farshad , Papenberg Goran , Mangialasche Francesca , Vetrano Davide Liborio
Published: December 2023

Background

Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) have been linked to aging‐related brain tissue loss and cognitive decline, both related to neurodegeneration. Recently, NfL and GFAP have become quantifiable in blood; little is known about their association with brain structure in aging adults.

Method

Single‐Molecule Array (SIMOA) technology was used for ultra‐sensitive detection and quantification of NfL and GFAP in blood plasma at baseline in healthy volunteers (N = 102, 52 female, 52‐79 years old). These individuals also underwent magnetic resonance imaging twice, 3 years apart (N = 72 at follow‐up), and cognitive testing. We examined the relationships among NfL, GFAP, age, brain atrophy parameters (gray‐matter volume ‐ GMV, cortical thickness ‐ CT) and cognitive performance (composite score of episodic and working memory, executive functions and perceptual speed). The relationships between blood markers, GMV and CT were assessed using voxel‐ and surface‐based morphometry, cross‐sectionally and longitudinally, adjusting for age, sex and education.

Result

Older age was related to higher levels of NfL and GFAP (ps < .001; Figure 1). Cross‐sectionally, older age was related to lower GMV in the hippocampi and lateral middle temporal regions, and lower CT in lateral frontoparietal areas. Longitudinally, atrophy was located in fronto‐parieto‐temporal regions, more strongly in the left hemisphere (all ps < .05 Family‐Wise Error corrected). Controlling for age, sex, education and total intracranial volume, higher NfL levels were associated with lower volume in inferior temporal regions (cross‐sectionally), and with atrophy in right hippocampus (longitudinally) (p < .001 uncorrected; Figure 2). Higher GFAP levels were associated with lower volume and thinner cortex in frontoparietal regions, and atrophy in right frontal cortex (p < .001; Figure 2). After splitting the individuals as decliners and non‐decliners based on their cognitive‐performance changes, it was found that the negative associations between NfL and inferior‐temporal volume, and between GFAP and fronto‐temporal volume, were driven by the decliners (Figure 3).

Conclusion

Higher NfL or GFAP levels are related to atrophy, beyond age, in key regions known to be affected in neurodegenerative disorders, possibly indicating early neuropathological changes.
Using Virtual Reality to Assess Spatial Cognition in Subjective Cognitive Decline and Mild Cognitive Impairment due to Alzheimer’s Disease
Authors: Pai Ming‐Chyi
Published: December 2023

Background

Spatial navigation impairment (SNI) is prevalent in people with Alzheimer’s disease (AD) continuum and may appear in the initial clinical stage. To detect this deficit in people at risk may not only help to prevent getting lost or missing incidents, but also provide a useful clinical feature for diagnosis. Traditional assessments for SNI include questionnaires, paper pencil and maze tests, or video games. Although a real‐world setting is more valid, direct, and accurate, it has many unexpected conditions such as weather, obstacles, or accidents. Thanks to technology, virtual reality (VR) is a new way to assess SNI.

Method

We used PJVR to test spatial navigation ability in cognitively unimpaired (CU), subjective cognitive decline (SCD) and mild cognitive impairment due to AD (MCI‐AD). The PJVR is the VR version (Vive Pro Eye Head‐mounted Display, HTC) of the PJ device, which was developed by Pai and Jan and has been successfully verified its power to discriminate each other among CU, MCI, and mild AD. With a map provided and using joysticks or handles, participants were requested to reach five points in a 660‐meter path on our university campus. Linear deviation in meters in each point was treated as the variable for comparison. A pre‐test training course was given to facilitate the procedure.

Result

118 subjects signed informed consent and 87 (73.7%) completed the trials, including 18 CU, 41 SCD and 28 MCI‐AD. Fourteen, or 11.9%, of all participants failed the trials due to cybersickness. The averaged linear deviations of the CU, SCD and MCI‐AD were 36.1 (38.2), mean (S.D.), 40.8 (44.4), and 93.7 (46.8) meters respectively (p<0.000). The linear deviation of the PJVR of the participants was correlated with the Questionnaire on Everyday Navigation Abilities (p<0.001), indicating a good real‐world validity.

