bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Changes in Quantitative MRI‐based Biomarkers and Its Association with Pathology of Alzheimer’s Disease – A Longitudinal Study
Authors: Fan Xiang , Cai Yuan , Liu Wanting , Zhao Lei , Luo Yishan , Shi Lin , Mok Vincent Chung Tong
Published: January 2025

Background

Alzheimer’s disease (AD) resemblance atrophy index (AD‐RAI) is a novel MRI‐based machine‐learning derived biomarker for AD that is valid in the detection of early AD. We aimed to investigate the association between the serial change of AD‐RAI and cognitive progression overtime among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects with and without A+T+ (i.e., Aβ+ and Tau+) and to compare it with other conventional MRI biomarkers (i.e., hippocampal volume (HV), hippocampal fraction (HF), brain parenchymal volume (BPV) and fraction (BPF)), which have been used in the past as surrogate markers for AD.

Method

We selected participants from the ADNI databases and included those aged 55 to 90 years, diagnosed with CU and MCI at baseline with high‐quality volumetric MRI data and CSF at baseline, and at least once matched T1W scans and CSF during follow‐up. We define A+T+ based on the threshold value of Aβ1‐42 and ptau in CSF. A total of 168 participants were recruited with serial MRI scans and corresponding CSF in total. We assessed longitudinal changes of the MRI biomarkers (i.e., AD‐RAI, HV, HF, BPV, BPF) in correlation with changes in time and conversion status with and without A+T+. We used a linear mixed‐effects model (LMM) in SPSS 26.0 to explore the serial changes of the imaging biomarkers and interaction effects with and without A+T+ over time, and further explore the association between dynamic CSF Aβ1–42 and dynamic changes in the imaging biomarkers’ interaction effects over time.

Result

AD‐RAI with A+T+ increased significantly faster than non‐A+T+ over time (P < 0.05), while HV and HF with A+T+ decreased significantly faster than non‐A+T+ over time (P < 0.05, respectively), which performed better than BPV/BPF. Serial AD‐RAI was significantly associated with changes in CSF Aβ1–42 over time, which outperforms other imaging biomarkers.

Conclusion

Serial AD‐RAI outperforms other conventional biomarkers in correlating with AD pathologies. It may be used as a surrogate marker for monitoring disease progression or treatment response in AD.
Improving Wellbeing in At‐Risk Familial frontotemporal dementia (IWARF): a feasibility study of a blended digital/human online intervention
Authors: Harding Emma , Hayes Oliver S , Brotherhood Emilie V , Greaves Caroline V , Goldsmith Sophie E , Rohrer Jonathan D. , Stott Joshua
Published: January 2025

Background

Familial frontotemporal dementia is an autosomal dominant heritable form of frontotemporal dementia, a form of dementia characterised by changes in personality, behaviour and communication which typically onsets in mid‐life. Children of an affected parent are at 50% risk of inheriting the responsible genetic mutation and developing frontotemporal dementia themselves. Individuals living at‐risk have high psychological morbidity, for example they report struggling with guilt and anxiety about risk to themselves and their children, decisions about whether to get tested, uncertainty about onset of symptoms, and see their risk as a barrier in life. Despite this high psychological morbidity there are no tailored interventions available to support those living at‐risk of familial frontotemporal dementia.

Methods

Guided by Medical Research Council frameworks we have co‐developed a brief blended Acceptance and Commitment Therapy‐informed person/digital intervention to support individuals at‐risk of familial frontotemporal dementia. The intervention was developed in consultation with experts‐by‐experience and clinical neurology, psychology and genetic counselling experts. It is designed to be self‐paced over 6‐8 weeks, and involves a number of online modules including informational content, videos and independent activities, interspersed with three one‐hour check‐in sessions with a facilitator. We are conducting a mixed‐methods feasibility study (n = 10), with participants with a range of genetic statuses (known mutation carrier, known non‐carrier, unknown). Participants will complete pre‐ and post‐ measures of mood, adaptation to genetic information and psychological flexibility and a qualitative interview to capture their experience of the intervention and its impact on wellbeing.

Results

We will report on adherence, attrition and acceptability of the intervention, any identified barriers and facilitators to engaging with the intervention, and plans for adaptation and refinement.

