bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of NULISA™ CNS Disease Panel 120 for comprehensive proteomic profiling of neurodegenerative diseases
Authors: Ma Xiao‐Jun , Iyengar Shweta , Deshmukh Shalaka , Comandor Roopa , Kim Sean , Xu Xiaomei , Qiu Xioalei , Zhang Bingqing , Luo Yuling
Published: January 2025

Background

The development of reliable blood biomarkers for neurodegenerative diseases (NDDs) has been hindered by the lack of tools with sufficient sensitivity to detect low concentrations of brain‐derived proteins in plasma or serum in a highly multiplexed manner. NULISA™ (NUcleic acid‐Linked Immuno‐Sandwich Assay) has emerged as a promising solution, with attomolar sensitivity and capable of high multiplexing in a fully automated system. In this study, we introduce NULISA CNS Disease Panel 120, a 120‐plex NULISAseq assay for profiling key hallmarks of NDDs in both blood and cerebrospinal fluid (CSF).

Methods

NULISA CNS Disease Panel 120 includes many established and emerging disease markers such as amyloid beta 38/40/42, phosphorylated Tau (p‐Tau181, p‐Tau217, and p‐Tau231), neurofilament light and alpha synuclein as well as APOE ε4 for APOE status. NULISA single‐plex assays for each target were developed and pooled into a 120‐plex assay with signal tuning to optimize detection of both low and high abundance targets simultaneously in both plasma and CSF samples. Performance assessment included target detectability, assay precision, and detection of differential abundance between disease and control groups using plasma (n=38) and CSF (n=29) samples from NDD patients and age‐matched controls.

Results

We developed a CNS disease panel consisting of 120 targets linked to various pathways and processes characteristic of NDDs. Using just 10 µL of plasma or CSF, NULISA™ CNS Disease Panel 120 detected approximately 95% of targets in plasma and around 85% in CSF. It demonstrated high precision, with a median coefficient of variation (CV) of approximately 6.0%. Through linear regression analysis, we identified both known and novel proteins exhibiting significant differences in abundance between disease and age‐matched controls. Furthermore, the APOE ε4 assay accurately classified donor APOE status into carriers and non‐carriers using both sample types.

Conclusion

We developed a comprehensive CNS disease‐targeted panel for the NULISA platform to meet the increasing demand for blood‐based biomarker discovery and validation. NULISA CNS Disease Panel 120 provides a powerful new research tool for the early detection and diagnosis of NDDs and developing novel therapeutic interventions.
Using a Community Based Participatory Research Approach to recruit American Samoans for Alzheimer’s Disease and Related Dementia Research
Authors: Tuatoo Grace
Published: January 2025

Background

The Puipui Malu Manatu (PMM) study (RF1AG075904) is determining Alzheimer’s Disease and Related Dementias (ADRD) prevalence by administering cognitive assessment tools and determining prevalence of known genetic and plasma biomarkers. The sampling method uses a cluster and selection process to obtain a randomized sample of 1089 adults that is generalizable to the population. Research hesitancy exists due to historical abuse of non‐Indigenous researchers conducting studies that are not reflective of the community health needs. Community based participatory research (CBPR) approaches utilize diverse stakeholders in various levels of a study to ensure trust, respect, and reciprocity between the researchers and a community. Our previous studies have shown using CBPR approach with a cultural lens that shows fa’aaloalo (respect) have been effective in recruiting participants.

Methods

We incorporated CBPR approaches that follow the Fa’aSamoa (Samoan way/culture) to promote awareness of the PMM objectives and recruit eligible participants. The adherence of cultural protocol was accomplished by presenting at the Office of Samoan Affairs (OSA). The OSA is comprised of the Pulenu’u (village mayor), led by an Ali’i (Paramount Chief), and is the cultural governance body for villages. Essentially making them gatekeepers to eligible participants. The Secretary of Samoan Affairs provided a letter of support, granting the access to the villages via Pulenu’u. We implemented the “PMM on Wheels” in the remote village of Aoa in collaboration with the Pulenu’u.

Results

The support from the OSA and Pulenu’u allowed for the first “PMM on Wheels” to be conducted. The staff recruited 10 eligible participants who would not be able to access the two study site locations. Furthermore, we were able to maintain randomization in our sampling strategy. Participants completed cognitive assessments and provided a blood sample. Future events are scheduled in the beginning of 2024.

Conclusion

Negative reactions towards research studies in Indigenous populations have been supported by historical abuses by non‐Indigenous researchers. Utilizing CBPR with a cultural lens in the American Samoa population has shown rebuild trust and fa’aaloalo to better the health outcomes of the community.
Foodomics: Links to cognition and AD markers of disease
Authors: Labus Jennifer S , Nho Kwangsik , Zuffa Simone , Batra Richa , Meehan Michael , West Kiana , Zemlin Jasmine , Caraballo‐Rodriguez Andres Mauricio , Dorrestein Pieter , Kaddurah‐Daouk Rima ,   Alzheimer's Gut Microbiome Project Consortium (AGMP)
Published: January 2025

Background

Diet has been associated with memory, emotion/stress regulation, structure and function of the hippocampus and amygdala and attenuation of cognitive aging. There is a well‐recognized lack of reliability in self‐reported dietary intake and great interest in objective metabolic readout of dietary patterns. In this study we constructed dietary profiles from untargeted metabolomics data using a novel metadata‐based source annotation method developed at the Dorrestein Lab, also referred to as “foodomics”. The aim of was to link these objective metabolic readouts of dietary intake to cognition and AD markers of disease.