Conclusion

Although the rate of cybersickness is higher as compared with the reports from Western countries, most of the participants completed the trials. The PJVR is feasible to assess spatial cognition and able to discriminate CU/SCD from MCI‐AD. To simplify PJVR to be practical is important to welcome the era of digital cognitive assessment.
Ethnic Disparities in Clinical Presentation of Patients with Early‐Onset Alzheimer’s Disease
Authors: Yang Meredith , Yoon Suemin , Covaciu Rachel , Mastrianni James , Seibert Kaitlin
Published: December 2023

Background

Early‐onset Alzheimer’s Disease (EOAD) affects patients under age 65 and may present with non‐amnestic features. Black patients are half as likely as White patients to be diagnosed despite twice as many risk factors. Ethnic disparities in EOAD have not been fully characterized.

Methods

We retrospectively collected data on ethnicity, level of education, Montreal Cognitive Assessment (MoCA) scores on EOAD patients diagnosed between 2017 and 2022 at The University of Chicago Memory Center.

Results

Of 88 total patients, 60 (68.8%) identified as White and 28 (31.8%) identified as Black. Age at diagnosis was 57.3 ± 5.24 years in Black patients compared to 55.9 ± 5.69 years In White patients. Average time to diagnosis was longer in Black patients (5 ± 9.21 yrs.) vs White patients (3.5 ± 6.44 yrs). Black patients had lower MoCA scores than Whites at presentation (12.17 ± 6.91 vs 15.15 ± 5.92), despite similar education levels among Black vs. White patients (14.71 ± 2.30 vs 15.21 ± 3.00).

Black patients more commonly displayed an amnestic profile (19 or 67.9%) than a non‐amnestic presentation (9 or 32.1%), although 2 patients (7.14%) presented with visual symptoms suggestive of posterior cortical atrophy (PCA), 5 (17.9%) patients had prominent language symptoms suggestive of logopenic primary progress aphasia (l‐PPA) and 1 (3.6%) patient had an executive presentation, suggestive of executive variant of AD (EAD). In White patients, 11 (18.3%) were diagnosed with PCA, 10 (16.7%) with EAD and 8 (13.3%) with l‐PPA.

Differences were noted in the application of diagnostic tests, in that neuropsychological testing (NPT) and CSF testing were less often ordered in Black patients (NPT: 8 (29%) in Blacks vs 45 (75%) Whites, p = 0.001; CSF: 4 (14%) Blacks vs 30 (50%) Whites, p = 0.002).

Conclusion

In our cohort, Black patients with EOAD were on average older, more advanced, and experience longer delays and differences in diagnostic management than their White counterparts. Further work is needed to characterize the barriers to diagnosis for Black patients with EOAD and the potential differences in clinical presentations.
FedExosome: profiling AD‐related mitochondrial DNA and microRNAs isolated from neuronal‐enriched peripheral blood packages
Authors: Hall Courtney , Garlotte Isabelle , Subasinghe Kumudu , Barber Robert , Phillips Nicole
Published: December 2023

Background

Alzheimer’s disease (AD) is a complex disease characterized by impaired memory, diminished cognition, and specific brain pathology (i.e., accumulation of amyloid beta plaques and tau tangles). AD progression is often difficult to detect with the earliest clinical symptoms appearing decades after key neuropathological changes have occurred. Accurate diagnosis early, between initial disease onset and clinical manifestation, could reveal critical aspects of pathogenesis and inform the development of effective therapeutic strategies to prevent neuronal death. Evidence suggests that early alterations in the AD brain can propagate to local and distal cells through the biological packages secreted by neurons. These neuronal‐enriched extracellular vesicles (NEEVs) can cross the blood‐brain barrier and are capable of mediating systemic inflammation in response to CNS‐sourced stress through their mitochondrial DNA (mtDNA) and microRNA (miRNA) cargo. Circulating NEEVs may therefore serve as an easily accessible, early indicator of the forthcoming neuropathological changes in the AD brain. Here, we develop a higher throughput workflow for profiling mtDNA and miRNA in plasma NEEVs and apply the workflow to clinical samples collected longitudinally from participants in the Texas Alzheimer’s Research and Care Consortium.

Method

Human plasma samples were processed using a two‐step method involving (1) precipitation of total exosomes with ExoQuick (SBI) and (2) immunoprecipitation‐based enrichment of NEEVs with a biotinylated antibody against a well‐established neuronal surface marker (CD171). Captured NEEVs were stained and analyzed using flow cytometry as well as nanoparticle tracking analysis (NTA). DNA and RNA were then extracted for mtDNA quantification and miRNA sequencing.

Result

The protocol modifications implemented in this project were compared based on particle size, distribution, and purity as well as absolute mtDNA load and spike‐in normalized miRNA read counts. These data not only demonstrate the feasibility of profiling the mtDNA and miRNA from 500µL of plasma NEEVs but have also resulted in a higher throughput workflow for processing TARCC patient samples.