Conclusion

Findings will inform the refinement of the intervention and determine primary and secondary outcome measures for a full randomised controlled‐trial starting in Spring 2024 to test the efficacy of this first‐of‐its‐kind blended digital/human online intervention to improve wellbeing for those living at‐risk of familial frontotemporal dementia. Findings will also inform adaptation to other autosomal dominant conditions (e.g. familial Alzheimer’s disease), in which there are some disease‐specific differences in symptomatology alongside similar unmet psychological needs for those living at‐risk.
Unlocking Tau PET Accessibility: a Machine Learning‐Based Prediction of Tau Pathology from Plasma, MRI and Clinical Variables
Authors: Karlsson Linda , Vogel Jacob W. , Strandberg Olof , Arvidsson Ida , Åström Kalle , Seidlitz Jakob , Bethlehem Richard A.I. , Stomrud Erik , Ossenkoppele Rik , Ashton Nicholas J. , Blennow Kaj , Palmqvist Sebastian , Smith Ruben , Janelidze Shorena , Binette Alexa Pichet , Mattsson‐Carlgren Niklas , Hansson Oskar
Published: January 2025

Background

A key characteristic of Alzheimer’s disease (AD) is cerebral aggregation of tau. These aggregates can be quantified and localized with positron emission tomography (PET), which improves the diagnostic and prognostic work‐up of AD. However, tau‐PET is expensive and not available in clinical settings globally. With emerging disease‐modifying therapies for AD, comprehensive and accessible ways to estimate the load and distribution of tau pathology are becoming crucial. Here, we address this problem with machine learning (ML) models trained to predict tau‐PET outcomes from accessible features only (clinical variables, plasma biomarkers and MRI).

Method

The study included 1195 participants from the BioFINDER‐2 (BF2) cohort. BF2 was split into 80% train and 20% test sets. We created a rigorous ML pipeline that, with 10‐fold cross‐validation, evaluated different feature selection steps and estimators in a combined grid‐search and Bayesian optimization set‐up (Figure 1). The three variable blocks (clinical, plasma and MRI) were used as features (together and separately) to predict two tau‐PET characteristics: 1) tau load in the temporal cortex 2) hemispheric asymmetry of temporal tau load in tau positive participants (as an example of clinically relevant spatial information). External validation was performed in the BF2 test set, BioFINDER‐1 (BF1, n=147), ADNI (n=136), OASIS (n=46) and A4 (n=45). Note that ADNI, OASIS and A4 did not include plasma biomarkers.

Result

Feature combinations including plasma (particularly plasma p‐tau217) resulted in the best prediction of tau‐PET load (Figure 2). The best performing model was a combination of plasma and MRI variables in a CatBoost regressor, which achieved SUVR mean absolute error (MAE) = 0.155 and R‐squared = 0.700 on unseen data. For prediction of hemispheric asymmetry, models using MRI features performed best, and regions in the temporal lobe had the greatest contribution to the models (Figure 3). Top performance on unseen data was laterality index MAE = 6.74 and R‐squared = 0.423 in a SVR model including MRI and clinical variables.

Conclusion

Generalizable machine learning models reveal the potential in predicting tau PET from more accessible variables (particularly plasma biomarkers and MRI), which can unlock global accessibility to one of the most informative in vivo diagnostic techniques of AD.
Online awareness: A key element of functional cognition
Authors: Marks Timothy S , Edwards Dorothy F.
Published: January 2025

Background

Intact awareness of impaired task performance can facilitate the adoption of cognitive strategies to support performance. However, most studies have not examined awareness of task performance (an element of metacognition) relative to complex everyday activities. The Weekly Calendar Planning Activity (WCPA) is a performance‐based assessment of functional cognition that includes indicators of awareness during performance of a simulated complex instrumental activity of daily living (IADL). This study examined if community‐dwelling adults’ Accuracy (primary outcome) and Strategy scores on the WCPA differ according to the individual’s awareness of task performance. Additionally, we examined whether functioning on the Performance Assessment of Self‐care Skills Checkbook Balancing and Shopping Task (PCST) as indicated by the Total Cues was associated with awareness on the WCPA.

