bluuebunny/crossref_metadata_2025 huggingface dataset:
Adjusting for CSF Reference Proteins Improves Biomarker Accuracy
Authors: Karlsson Linda , Arvidsson Ida , Åstr Kalle , Janelidze Shorena , Palmqvist Sebastian , Stomrud Erik , Mattsson‐Carlgren Niklas , Hansson Oskar
Published: December 2023

Background

CSF biomarkers are key AD descriptors, but the CSF volume as well as the production and clearance rates of proteins varies in individuals. Adjusting for reference proteins, which reflect these factors, might improve the accuracy of CSF biomarkers, similar to when normalizing CSF Aβ42 levels to Aβ40 levels. For other biomarkers, individual CSF dynamics are seldom adjusted for, which may result in disagreement with other techniques (e.g., PET). Additionally, this may contribute to inaccurate conclusions about CSF protein correlations that mainly exist due to high or low CSF dilution levels. The aim of this work is therefore to establish the use of CSF reference proteins to improve CSF AD biomarker accuracy.

Method

We used measurements of 2944 CSF proteins in the Swedish BioFINDER‐2 cohort (n = 982, 80% train and 20% test). Reference protein candidates (reflecting CSF dilution levels without being related to any disease) were searched for in a data‐driven manner, using t‐distributed stochastic neighbor embedding (t‐SNE) and a semi‐supervised K‐means clustering algorithm. The final candidate proteins were evaluated in logistic regression models, using CSF P‐tau181 and CSF Aβ42 as main predictors of tau‐PET and amyloid‐PET, respectively.

Result

Most proteins were associated with an individual dilution level, although at different strengths (Fig 1 and Fig 2e). From the different colorings of the t‐SNE space, proteins of similar expressions were placed nearby, creating areas of extra interest (yellow areas in subfigures 2c‐2h). The semi‐supervised K‐means algorithm highlighted an area (cluster 11) containing proteins with superior reference protein characteristics, from which single reference protein candidates were identified. All examined references (e.g., Aβ40, NTRK3, NTRK2, BLMH,CBLN4, PTPRN2 or PTPRS) outperformed using no reference for both the P‐tau181 and Aβ42 model (Figure 3). For P‐tau181, highest performance was achieved using CBLN4 (AUC = 0.944). For Aβ42, Aβ40 performed best as reference (AUC = 0.992).

Conclusion

The individual CSF dilution level affects many CSF proteins. We describe several novel and previously suggested CSF reference proteins, which can significantly improve the accuracy of CSF biomarkers as key AD descriptors.
A randomized, double‐blind, placebo‐controlled phase 1b study to evaluate the safety, tolerability, and pharmacodynamics of an anti‐amyloid‐β antibody SHR‐1707 in patients with mild cognitive impairment and mild Alzheimer’s disease
Authors: Shi Jiong , Cheng Zhaozhao , Lv Xinyi , Wang Qiong , Ye Zi , Qiu Hongyan , Zhu Mengyuan , Feng Sheng , Wang Yuqi , Cheng Gang
Published: December 2023

Background

SHR‐1707 is a humanized monoclonal antibody against amyloid‐β (Aβ). Pharmacodynamic studies in vitro showed that SHR‐1707 is more potent than lecanemab. SHR‐1707 had similar affinity to Aβ fibrils and protofibrils and relatively higher affinity to Aβ monomers than lecanemab. In 5xFAD transgenic mouse model of Alzheimer’s disease (AD), SHR‐1707 safely reduced brain Aβ deposition and ameliorated memory deficits. Phase 1 studies in China (NCT04973189) and Australia (NCT04745104) had demonstrated the safety and tolerability of SHR‐1707 in healthy young adults and elderly subjects at up to 60 mg/kg. The preclinical and clinical evidence support further development of SHR‐1707. Hence, we designed a phase 1b trial of SHR‐1707 to evaluate the safety, effective dosage, and effects on brain Aβ deposition in patients with mild cognitive impairment (MCI) due to AD or mild AD.

Method

This is a randomized, double‐blind, dose‐escalation, placebo‐controlled phase 1b study (NCT05681819; Figure 1). Patients with MCI due to AD or mild AD aged 55‐85 years will be randomized to placebo or intravenous SHR‐1707 at escalated doses of 5, 10, 20, and 40 mg/kg every 2 weeks for 26 weeks. Randomization will be based on the treatment to placebo ratio of 3:2 for 5 mg/kg dose group (N = 5, ≥3 ApoE ε4 carriers) and 10:2 for the remaining dose groups (for each group: N = 12, ≥5 ApoE ε4 carriers). In the following open‐label extension study, all patients will be assigned to SHR‐1707 for 52 weeks. The primary objective is to assess the safety and tolerability of 26‐week treatment of SHR‐1707. Secondary objectives are to assess effects on brain Aβ deposition by positron‐emission tomography, pharmacokinetic and pharmacodynamic profiles in blood and cerebrospinal fluid, immunogenicity, and clinical efficacy with 26‐week treatment of SHR‐1707; and long‐term safety, tolerability, and effects on brain Aβ deposition with 78‐week treatment. Figure 2 lists all study endpoints.

Result

The study is ongoing in China. Topline results are expected in Q1 2024.