Method

Untargeted metabolomic profiling (LC‐MS/MS) was applied to blood samples from 872 individuals from the ADNI cohort (182 cognitive normal individuals, 449 MCI, 103 significant memory concern, and 139 AD); for whom brain imaging data was also collected. Principal component analysis (PCA) was to derive a dietary profile that explained the most variance in the dataset. Whole‐brain voxel‐wise analysis was applied to determine association between dietary intake profiles and brain amyloid‐β deposition (amyloid PET), gray matter density (brain atrophy; MRI), and glucose metabolism (FDG PET) using a multivariate regression analysis with SPM12. The general linear model was used to examining the associations of the dietary profile with cognition and AD markers. Covariates included age, education, sex, and BMI.

Result

Correlation between the first principal component (PC1) and the relative abundances of foods at level 3 of the food ontology showed that PC1 explained variance derived from food intake within poultry, dairy, meat, egg, vegetable, legume and seafood categories (Figure 1). Greater intake of poultry, dairy, and meat was significantly associated with 1) reduced glucose metabolism and brain gray matter atrophy in the frontal, parietal, and temporal (including the hippocampus; Figure 2,3) and 2) difficulties with executive functioning (p=0.03) and memory at baseline (p=0.002), longitudinal decreases in memory functioning over time (p=.02), and increases in baseline plasma levels of neurofilament light chain at baseline (p=.02).

Conclusion

Dietary intake selectively influences glucose metabolism and gray matter atrophy of brain regions preferentially targeted in AD, cognition and neurofilament light chain. This proof‐of‐concept study supports the hypotheses that diet influences the progression of the disease. NIA U19 AG063744
Sex differences in the association of cognitive impairment and sleep‐disordered breathing measures among diverse adults
Authors: Milton Sasha , Peltz Carrie B. , Redline Susan , O'Bryant Sid E. , Yaffe Kristine , Leng Yue
Published: January 2025

Background

Growing evidence reports an association between sleep‐disordered breathing (SDB) and cognitive impairment, including mild cognitive impairment (MCI) and dementia. However, there is limited research on the link between cognitive impairment and in‐home measures of SDB and how this association may differ by race, ethnicity, and sex.

Method

We studied 822 individuals who were enrolled in the community‐based Health and Aging Brain Study‐Health Disparities (HABS‐HD)‐Dormir study. In‐home measures of SDB were collected using WatchPAT (WatchPAT‐200). Data were processed using the zzzPAT software (5.2.79.7p) and manually edited by trained polysomnologists. Measures included the respiratory event index (REI), oxygen desaturation index (ODI), snoring volume (percentage of the night over 40 dB), and oxygen saturation (SpO2; three measures, including percentage of night at SpO2 <90%, mean SpO2, and minimum SpO2). A comprehensive clinical evaluation was used to determine normal cognition (NC), MCI, or dementia.

Result

Our sample (mean [SD] age = 66.6 [8.5] years) was 66.2% women; 34.7% Mexican American and 21.2% Black; and 17.3% MCI and 4.1% dementia. After adjustment for age, race, sex, body mass index (BMI), and comorbidities, participants with MCI/dementia had greater odds of a non‐rapid eye movement (NREM)‐ODI of ≥15 [OR (95% CI) = 1.60 (1.02,2.5)] compared to those with NC. Additionally, men with MCI/dementia were more likely to snore at >40 dB for >25% of the night [OR (95% CI) = 2.08 (1.13,3.82)] and to have a rapid eye movement (REM)‐REI ≥15 [OR (95% CI) = 1.87 (1.01,3.61)] than men with NC, while these associations were not present for women [OR (95% CI), snoring = 0.74 (0.42,1.27), p for interaction = 0.02; REM‐REI: 0.88 (0.49,1.62), 0.09]. Other measures of SDB were not associated with cognitive diagnoses. The associations between cognitive diagnoses and SDB measures were similar across race groups.

Conclusion

Among middle‐aged to older men and women, measures of SDB varied in their association with MCI or dementia by sleep stage and by sex. Future investigations should consider sleep‐state specific sleep disturbances as markers or risk factors for cognitive impairment and examine potential sex differences in those associations.
Potential probiotic (L. plantarum, L. pentosus, P. pentosaceus, W. cibaria and L. rhamnosus) alleviates memory impairment in lipopolysaccharide‐induced cognitive dysfunction and neurotoxicity in mice brain via protection against neuroinflammation and neurodegeneration
Authors: Obisesan Abiola Oluwatosin , Dodo Samuel O , Adeniyi Funmilayo Racheal , Olayinka Juliet Nnenda , Adeoluwa Olusegun Adebayo , Fafure Adedamola O
Published: January 2025

Background

The impact of probiotics as gut and immunological modulator in restoring gut microbial balance and immune cells expression have generated much attention in the health sector. Its inhibitory effect on bacterial translocation and associated neural inflammatory processes has been reported. However, there is scarcity of data on its neuroprotective impact against neuroinflammation‐associated neurodegeneration and memory impairment. Therefore, we tested the neuroprotective capabilities of the probiotic strains against lipopolysaccharide (LPS)‐induced neurotoxicity and memory impairment in mice.

