bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of COVID‐19 and telehealth implementation on Patient Centered Outcome Measures completion by patients with Alzheimer’s and related disorders in an academic memory center
Authors: Gubler Boston , Finch Kelly , Holden Samantha K. , Mullen Rebecca , Matlock Daniel D , Pressman Peter S.
Published: December 2023

Background

Patient Centered Outcome Measures (PCOMs) are increasingly recognized as a means of improving clinical efficiency, particularly when completed electronically ahead of clinic visits. However, PCOM completion is often far from consistent. The shift to telehealth introduced by the Covid‐19 pandemic changed how patients and caregivers engaged with medical care, possibly encouraging increased participation in electronic assessments. We questioned how the pandemic influenced electronic PCOM completion by our patients with Alzheimer’s disease (AD) and their caregivers.

Methods

Patients and caregivers were routinely invited to fill electronic PCOM questionnaires prior to visits both before and during the Covid‐19 pandemic. PCOMs assessed the predominant cognitive domain of concern, other diagnostically useful symptoms, disease severity, neuropsychiatric symptoms, and caregiver wellbeing. A date of 3/15/2020 was set as the onset of the pandemic for this study, after which time our clinic converted to telehealth visits only. We tallied rates of completion of electronic surveys by patients and/or caregivers three and a half months before and after that time, comparing completion rates by two proportion Z‐test.

Results

During this timeframe, across a total of 402 visits (total: 333 individuals, 69 returns; AD: 73 individuals, 6 returns), caregivers and/or patients were offered an opportunity to fill PCOMs ahead of the visit. Across all clinical diagnoses combined, the probability of a visit being associated with filled PCOMS was greater after switching to only telehealth (caregivers: P = 0.005, patients: P = 0.016). Additionally, after the shift to telehealth, AD‐related visits were twice as likely to have completed preclinical electronic PCOMs (caregivers: P = 0.002, patients: P = 0.008). Approximately 33.3% of PCOMS to be filled by AD caregivers were completed before the telehealth shift, and 67.5% were afterwards. Approximately 26.7% of patient PCOMs were filled before the change, and afterwards this percentage rose to 55.0%.

Conclusion

The beginning of the Covid‐19 pandemic and subsequent shift towards telehealth‐only practice was associated with greater use of electronic PCOMs by all patients, including those with AD and their caregivers. Increased acceptance of electronic PCOMs seems to offer promising opportunities for remote assessment in the future of dementia diagnosis and care.
TELL: A web‐based app to capture speech and language markers of neurodegeneration
Authors: Garcia Adolfo M
Published: December 2023

Background

Over the last decade, the search for scalable markers of neurodegeneration has been boosted by automated speech and language analysis (ASLA). Participants are asked to produce natural discourse, generating acoustic and linguistic data that can be digitally extracted and analyzed with statistical or machine learning methods. This approach has revealed subtle patterns that differentiate among disorders, predict core symptom severity, correlate with anatomo‐functional brain alterations, and identify autopsy‐confirmed pathology years before death. Accordingly, multiple studies have described ASLA as a promising resource for patient assessment. However, this translational potential remains unfulfilled, as the underlying technologies are unavailable for immediate clinical use. Aiming to tackle this issue, we developed the Toolkit to Examine Lifelike Language (TELL), a web‐based app for collecting, storing, analyzing, and visualizing speech data.

Method

TELL version 1.0 was developed by an interdisciplinary team of language, brain health, and data science experts. We designed a speech elicitation protocol comprised of validated spontaneous, semi‐spontaneous, and non‐spontaneous tasks with different cognitive demands. Each task is analyzed via ASLA algorithms capturing word frequency, affective valence, and emotional magnitude, as well as rhythm‐ and pitch‐related features. On‐the‐fly results are offered through intuitive visualizations for each metric. The measures are complemented with a language profile survey. Audio files, transcriptions, and data matrices can be downloaded for offline analysis. The app runs on multiple devices, requires no installation, and offers multi‐language capabilities.

Result

TELL version 1.0 is now being used in 10 sites worldwide, mainly including low‐income countries. Preliminary results from persons with Alzheimer’s and Parkinson’s disease, as well as frontotemporal dementia, show that its metrics are sensitive for disease identification, discrimination, and monitoring. Updates have been implemented drawing from users’ feedback. Funds have been secured to develop TELL version 2.0, with novel metrics, improved speech‐to‐text algorithms, and a streamlined front end.

Conclusion

TELL turns basic language science methods into clinically usable tools, offering an objective, low‐cost, non‐invasive complement to classical assessments. More generally, it illustrates how digital technologies can foster equitable insights on brain health. Ongoing updates will further increase its capacity to establish scalable markers of diverse neurodegenerative diseases.
Age differentially mediates the relationship between plasma biomarkers and cognition detected by digital screening
Authors: Toniolo Sofia , Zhao Sijia , Scholcz Anna , Amein Benazir , Gallacher Anne , Ganse‐Dumrath Akke , Bukala Bernard R , Thompson Sian , Manohar Sanjay , Zetterberg Henrik , Husain Masud
Published: December 2023

Background

Plasma biomarkers are emerging as a useful tool to measure neurodegeneration, particularly in patients with Alzheimer’s Disease (AD). Digital cognitive testing is also increasingly used to detect cognitive changes in AD. Age is a major determinant of performance at cognitive testing and can affect the levels of different plasma biomarkers. However, little is known about how age mediates the relationship between plasma biomarkers and cognition.