Conclusion

This trial will obtain safety, tolerability, pharmacokinetics, pharmacodynamics, immunogenicity, and clinical efficacy data of SHR‐1707 to support advancement to confirmatory phase 2 or 3 studies in patients with MCI due to AD and mild AD.
Development of Clinical Trial Simulation Tools for Alzheimer’s Disease through the Critical Path for Alzheimer’s Disease (CPAD) Consortium
Authors: Sivakumaran Sudhir , Cullen Nicholas , Lau Corissa , Priest Eileen , White Hazel , Irizarry Michael C. , Romero Klaus , Karten Yashmin
Published: December 2023

Background

Optimized clinical trial design remains a major challenge in drug development for Alzheimer’s Disease AD). To advance our understanding of the underlying pathophysiology of disease and help optimize clinical trial design, CPAD developed a clinical trial simulation (CTS) tool for the pre‐dementia stages of Alzheimer’s disease, using CDR‐SB as the primary endpoint. The tool is based on a disease progression model integrating baseline hippocampal volume, the effect of patient drop‐out and relevant sources of variability. The CTS was enhanced using data from contemporary clinical trials, adding fluid and imaging biomarkers of amyloid (Aβ) and tau pathology. Also included are dropout models, a placebo effect model, as well as drug‐effect models. Positron Emission Tomography (PET) measures of tau deposition, leveraging ongoing collaborative efforts to develop a standardized quantification scale across different tau tracers, will also be incorporated, to develop the first disease progression models utilizing a harmonized tau‐PET scale.

Method

Data were harmonized and both linear and non‐linear mixed effects models were developed for multiple endpoints, including demographics, time from and to diagnosis, genetic status (APOE4). Monte Carlo simulations were performed to compare the statistical power by sample size in trials with and without enrichment using relevant covariates. A longitudinal mixed‐effects model was fit with longitudinal tau and neurodegeneration outcomes. Cognition and biomarkers were explored in a multivariate model.

Result

As of October 2022, CPAD’s clinical trial repository contains over 7,000 unique participants that have baseline CDR‐SB measurement, 4,000+ participants with baseline Aβ measures (fluid or PET), and 2,000+ participants with baseline measures of amyloid, tau (e.g., cerebrospinal fluid p‐tau and/or tau‐PET), and neurodegeneration (e.g., MRI or neurofilament light). With these data, we modeled longitudinal trajectories of cognitive decline using baseline levels of amyloid, tau, and neurodegeneration. Future work will add models of longitudinal biomarker trajectories.

Conclusion

The disease progression models will serve as the basis for a clinical trial simulation tool to facilitate design of contemporary clinical trials based on a quantitative understanding of the biological progression of key pathological features, amyloid and tau deposition, of AD.
A generalizable unsupervised graph‐based approach for anomalous event detection in people living with dementia
Authors: Bijlani Nivedita , Nilforooshan Ramin , Maldonado Oscar Mendez , Kouchaki Samaneh
Published: December 2023

Background

Sensor‐based remote health monitoring of persons living with dementia (PLwD) can be used to monitor the progression of their condition with minimal intrusion. This helps minimize preventable hospital admissions, while allowing researchers to improve their understanding of dementia. Existing approaches for detecting anomalies in activity and behavior in PLwD are challenged by data noise, drift, label reliance, and poor explainability and generalizability due to wide inter‐individual variability.

Method

We propose and evaluate a solution that combines graph learning with the Contextual Matrix Profile (CMP), an ultra‐fast distance‐based discord detection technique. Daily household movement data collected via passive infrared sensors are used to generate multivariate CMP. This is encoded as a set of time‐evolving graphs. A self‐supervised graph model is trained to separate graphs by distance, so discordant time blocks show up as anomalous graphs. Differences between successive graph embeddings are subject to moving average thresholding to detect anomaly. We compare our method to four state‐of‐the‐art outlier detection algorithms, and demonstrate the generalizability of a distance‐based graph model trained on one cohort, to anomaly detection in unseen individuals.

Result

Graph‐enhanced CMP models outperform state‐of‐the‐art algorithms, yielding 74% recall with a 5.7% alert rate and 88% household‐level validity when evaluated on 13,426 days’ data from 42 households with 145 agitation events, collected by the UK Dementia Research Institute between August 2019 and April 2022. Similar results are obtained for a 23‐participant, 5284‐day Falls cohort: 72% recall, 5.85% alert rate and 83% household‐level validity. Pretrained models yield similarly high performance for unseen households in both cohorts. Experiments on the publicly available PAMAP dataset reveal superior top‐k alert performance. Explainability is achieved via the CMP that is the source for graphs.

Conclusion

We address the need for generalizable anomaly detection models for multivariate time series sensor data in remote health monitoring. While the CMP allows the ability to denoise and detect patterns at a household level, a graph model constructed in the distance space is generalizable across households. With higher sensitivity, fewer alerts than state‐of‐the‐art methods and inherent explainability, graph‐CMP models offer a clinically meaningful unsupervised anomaly detection technique for dementia and beyond.
Human and mouse seeds differentially affect Aβ aggregation by modulating the inflammatory response
Authors: Andreo‐Lopez Juana , Cantero‐Molina Francisco , Bettinetti‐Luque Miriam , Huynh Kelly Do , Nguyen Marie Minh Thu , Cheung Alwin , Tran Janine Pham , Da Cunha Celia , Trujillo‐Estrada Laura , Nuñez‐Diaz Cristina , Martini Alessandra Cadete , Forner Stefania , Gutierrez Antonia , LaFerla Frank , Baglietto‐Vargas David
Published: December 2023