Method

Forty eight mice (n = 12) weighing 25 ‐ 30 g were randomly classified into four groups consisting of probiotic strains (107 CFU/ml, orally), donepezil (3 mg/kg, intraperitoneally (i.p.)), normal saline (10 ml/kg, orally), and LPS (0.25 mg/kg i.p) group. LPS was injected 60 min after treatments for seven days. Novel object recognition (NORT) and Y‐maze tests were performed 24 h following the last treatment to assess cognitive functions. Dendritic spine of the dentate gyrus was stained with Golgi cox. Immunohistochemistry detected brain‐derived neurotrophic factor (BDNF) expression as well as Iba 1 and amyloid beta activation in the hippocampus and prefrontal cortex, while enzyme‐linked immunosorbent assay was used to measure neuroinflammation (tumor necrosis factor‐α (TNF‐α), interleukin‐1 beta (IL‐1β), interleukin‐12 (IL‐12), and interferon gamma (IFN‐γ)) and oxidative stress biomarkers (glutathione (GSH) and malondialdehyde (MDA)).

Result

Probiotics reduced elevation of pro‐inflammatory cytokines, MDA levels and enhanced GSH levels in the brain. Probiotic strains enhanced BDNF expressions, reduced microglia and amyloid beta activation in the hippocampus and prefrontal cortex of LPS‐induced mice.

Conclusion

These finding show that probiotic strains may possess neuroprotective effect against LPS‐induced cognitive impairment and neurodegeneration via antioxidant and anti‐inflammatory mechanisms.
Assessing treatment value under uncertainty: Measuring treatment value for a new treatment for cognitive impairment
Authors: Shafrin Jason , Than Kyi‐Sin , Kim Jaehong , Fajnor Jacob , Mearns Elizabeth S , Kowal Stacey L , Majda Thomas , Hlavka Jakub
Published: January 2025

Background

The value payers and policymakers traditionally place on novel treatments for Alzheimer’s and other neurological diseases that cause cognitive impairment (CI) and dementia often ignores disease baseline severity. More patient‐centered economic evaluations—such as those estimating “insurance value”—incorporate the fact that individuals are typically risk‐averse and place high value on generous coverage of treatments in the event that they develop CI, such as severe dementia, later in life. This study aims to estimate this insurance value, accounting for risk aversion, relative to the value of the same treatment based on traditional payer cost effectiveness approaches.

Method

A survey was administered to US residents aged ≥ 21 years. First, a multiple random staircase design was used to elicit respondents’ willingness to pay for insurance coverage of a hypothetical, novel treatment that delays progression from mild CI to dementia relative to best supportive care. The treatment’s “insurance value” was calculated as respondent’s stated willingness to pay less traditional value assessment estimates [i.e., the product of annual incidence (0.4%) and monetized, discounted value of quality‐adjusted life years (QALY) gained from treatment (0.652 QALYs x $100,000 per QALY)]. Risk aversion over quality‐of‐life outcomes was also estimated.

Result

Among n = 295 respondents, 64.9% were female and average age was 51.1 (SD = 16.0). Willingness to pay for generous insurance coverage of a novel treatment delaying the onset of dementia was $646.88 per year compared to the value of the same treatment of $260.80 calculated under traditional cost‐effectiveness approaches. In other words, treatment value of novel treatments for CI were 2.5 times higher using the patient‐centered insurance value approach than using the traditional cost‐effectiveness methodology. Respondents were found to be risk averse (relative risk aversion = 1.49, 95% CI: 1.29, 1.68).

Conclusion

Individuals place significant value on treatments that delay onset of cognitive impairments such as severe dementia. Traditional cost‐effectiveness may understate treatment value relative to more patient‐centered approaches that incorporate “insurance value”.
Structural and metabolic topological alterations underlying butylphthalide treatment in mild cognitive impairment due to Alzheimer’s disease and topology‐based machine learning for drug efficacy
Authors: Han Xiaodong , Gong Shuting , Wang Pin , Li Ruina , Chen Runqi , Xu Chang , Sun Wenxian , Gong Jin , Li Shaoqi , Wei Cuibai
Published: January 2025

Background

Effective early intervention of mild cognitive impairment (MCI) is the key for preventing dementia. However, there is currently no drug for MCI. As a multi‐targeted neuroprotective agent, butylphthalide has been demonstrated to repair cognition in patients with vascular cognitive impairment, and has the potential to treat MCI due to Alzheimer’s disease (AD). However, the pharmacological mechanism of butylphthalide from brain network perspective is not clear.

Method

In this clinical trial, 270 patients with MCI due to AD were assigned at a ratio of 1:1 to receive either butylphthalide or placebo for one year. Alzheimer’s disease assessment scale‐cognitive section (ADAS‐cog) scores was set up as the primary endpoint, and effective treatment was defined as the decrease of ADAS‐cog>2.5. T1‐magnetic resonance imaging and fluorodexoyglucose positron emission tomography data were collected in baseline and follow‐up, and the Kullback‐Leibler divergence similarity estimation method was applied to construct the individual structural and metabolic networks. We used repeated‐measures analysis of variance to investigate group (drug group vs. placebo group; effective group vs. ineffective group)‐time interactions on ADAS‐cog and network metrics, and support vector machine was applied to develop the predictive models.