Method

38 AD and 48 age‐matched controls were recruited from the Oxford Centre for Cognitive Disorders. We used a fully remote digital visual short‐term memory (STM) task (Figure 1) and extracted eight cognitive metrics (Figure 1): Identification Accuracy (percentage of correctly identified items), Absolute Error (distance from the response location to the original item), Target detection (probability of correctly identifying the target), Misbinding (erroneously localizing an item to the remembered location of another item in memory), Guessing (random guessing), Identification and Localization Time (time to identify and drag the correct object to its remembered location), and memory Imprecision (width of the distribution around the target). Plasma p‐tau 181, GFAP, NFL, Aß40 and Aß42 were measured, and the Aß42/40 ratio was calculated. In Model 1 (Figure 2) the correlation between digital cognitive metrics and plasma biomarkers is shown, while in Model 2 age was regressed out. A mediation analysis was then performed to look at the effect of age as a mediator.

Result

In Model 1, most cognitive metrics on the STM task were strongly associated with p‐tau 181, GFAP and NFL. Identification Accuracy was also negatively correlated with the Aß42/40 ratio. No association with Aß42 or Aß40 was found. However, regressing out age had a profound impact on these correlations, particularly for GFAP and NFL, while p‐tau 181 was not significantly affected (Figure 2 and 3). The mediation analysis (Figure 3), shown for Identification Accuracy, confirmed that age had a more profound impact on GFAP and NFL compared to p‐tau 181.

Conclusion

These new digital metrics show a strong correlation with plasma biomarkers. Finally, age is an important mediator between plasma biomarkers and cognition, but that varies across different biomarkers.
Gene co‐expression network analyses in Mild cognitive impairment
Authors: Dorsant‐Ardon Valerie , Sanjay Apoorva Bharthur , Rocha Luis M , Correia Rion Brattig , Apostolova Liana G.
Published: December 2023

Background

Multiomic data analysis has been extensively developed in recent years. Particularly, microarray data can be used as biomarkers of disease of progression specially in pathologies as cancer, autoimmunity and others. (Dahinden et al., 2010; Soleimani Zakeri et al., 2020). This modality of data analysis can also be employed in other multifactorial diseases as Alzheimer’s disease including the progression from normal cognition to mild cognitive impairment and finally to dementia. These genes work in intricate relationship with each other. The establishment of computational gene interaction networks shows the intricacy of the biological systems but increases the complexity of the analysis, for this reason, the removal of redundant edges leaves a network backbone revealing important driver nodes that are essential for the observed interactions, reducing the number of genes of interest and narrowing potential diagnostic or therapeutic targets. (Gates et al., 2021).

Method

We used data from the ImaGENE study and the Weighted gene co‐expression network analysis (WGCNA) pipeline to analyze gene‐gene interactions of mRNA transcripts obtaining hierarchical clustering of genes and eigengenes in a sample of 160 individuals (Table 1). The backbones were obtained using the shortest path computation. (Gates et al., 2021; Simas et al., 2021). Gene ontology was used to classify processes associated with these genes.

Result

We identified 42 hubs of differentially expressed genes and we analyzed the top 5 groups with the strongest association with amnestic mild cognitive impairment (MCI) phenotype (pfdr<0.0001). This cluster consisting of 46 genes was further classified according to function and interactions with other nodes in the backbone identifying processes like calcium signaling, nucleotide excision repair, fatty acid metabolism among others.

Conclusion

There is an identifiable difference in gene expression in individuals with MCI compared to normal controls. The analysis of the backbone of the gene hubs allowed to reduce the number of genes of interest. This approach can help to elucidate important biological interactions, potential therapeutic targets and could eventually be used as risk factors markers for the development of MCI and AD.
Association of plasma biomarkers with cognitive function in persons with dementia and cognitively healthy in the Democratic Republic of Congo
Authors: Ikanga Jean N , Patel Saranya Sundaram , Roberts Blaine Russell , Schwinne Megan , Hickle Sabrina , Verberk Inge M.W. , Epenge Emmanuel , Gikelekele Guy , Tshengele Nathan , Kavugho Immaculee , Mampunza Samuel , Yarasheski Kevin E. , Teunissen Charlotte E. , Stringer Anthony Y , Levey Allan I. , Alonso Alvaro
Published: December 2023

Background

Cross‐sectional and longitudinal measurements of plasma biomarkers of Alzheimer’s disease (AD) in Western countries are being applied in clinical practice, whereas their associations with culturally validated cognitive tests in other settings remain unknown. We aim to examine cross‐sectional association of plasma protein biomarker concentrations and APOE proteotype with cognitive function and explore the discriminative role of these AD biomarkers in such an association.

Method

This is a cross‐sectional retrospective study completed from 2018 to 2022 in the Democratic Republic of Congo (DRC). Subjects were recruited from clinics, hospitals, churches, and across DRC. The study started in January 2018 until December 2022. Data were analyzed from May 2022 to December 2022. The DRC Memory clinic team recruited 1430 individuals 65 years and over. Based on Community Screening Instruments for Dementia (CSID), and Alzheimer’s Questionnaire (AQ), and DSM‐5 diagnostic criteria, participants included 44 individuals classified as major neurocognitive disorder (dementia) and 41 as healthy controls (HC). Subjects underwent cognitive assessment with a validated, culturally‐tailored cognitive battery. AD plasma biomarkers (Aβ42, Aβ40, Aβ42/40, p‐tau 181), APS (derived from Aβ42/40, APOE status, and age), and APOE proteotype were utilized to assess for genetic risk.