Background

Alzheimer’s Disease (AD) is a neurodegenerative proteinopathy in which Aβ can misfold and aggregate into seeds that structurally corrupt native proteins, mimicking a prion‐like process. These amyloid aggregation and propagation processes are influenced by three factors: the origin of the Aβ seed, time of incubation and host. However, the mechanism underlying the differential effect of each factor is poorly known. Previous studies have shown that the Aβ source is relevant for the amyloid process, since its pathogenicity is different according to its origin. Furthermore, recent evidence suggests that microglia plays a key role in the amyloidogenic event, and can modulate the propagation and aggregation process. Here, we seek to perform a comparative study to determine whether Aβ seeds from humans vs a familial AD line (the 3xTg‐AD model) are more efficient to generate amyloid aggregates, as well as the role of the microglia in the propagation process.

Method

Amyloid seeds from AD patient (stage C for amyloid; from the Alzheimer’s Disease Research Center at UCI) and 25 mo‐3xTg‐AD mice were injected into the hippocampus of 7‐8‐month‐old 3xTg‐AD mice. They were analyzed 10 months post‐surgery for amyloid and microglia markers.

Result

Our findings demonstrated that amyloid seeds from the human patient seem to induce a more aggressive amyloid pathology compared to seeds from aged 3xTg‐AD mice. Moreover, human and mice seeds differentially affect the presence of plaque‐associated microglia in 3xTg‐AD mice.

Conclusion

These results suggest that seeds from human patients seem to be more amyloidogenic than from aged 3xTg‐AD mice, and also microglia cells may play a key role in this differential effect. Therefore, more profound understanding these factors will provide key insight on how amyloid pathology progresses in AD.

Grant support: This study was supported by Minister of Science and Innovation grant PID2019‐108911RA‐100 (D.B.V.), Alzheimer’s Association grant AARG‐22‐928219 (D.B.V), Beatriz Galindo program BAGAL18/00052 (D.B.V.) and Institute of Health Carlos III (ISCiii) grant PI18/01557 (A.G.) co‐financed by FEDER funds from European Union.
Wisconsin Longitudinal Study (WLS), the Initial Lifetime’s Impact on Alzheimer’s Disease (WLS‐ILIAD): A Novel Opportunity to Study the Influence of Education on ADRD
Authors: Lange Kate , Williams Victoria J. , Strait Brittani J , Fischer Anne M , Herd Pamela , Asthana Sanjay
Published: December 2023

Background

The importance of education in shaping brain health and dementia risk are increasingly supported, although the mechanisms by which these life course factors impact late life cognition remain elusive due to a scarcity of full life‐course longitudinal studies. A new data collection wave of the Wisconsin Longitudinal Study (WLS), the Initial Lifetime’s Impact on Alzheimer’s Disease (WLS‐ILIAD), stands to address this gap. The WLS cohort is a randomly selected community sample that’s been followed since 1957, offering a wealth of prospectively collected lifespan data to pull from. Now that this cohort has reached their 80’s, the ILIAD study aims to detect dementia prevalence in this sample, and when combined with prior data waves, offers an unparalleled opportunity to explore how full life‐course and sociodemographic factors shape the relationship between education and dementia risk and resilience.

Method

WLS‐ILIAD employs a multi‐phasic study design. In Phase 1, the modified Telephone Interview for Cognitive Status (TICS‐m) was administered to all eligible participants to screen for dementia risk. Those performing below cutoff (TICS‐m≤28) were selected for Phase 2 to complete more robust cognitive assessment and to obtain comprehensive health history. Cognitive diagnoses were determined by multidisciplinary consensus panel. Proxy assessments were employed for participants who were deceased or unable to complete the assessment.

Result

Preliminary results indicate a response rate of ∼78%. Approximately 4,800 participants completed Phase 1, with 1,227 (26%) falling below cutoff for dementia risk (TICS‐m≤28). Of those completing Phase 2, 460 participants were classified as normal cognition, 443 mild cognitive impairment (MCI), and 197 dementia. Another 300 dementia cases were identified via proxy. Participants diagnosed with MCI or dementia tended to be older, ApoeE‐4 allele carriers, and had a lower high school IQ. Of those diagnosed with dementia, 88% reported no prior clinical workup or existing cognitive diagnosis.

Conclusion

Results of the WLS‐ILIAD study yields detailed cognitive diagnostic classifications for this sample. When combined with prospectively collected life course data, the WLS cohort offers a unique opportunity to explore the impact of education on risk and resilience factors for dementia outcomes, leading to important public policy and public health implications.
The decline of quantitative EEG goes along with neuropathology in Alzheimer’s Disease
Authors: Poloni Tino Emanuele , Negro Giulia , Cassini Paola , Profka Xhulja , Rossi Michele , Davin Annalisa , Ferrari Riccardo Rocco , Terzoli Valeria , Guaita Antonio , Ceroni Mauro , Medici Valentina
Published: December 2023

Background

Few studies investigate the correlation between the quantitative EEG (QEEG) and the neuropathological picture. The purpose of this study is to explore how QEEG can recognize the type and extent of neuropathological changes.