Result

Butylphthalide significantly improved the cognition of patients with MCI due to AD (multivariable‐adjusted P<0.05). There were some overlapped structural network metrics on which both the treatment group‐time interactions and efficacy group‐time interactions were potentially significant (uncorrected multivariable‐adjusted P<0.05), and the metrics were: global efficiency, degree centrality and nodal efficiency of left paracentral lobule, degree centrality of right inferior temporal gyrus, and nodal efficiency of left superior frontal gyrus, medial. Of these an increased degree centrality of left paracentral lobule was significantly related to poorer cognitive improvement. Further simple effects analyses revealed an significantly increased global efficiency in structural network under both treatment and effective treatment of butylphthalide (multivariable‐adjusted P<0.05). Predictive model based on baseline multimodal network metrics exhibited the highest accuracy (88.93%) for predicting butylphthalide’s efficacy.

Conclusion

Butylphthalide may improve cognitive function in patients with MCI due to AD by repairing abnormal organization in structural networks. Baseline multimodal network metrics could be potential predictive markers of therapeutic efficacy of anti‐AD drugs.
APPLICATION OF CLASSICAL AND MACHINE LEARNING MODELS ON OASIS ‐ 2 DATA
Authors: Arslan Rümeysa Rana
Published: January 2025

Background

Alzheimer’s disease (AD) is a significant global health issue that affects both individuals and society for older adults. Early detection is essential in Alzheimer’s disease, as there is no definite treatment, and prevention is possible through early detection. In the studies of Alzheimer's disease, different approaches are used to understand the characteristics of the disease, including imaging methods such as MRI scans, biomarkers, and quantitative data from MRI scans. With these methods, the cognitive status of individuals could be determined. It is essential to detect the features affecting Alzheimer’s disease and detect the disease early and automate the detection and prediction by using modeling tools and by examining the datasets.

Method

The symptoms of the disease can be observed over time, making the structure of the study longitudinal. Classical statistical models and machine learning algorithms can be used to analyze these datasets. The OASIS – 2 dataset is employed to find the features affecting dementia status and compare models' performances. The classical mixed models, their extended versions, and hybrid models, Boruta, GEE, GLMM, HGLM, GLMMLasso, GPBoost, GLMMTree, and HRF, are used to analyze the longitudinal dataset with a small sample size and binary outcome. Model performances are measured using accuracy, F1 score, sensitivity, and specificity, and the results are interpreted using the odds ratio.

Result

GPBoost learns and classifies the dementia status well but overfits due to the small sample size in the dataset, and tree‐based algorithms are efficient in predicting the dementia status when a new subject enters the study.

Conclusion

The common significant variables to address the dementia status of individuals are MMSE, nWBV, education, gender, and age. The results also indicate that the increase in MMSE score means the patient is less likely to be demented; the increase in normalized whole brain volume indicates a less probability to be demented; increase in socioeconomic status results in the patient having less probability to be demented; males are more likely to be demented; age has a negative impact on being demented; the increase in education years results in the patient having less probability to be demented.
Sleep and Cognition in the Long Life Family Study
Authors: Gordon Emma , Gu Yian , Cosentino Stephanie , Andersen Stacy L. , Ukraintseva Svetlana
Published: January 2025

Background

Many studies have demonstrated an association between sleep and cognition in older adults. The Long Life Family Study (LLFS) has followed families enriched with longevity since 2006 and has shown that this cohort has slower rates of cognitive decline than their spouse controls and the general public. Understanding how sleep and cognition are related in this population can improve our understanding of the key to long life.

Method

Our study includes 2344 participants from the LLFS, who were ≥60 years at baseline, and completed sleep and cognitive measures. A neuropsychological battery was used to measure episodic (Logical Memory IA and IIA from the Wechsler Memory Scale ‐Revised (WMS‐R)), semantic (Categorical Fluency Test), and working memory (Number Span Forward and Backward Tests) at baseline (2006‐2009), and in a subset of 1633 participants at the follow‐up visits 6.9 (SD = 2.7) years later. Sleep habits were assessed once using the Health Habits (HH) Questionnaire between the two cognitive measures. The association between sleep duration and memory was examined using generalized estimating equations models that accounted for relationship with the long‐life families.

Result

Compared to those with 6.5‐8.5 hours of sleep, those with > 8.5 hours of sleep had lower episodic memory scores at baseline (b = ‐0.705, p = 0.021), but not at follow‐up (b = ‐0.627, p = 0.149), after controlling for age, sex, field center, APOE, and generation. Sleep duration was not associated with semantic or working memory. Those who had > 8.5 hours of sleep had faster decline in all memory scores, although not significantly. There was no difference in memory scores comparing < 6.5 hours of sleep to 6.5‐8.5 hours of sleep.