Method

Using data collected as part of a larger study we performed a cross‐sectional analysis of 274 community‐dwelling adults aged 55 to 93 years. Online awareness was evaluated on the 17‐item version of the WCPA (WCPA‐17) using participant subjective ratings of performance compared to actual observed performance. Participant data were classified into two groups: those who were aware of their performance versus those who over‐rated performance. A one‐way Analysis of Covariance was used to test three dependent variables, Accuracy scores on the WCPA‐17, number of Strategies used on the WCPA‐17, and Total Cues on the PCST, against the bimodal awareness state while controlling for age, education, and number of chronic health conditions as covariates.

Result

Individuals categorized as aware of their performance on the WCPA‐17 had significantly better Accuracy scores on the WCPA‐17 (F(4,269) = 65.80, p < .001), used more Strategies on the WCPA‐17 (F(4,269) = 4.30, p = .039), and needed fewer Total Cues on the PCST (F(4,269) = 9.15, p = .003).

Conclusion

Overall, the group categorized as aware on the WCPA‐17 performed better on all functional cognition performance scores. Intact online awareness is critical to performance on complex IADLs and can be evaluated with functional cognition assessments. The WCPA‐17 can be used to evaluate awareness in the context of complex IADL and may be useful for assessment and intervention planning.
More than burden: the relationship between caregivers and people with dementia unmet needs
Authors: Bertola Laiss , da Mata Fabiana A F , Ramos Ari Alex , Godoy Carolina , Júnior Haliton Alves de Oliveira , Ferri Cleusa P
Published: January 2025

Background

People with dementia (PWD) have several unmet needs during the syndrome progression. More unmet needs are related to worse outcomes, such as hospitalizations, injuries, and death. The caregiving burden has been related to more PWD unmet needs. However, looking beyond the burden to a broader impact of caring activities on the carer’s life is necessary. This study aims to verify if caregivers' unmet needs predict PWD unmet needs beyond the burden.

Method

In‐home interviews of a nationally distributed sample of 140 dyads (caregiver and PWD) assessed the care needs of both using the Johns Hopkins Dementia Care Needs Assessment (JHDCNA 2.0). We considered each item as 0 ‐ not needed or needed and fully met, or 1 – needed and partially met or unmet. Beyond the care assessment, the interview included several measures, including sociodemographic, caregiver burden (Zarit Burden Scale), mental health, quality of life, and information about dementia care. We conducted regression models to verify which information of the dyad best predicted more PWD unmet needs. Additionally, we performed a mediation analysis to confirm if the caregiver’s burden impacts the PWD unmet needs by its effects on the caregiver’s unmet needs.

Result

PWD had at least two unmet needs of 44 (M = 18,1; SD = 6,9), the caregiver had a mean of 11,4 (SD = 3,8) unmet needs, and 71.4% reported burden (Table 1). The PWD being male, having less education, and having more neuropsychiatric symptoms, combined with the caregiver being male, having fewer years as the primary caregiver, and having more unmet needs were associated with more PWD unmet needs (Table 2). Mediation results indicate that the burden only indirectly affects the PWD’s unmet needs through the unmet needs of the caregiver (Table 3).

Conclusion

Unmet needs are a reality for the dyad. Considering that family members predominantly provide care in low‐ and middle‐income countries, supporting caregivers is essential for their health and for them to be able to reduce the unmet needs of PWD. The impact of the caregiving burden extends beyond mental health, operating in a complex environment of unmet needs.
Hispanic/Latino ethnicity moderates the plasma P‐tau217 and memory relationship in older adults across the cognitive continuum
Authors: Lee Shannon Y. , Emanuel Olivia M , Matusz Emily F , Bove Jessica , Fiala Jacob , Arias Franchesca , Levy Shellie‐Anne , Marsiske Michael , Rosselli Monica , Curiel Rosie E , Loewenstein David A. , Duara Ranjan , Velez‐Uribe Idaly , Barker Warren W , Vaillancourt David , Armstrong Melissa J , Smith Glenn E. , Asken Breton M.
Published: January 2025

Background

Plasma P‐tau217 demonstrates strong sensitivity and specificity for Alzheimer’s disease (AD) neuropathological change, but existing studies are often ethnically homogeneous. Assumptions about how well plasma P‐tau217 relates to key AD‐related cognitive outcomes like memory may not generalize. We assessed whether the association between plasma P‐tau217 and memory depended on ethnicity in a sample of Hispanic/Latino and non‐Hispanic/Latino White older adults.