Method

The EEG traces and brains belonging to 14 donors of the Abbiategrasso Brain Bank were analyzed. The subjects suffered from neurocognitive disorders due to AD, LBD or AD/vascular lesions (mixed dementia‐MD), with different stages of clinical and neuropathological severity. Clinical and neuropathological characterization was performed according to our protocol; biochemical measurements to determine the amount of proteinopathies are in runtime on frozen samples. QEEG analysis considered the relative power distribution (RPD) of the frequency bands (β, α, θ, δ) and the peak frequency (PF), i.e. the most represented frequency considering all the leads. The PF was measured every 2 seconds for 200‐400 samples, and then averaged. The Kruskall‐Wallis test was used for the comparison between groups.

Result

The clinical diagnosis included: 2 MCI, 4 AD, 6 MD, and 2 LBD. The neuropathological definite diagnosis demonstrated frequent co‐pathologies, and some discrepancies compared to the clinical diagnosis. The neuropathological characterization identified 2 cases with low AD pathology (corresponding to the 2 MCI), 8 cases with intermediate or high AD pathology (4 MD with concomitant cerebrovascular disease), and 4 cases with prevalent LBD pathology. Considering both clinical and neuropathological diagnoses, the comparison between groups revealed no significant differences in QEEG parameters. Nonetheless, a trend emerges towards a lower β‐RPD and a higher θ‐RPD in cases with prevalent LBD pathology. Grouping based on the severity of AD pathology (2 low, 4 intermediate, 4 high) demonstrated significant differences depending upon the neuropathological scoring with a progressive decrease of α‐RPD (p = 0.029) and PF (p = 0.019), and an increase of δ‐RPD (p = 0.020).

Conclusion

RPD and PF show low discriminatory capacity on etiology. Nonetheless, the presence of LBD seems to boost the EEG slowing. The PF slowing down parallels the increase of AD pathology, representing an indicator for the degenerative load. PF is a simple QEEG parameter, easily obtainable through standard digital EEG; it can be useful for monitoring neurodegenerative burden and disease evolution.
Predicting Poor Sleep in People Living with Dementia: An Analysis of In‐Home Activities and Physiology Measurements During the Daytime
Authors: Chen Yu , Nilforooshan Ramin , Barnaghi Payam
Published: December 2023

Background

The use of Internet of Things (IoT) technologies can help with remote monitoring of People Living With Dementia (PLWD) at their homes, ensuring effective and prompt provision of healthcare services. This study provides an analysis of data collected as part of a long‐term research project initiated by the UK Dementia Research Institute’s Care Research and Technology Centre, which aims to understand and slow down the progression of dementia. The goal of this work is to examine the relationship between daytime living status (i.e. activities and psychiatric measurements) and nighttime sleep quality, as poor sleep has been linked to the development of dementia. Early prediction of poor nighttime sleep through monitoring daytime activities may offer an opportunity for intervention, leading to an improvement in sleep quality. In order to achieve this goal, we have developed a classification model to predict poor sleep based on daytime living status.

Method

The activity data is from sensors placed throughout each participant’s home, tracking their movements between 6:00 AM and 7:00 PM each day. The physiological measurements are also taken daily, primarily in the daytime. Sleep is considered poor if more than 50∖% of the time is spent in the “Awake” state out of the total sleep duration (the sum of four sleep states: “Awake”, “Deep”, “Light”, “REM”). Machine learning classification models are applied to predict whether nighttime sleep is poor or not. Also, feature importance analysis can be conducted to identify activity patterns that contribute to poor sleep.

Result

The dataset includes 91 participants with dementia and the collection period spans from June 29th, 2021 to December 31st, 2022. A Gradient Boosting tree classifier was trained and evaluated using 10‐fold cross‐validation. 7% of the data are positive samples. The average sensitivity was 81.1% with a standard deviation of 6.6%, and the average specificity was 78.3% with a standard deviation of 2.3%.

Conclusion

The study suggests that further improvement can be made by analysing time‐dependency within the data and utilising more advanced models. The combination of IoT and machine learning shows the potential to greatly benefit healthcare services for PLWD on a daily basis.
Clinical effectiveness of treatments for the management of anxiety in community dwelling people living with dementia: a systematic review and meta‐analysis
Authors: Nimmons Danielle , Aker Narin , Jordan Kelvin P , Cooper Claudia , Davies Nathan , Manthorpe Jill , Chew‐Graham Carolyn A , Kingstone Tom , Petersen Irene , Walters Kate
Published: December 2023

Background

People living with dementia commonly experience distress or behavioural and psychological symptoms, such as anxiety, which are associated with worse outcomes in this population. Symptoms of anxiety can be challenging to manage, as there is limited evidence supporting the prescription of psychotropic medications and it is unclear if conventional psychological treatments, such as cognitive behavioural therapy, are effective. The aim of this systematic review and meta‐analysis was therefore to investigate the effectiveness of pharmacological and non‐pharmacological treatments for the management of anxiety in community dwelling people living with dementia.

Method

A systematic review and meta‐analysis was conducted of randomised controlled trials until January 2022, searching EMBASE, CINAHL, MEDLINE and PsycInfo. This is currently being updated to Jan 2023. Standardised mean differences were estimated at follow‐up between treatments and pooled across studies using random‐effects models. The Cochrane risk‐of‐bias tool for randomized trials assessed risk of bias and meta‐analysis was performed if three or more studies of a treatment group were available.

Result

Twenty‐seven studies (comprising 2517 participants) were included. We categorised these as pharmacological interventions (n = 8), non‐pharmacological group interventions (n = 8) and non‐pharmacological individual interventions (n = 11). Pharmacological interventions with evidence of potential effectiveness included olanzapine, loxapine, citalopram, buspirone and risperidone; and those with no evidence of effectiveness were thioridazine and haloperidol. Meta‐analyses was not performed due to study heterogeneity.