Conclusion

This work represents the first successful attempt to simultaneously quantify mtDNA and sequence miRNA in the relatively small subpopulation of plasma EVs that originate from neurons. Future studies will harness the protocol developed herein to assess the biomarker potential of NEEVs in the TARCC cohort.
Tissue inhibitor of matrix metalloproteinases 4: a novel marker associated with CAA
Authors: Jäkel Lieke , Stellingwerf Arno , Kort Anna M. , Kusters Benno , Schreuder Floris H.B.M. , Klijn Catharina J.M. , Kuiperij H. Bea , Verbeek Marcel M.
Published: December 2023

Background

We have previously shown that matrix metalloproteinase 9 (MMP9) and tissue inhibitor of proteinases 3 (TIMP3) are specifically expressed in the vasculature of patients with cerebral amyloid angiopathy (CAA). Moreover, we have demonstrated increased MMP9 and decreased TIMP3 levels, as well as an altered MMP9:TIMP3 ratio in the vasculature of CAA patients that suffered from intracerebral haemorrhages (CAA‐ICH) compared to CAA patients without ICH (CAA‐nonICH). We now extended our studies to investigate whether TIMP4 may have a similar role in CAA, as this has not been studied before.

Method

Using immunohistochemistry, we studied occipital lobe tissue of 44 controls (mean age 78.4 years; 50% female) and 58 CAA patients (77.5 years; 55% female; 40 CAA‐nonICH and 18 CAA‐ICH). Vascular TIMP4 staining was scored in a semiquantitative manner. Using ELISA, we measured TIMP4 CSF levels of 33 CAA patients (mean age 72.2 years; 47% female) and 35 controls (mean age 71.2 years; 51% female). For a subset of CSF samples (11 CAA samples and 14 controls), the levels of MMP2, MMP9, and MMP14 have been determined previously, and now their ratios to TIMP4 were calculated. Differences between CAA patients and controls were assessed using (ordinal) linear regression analysis.

Result

In brain tissue, CAA cases had increased vascular TIMP4 expression when compared to controls (p = 0.00002, figure 1). TIMP4 expression did not differ between CAA‐nonICH and CAA‐ICH cases. In the absence of vascular TIMP4 staining, we often observed perivascular staining. Decreased levels of perivascular TIMP4 staining were observed in CAA‐ICH cases when compared to CAA‐nonICH cases (p = 0.045) and to controls (p = 0.035). CSF levels of TIMP4 were decreased in CAA patients compared to controls (p = 0.03, figure 2). In addition, the ratios of MMP2 (p = 0.038), MMP9 (p = 0.005), and MMP14 (p = 0.025) to TIMP4 were increased in CAA patients compared to controls.

Conclusion

We demonstrated increased TIMP4 expression in vessel walls of CAA patients compared to controls. In contrast, TIMP4 CSF levels were decreased in CAA patients compared to controls, whereas MMP:TIMP4 ratios were increased, indicating a disbalance of MMP/TIMP4 levels in CAA pathophysiology.

Funding: BIONIC project (no. 733050822, ZonMW) and CAFÉ project (no. 5R01NS104147‐02, NIH).
Association between blood pressure and Alzheimer’s disease biomarkers in cognitively unimpaired adults
Authors: Osset Mariona , Sánchez‐Benavides Gonzalo , Buongiorno Mariateresa , Sierra Alejandro De La , Shekari Mahnaz , Minguillon Carolina , Kollmorgen Gwendlyn , Carboni Margherita , Zetterberg Henrik , Blennow Kaj , Suarez‐Calvet Marc , Gispert Juan Domingo , Grau‐Rivera Oriol ,   for the ALFA study
Published: December 2023

Background

High blood pressure is an established risk factor for dementia. However, the underlying mechanisms are not completely understood. We aimed to evaluate the association between blood pressure and Alzheimer’s disease (AD) biomarkers in cognitively unimpaired adults from the ALFA+ study.

Method

We analyzed data from 301 participants with available cross‐sectional blood pressure measures (acquired by trained staff with an oscillometric device after 5 minutes of rest) and cerebrospinal fluid (CSF) AD core biomarkers data (CSF p‐tau and t‐tau were measured with Elecsys® immunoassays and CSF Aβ42 and Aβ40 with the Roche NeuroToolKit, a panel of robust prototype assays, both from Roche Diagnostics International Ltd), and a subset of 278 participants with amyloid PET data, of whom 110 had a second follow‐up PET acquisition (3.4 years after in average). We used separate linear regression models to analyze the association of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP = SBP‐DBP) with CSF and PET biomarkers at a cross‐sectional level, and their association with the annualized rate of change in amyloid PET [(follow‐up centiloids – baseline centiloids) / years between PET scan acquisition]. We adjusted all models by age, sex, APOE status, waist‐to‐hip ratio, dyslipidemia, diabetes, tobacco and alcohol consumption, physical activity, and antihypertensive treatment.