Method

We studied 273 1Florida ADRC participants with normal cognition, mild cognitive impairment (MCI), or dementia (Table 1). All participants had plasma samples analyzed for P‐tau217 (ALZPath) and neuropsychological assessments. Using Pearson’s correlations, we first evaluated the bivariate association between P‐tau217, Craft Story verbatim recall (verbal memory), and Benson Figure recall scores (visual memory) overall and stratified by ethnicity. To determine whether ethnicity moderated the effects of P‐tau217 on memory, we used multiple linear regression to assess the interaction of P‐tau217 and ethnicity (Hispanic/Latino vs. non‐Hispanic/Latino) controlling for age, sex, education, and testing language. Post hoc sensitivity analyses separately evaluated individuals below and above internal Aβ PET‐derived P‐tau217 cutoffs for “AD positive” concentration.

Result

Higher P‐tau217 was significantly associated with worse verbal (r= ‐0.38, p < 0.001) and visual memory (r= ‐0.31, p < 0.001) overall and separately in Hispanic/Latino (r= ‐0.56, r= ‐0.57; p’s <.001) and non‐Hispanic/Latino White participants (r= ‐0.30, r = ‐0.34; p’s < 0.001). Ethnicity significantly moderated P‐tau217 associations with verbal (β= ‐0.38, p= 0.001) and visual memory (β = ‐0.38, p= 0.001). The negative relationship between P‐tau217 and memory was significantly stronger for Hispanic/Latino than non‐Hispanic/Latino participants. P‐tau217 and demographic covariates explained more variance in verbal (R2= 0.39) and visual memory (R2= 0.37) for Hispanic/Latino than non‐Hispanic/Latino Whites (R2= 0.16 and R2= 0.19, respectively). Post hoc analyses suggested these findings were driven by individuals on the AD continuum.

Conclusion

AD pathology, measured via plasma P‐tau217, may more strongly relate to memory function in Hispanic/Latino than non‐Hispanic/Latino Whites. Findings have implications for the potential roles of co‐pathology or unexplored risk factors in explaining memory loss beyond AD across demographic subgroups. Ethnically representative studies will improve translation of AD biomarkers and inform anticipated AD‐directed treatment effects.
Predicting Alzheimer’s Diseases and Related Dementias in 3‐year timeframe with AI Foundation Model on Electronic Health Records
Authors: Zhu Weicheng , Tang Huanze , Rajamohan Haresh Rengaraj , Madaan Divyam , Chaudhari Ankush , Huang Shih‐Lun , Ma Xinyue , Chopra Sumit , Dodson John , Brody Abraham A. , Masurkar Arjun V. , Razavian Narges
Published: January 2025

Background

As disease‐modifying interventions advance, there is a critical need to detect Alzheimer’s disease and related dementias (ADRD) at the earlier, pre‐symptomatic stages. Transformer is a powerful model used to understand high‐dimensional data like images and languages. In this study, we propose a transformer‐based algorithm for predicting mild cognitive impairment (MCI) and ADRD 12 to 36 months in advance based on electronic health records (EHR).

Method

Our study analyzed EHR from NYU Langone between Jan 1 2014 and Jun 29 2022. The patient records were analyzed with sliding windows (Figure 1b): For every index date with at least one‐year lead‐time to onset, records from one preceding year were used as features, and the MCI/ADRD onset within 1‐3 years after the index date served as outcome labels. Patients with MCI/ADRD records in the feature and gap window are excluded to avoid data leakage.

Our prediction framework included two stages ‐ pretraining and finetuning (Figure 1a, c, d). First, we pretrained a foundation Transformer‐based model (EHR‐BERT) using the full cohort, which enabled the model to understand the semantic meanings of variables in EHR. Then we finetuned the pretrained model with the MCI/ADRD outcome labels to identify the potential MCI/ADRD patients. Final predictive performance was evaluated on a fully held‐out validation cohort.