Some non‐pharmacological treatments were found to be effective in reducing anxiety in people living with dementia, compared to usual care or active controls. For interventions aimed at individuals the pooled standardised mean difference was ‐0.41 (CI: ‐0.71, ‐0.11) and for those aimed at groups it was ‐0.44 (CI: ‐0.79, ‐0.09). When examining different type of intervention, results suggest music therapy and muscular approaches (e,g, relaxing massage) were effective in reducing anxiety symptoms, while cognitive approaches and sensory stimulation were not. We will present additional findings from updated searches.

Conclusion

Results suggest non‐pharmacological interventions can be effective in reducing anxiety in community‐dwelling people living with dementia. This supports the development and use of more group‐based non‐pharmacological interventions to help reduce anxiety among people living with dementia in the community and their carers.
Recruitment and Retention for Alzheimer’s Disease Diversity Genetic Cohorts in the ADSP (READD‐ADSP)
Authors: Byrd Goldie S. , McInerney Katalina
Published: December 2023

Background

Genomic studies constitute a proven approach for identifying new therapeutic targets. However, there is a strong European bias that exists in AD genetic studies. This study will increase the global resource of the (ADSP) by including underrepresented African ancestry (African Americans (AA), African (Af)) and Hispanic/Latinx (HL) individuals. Reasons underlying these disparities are complex, but notable barriers to research participation for AA and HL communities must be addressed to improve participation.

Method

READD‐ADSP will recruit, retain, and evaluate 13,000 participants of diverse ethnicity, including 5,000 Af, 4,000 AA, and 4,000 US HL. The study in Africa involves multiple sites in 9 African countries operating under the African Dementia Consortium (AfDC). Socio‐demographic, clinical, and neurocognitive data will be obtained using protocol‐guided evaluation procedures that were developed to accommodate different cultures, to support phenotype harmonization, and for joint studies of biological and social risks of AD. A US and AfDC clinical adjudication committee will apply culturally algorithms for AD to adjudicate data from the cohorts.

Communities are engaged through culturally informed efforts to improve trustworthiness and to understand how to both recruit and retain diverse populations,

Result

Successful recruitment and retention of a globally diverse, well‐phenotyped cohort for genetic studies requires a multi‐level recruitment strategy, which includes building trust in diverse communities, and using evidence‐based community engaged research principles. In order to reach our enrollment goal, we engage diverse communities through a culturally relevant marketing campaign, using market research to inform best practices. We use clinic‐based strategies, as well as family and stakeholder involvement for snowball recruitment. Finally, we provide culturally appropriate training and resources to assure highly skilled multi‐site recruitment teams. We have recruited over 2,500 underrepresented participants, including 200 multi‐plex families using these strategies.

Conclusion

Outcomes from READD‐ADSP will enhance focused, precision medicine approaches for AD and reduce global health disparities across ancestries. In addition to clinic‐based strategies, community‐based strategies that recruit and retain diverse populations require intentional investments that remove trust barriers and support community priorities.
PREVENT‐AD cohort: from normal to impaired cognition, who are declining and why? Preliminary results
Authors: Tremblay‐Mercier Jennifer , Picard Cynthia , Breitner John C.S. , Villeneuve Sylvia , Poirier Judes ,   PREVENT‐AD Research Group
Published: December 2023

Background

The StoP‐Alzheimer Center follows a cohort of cognitively normal participants at risk of developing Alzheimer’s disease (AD) due to their parental history (PREVENT‐AD cohort). Cognitive impairments were detected in 17% of the cohort (66 out of 386) mostly after between 4 to 6 years of follow‐up, at an average age of 70 ± 7 years of age.

Method

We looked at various variables at baseline (demographics, blood results, medical history, cognition, genetic variants, AD pathology, mood) to describe the differences between the participants who maintained a normal cognition versus those who declined.

Result

Difference in ApoE4 status was not as important as expected with 39.4% ApoE4 carriers in the decliner group compared to 38.2% in the normal group (Table 1). Despite a normal cognition at baseline, we found subtle but significant lower cognitive performance in the decliner group on the MoCA (‐1 pt) and the Repeatable Battery for the Assessment of Neuropsychological Status (‐5 pts). Systolic blood pressure and glycosylated hemoglobin were slightly more elevated in the decliner group (132 mmHg versus 128 mmHg and 5.6% versus 5.4% respectively). When asked about their past medical history, more participants were treated for hypertension, hyperlipidemia and diabetes in the decliner group. At the level of brain AD pathology measured by PET, the decliner group presented higher levels (standard uptake values) of amyloid and tau. Overall, 27% of the decliner group were amyloid AND tau positive compared to 7% in the normal group. The decliner group also showed lower smell identification performances at baseline when compared to the group who didn’t decline.