Result

Individuals with dementia had significantly lower Aβ42/40 levels, higher APS, and higher APOE ε4 prevalence compared to HC. Linear regressions showed significantly associations between Aβ42/40 and APS with ANT, ALMT, and AVMT scores, while APOE ε4 presence was associated with ANT, ALMT, AVMT, and APT scores. APS showed the highest AUC value (AUC = 0.78, 95% CI: 0.68‐0.88) followed by Aβ42/40 (AUC = 0.75, 95% CI: 0.66‐0.86) and APOE ε4 (AUC = 0.69 (CI 0.57‐0.81) in discriminating dementia from HC.

Conclusion

Select AD biomarkers were associated with cognition and differentiated dementia from HC, consistent with extant research. These findings may have implications for the assessment of AD biomarkers in DRC.
Investigations of Serum Metabolomic Relationships between Lung Cancer and Alzheimer’s Disease using Nuclear Magnetic Resonance Spectroscopy
Authors: Cheng Leo L. , Kobus Zuzanna , Bobus Marta , Su Li , Christiani David C.
Published: December 2023

Background

Alzheimer’s Disease (AD) and Lung cancer (LuCa) are among the leading causes of mortality in the United States. Remarkably, several studies demonstrated a potential inverse co‐morbidity of AD with LuCa. Possible explanations related to the cell cycle (dys)regulation include presence of specific neuropathological features, immune checkpoint functions and increased circular RNA levels. Metabolomic profiles for LuCa or AD alone have been proposed. Here, using high‐resolution magic angle spinning (HRMAS) MRS, we aim to study metabolomic relationship between the two diseases with serum metabolomic profiles for matched LuCa patients, with and without AD, by comparing serum profiles measured from matched healthy controls.

Methods

LuCa sera from of patients with (LCAD, n = 10, 3M, 7F, 77.3±7.7yrs) and without (LCnonAD, n = 10, 3M, 7F, 77.4±5.2yrs) clinically defined AD were obtained from Harvard/MGH Lung Cancer Susceptibility Study (a.k.a. BLCS) Repository, with individually age‐ and gender‐matched healthy controls (Ctrl‐LCAD and Ctrl‐LCnonAD, n = 10/each) obtained from the MGB BioBank. HRMAS proton NMR for these 40 samples were measured on 10 µl, at 4°C with a spin rate of 5000 Hz using a Bruker Avance 600 MHz spectrometer. Spectra were analyzed with Bruker Topspin 3.6.2. Statistical analysis was performed using JMP Pro on 18 spectral regions identified from HRMAS proton NMR.

Results

As a survey of the entire data ensemble of 18 spectral regions measured from 40 samples, the hierarchical clustering analysis (Fig. 1) seems to associate different groups into different clusters. Unsupervised principal component analysis (PCA) conducted on all spectral regions generate PCs (PC1 and PC2) that can differentiate among groups (Fig. 2). Further noticed that, four out of 18 regions can significantly differentiate LCAD from LCnonAD. Calculations of PCA using these four regions result in PC1_4regions that can significantly differentiate LCAD from LCnonAD (Fig. 3). Collectively evaluating potential contributing metabolites towards PC1_4regions indicate increases in myo‐inositol suggesting towards LCAD, which increases in creatine, phosphocreatine, serine, aspartate, tyrosine, proline, glutamine, and 2‐oxoglutarate suggesting towards LCnonAD.

Conclusion

Our findings, whilst preliminary, seem promising in guiding further investigations into serum NMR metabolomics for better understanding LuCa‐AD metabolic relationships.
Comparative efficacy of cognitive training and physical activity interventions delivered using technology‐based or face‐to‐face approaches in patients with cognitive impairment: A systematic review and network meta‐analysis
Authors: Ye Yifan , Zhang Lifeng , Huang Likui , Lei Ming , Chen Liangying , Song Rui , Wang Jia
Published: December 2023

Background

In recent years, there has been a growing development of cognitive training and physical activity interventions delivered through technology‐based or face‐to‐face approaches for patients with cognitive impairment. However, it remains unclear which combination of approaches is effective and preferred.

Methods

We searched Pubmed, Web of Science, Embase, the Cochrane Library, MEDLINE, and PsycInfo through November 2022 and included randomized controlled trials that examined the effectiveness of CT+PA‐T (combining cognitive training and physical activity using a technology‐based approach), CT+PA‐F (combining cognitive training and physical activity using a face‐to‐face approach), CT‐T (technology‐based cognitive training), CT‐F (face‐to‐face cognitive training), PA‐T (technology‐based physical activity), and PA‐F (face‐to‐face physical activity) in patients with cognitive impairment. The primary outcomes included global cognitive function, executive function, memory cognition, Activities of Daily Life (ADL), depression, and Quality of Life (QOL). Network meta‐analyses were performed using a random effects model.

Results

A total of 141 studies with 12060 patients were included. CT+PA‐T was the most effective for improving global cognitive function (SUCRA = 89.9%, SMD = 0.91, 95%CI = 0.41 to 1.40), ADL (SUCRA = 97.1%, SMD = 1.19, 95%CI 0.39 to 1.98), and reducing depression (SUCRA = 93.8%, SMD = ‐1.11, 95%CI ‐2.09 to ‐0.13). CT‐T had the highest probability in developing memory function (SUCRA = 94.4%, SMD = 0.62, 95%CI 0.39 to 0.85) and QOL (SUCRA = 75.3%, SMD = 0.53, 95%CI 0.00 to 1.07) in patients with cognitive impairment. For executive function, CT+PA‐F had the highest probability in all patients with cognitive impairment (SUCRA = 86.1%, SMD = 0.49, 95%CI 0.26 to 0.72), while CT+PA‐T and CT‐T were best in patients with MCI (SMD = 0.59, 95%CI 0.30 to 0.88) and dementia (SMD = 0.87, 95%CI 0.37 to 1.36), respectively.