Result

Pretraining used EHRs from 1.98M patients; 947K records from 366K patients over 60, without preexisting MCI/ADRD, were used for finetuning in the downstream prediction task. The demographics are shown in Table 1. We evaluated the prediction performance on a held‐out validation set, consisting of 118,516 records from 46,082 patients. The model obtained AUROC at 0.761 [0.760, 0.762] for prediction in 0‐3 years and 0.740 [0.739, 0.742] in 1‐3 years. Figure 2 shows that EHR‐BERT performed better than existing algorithms in PPVs at the same sensitivity level.

Conclusion

In this study, our transformer‐based AI foundation model, trained on large‐scale electronic health records, demonstrated strong capability in predicting MCI/ADRD up to three years in advance. This algorithm will allow us to advance the current recruitment of dementia screening.
Enhancing Community Engagement for Dementia Research in Africa: The Integral role of Community Advisory Boards in Recruitment and Retention
Authors: Farombi Temitope Hannah , Arulogun Oyedunni , Nichols Michelle , Olorunsogbon Olorunyomi F , Kumolu Timilehin , Ogunronbi Mayowa , Sanni Taofeek Adedayo , Mutiso Victoria , Uthman Muhammed , Sule Abdullateef , Assey Emmanuel , Mwombeki Innocent , Onoria Joy , Onunka Godspower Chibuke , Tagoe Benedict , Melkamu Selem K , Adigwe Ifeoma , Ogunyemi Adedoyin O , Gyabaah Solomon , Byrd Goldie S. , Ogunniyi Adesola , Pericak‐Vance Margaret A. , Akinyemi Rufus O. ,   Africa Dementia Consortium
Published: January 2025

Background

Historically, efforts to engage under‐represented communities in health research have encountered limited success, attributable to inadequate community participation, acceptability, and ownership. Globally, an innovative strategy to foster community involvement in research is the establishment of Community Advisory Boards (CABs). These boards consist of stakeholders from the target community, providing partnership and support throughout all phases of the research, from conception to implementation and evaluation. In pursuit of effective recruitment and retention into the Recruitment and Retention of Alzheimer’s Disease Diversity Genetic Cohorts‐ Alzheimer’s disease Sequencing Project (READD – ADSP) Study, each participating site within the African Dementia Consortium (AfDC) constituted a Community Advisory Board.

Method

A comprehensive standard operating procedure outlining the group’s activities and delineating the composition and role of the CAB within the READD_ADSP project was developed. Eligible members received letters of invitation, and those who agreed were convened for an inaugural meeting to discuss project aims, objectives, and other pertinent details using the SOP as template.

Result

About 14 CAB with 120 members have been established across the nine African sites. Each board comprised a diverse mix of geriatricians, public health leaders, community and religious leaders, retiree organizations, dementia caregivers, NGO dedicated to person living with dementia, media organizations, legal experts, and communication experts. Inaugural meetings at each site demonstrated a high level of interest and motivation to collaborate with the research team for the promotion of recruitment, retention, and advocacy. Using culturally appropriate names for dementia, case identification and referral system, lack of awareness and skilled personnel were among many concerns raised at the cab meetings. There is ongoing to continue to address these concerned raised for effective recruitment at the community.

Conclusion

The strategic partnership with community stakeholders, facilitated through the Community Advisory Boards, proved effective in achieving recruitment and retention goals for dementia research.
The new landscape of APOE genotyping in the Alzheimer’s Clinic: Harnessing genetic counseling experience to create digital tools to support patients considering anti‐amyloid therapies
Authors: Wood Elisabeth , Cacioppo Cara , Weinberg Michelle , Dratch Laynie , Azage Meron , Mim Rajia , Ofidis Demetrios , Milinski Sarah , Langlois Carolyn , Harkins Kristin , Erickson Claire M , Egleston Brian L , Karlawish Jason , Langbaum Jessica B. , Bradbury Angela R.
Published: January 2025

Background

With the advent of FDA approved anti‐amyloid therapy and recognition of increased side effects in APOE e4 carriers, APOE testing is now recommended for patients considering anti‐amyloid therapies such as lecanemab. Given the therapeutic implications and anticipated volume of eligible patients, the traditional model of in‐person, pre‐ and post‐test genetic counseling is not feasible to incorporate in clinical pathways. Alternative delivery models, including digital tools and telehealth, will be key in providing APOE genetic counseling support.