Conclusion

Lower memory scores at baseline predicted longer sleep time subsequently, while sleep time did not predict memory performance on follow‐up. Overall, the current study did not support sleep duration as a significant contributor to memory decline. This contradicts some earlier findings and prompts further investigation into the connection between sleep and cognition, especially within this population and specifically into whether increased sleep time and memory decline share an underlying mechanism, or memory decline causes longer sleep time.
Design of a Phase 1, First‐in‐human, Randomized, Double‐blind, Placebo‐controlled, Single and Multiple Ascending Dose Study of a Novel Orally Administered TREM2 Agonist (VG‐3927) in Healthy Volunteers
Authors: Rajagovindan Raj , Gaudreault Francois , O’Mara Ryan , Thackaberry Evan A. , Stromme Jessica , Gray David L. , Meier Andreas
Published: January 2025

Background

VG‐3927 is a highly potent, selective, brain penetrant, oral small molecule TREM2 agonist that is currently under development for the treatment of Alzheimer’s disease (AD). TREM2, a receptor expressed on microglia in the brain is critical to microglial function in health and in disease. Among microglia‐associated AD risk genes, partial loss‐of‐function variants of TREM2 confer 2‐3 fold increase in risk for developing AD, motivating efforts to identify pharmacological agonists targeting TREM2 as a therapeutic option. VG‐3927 is designed to act as a molecular glue that potentiates the TREM2 signaling response to natural damage ligands and is hypothesized to promote microglial function and health, and tissue repair mechanisms regulated by microglia thereby slowing disease progression in AD.

Methods

The Phase 1 randomized, double‐blind, placebo‐controlled study will evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics after single‐ (SAD) and multiple‐ascending dose (MAD) of orally administered VG‐3927 in healthy volunteers. The study will enroll healthy adults aged 18 to 55 years and include SAD and MAD cohorts that are planned to be tested sequentially in a dose‐escalating manner. Eight participants will be randomized in a 6:2 allocation ratio to VG‐3927 or placebo into each of the planned cohorts. The treatment period for the SAD and the MAD portions will be 1 day and 14 days respectively with safety follow‐up through 28 days after the last dose for both portions. Study assessments to investigate safety and tolerability will include physical exams, neurological exams, vitals, ECG, clinical laboratory, C‐SSRS and AE reporting in all cohorts. Blood samples will be collected in all cohorts to characterize the pharmacokinetics and CSF samples will be collected in selected cohorts to investigate biomarkers of target engagement and downstream pharmacodynamic activity.

Results

The study dosed its first participant in October 2023 and is currently ongoing. The design of the Phase 1 study will be presented.

Conclusions

The ongoing Phase 1 study will assess the safety, tolerability, pharmacokinetics, and pharmacodynamics of VG‐3927 in healthy volunteers and is expected to inform subsequent development in AD.
Characterization of cerebrospinal fluid tau MTBR species binding to Bepranemab
Authors: Barthélemy Nicolas R. , He Yingxin , Androff Brendan , Li Yan , Nguyên Thi Liên‐Anh , Downey Patrick , McDade Eric , Bateman Randall J.
Published: January 2025

Background

Alzheimer’s disease neuropathology involves the deposition in brain of aggregates enriched with microtubule‐binding‐region (MTBR) of tau adopting an abnormal conformation between residues 306‐378 in the core of aggregates. Anti‐tau drugs targeting around this domain have the potential to interfere with the cell‐to‐cell propagation of pathological tau. Bepranemab is a humanized monoclonal Ig4 antibody binding to tau residues 235‐250. Previous studies showed this antibody binds to tau monomers; inhibits tau seeding in cellular assay and prevents tau pathology spread in a mouse model. The target engagement of bepranemab in human biofluids is unknown. This study aims to characterize cerebrospinal fluid (CSF) tau species binding to this antibody.

Methods

We used mass spectrometry (MS) to characterize CSF tau species precipitating with bepranemab cross‐linked to sepharose beads. Precipitated CSF tau species were digested with trypsin and tau peptides were quantified by signal comparison to peptides from tau labeled standard. We characterized and compared the amount of bepranemab‐reactive tau species recovered from neat CSF and from CSF initially depleted from N‐terminal and Mid‐domain truncated tau species. Then, we analyzed Bepranemab precipitates in CSF samples from 14 asymptomatic dominantly inherited Alzheimer’s disease (DIAD) mutation carriers (aMC), 16 symptomatic (sMC) and 15 non‐carriers (NC).

Results

Bepranemab bound to a mixture of CSF N‐terminal and Mid‐domain tau‐truncated fragments including mainly 226‐254 tau residues on their C‐terminal domain (Figure 1). Bepranemab‐reactive species not containing the N‐ter and the Mid‐domain of tau were mostly comprised of fragments including tau residues 226 to 267. Minor bepranemab‐reactive tau species contained tau residues 275 to 290 on their C‐terminal. Tau peptides after residues 317 were not detected above the MS limit of detection. In DIAD, the pool of bepranemab‐immunoreactive CSF tau fragments significantly increased in asymptomatic and symptomatic mutations carriers respectively (Figure 2).

Conclusions

The pool of CSF tau species included a subset of tau MTBR‐containing fragments recovered by bepranemab. A minor fraction of these fragments had domains overlapping with the upstream domain constituting the AD tau aggregate core. These fragments increased over DIAD stages. Our study supports bepranemab engagement against a specific pool of tau species in CSF. This work was sponsored by UCB.
Prevalence and factors associated with the burden of caregivers of older adults with post‐COVID syndrome
Authors: Cintra Fabiana Carla Matos da Cunha , Cintra Marco Túlio , Vallle Estevão Alves , Lommez Vitória Lanza , Carvalho Júlia Monção Dias , Duarte Antônio Augusto De Carvalho , Azevedo Gerson Santos , Fortini Iza de Faria , Viana Bernardo De Mattos , Bicalho Maria Aparecida Camargos
Published: January 2025

Background

Post‐Covid syndrome is related to functional, cognitive, psychological and physical impairments in older adults, which has been associated with caregiver burden.