Conclusions

These preliminary findings suggest that technology‐based intervention is an effective approach to improving the well‐being of patients with cognitive impairment. CT+PA‐T and CT‐T had the highest probability of being the most effective intervention for slowing global cognitive function decline and improving memory function among patients with cognitive impairment, respectively.
Cross‐Sectional and Longitudinal Associations of Mild Behavioural Impairment‐Apathy and Alzheimer’s Disease‐Related Biomarkers
Authors: Vellone Daniella Alicia , Ismail Zahinoor
Published: December 2023

Background

Apathy, characterized by decreased interest, initiative, and emotional reactivity, is amongst the most common neuropsychiatric symptoms in Alzheimer’s Disease (AD) dementia, but it can also manifest in prodromal, and even preclinical disease stages. Apathy in individuals who are cognitively normal and who have mild cognitive impairment (MCI), is associated with accelerated progression to AD, and apathy in AD has been associated with greater disability, lower quality of life, poorer health, greater caregiver distress and burden, as well as higher morbidity and mortality. The multitude of negative outcomes associated with apathy highlight the importance of research whose primary goal is to identify mild behavioural impairment(MBI)‐apathy in non‐dementia samples and combine this behavioural syndrome with well‐established AD‐biomarkers, such as beta‐amyloid (Aβ), phosphorylated tau (p‐tau), and total tau (t‐tau), to better predict AD dementia risk.

Method

Dementia‐free participants in the Alzheimer’s Disease Neuroimaging Initiative were stratified as MBI‐apathy and no neuropsychiatric symptoms (no‐NPS) based on Neuropsychiatric Inventory (NPI) and NPI‐Questionnaire (NPI‐Q) scores at two consecutive visits. Covariates of interest included age, sex, apolipoprotein ε4 carriership, years of education, Mini Mental State Examination scores, and the questionnaire NPS status was derived from. Linear regressions assessed the association of MBI‐apathy (predictor) with Aβ40, Aβ42, p‐tau181, t‐tau, Aβ40/Aβ42, p‐tau181/Aβ42, and t‐tau/Aβ42 (outcome variables). We also used linear mixed effect models for repeated measures to investigate change in our outcome variables across a two‐year period.

Results

Of the 253 participants (127 CN); 51 had MBI‐apathy. MBI‐apathy was found to be significantly associated with baseline p‐tau181/Aβ42 (p<0.05) and t‐tau/Aβ42 (p<0.05) ratios. MBI‐apathy was also found to be significantly associated with changes in Aβ42 (p = 0.001), Aβ40/Aβ42 (p<0.01), p‐tau181/Aβ42 (p = 0.001), and t‐tau/Aβ42 (p = 0.001) levels and ratios over a two‐year period.

Conclusion

To our knowledge, this is the first study examining the relationship between MBI‐apathy and AD‐related biomarkers. Results suggest that MBI‐apathy is significantly associated with several AD‐related biomarkers both cross‐sectionally and longitudinally. Combining the presence of persistent and emergent apathy with these biomarkers might serve as a prognostically useful approach for predicting AD dementia at a time when there is opportunity for intervention.
Impact of White Matter Hyperintensities on domain‐specific cognition in Southeast Asians
Authors: Wang Jia Dong James , Leow Yi Jin , Vipin Ashwati , Kumar Dilip , Kandiah Nagaendran
Published: December 2023

Background

Dementia affects 55 million people worldwide, with 60% of the burden in Asia. White Matter Hyperintensities (WMH) is a key marker of small vessel disease, with high prevalence in Asian populations with prodromal and clinical dementia. WMH is described as: Deep White Matter Hyperintensities (DWMH), Periventricular Hyperintensities (PVH) or Fazekas‐Total (DWMH and PVH).

However, association between WMH topography and performance in specific cognitive domains remains unexplored. Thus, this study aims to characterise the impact of Fazekas‐Total, DWMH and PVH on different cognitive domains.

Method

304 participants (mean age 60.6, mean education years 14.2, mean Montreal Cognitive Assessment 25.99, 43.8% males) from Biomarkers and Cognition Study, Singapore (Dementia Research Centre (Singapore)) met the inclusion criteria.

Eight domains of cognition were tested: global cognition, learning and memory, language, executive function, complex‐attention, perceptual‐motor, social‐cognition, and processing speed.

Normality tests, correlation analysis and stepwise regression (with Benjamini and Hochberg False Discovery Rate correction) were performed to understand association between Fazekas‐Total, DWMH, PVH on domains of cognition tested, accounting for age, education, and gender.

Two approaches were used for data analysis: (1) by grouping participants as Mild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD) and Cognitively Normal (CN) as per the National Institute on Aging‐Alzheimer’s Association (NIA‐AA) criteria and (2) by grouping participants’ WMH as confluent (DWMH ≥2 and PVH ≥3) and non‐confluent.