Methods

The Penn Telegenetics Program provided APOE genotype disclosure to cognitively intact participants across the United States in two Alzheimer’s prevention studies (API Generation Studies 1 and 2). An ancillary, multi‐site randomized study (CONNECT 4 APOE) evaluated the relative advantages of real time videoconference over telephone for disclosure of APOE genotype results within the API Generation Program. Outcomes of these studies informed the development of digital tools to support genetic counseling and educational needs specific to this patient population. Standard user and usability testing as well as rapid cycle testing were used in the development of digital tools.

Results

Over 2600 API Generation Program participants received APOE genotype disclosure via the Penn Telegenetics Program, and over 600 participants enrolled in the ancillary CONNECT 4 APOE protocol. This work informed the development of clinical chatbots for patients undergoing APOE testing for anti‐amyloid therapy. These chats include an education chat for patients prior to receiving APOE results and an APOE result specific chat to provide support to patients after receipt of results. Chatbot development and results of rapid cycle testing with patients will be described. Additionally, experiences with initial implementation of these digital tools and requests for genetic counseling among patients and their relatives will be reported.

Conclusions

Harnessing the experiences and outcomes from the described studies provides a unique opportunity to better understand use of telehealth modalities for APOE genotype disclosure and launch the development of digital tools that can further support the genetic counseling needs of this patient population. As indications for APOE testing rapidly increase, alternative delivery models will be critical to maximizing benefits and limiting harms.
Biomarker Differences in Post‐acute Sequelae of COVID‐19 Patients Compared to Controls
Authors: Boutajangout Allal , Frontera Jennifer A. , Masurkar Arjun V. , Debure Ludovic , Ahmed Wajiha , Vedvyas Alok , Links Jon , Jiang Li , Thawani Sujata , Sun Zhe , Ghuman Mobeena , Pirraglia Elizabeth , Betensky Rebecca A , Shao Yongzhao , Ge Yulin , Wisniewski Thomas
Published: January 2025

Background

Cognitive impairment is a major symptom among patients with post‐acute sequelae of COVID‐19; the underlying pathogenesis is unknown. This impairment may be associated with changes in the level of plasma biomarkers of neurodegeneration and neuroinflammation.

Method

Plasma samples were collected from COVID‐19 patients (Covpos, median 724 days from index SARS‐CoV‐2 infection), and from non‐COVID‐19 controls (Covneg; no history of SARS‐CoV‐2 infection and negative SARS‐CoV‐2 nucleocapsid antibody). All patients underwent neuropsychological testing using the Uniform Data Set Version‐3 Cognitive Battery. Patients were coded as having cognitive impairment (Cogabnormal) based on neuropsychological testing (≥1 abnormal test result) or cognitively normal (Cognormal) (normal performance). Plasma biomarker assays Aβ40, Aβ42, NFL, and GFAP were measured using an N4PE kit. pTau181 V2 was measured on the pTau181 kit, using Simoa HD‐X technology that employs sensitive immunoassays with a limit of detection under 100 fg/ml. Multiple linear regression models were fit for each biomarker, with covariates of binary cognitive status and COVID‐19 and their interaction, and age, sex and education. If the interaction term was not statistically significant (p<0.05), it was removed from the model. No adjustments were made for multiple comparisons in this exploratory analysis.

Results

A total of 131 subjects were enrolled: Covpos / Cognormal (n=61), Covpos/Cogabnormal (n=46), Covneg/Cognormal (n=11), and Covneg/Cogabnormal (n=13). The Cog‐Covid interaction terms were significant for Aβ42 and pTau181/Aβ42 ratio. The mean levels of Aβ42 in Covpos/Cogabnormal is significantly lower than in Covpos/Cognormal (‐1.05, 95%CI[‐1.74,‐0.36], p=0.003), and trending lower in Covneg/Cogabnormal (‐1.12, 95%CI [‐2.26,0.01], p=0.05), and not significantly different in Covneg/Cognormal. Older subjects had a higher pTau181/Aβ42 ratio (0.05, 95%CI[0.03,0.07], p<0.001). The levels of pTau181/Aβ42 ratio in Covpos/Cogabnormal were significantly higher than in Covneg/Cogabnormal (1.68, 95%CI [0.60,2.76], p=0.003), and in Covpos/Cognormal (0.92, 95%CI[0.27,1.58], p=0.007) and not significantly different in Covneg/Cognormal. Other biomarkers showed no significant differences between any of the groups.