Result

Higher baseline SBP (but not DBP or PP) was significantly associated with increased amyloid PET uptake over time (p = 0.043). In cross‐sectional analyses, DBP was negatively associated with Aβ42 (p = 0.013), Aβ40 (p = 0.026), and t‐tau (p = 0.045), and marginally associated with p‐tau (p = 0.069), but not with the Aβ42/40 ratio nor baseline amyloid PET uptake. Associations with Aβ42 and t‐tau were no longer significant after further adjustment by CSF Aβ40 levels. SBP and PP were not associated with CSF biomarkers or baseline amyloid PET uptake.

Conclusion

Higher SBP is associated with longitudinal brain amyloid accumulation, which reinforces the importance of blood pressure control in AD prevention. DBP is also associated at a cross‐sectional level with AD biomarker concentration in CSF, but the attenuation of this association after adjusting by Aβ40 suggests a non‐specific.
Deep Learning Based Estimation of Synthetic Tau PET from Amyloid PET
Authors: Naseri Maryam , Carmichael Owen T.
Published: December 2023

Background

Alzheimer’s disease (AD) is the most common pathological substrate for dementia. Both tau and amyloid positron emission tomography (PET) scans are valuable for evaluating innovative treatments and studying AD progression. However, tau‐PET is extremely expensive and not universally available. Estimating tau‐PET images from amyloid‐PET would mitigate these concerns. In this study, we proposed a novel application of the Conditional Generative Adversarial Network (cGAN) framework to generate high quality tau‐PET (18F‐flortaucipir) scans from the corresponding amyloid‐PET (18F‐florbetapir) scans.

Method

A dataset of 475 individuals who underwent both 18F‐florbetapir and 18F‐flortaucipir scans with different clinical diagnosis (Table 1) were used in our study from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) online depository. Our cGAN model was trained for 50 epochs using real, corresponding amyloid‐tau PET pairs. The resulting model takes real amyloid‐PET images as input and outputs synthetic tau‐PET images (Figure 1.a). The similarity between synthetic and real tau‐PET images was evaluated via the structural similarity index (SSIM), peak signal to noise ratio (PSNR), and normalized root mean squared error (NRMSE). Furthermore, we extracted regional standard uptake value ratios (SUVRs) and meta‐region of interest (ROI) SUVRs from the real tau‐PET scans and synthetic tau‐PET scans. The utility of the synthetic tau‐PET meta‐ROI SUVR for identifying real tau‐PET scans that are tau positive was evaluated in terms of true positive rate (TPR), false positive rate (FPR), and the area under the receiver operating characteristic (ROC) curve (AUC).

Result

Our cGAN model yielded a SSIM of 0.917, a PSNR of 27.04, and a NRSME of 0.18 on the test set. The ROC curve analysis (Figure 2) resulted in an AUC of 0.84%. By applying a cut‐off threshold corresponding to the model optimal operating point, a TPR of 90% and FPR of 28% were achieved. The SUVR analysis yielded a mean absolute percentage error of 8.3% ± 6.5% on the test dataset.

Conclusion

The proposed cGAN model generated high quality 18F‐flortaucipir PET images from 18F‐florbetapir PET images (Figure 1.b). This could be highly useful in a screening paradigm to use amyloid‐PET to identify those individuals most likely to be tau positive.
Neurite‐based white matter alterations in MAPT mutation carriers: A multi‐shell diffusion MRI study in the ALLFTD consortium
Authors: Corriveau‐Lecavalier Nick , Tosakulwong Nirubol , Lesnick Timothy G. , Reid Robert I. , Schwarz Christopher G. , Senjem Matthew L. , Jack Clifford R. , Jones David T. , Vemuri Prashanthi , Rademakers Rosa , Ramos Eliana Marisa , Geschwind Daniel H. , Knopman David S. , Botha Hugo , Savica Rodolfo , Radford Jonathan Graff , Ramanan Vijay K , Graff‐Radford Neill R , Wszolek Zbigniew , Forsberg Leah K. , Petersen Ronald C. , Heuer Hilary W. , Boxer Adam L. , Rosen Howard J. , Boeve Brad F. , Kantarci Kejal
Published: December 2023

Background

We aimed to assess axonal integrity in MAPT mutation carriers and early white matter (WM) neurodegeneration in asymptomatic carriers using traditional diffusion tensor imaging (DTI) measurements, i.e., fractional anisotropy (FA) and mean diffusivity (MD), and neurite orientation dispersion and density imaging (NODDI).