Result

Higher Fazekas‐Total was associated with slower processing speed (p = 0.0255, R = ‐0.039) in prodromal participants (MCI and SCD). Higher PVH was associated with slower processing speed in MCI (p = 0.017, R = ‐0.32) and CN (p = 0.017, R = ‐0.663) participants. Higher PVH was significantly associated with poorer learning and memory (p = 0.045, R = ‐0.043) in SCD participants. Higher DWMH was significantly associated with poorer learning and memory (p = 0.017, R = ‐0.765) in CN participants.

Conclusion

These results demonstrate differential association between PVH, DWMH and cognitive domains, thus the location of WMH determines the affected cognitive domains. Therefore, it is worthwhile to assess PVH and DWMH in clinical cognitive outcomes separately and to understand the upstream pathobiology of DWMH and PVH.

Furthermore, higher Fazekas‐Total was strongly associated with slower processing speed in prodromal participants and could be a marker of cognitive decline.
α‐Synuclein in Blood CNS‐originating Extracellular Vesicles For Parkinsonian Disorders: Systematic Review and Meta‐analysis
Authors: Taha Hash Brown , Ati Shomik S.
Published: December 2023

Background

Parkinsonian disorders, including Parkinson’s disease (PD), multiple system atrophy (MSA), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS), present shared early motor symptoms but differing cellular and regional pathophysiology. Accurate premortem diagnosis remains challenging. Extracellular vesicles (EVs) contain cell‐state‐specific biomolecules and can cross the blood‐brain barrier to the peripheral circulation, providing a unique central nervous system (CNS) insight. Measuring biomarkers in blood CNS‐originating EVs have become a promising avenue for minimally invasive diagnostics. This study evaluated the potential the levels of blood‐isolated neuronal and oligodendroglial EVs (nEVs and oEVs) α‐synuclein (α‐syn) proteoforms in parkinsonian disorders.

Method

We searched PUBMED, EMBASE, google scholar and recent reviews of the literature to include studies that have measured mean ± SD of α‐syn in putative nEVs and oEVs in patients with PD and at least one other parkinsonian disorder or healthy controls (HCs). Thirteen studies were included in the final meta‐analysis and demographic and clinical variables were collected for meta‐regressions. We quantified the effect size (SMD) using an inverse‐variance random‐effects model. QUADAS‐2 was used to assess risk of bias. Begg’s rank correlation and Egger’s regression tests were used to assess publication bias.

Result

The studies included 1,565 patients with PD, 206 with MSA, 21 with DLB, 172 with PSP, 152 with CBS and 967 HCs. Findings suggest that a combination of nEVs and oEVs α‐syn concentrations are higher in patients with PD vs. HCs (k = 14, SMD = 0.21; 95% CI 0.01, 0.42 p = 0.021), while nEVs α‐syn is lower in patients with PSP and CBS vs. PD (k = 6, SMD = ‐1.04; p = 0.0017) or HCs (k = 4, SMD = ‐0.41, p < 0.001). Additionally, α‐syn levels in oEVs didn’t effectively differ among PD, MSA, or HCs, contradicting the literature. Meta‐regressions showed demographic/ clinical were not significant predictors of nEVs or oEVs α‐syn concentrations.

Conclusion

These findings highlight the need for adopting more rigorous, standardized procedures and independent validations across all laboratories studying biomarkers in CNS‐originating EVs. Additionally, there is a pressing need for improved biomarkers to distinguish among parkinsonian disorders more effectively.
Caregiver Enablement Training to Support Homecare: A Study from India
Authors: Tandon Ravina , N Navya , Dasgupta Jayashree
Published: December 2023

Homecare is the prevalent model of dementia care in India and ‘attendants,’ who are non‐trained lay workers are often employed in Indian households to assist with personal care, ADL and other support which the family may need. Providing training to these attendants can support continued dementia care at home. We present initial data from a caregiver enablement program (CEP) being provided in India.

Methods

The (CEP) consists of a minimum of 6‐8 individually tailored sessions beginning with a clinical evaluation. Using a collaborative approach, challenging areas of caregiving are identified and prioritized. Across the sessions, information about what may be contributing to these challenges and tips for providing care are provided by a dementia trained specialist. Attendants and family members are encouraged to use these approaches and feedback was discussed in an iterative manner to improve the caregiving process and address emerging issues.

Results

Ten families availed the caregiver enablement program, out of those 2 patients were living with their 24 hours attendant and 8 patients were living with family and attendants. The caregiver enablement program was conducted online, offline and in hybrid mode, 5 of them were online sessions, 4 offline sessions and one hybrid session (session conducted at home and online). Patients had moderate to severe stage dementia (Hindi MMSE Mn = 13.3, SD = 5.7; Caregiver burden: Zarit burden interview Mn = 29.8 SD = 19.6).

Key areas where enablement was required were basic understanding of dementia, acceptance of the illness by the family and that they need external support, how to manage challenging behaviours like toileting, bathing, dressing, incontinence, transferring and feeding, how to engage the patient in meaningful activities and the need for environment modifications to improve safety and managing challenging behaviours. Psycho educational skill building, multi component intervention was found to be effective in the present study to combat the concerns shared by the attendants/family members.