Method

Cross‐sectional study nested within a prospective cohort, which recruited participants aged 60 and over, and their respective caregivers, twelve months after laboratory diagnosis of Covid‐19. The project was approved by UFMG’s ethics committee. The Zarit Burden Interview and Hamilton depression scales were used to assess caregiver burden and depression, respectively. d. Caregiver burden was categorized as present with a cutoff of 15 points. The Chi‐Square and Mann Whitney tests were used for categorical and continuous variables, respectively. Variables with a p value <0.2 were subjected to multivariate analysis using the backward method. The SPSS statistical package, version 25.0, was used.

Result

52 participants and their respective caregivers were evaluated. Among the participants, 60.8% were hospitalized, had a mean age of 72.39±9.1 years, education of 7.67±4.7 years and 51% were female. Caregivers had a mean age of 55.27±15.9 years, education of 10.9±4.8 years, 76.5% were female, 92.1% were spouses or children, 64% lived with the participant and 44% had income between 1 and 2 minimum wages. The prevalence of caregiver burden was 54.2%, being 42.3% of these cases of moderate intensity. An association was observed, in univariate analysis, with the caregiver’s depressive symptoms OR = 1.331 (95%CI 1.109‐1.598; p‐value<0.001), participant’s depressive symptoms OR = 5.429 (95%CI 1.285‐22.941; p‐value = 0.005) and living with the elderly OR = 3.073 (95%CI 1.299‐7.269; p‐value = 0.004). After multivariate analysis, only the caregiver’s depressive symptoms showed an association OR = 1.331 (95% CI 1.109‐1.598; p‐value = 0.002).

Conclusion

The prevalence of burden among caregivers of elderly people with Post‐Covid Syndrome was high and was associated with caregiver’s depressive symptoms, indicating the need for long‐term support and assessment of this population.
Assessment improved of cognitive impairment with artificial intelligence in the user‐web‐mobile application
Authors: De León Arturo Del Bosque‐Díaz , García‐Vázquez Mireya Saraí , Ramírez‐Acosta Alejandro Álvaro , Aguilar‐Navarro Sara Gloria , Mimenza Alberto Jose
Published: January 2025

Background

The World Health Organization forecasts a population of 2,000 million people over 60 years by the year 2050, with 7% of this population suffering from dementia. Making a constant clinical‐technological evaluation of older adults allows early detection of the disease and provides a better quality of life for the patient. In this sense, the research and development of innovative technological systems for the early detection of the disease, its monitoring and management of the growing number of patients with cognitive diseases has increased in recent years, integrating data collection and its automatic processing based on geriatric metrics into these systems using artificial intelligence (AI) methods.

Method

This research presents an interactive web platform that allows users with any intelligent device with internet access, to remotely perform an automated assessment of the Montreal Cognitive Assessment (MoCA) test. We use AI and neural network methods for binary and multiclass classification to obtain assessment scores according to geriatric metrics. The application provides an automated evaluation of the MoCA test, which can then be validated remotely by a mental health specialist.

Result

The tests performed show a correct correspondence in the handling of the information and results of each MoCA item with respect to the database. For the test database evaluated with the application, results are obtained with 100% accuracy and equal to the evaluations performed by specialists.

Conclusion

This automated assessment provides great help to the medical specialist in the process of detection and evaluation of cognitive impairment, significantly improving the quality of healthcare. The management and organization for the follow‐up of the patient’s cognitive impairment is done through the information of the tests performed, their evaluation and the clinical history of each patient. This information is consulted and managed by the doctor for the patient’s follow‐up; the caregiver/family member has access to tests performed, their evaluation and all the follow‐up that the doctor gives to the patient.

The interface was developed thinking in the elderly. It is intuitive, with the relevant information and graphic elements, the procedure for using the application is explained step‐by‐step, the colors used are comfortable for eye care.
Characterizing the Effects of Focused Ultrasound Therapy in Healthy and Alzheimer’s Disease Neurons
Authors: Shteyman Amy , Noel Rebecca L , Konofagou Elisa
Published: January 2025

Background

Focused ultrasound (FUS)‐induced blood‐brain barrier opening (BBBO) is a technique for safely, non‐invasively, and transiently opening the blood brain barrier in a targeted area of the brain. Pre‐clinical and clinical studies have shown that FUS is capable of decreasing amyloid plaque load and stimulating neurogenesis in Alzheimer’s Disease (AD) models, in addition to being safe for use in human patients. However, the effect of FUS‐BBBO on neurons has not yet been characterized, despite its crucial role in cognition and regulating brain function. The purpose of the study was to characterize the effects of FUS‐BBBO on neurons in an AD model in order to elucidate the effects of this emerging therapeutic on patients with AD.

Method

In this study, a triple transgenic (3xTg) mouse model of AD was used to investigate the effects of FUS‐BBBO on neurons in progressed AD. The relative expression of 80 key AD genes was compared between 4 different groups: naive wild‐type mice, naive 3xTg mice, FUS‐BBBO treated wild‐type mice, and FUS‐BBBO treated 3xTg mice, with two mice per condition. 2 days post‐FUS‐BBBO, hippocampal neuronal nuclei were isolated for qPCR to quantify relative changes in gene expression between the experimental groups.