Conclusion

Main differences between the groups at baseline are related to AD pathology, vascular risk factors and cognitive and smell identification capacities. Other available variables such as brain structure, cerebrospinal fluid proteins, additional cognitive tests, lifestyle questionnaires, and genetics variants need to be analyzed along with trajectories and change over time. As a growing number of participants are declining cognitively and are still followed annually with multimodal evaluations, we trust that further investigations will help better understand the development of cognitive impairment.
Preliminary Acceptability and Efficacy of a Brief Computerized Intervention Targeting Loneliness in Older Adults
Authors: Schubert Frederick T , Schmidt Norman B
Published: December 2023

Background

Loneliness in older adults has been linked to an increased risk for dementia as well as physical and mental health issues. In recent years, computerized interventions have emerged as a promising strategy for addressing mental health issues such as loneliness given their ease‐of‐use, efficiency, and high level of scalability. “Combatting Social Isolation” (CSI) is one such intervention that is brief, web based, and has demonstrated efficacy in targeting two risk factors central to social disconnection (perceived burdensomeness and thwarted belongingness). This study sought to adapt the existing CSI protocol for older adults reporting loneliness and obtain preliminary acceptability and efficacy data in a randomized clinical trial.

Method

Participants were community‐dwelling adults 60 years of age or older who reported experiencing loneliness. This is an ongoing clinical trial with an expect final sample size of 60. Currently, 13 participants have been randomized to complete either CSI or a similar web‐based control which provides information regarding a healthy lifestyle. Participants completed measures assessing acceptability and loneliness pre‐intervention, post‐intervention and at 1‐month follow up. The sample was 53.8% female and varied in age from 63 to 80 years old (M = 70.54; SD = 5.40).

Result

Following completion of the CSI intervention, 100% of participants (N = 7) reported that the intervention was at least somewhat logical, 85.7% reported that they expected it to be at least somewhat successful in reducing their symptoms, and 85.7% of participants rated the quality of the intervention as good or excellent. Descriptive statistics revealed that total UCLA loneliness scale scores for both groups were lower at post (M/SDCSI = 50.33/7.63; Control = 40.83/8.08) and 1‐month follow up (M/SD CSI = 51.33/8.00; Control = 40.17/9.24) compared to pre‐intervention (M/SD CSI = 54.43/9.25; Control = 44.50/9.96). Mean scores were not compared between groups due to small sample size, however, data continues to be collected and inferential statistics will be available for presentation.

Conclusion

These preliminary results suggest that most participants considered the CSI intervention to be acceptable. Though the current sample is underpowered to detect between‐groups differences in loneliness, initial trends support a decrease in loneliness over time. However, more data needs to be collected to determine whether these reductions are unique to the intervention.
Consequences of mitochondrial DNA depletion in microglial cells
Authors: Molina Carmen Romero , See Wen Yi , Liu Yiyuan , Pa Judy , Wilkins Heather M , Swerdlow Russell H , Goate Alison , Andrews Shea J
Published: December 2023

Background

Mitochondrial dysfunction is an early and prominent feature of Alzheimer’s disease (AD). We have recently published that lower brain mitochondrial DNA copy number (mtDNAcn) is associated with a greater odds of AD neuropathological change and worse cognitive performance. As it is known that microglial cells play an important role in AD, we want to address how a reduction in mtDNAcn may affect microglial function.

Methods

microglial BV2 cells were treated with ethidium bromide (etbr) (1ug/ml) for 5 days to achieve a 95% reduction of mitochondrial‐encoded genes expression. Cells were characterized by RNAseq and Seahorse experiments. BV2 cells were challenged with latex beads and 10uM zymosan‐pHrodo for 24 hours and phagocytosis was analyzed by flow cytometry. BV2 cells were stimulated with LPS (100ng/ml) for 3 hours to measure cytokine release by qPCR and ELISA. After BV2 stimulation, fresh media (without LPS or etbr) was conditioned for 6 hours and collected to treat neurons (SH‐SY5Y cells) and human primary astrocytes for 24 hours. RNA and protein samples were collected.

Results

mtDNAcn reduction led to a dramatic reduction in oxidative phosphorylation and a mild reduction in proliferation. RNAseq data showed an increase in the hypoxia signature and cellular senescence, coupled with a reduction in biosynthetic process and response to interferon. No changes were observed in phagocytic capacity. However, after LPS stimulation, etbr‐treated cells showed a reduction in the production of IL1B and IL6 cytokines, suggesting an impairment in the response to challenge. Neurons exposed to media from etbr‐treated BV2 cells showed an increase in MAPT and APOE expression. Samples from astrocytes are currently being analyzed.

Conclusions

mtDNAcn reduction impairs mitochondrial respiration, which affects the production of cytokines in response to stimulus and leads to cell senescence in microglial cells. Cytokines released by microglia affected neuronal expression of AD‐related genes.
Advancing the understanding of Aβ plaques through a systematic comparison of statistical methods applied to hyperspectral Raman data
Authors: Haessler Annika , Jung Nathalie , Windbergs Maike
Published: December 2023

Background

While fluorescence microscopy is widely applied in Alzheimer’s disease (AD) research, spectroscopic imaging methods like Raman imaging have only emerged recently. As a label‐free, chemically selective method, Raman microscopy can complement established imaging approaches by providing data as hyperspectral images, containing information on the molecular structure, composition, and distribution within a sample. However, brain tissue is a challenging tissue to analyze, since spectral variations in the sample are extremely low. Thus, to analyze pathologic hallmarks such as beta‐amyloid (Aβ) plaques, including the surrounding tissue, a systematic approach to accessing hyperspectral images is needed and herein presented.