Conclusion

This study demonstrates how up‐skilling lay workers through training on dementia and management of challenging behaviours can support home care. Supporting the informal care system with specialised training can be an effective way of providing dementia care in low resource settings.
Head‐to‐head comparison of aptamer‐ and antibody‐based proteomic platforms in CSF samples of a real‐world large cohort of a memory clinic
Authors: Puerta Raquel , Cano Amanda , Smets Bart , García‐González Pablo , Haidar Mansour , Olivé Clàudia , Emon Asif , de Rojas Itziar , Sung Yun Ju , Frikke‐Schmidt Ruth , Marchant Natalie L , Lambert Jean‐Charles , Valero Sergi , Ramirez Alfredo , Cruchaga Carlos , Boada Mercè , Socorro Alfredo Cabrera , Ruiz Agustin
Published: December 2023

Background

High‐throughput proteomic platforms are an useful strategy to detect novel biomarkers and pathways involved in Alzheimer’s disease (AD) development. Due to the novelty of these techniques, an extensive quality control assessment is needed to ensure the reliability of those protein measurements. In this study, we aimed to assess the reproducibility and reliability of SomaScan and Olink proteomic platforms and select top‐performing proteins for further analysis.

Method

To assess CSF proteomic measurements, we used the SomaScan 7k platform (an aptamer‐based technique) measuring 7335 human proteins, and Olink proteomics platform (Explore panel, an antibody‐based technique), measuring 3072 proteins in a subset of 509 individuals from ACE Alzheimer Center Barcelona (Spain). To assess intra‐ and inter‐platform reproducibility and reliability, we evaluated 1) the correlations of aptamers of two studies carried out in the same samples with SomaScan platform and 2) the correlation between SomaScan vs Olink proteomics, respectively. Then, we created a metric of 6 categories of reproducibility combining both intra and inter‐ correlation analysis, considering good (r > 0.5), modest (0.2 > r ≥ 0.5), poor (r ≤ 0.2) correlation. We considered proteins in the top 3 categories as potential candidates to further analysis.

Result

From the intra‐platform analysis, only 2402 proteins (35.45%) showed a Pearson’s correlation higher than 0.5. Regarding inter‐platform assessment, 2160 proteins were overlapping between both platforms. From these overlapping proteins, 712 proteins exhibited a Pearson’s r > 0.5 (26.67%). We considered potential candidate proteins those with good intra‐ and inter‐platform correlation (n = 687, 9.02%), only good intra‐platform correlation (n = 2015, 26.45%) and modest intra‐ and inter‐platform correlation (n = 5, 0.06%) for analysis.

Conclusion

The validation of the reproducibility and reliability of the new proteomics platforms is essential for the correct analysis of the results. The classification of measured proteins in different categories could be useful to increase the confidence in these highly multiplexed proteomic panels.
Estimating Mild Cognitive Impairment and Mild Dementia due to Alzheimer’s disease in the United States
Authors: Spargo Drew , Zur Richard , Lin Pei‐Jung , Synnott Patricia G , Klein Eric , Hartry Ann
Published: December 2023

Background

In the United States (US), early Alzheimer’s disease (AD) is underdiagnosed due to numerous factors such as inadequate lab testing, lack of symptom awareness, misdiagnosis, and social stigma. AD has a long prodromal stage, and the potential for early diagnosis is important to effectively use disease‐modifying drugs. Our research aims to estimate the prevalence of mild cognitive impairment (MCI) and mild dementia due to AD among individuals ≥60 years old in the US.

Method

Using currently available data from a comprehensive literature review in a population cascade calculation, this study estimates the diagnosed prevalence of early AD in the US. It also evaluates uncertainty associated with different estimates using all upper or all lower 95% confidence intervals reported in the literature and highlights data gaps for estimating the population living with MCI and mild dementia due to AD.

Result

We estimated that in 2022 approximately 666,646 individuals (0.87% of those aged 60 years and older) had MCI due to AD (range: 351,926 – 1,227,776) and approximately 620,850 individuals (0.81% of those aged 60 years and older) had mild dementia due to AD (range: 445,082 – 820,339). In a US population of 76 million aged 60 or older in 2022, the size of the population with MCI due to AD and mild dementia due to AD increased with age, from 103,947 individuals in people 60‐64 years of age to 264,915 in people ≥90 years of age.

Conclusion

Current data sources suggest that the range of prevalence of MCI due to AD or mild dementia due to AD in the US is wide, but estimates are similar to other studies in literature. Slight differences may reflect changes in diagnostic tools, alternative prevalence sources used in computation, and alternative (PET, CSF) cutoffs to determine amyloid positivity. As new amyloid‐targeting therapies become available, additional research to obtain accurate estimates on diagnosis and amyloid positivity in more real‐world populations are required to reduce uncertainty. Given challenges around diagnosis and access to technology and specialists, planning will be required to optimize the value of new treatment advances such as amyloid‐targeting therapies.
Cost‐effectiveness analysis of Donepezil versus Physical exercise in patients with AD or MCI
Authors: Alfayoumi ibrahim N
Published: December 2023

Background

A growing area of research has investigated the outcomes of donepezil and physical exercise activities in human beings with Alzheimer`s disease (AD) and Mild Cognitive Impairment (MCI). AD is characterized by excessive cognitive impairments which might be related to deposition of amyloid plaques(Aβ) in extracellular areas, mainly cortical dysfunctions and neuronal loss. Mild Cognitive Impairment (MCI) is the degree among the predicted decline in reminiscence and questioning that occurs with age and can later progress into dementia. MCI can also additionally consist of issues with reminiscence, language, or judgment.

Objective

To develop a cost effectiveness analysis of physical exercise as opposed to donepezil for the control of AD and MCI.