Result

In wild‐type mice treated with FUS, synaptic plasticity and neurogenesis genes were over‐expressed. Key AD genes related to amyloid‐beta clearance, neurogenesis, and acetylcholine metabolism began to return to baseline wild‐type values in AD mice treated with FUS in comparison to untreated AD mice.

Conclusion

This study offers preliminary characterization of the effects of FUS in neurons in both WT and AD mice. Future work will help understand the therapeutic effects of FUS BBBO treatment for patients with AD.
Sensitivity, specificity, and regression‐based norms for the digital version of the Neurocognitive Frailty Index
Authors: Pakzad Sarah , Bourque Paul , Saucier Daniel
Published: January 2025

Background

Integrating technology in the cognitive assessment process could help with dementia care and management (Astell et al., 2019). The aim of this research was to assess the sensitivity and specificity, as well as establish regression‐based norms, for the digital version of the Neurocognitive Frailty Index (NFI, Pakzad et al., 2017).

Method

The digital version of the NFI was administered alongside the Montreal Cognitive Assessment (MoCA) on 238 people aged 50+ recruited from various communities across the province of New Brunswick, Canada. Agreement for mild cognitive impairment (MCI) between the digital NFI and the MoCA were analyzed. Normative data for the digital NFI was also derived from the study sample by modeling the distribution of the raw test scores conditional upon the norm‐predictors (age, sex, and level of education).

Result

Mean digital NFI score and standard deviation was 56.3±5.91, while mean MoCA score and standard deviation was 26.4±2.89. Area under the curve (AUC) for detecting MCI with the digital NFI in comparison to recommended MoCA cut‐off of normal ≥ 26 was 0.89 (0.84‐0.93 95% confidence interval). The optimal digital NFI cut‐off score for MCI was normal ≥ 57 with sensitivity of 0.92 and specificity of 0.78. All predictors contributed to establishing regression‐based norms for the digital NFI as to calculate expected scores given the age, sex, and level of education of an individual.

Conclusion

Age, sex, and education should be considered when using the NFI assessment tool. This will be facilitated by the regression‐based calculator created from these results that will be imbedded into the digital version of the NFI. This will provide percentiles for a subject’s NFI score within a personalized report that is auto generated upon test completion within the online digital NFI platform. The study results attest to the robustness of the digital version of the NFI as a measure with significant sensitivity and specificity.
Trajectories of work‐history and their associations with cognitive impairment in later life
Authors: Fu Peipei , Wang Yi
Published: January 2025

Background

The associations between work‐history trajectories and cognitive impairment among older adults were unknown. We investigated the association between work‐history patterns and cognitive trajectories in later life.

Method

We conducted the study by using four regular waves and Life History survey in the Harmonized Dataset of the China Health and Retirement Longitudinal Study (CHARLS), included 5511 participants (47.5% were female, 2619/5511) aged 60 years or older in China. Cognitive function was measured using Telephone Interview for Cognitive Status (TICS). We utilized sequence analysis to model the work‐history patterns of each individual between age 20 and 60. All work sequences are grouped into 7 trajectories, distinguished by salient occupational characteristics and dynamic career changes over the entire observation period. Growth curve modeling was performed to capture how the life course of work impacts both the static level and dynamic trend of the elderly’s cognitive function.

Result

Respondents with Stable Farming pattern displayed a 1.73 lower average cognitive functioning scores (p<0.001), and respondents belong to Farming to Late‐Non‐Agriculture had a 1.12 lower level (p<0.05). Respondents with Non‐agriculture to Late‐retirement or long‐run inactive patterns initially started with higher levels of cognitive functioning and declined at lower rates. Conversely, respondents with stable farming work pattern exhibited the worst cognitive functioning, in terms of both initial level and decline rate. No apparent evidence suggested there are significant differences on cognitive faculty in later life between the reference group and cluster 2 (Non‐Agriculture to Farming), cluster 5 (Non‐Agriculture to Late‐Retirement), cluster 3(Long‐term Inactive) and cluster 7(Long‐term Inactive).

Conclusion

We identified people who remained in farming enduringly or for prolonged durations showed diminished cognitive functioning levels and a heightened susceptibility to cognitive decline. Hence, it is of paramount importance to direct attention towards the cognitive well‐being of farmers or individuals with a substantial history of farming as they progress into their later years.
Social network size attenuates the negative effect of plasma pTau181 on memory and medial temporal lobe volumes
Authors: Lo Carina , Callies Lana S. , Diaz Valentina E. , Chen Coty , Tucker Miwa , Hallgarth Savannah R. , Saloner Rowan , Dutt Shubir , Watson Caitlin Wei‐Ming , Casaletto Kaitlin B. , Kramer Joel H. , Paolillo Emily W.
Published: January 2025

Background

Social health factors have been robustly associated with better cognitive health in older adults; however, less is known about how social network size affects the relationship between in‐vivo biomarkers of Alzheimer’s disease (AD) pathology and brain aging outcomes. We examined the independent and interactive relationships between plasma pTau181 and social network size on memory function and medial temporal lobe (MTL) volume in older adults.