Method

Regions of interest containing Aβ plaques in brain sections of 10 month old APP/PS1 (Amyloid‐Precursor‐Protein / Presenilin‐1) mice were imaged using a confocal Raman microscope (WITec GmbH, Ulm, Germany). The hyperspectral Raman data sets were processed using Project 4 software (WITec GmbH, Ulm, Germany), in‐house written Matlab scripts (The Mathworks, Inc., Natick, USA) and the Matlab‐integrated RamanLight App.

Result

By comparing univariate peak integration analysis and multivariate methods, such as hierarchical cluster analysis, spectral unmixing, and 2D correlation spectroscopy on the same hyperspectral Raman data set of an Aβ plaque and its surrounding tissue, the approaches could be systematically studied. pathological structures in the tissue can only be successfully differentiated, if multivariate methods (cluster analysis, spectral unmixing) are used. Nonetheless, univariate peak integration can provide basic spatial and compositional information on the tissue and the Aβ plaque. By applying 2D correlation spectroscopy, interfaces between the Aβ plaque and the surrounding tissue can be thoroughly analyzed.

Conclusion

In this study, a hyperspectral Raman image of an Aβ plaque and the surrounding tissue has successfully been analyzed with diverse explorative statistical methods to access Therefore, this study paves the way for the application of label‐free techniques such as Raman imaging into AD research by serving as a guide for the systematic analysis of hyperspectral images of pathological structures.
Genes and Cognition, a recallable cohort to study Dementia/Alzheimer’s disease
Authors: Rahman Md Shafiqur , Hill Steven M , Tom Brian D M , Chinnery Patrick F , BioResource NIHR
Published: December 2023

Background

Decades of research have not resulted in a cure for dementia/Alzheimer’s disease (AD). Most treatments have failed to benefit patients in clinical trials, potentially due to treatment being provided too late when brain damage is irreversible. There is an urgent need to understand the disease mechanism at the preclinical and prodromal stages of AD, which requires early identification of participants at risk of AD.

Method

We attempt to address this need by establishing an open cohort named Genes and Cognition (GC), nested within NIHR Bioresource (https://bioresource.nihr.ac.uk/) and comprising 21,051 healthy people aged 17‐85 who consented to be recalled for follow‐up studies. Participants took 11 cognitive tests (CTs) covering various domains of cognition. We examined the association between CT scores and demographic characteristics, explored phenotypic and genotypic correlations between CTs, and estimated SNP‐based heritability. In addition, AD polygenic risk (high vs low) was determined in 10,038 participants using 20 single nucleotide polymorphisms (SNPs) from Lambert et al. (PMID:24162737) to identify the earliest age with a noticeable score difference in CTs.

Result

CT scores (higher score indicates poorer performance) were associated with age and gender differences were significant for each CT score. Significant linear trends were observed between CTs and educational attainment. Genetic correlations between tests were stronger than the phenotypic correlations. SNP‐heritability for CTs and general cognitive ability ranged from 8‐28%. We observed that three CTs (Reaction Time, Stroop Box, Stroop Ink) began deviating around age 55 between high (≥ 96th percentile) and low (≤ 95th percentile) AD polygenic risk groups, although not significant. Similar deviations in some CTs were observed among APOE E4 allele carriers compared to E3/E3 carriers. However, AD risk groups determined without including the APOE region indicated such deviation after age 65.

Conclusion

We presented preliminary findings for the GC study cohort. Our results suggest that AD polygenic risk measured with or without APOE region may be less beneficial than the two APOE SNPs (rs429358 and rs7412) alone for the early identification of AD. Repeated CT measures would shed more light on this observation; therefore, we aim to investigate this with CTs repeated at two years intervals.
Psychometric analysis of validity, generalizability, and extrapolation inferences of Modified Mini Mental Status Examination (3MSE) scores in American Indian adults
Authors: Suchy‐Dicey Astrid M , Vo Thao , Oziel Kyra , King Roxanna , Buchwald Dedra , French Brian
Published: December 2023

Background

The Modified Mini‐Mental State Examination (3MSE) is a cognitive assessment tool covering multiple domains often used to screen for dementia. Psychometric studies have demonstrated consistent 3MSE test performance across multiple racial/ethnic populations, but American Indians have been underrepresented in clinical validity studies. Population‐based cohort data suggests relatively low score distributions in American Indians, emphasizing a critical need for formal psychometric assessments.

Method

The Strong Heart Study recruited 818 American Indians aged 65‐95 years from 3 states for cognitive examinations in 2010‐13; 403 survivors repeated exams in 2017‐19. Participants self‐reported age, sex, education, and bilingual ability; trained personnel administered the 3MSE. We conducted psychometric analyses to support validity inferences, including scoring using confirmatory factor analysis, generalizability with internal consistency‐reliability estimates, and extrapolation via multiple indicator multiple cause models for differential item functioning.

Result

Participants were mean 73 years (SD 5.9), 67.5% female, mean 12.6 years education, mean 3MSE score 88.4 (SD 9.7); at repeat examination (mean 6.7 years later) mean 3MSE score was 87.1 (9.5). For a scoring inference, factor analysis supported a 4‐factor/second‐order model (comparative fit index: 0.91). The four factors included verbal‐episodic memory (short, long recall; λ: 0.81‐0.82), language‐executive function (animal, command, naming, obey, repetition, similarities; λ: 0.40‐0.58), psychomotor‐working memory (reversal, writing; λ: 0.49‐0.65), and orientation‐visuoconstruction (orientation, pentagons, registration, spatial, temporal; λ: 0.11‐0.69). For generalizability, we detected acceptable internal consistency (>0.90 total score) and strong test‐retest reliability (Pearson’s r: 0.47‐0.78, all p<0.05). For extrapolation and group differences, overall test performance was strongly associated with age and education, but not sex; language use (bilingual) was significant and strongly associated with psychomotor‐working memory factor (β: 0.12‐0.40, p<0.05), but not with the language‐executive function factor (β: 0.01‐0.10).