Methods

A partitioned survival model was developed to assess the cost‐effectiveness of donepezil versus exercise. Cost of physical exercise was obtained from Medicare physical exercise Advantage Plans’ average price, and for donepezil, the average retail price within the United States was used. The model was developed from a US payer perspective and was envisioned for a time horizon of one‐year. Outcome/Effectiveness was represented via way of means of Effect size (g) values that have been acquired from a scientific overview and meta‐evaluation posted article. MMSE scale turned into the evaluation device for AD and the ADAS scale turned into the device for MCI. One‐way sensitivity analyses were performed on all parameters.

Results

In the base case analysis, exercise was more expensive than donepezil ($420 vs $384) but yielded an improved benefit of MMSE (0.46 vs 0.23) with an incremental cost effectiveness ratio (ICER) of $159 for AD patients. As for the MCI patients, donepezil showed an improved benefit of ADAS (‐0.13 vs ‐0.21) over exercise and had an ICER of $459. The probabilistic sensitivity analysis showed an ICER of $162 for MMSE/AD and $480 for ADAS/MCI.

Conclusion

In AD patients, exercise was confirmed to have an incremental benefit of 0.225 as compared to donepezil; however, in MCI patients, donepezil confirmed incremental benefit of 0.078g as compared to exercise.
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Authors: Lim Trecia Yu Shan , Van Koh Siew , Chan Catherine Qiu Hua
Published: December 2023

With increasing prevalence of dementia, there is a need for a more inclusive society to raise awareness, share knowledge and ensure continuity of care from hospital to community. In SingHealth Community Hospitals (SCH), we aim to build a pipeline of competent multidisciplinary healthcare professionals in providing holistic and quality dementia patient care through staff education. Thus, we have conducted educational talks and Electronic Direct Mail to raise dementia awareness and didactic lectures focusing on person‐centred care (PCC), communication strategies and managing behaviours of concern. However, application of PCC in Behavioural and Psychological Symptoms of Dementia (BPSD) is not one that can be taught and learnt via lectures alone, and staff still expressed difficulties in applying the learnings in managing patients with dementia with BPSD at work. As a result, there were also workplace safety concerns where staffs sustained injuries from patients who turned aggressive or were agitated due to unmet needs.

Hence, the team came out with simulation practical sessions using the enriched model to allow staffs to apply the theories learnt during didactic lectures. This new pilot practical sessions were conducted over a period of 6‐months across two SCH ‐ Sengkang Community Hospital and Outram Community Hospital. The team developed various personas based on the common behaviours of concern that are seen in the hospital for better application of skills taught. Staffs were encouraged to use various communication and treatment strategies to engage and manage the behaviours of concern after understanding the personas.

To evaluate the simulation practical sessions effectiveness, a pre‐and‐post‐measurement of staffs’ confidence in managing patients with BPSD and their knowledge on how to manage patients with BPSD in the ward, and qualitative feedback on the modules were obtained. Overall, there is an increase in confidence and knowledge level by 24% and 46% respectively post‐sessions, and participants felt that role‐playing allowed them to have better understanding on handling certain situations and to apply their skills and knowledge learnt. In conclusion, there is a successful spread of this session in SCH, and we aim to spread the knowledge to the rest of the multi‐disciplinary team members in future.
Contraception in Female Volunteer in Alzheimer’s Prevention Initiative Autosomal‐dominant Alzheimer’s disease Colombia Trial, a Phase II Clinical Trial to Test Safety and Efficacy of Crenezumab
Authors: Martínez Juan F , Bustamante Christian , Navarro Alexander , Lopera Margarita M , Villegas Gustavo , Acosta‐Baena Natalia , Duque Sindy , Tariot Pierre N. , Langbaum Jessica B. , Ríos‐Romenets Silvia , Lopera Francisco
Published: December 2023

Background

In most prevention clinical trials contraceptive use is required. The API ADAD Colombia Trial was a phase II, double‐blind, placebo‐controlled clinical trial to evaluate the safety and efficacy of the investigational product crenezumab. Trial period A was carried out from 2013 to 2021, during which 252 cognitively unimpaired PSEN1 E280A mutation carriers and non‐carriers were enrolled to be treated with crenezumab or placebo, including 159 women from 30 to 60 years of age. We describe strategies to address contraception in female volunteers.

Method

For women of childbearing age, using two contraceptive methods and taking a pregnancy test before each administration of the investigational product was required. Different strategies were used to try to guarantee the adherence of the participants to the contraception methods: comprehensive educational activities, educational brochures, annual newsletters, medical advice on contraception methods and in some cases referral to a gynecology specialist to select the best contraception method. The General Fertility Rate (GFR) was used to evaluate the efficacy of the implemented strategies for contraceptive use. Using the parametric Welch’s t‐test, we compared the GFR rates between trial volunteers and the Colombian population using data reported by the National Administrative Department of Statistics.

Result

Tubectomy plus condom use 33.9% (54/159) and oral contraceptives plus condom use 15.1% (24/159) were the most common combinations used by volunteers. Ten women (6.3%) became pregnant during trial period A. Four of these pregnancies were due to therapeutic failure because at each visit the use of contraceptive methods was controlled and recorded in the medical history, three due to inappropriate contraceptive drug use reported by the participants, two were planned by the volunteers and one participant with difficulties in adherence to follow up visits. Significantly lower mean of GFR (p‐value = 2.68×10‐5) was observed in API ADAD volunteers compared to the Colombian population over the 7 years.