Method

Participants were 58 community‐dwelling older adults (mean age = 75.8 ± 5.6 years, mean education = 17.2 ± 1.8 years, 57% female, 91% cognitively unimpaired) enrolled in research at the UCSF Memory and Aging Center. Participants completed blood draws with plasma analyzed for pTau181 concentration, neuropsychological testing, brain MRI, and the Social Network Index, a self‐report questionnaire measuring a participant’s social network size (total number of people the participant contacts at least once every two weeks). To investigate whether social network size moderates the relationship between AD pathology and memory, multiple linear regression models examined the interactions between plasma pTau181 and social network size on verbal memory (California Verbal Learning Test–II delayed free recall), visual memory (Benson Figure recall), and bilateral MTL volume controlling for age, sex, education, and intracranial volume (MRI model).

Result

Social network size and plasma pTau181 did not independently relate to MTL volume (ps>0.39), verbal memory (ps>0.53), or visual memory (ps>0.36). The interaction between social network size and plasma pTau181 on verbal memory was also not significant (p = 0.62). However, social network size significantly moderated the effect of plasma pTau181 on both visual memory (β = 0.33, 95%CI [0.13, 1.13], p = 0.015) and MTL volume (β = 0.27, 95%CI [0.05, 0.90], p = 0.03), such that negative effects of higher plasma pTau181 on worse visual memory and lower MTL volume were both attenuated with larger social network size.

Conclusion

Consistent with prior literature, results suggest a potential neuroprotective effect of social network size on AD‐related cognitive and brain aging. These findings highlight the importance of promoting protective lifestyle factors, including social network size, to support brain health in those at risk for AD‐related cognitive decline.
Do patients with early‐stage cognitive impairment have an increased risk to develop malnutrition? A cross‐sectional study
Authors: Lopes Pedro de Castro , Leopoldino Amanda Aparecida Oliveira , Machado João Carlos Barbosa , Barbosa Maira Tonidandel , Garcia Luana Rodrigues , Aguiar Bianca Pessoa , de Souza Júlia Caroline Barbosa , Ferreira João Pedro Neres Antunes
Published: January 2025

Background

Malnutrition is a condition associated with negative outcomes in elderly patients, such as loss of functionality and mortality. The cause of malnutrition is multifactorial: secondary to changes in eating habits, dysphagia and loss of interest in food. It is a frequent condition in patients with advanced dementia. However, more studies are needed to deeply understand the relationship between nutritional status and cognition. The main objective of this study is to understand whether patients with early‐stage cognitive impairment have an increased risk for malnutrition, as well as patients with advanced dementia.

Method

This is a cross‐sectional study in which 87 community‐dwelling elderly people were included and evaluated in relation to the presence of cognitive impairment and malnutrition. Patients with severe cognitive impairment, assessed by a score less than 6 in the CS‐10 (Point Cognitive Screening) were excluded. Individuals with a score between 6 and 7 on the CS‐10 were considered to have mild or moderate cognitive impairment and participants with a score greater than 7 on this test were considered to have no cognitive impairment. In order to evaluate risk of malnutrition, the Mini Nutritional Assessment (MNA) questionnaire was applied. Patients with a score lower than 12 were considered at risk of malnutrition and score higher than this was considered to be at no risk. In order to evaluate the association between the characteristics, Pearson’s chi‐square test was used. If the p‐value was lower than the significance level of 0.05, it is possible to conclude the association between a lower punctuation at MNA and a worse score in CS‐10.

Result

Patients with alteration in MNA have an average score of 7.92 on the CS‐10. For patients who have not had any alteration in MNA, the mean score is 8.58 points. However, these differences are not significant (p‐value 0.088) and this is not a relevant association (p‐value 0.271).

Conclusion

Despite of a tendency for patients with mild cognitive impairment to have a higher risk for developing malnutrition, it is not possible to affirm this relationship from this study, since no statistically significant association was identified.
Alzheimer disease combination therapy: learning from the HIV drug development cascade
Authors: Piamonte Bernadeth Lyn C , Dinnerstein Eric
Published: January 2025

Background

Once an incurable deadly disease of urgent public health concern, human immunodeficiency virus (HIV) infection has now evolved into a chronic condition largely manageable with combination therapy as the treatment standard. In comparison, Alzheimer disease (AD) is a fatal illness that continues to pose epidemiologic and socioeconomic challenges not only to persons and families affected by it but also to the healthcare system as a whole. With the recent approval of multi‐targeted therapies in AD and numerous clinical trials in the pipeline, there is an urgency to search for ways to best maximize their efficacy and utility.

Method

In this review, we compared drug development in HIV and AD and suggested solutions to barriers to promote accelerated combination trials.

Result

The pathophysiology of both diseases is complex and involves multiple steps that may require combination treatment versus monotherapy. Barriers to combination therapy include pharmacological properties between and among drugs affecting their efficacy and safety, issues of high pill burden, conflicts of interest between stakeholders in drug development, the pharmaceutical industry culture of secrecy, and high regulatory hurdles. Pharmacoenhancement, single‐tablet regimens, use of therapeutic drug monitoring and routine medication reconciliation, intense collaboration among stakeholders, and deregulating drug development by giving priority reviews and introducing shorter timelines for approval of hopeful novel drugs and diagnostics are all possible solutions to these barriers.

Conclusion

The history and evolution of combination therapy in HIV offer a good model of accelerated development of successful combination therapy for AD.