Conclusion

Overall, these patterns of evidence support clinical interpretation of 3MSE scores among American Indian elders, with consideration of age and education and possibly also bilingual status or usual language use. Furthermore, these findings suggest that previously‐observed population differences in 3MSE score may result from unaddressed social determinants. Future research should address possible influence of socioeconomic, cultural, historical, or behavioral factors not currently addressed in neuropsychological practice.
Spatiotemporal characterization of tau pathology and dendritic atrophy in the human locus coeruleus
Authors: Adori Csaba
Published: December 2023

Background

Tau pathology of the noradrenergic locus coeruleus (LC) is a hallmark of several age‐related neurodegenerative disorders, including Alzheimer’s disease. However, comprehensive neuropathological examination of the LC is difficult due to its small size and rod‐like shape.

Method

To investigate the LC cytoarchitecture and tau cytoskeletal pathology in relation to possible propagation patterns of disease‐associated tau in a large‐scale and high resolution three‐dimensional view, we applied the state‐of‐the‐art volume immunostaining and optical clearing technology iDISCO+, combined with light sheet fluorescence microscopy. We examined AT8+ pathological tau in the LC/pericoerulear region of 20 brains from Braak neurofibrillary tangle (NFT) stage 0 to 6.

Result

We demonstrate a high morphological complexity of AT8+ cellular structures in the LC, representing various intracellular stages of NFT maturation and their diverse transition forms. We describe novel morphologies of neuronal tau pathology such as AT8+ cells with fine filamentous somatic protrusions or with disintegrating soma. We show that gradual dendritic atrophy is the first morphological sign of the degeneration of tangle‐bearing neurons. Irrespective of the Braak NFT stage, tau pathology is more advanced in the dorsal LC that preferentially projects to vulnerable forebrain regions in Alzheimer’s disease, like the hippocampus or neocortical areas. Moreover, already in the precortical Braak 0 stage, 3D analysis reveals clustering tendency and dendro‐dendritic close appositions of AT8+ LC neurons, AT8+ long axons of NFT‐bearing cells that join the ascending dorsal noradrenergic bundle after leaving the LC, as well as AT8+ processes of NFT‐bearing LC neurons that target the 4th ventricle wall.

Conclusion

Our study suggests that the unique cytoarchitecture, comprised of a densely packed and dendritically extensively interconnected neuronal network with long projections, makes the human LC to be an ideal anatomical template for early accumulation and trans‐neuronal spreading of hyperphosphorylated tau.
A new strategy for Alzheimer’s disease: low‐dose combination of radiotherapy and pharmacological epigenetic perturbation
Authors: Volmar Claude‐Henry , Ricciardi Natalie R , Modarresi Farzaneh , Lohse Ines , Andrade Nadja S , Newman Ian R , Brown Jonathan M , Borja Caroline , Marples Brian , Wahlestedt Claes
Published: December 2023

Background

Most Alzheimer’s disease (AD) drug discovery studies focus exclusively on one specific target. This approach has to date shown limited success in AD, mainly because this complex disease is multifactorial and involves numerous pathways. In light of the large number of disappointing clinical trials, the National Institute on Aging (NIA) and the Alzheimer’s Association (AA) published, in 2018, new guidelines recommending focusing on biomarkers of the AD continuum. These guidelines advise targeting Amyloid‐β (A), neurofibrillary tangles (T) and neurodegeneration markers (N), designated “ATN”, to advance AD research. Using 2 different approaches, we have been able to both reverse and prevent ATN burden in mouse models of AD. Indeed, our group has previously demonstrated that histone deacetylase inhibition (HDACi) and cranial radiotherapy (RT) independently improve (AD)‐like pathogenesis in cell and animal models. In the present study, we investigate the synergistic potential of using both RT and HDACi as a low‐dose combination therapy (LDCT) to further improve molecular and behavioral AD‐like phenotypes in AD models.

Method

LDCT consisted of daily administration of the HDAC3 inhibitor RGFP‐966 and/or bi‐weekly cranial x‐irradiation. Behavioral analyses, real‐time qPCR, NanoString technology, ELISAs and Western blots were used to assess the effects of RT, RGFP‐966 and LDCT on AD‐like pathogenesis in AD models. Additionally, innate immune response to LDCT was also assessed in vitro and in vivo using human and murine cell models and 3xTg‐AD mice.

Result

LDCT induced a tolerant, anti‐inflammatory innate immune response in microglia and increased non‐amyloidogenic APP processing. Both RT and LDCT improved spatial learning and memory in the Barnes maze test. No sensorimotor deficits were observed. LDCT induced a unique anti‐AD gene expression profile in the brain, that included upregulation of neurotrophic genes and downregulation of inflammation‐related genes. Brain region specific observations included lowered Aβ42/40 ratio, decreased Bace1, and reduced p‐tau181 levels.

Conclusion

This work shows that it is possible to attenuate AD‐related pathologies through the synergy of low doses of RT and HDACi treatment. This project supports a paradigm shift to a multipronged approach to AD therapeutics.