Conclusion

According the p‐value obtained to compare the GFR between trial volunteers and the Colombian population, the strategies used to address contraception by the site were effective for the prevention of pregnancies.
Neuroimaging Results and A4 in the Context of the LEARN Study
Authors: Sperling Reisa A. , Donohue Michael C. , Raman Rema , Rafii Michael S , Johnson Keith A. , Yaari Roy , Mancini Michele , Holdridge Karen C. , Case Michael G. , Sims John R. , Aisen Paul S. S ,   A4 and LEARN Study Group
Published: December 2023

Background

The A4 Study was a 240‐week, double‐blind, placebo‐controlled Phase 3 secondary prevention trial in cognitively unimpaired adults (ages 65‐85) with elevated amyloid on PET testing solanezumab, a monoclonal antibody targeting soluble amyloid‐beta. The companion LEARN Study enrolled participants who were otherwise eligible for A4 but did
not
show elevated amyloid.

Method

Entry criteria included CDR‐Global Scale (CDR‐GS) = 0, MMSE≥25, WMS Logical Memory = 6‐18, and elevated amyloid on florbetapir PET (for A4). The primary outcome measure was the Preclinical Alzheimer Cognitive Composite (PACC) with key secondary functional measures: Cognitive Function Index (CFI), Activities of Daily Living Scale (ADL), and CDR‐GS. A subset of participants underwent flortaucipir Tau PET.

Result

For A4, 1169 randomized: 578 to solanezumab and 591 to placebo. Treatment groups were well matched. Solanezumab did not slow cognitive decline on the PACC (mean change (95% CI): placebo ‐1.13 (‐1.45,‐0.81); solanezumab ‐1.43 (‐1.83,‐1.03); p = .260). Secondary clinical outcomes were consistent, numerically favoring placebo. Across both arms, 36.1% progressed to symptomatic AD, defined as CDR‐GS> 0 at two consecutive visits or final visit. Higher baseline amyloid levels were strongly associated with faster cognitive decline and greater risk of progression to symptomatic AD across both groups (p<.001). Amyloid continued to accumulate in both placebo (65.9 centiloid baseline, 19.3 increase) and solanezumab (66.2 centiloid baseline, 11.6 increase) groups. Tau PET showed similar increases in placebo and solanezumab groups in medial temporal lobe and neocortical composites, that were negatively correlated with PACC decline. No serious safety signals for solanezumab were identified, with only one case of ARIA‐E. ARIA‐H rates were similar across groups. LEARN participants (N = 538, 4.2 centiloid baseline on amyloid PET) did not demonstrate cognitive decline.

Conclusion

The A4 Study demonstrated the feasibility of conducting a large‐scale trial in preclinical AD, with cognitive and functional measures sensitive to decline. Solanezumab did not slow cognitive decline or clinical progression. Baseline amyloid PET was among the strongest predictors of decline across both placebo and solanezumab. LEARN participants did not demonstrate decline. These results suggest that amyloid plaque removal may be necessary even at this very early stage of AD.
omicSynth: an open multi‐omic community resource for identifying druggable targets across neurodegenerative diseases
Authors: Alvarado Chelsea X , Makarious Mary B , Vitale Dan , Koretsky Mathew J , Bandres‐Ciga Sara , Iwaki Hirotaka , Levine Kristin , Singleton Andrew , Faghri Faraz , Nalls Mike A , Leonard Hampton L
Published: December 2023

Background

While there have been recent successes for Alzheimer’s disease (AD) therapeutics, successful disease‐modifying treatments for AD and neurodegenerative disorders (NDD) remain rare, highlighting the importance of a mechanistic approach in creating therapies. There is an urgent need for disease‐modifying therapeutics, as the World Health Organization estimates dementia diagnosis to reach 78 million by 2030. Ultimately, in the absence of disease‐modifying therapies, the devastating health, social, and economic impacts of dementia and related NDDs will be catastrophic. Here, we generate new understandings on the basis of six NDDs, including AD, and to identify rational therapeutic targets that are genetically backed.

Method

We utilized six NDD specific genome wide association studies (GWAS) ‐ AD, amyotrophic lateral sclerosis (ALS), Lewy body dementia (LBD), Parkinson’s disease (PD), and Progressive supranuclear palsy (PSP) ‐ and multi‐omic data sets to perform Summary‐data‐based Mendelian Randomization (SMR) to identify genetic targets. We created a therapeutic scheme to classify identified target genes into strata based on known druggability and approved therapeutics for enabling drug discovery and repurposing. We prioritized identified genes as therapeutic targets of interest into three categories: “novel”, “known”, and “difficult”. In parallel, we provide mechanistic insights into disease processes and potential network‐level consequences of gene‐based therapeutics.

Result

We identified 116 AD, 3 ALS, 5 LBD, 46 PD, and 9 PSP target genes passing multiple test corrections (pSMR_multi < 2.95E‐06 and pHEIDI > 0.01) of which 15 were significant in more than two NDDs. Identified target genes were then classified into 41 novel targets, 3 known targets, and 115 difficult targets ‐ corresponding to our therapeutic scheme. Overall, we found four significant target genes in AD and PD, APOC4, LRRC37A2, MMRN1, and ZNF646, and one gene in companion gene networks in ALS, OXT, to present potential liver toxicity issues.

Conclusion

Our findings and a therapeutic scheme nominate 41 novel targets as promising for drug discovery and repurposing. In particular, KAT8 and KCNN4 present as promising gene targets for further drug development and repurposing. Existing therapeutic compounds, MG149 and Riluzole, target them both genes and have been successfully used in reducing NDD‐related symptomatology.