Method

We included available multi‐shell diffusion MRI data from 21 MAPT mutation carriers (16 asymptomatic; 5 symptomatic) and 31 non‐carrier family members as controls from the ALLFTD consortium. We used linear mixed‐effect models to assess WM abnormalities measured with FA and MD, neurite density index (NDI) and orientation dispersion index (ODI), combined across hemispheres. Separate models were conducted in all MAPT mutation carriers relative to controls while accounting for relatedness and age, then in symptomatic and asymptomatic carriers relative to controls. ComBat was used to harmonize data across sites.

Result

In models contrasting all MAPT carriers versus controls, WM alterations involved the cingulum bundle (FA, ODI), fronto‐temporal, entorhinal (FA, MD, NDI), and the inferior temporal WM (FA) after correcting for multiple comparisons (Fig. 1). In models contrasting symptomatic and asymptomatic MAPT carriers versus controls, symptomatic carriers had widespread involvement of the fronto‐temporal WM including the cingulum (FA, ODI), entorhinal (MD, FA, NDI), amygdala (MD, NDI) and inferior temporal (FA) areas after correcting for multiple comparisons. Asymptomatic carriers showed higher entorhinal MD and lower inferior temporal and cingulum FA relative to controls, and a more widespread pattern of higher ODI involved the medial temporal, superior temporal and occipital WM as well as long association and projection fibers including the internal capsule, cingulate bundle and fronto‐occipital fasciculi, although they were not statistically significant after correction for multiple comparisons.

Conclusion

Traditional DTI and novel NODDI measurements revealed some extent of overlap as well as divergences in patterns of WM abnormalities, indicating axonal loss is a feature of neurodegeneration in MAPT mutation carriers. Our results suggest that traditional DTI and novel NODDI measurements may have different sensitivities to WM alterations in MAPT mutation carriers, and that axon‐based metrics, particularly ODI measurements, may be more sensitive to the early WM involvement during the asymptomatic stage of the disease.
Robot‐Administered Serious Brain Games for Older Adults with Mild Cognitive Impairment or early‐stage Alzheimer’s Disease: A Pilot Study
Authors: Mahoor Mohammad , Abdollahi Hojjat , Donis Stephanie Melgar , Chileshe Lombe , Pittman Daniel , Emamian Eshrat
Published: December 2023

Background

Traditional methods for disease management have shown limited success treating AD/ADRD or mitigating its symptoms. Innovative technology such as Artificial Intelligence and Socially Robots, have begun to alleviate the growing need for novel solutions for AD/ADRD. While Socially Assistive Robots (SAR) are used to interact with patients with dementia or other mental disorders, to our knowledge, no such cooperative social robots have been studied to co‐play serious brain games with older adults with MCI or early‐stage AD/ADRD.

Method

The study involved 20 older adults (average age: 77.7; std: 6.43; 15 female) living in a care facility who were diagnosed with MCI or Early‐Stage ADRD (SLUMS 10‐25). They participated in 12 different games (e.g., Words, Picture Puzzle, Ryan Runs, Flow Control, Birds, Checkers, Solitaire, Birds Count, etc.) with a social companion robot named Ryan, every day for 8‐10 weeks. These games aimed to improve memory, cognitive function, and physical activity. Each participant had a Ryan device in their apartment and were trained on how to use it. The study collected data on usage time, win/loss rate, difficulty level, average score, and average duration per game, as well as depression screening (PHQ‐9) and SLUMS scores before, during, and after the study.

Result

Participants in the study spent 887 hours using Ryan. They spent 254 hours (28.7%) playing games on Ryan. On average they spent 12 minutes (std = 5 minutes) per day playing serious games with Ryan. Checkers, Flow Game, Picture Puzzle, Solitaire, and Word Puzzle, were the most popular games among all. On average, the SLUMS and PHQ‐9 scores improved by 3.3 and 2.43 points, respectively.

Conclusion

Our study also shows that on average, participants performed better over time in playing the games. For example, the average Win Rate or Scores of the participants in playing the Flow Game, Word Puzzle, improved over the weeks by about 0.5% and 29 scores, every week, respectively. That means participants were more engaged in playing those games and were able to focus and increase their score or win rate over time.