Conclusion

Biomarker levels of Aβ42 and pTau181/Aβ42 ratio in COVID‐19 plasma samples were significantly different in COVID‐19 patients with cognitive impairment compared to COVID‐19 patients with normal cognition. Additionally, among all patients with cognitive impairment, those with COVID‐19 had significantly higher ptau181/Aβ42, suggestive of an Alzheimer’s‐type neurodegenerative process.
Impact of Grey Matter Volume and White Matter Hyperintensities on Functional Capacity for Activities of Daily Living: A Study in the Alzheimer's Disease Continuum
Authors: Campo Cecilia Gonzalez , Henriquez Fernando , Contreras Patricio Riquelme , Lillo Patricia , Martínez‐Pernía David , Thumala Daniela , Aboitiz Francisco , Chonchol Andrea Slachevsky , Henriquez Rodrigo
Published: January 2025

Background

The Alzheimer's disease (AD) continuum is composed of the stages of Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI), and Alzheimer's Disease Dementia (ADD). The decrease in gray matter volume (GMV) secondary to cortical atrophy, commonly seen in this continuum, is related to cognitive and activities of daily living (ADL) impairment. Additionally, White Matter Hyperintensities (WMH), MRI abnormalities frequently observed in older adults and patients with dementia, are also associated with cognitive and ADL performance. This study aimed to evaluate the relationship of GMV and WMH on ADL performance across the AD continuum.

Method

We conducted a cross‐sectional study of 77 SCD, 30 MCI, and 23 ADD subjects, matched for age, sex, and education. ADL was assessed using the Technology‐Activities of Daily Living Questionnaire (T‐ADLQ). Total GMV was calculated via voxel‐based morphometry analysis in SPM12. Total (tWMH), periventricular (pWMH), and subcortical (sWMH) WMH lesions were calculated with the lesion prediction algorithm (LST) and the ALVIN mask (Figure 1a). Spearman correlation analysis was used to test associations among GMV, WMH, and ADL. A linear regression model was employed to assess the relative effect of GMV and WMH on ADL scores.

Result

ADD patients performed worse on ADL and showed decreased GMV and higher pWMH burden in comparison with all the other AD continuum groups (Table 1). Within the whole sample, worse ADL scores correlated significantly with decreased GMV and higher pWMH load (Figure 1b and 1c, respectively). In addition, lower GMV was correlated with greater pWMH load (Figure 1d). The linear regression model (R2= 0.183, F = 13.890, p = 0.000) showed that only GMV had a significant impact (Beta = ‐0.338, p = 0.000), while pWMH load did not significantly influence ADL performance (Beta = 0.164, p = 0.064).

Conclusion

Lower GMV and higher pWMH load are associated with worse ADL performance. These features differentially contribute to explain ADL performance across the AD continuum, with a more pronounced effect of GMV over pWMH. Widespread GM atrophy and pWMH burden are distinctive features of ADD, strongly suggesting a fundamental detrimental role of these structural brain abnormalities along the AD continuum.
Amyloidogenic biomarkers in Down syndrome
Authors: Bram Jessyka Maria de França , Cordeiro Augusto Magno Tranquezi , Sarno Tamires Alves , Talib Leda Leme , Gattaz Wagner Farid , Forlenza Orestes Vicente
Published: January 2025

Background

Due to the genetic characteristics of Down syndrome (DS), it is directly associated with a group of clinical manifestations resulting from premature aging and may present patterns of Alzheimer’s disease (AD). Thus, this study aimed to investigate AD biological markers in peripheral blood samples from adults and elderly individuals with DS and compare them with individuals with normal karyotype.

Methods

The DS group was subclassified into 55 SD without evidence of cognitive decline (DSNC) and 27 DS with cognitive decline (SDAD). Two comparative groups composed of euploid individuals were constituted, 23 elderly with AD (AD) and 76 adults and elderly with normal cognition (Control). AD biomarkers were determined in platelets and plasma, including the Amyloid Precursor Protein ratio (APPr) between secreted 130‐ and 110kDA peptides, the protein expression of ADAM10, BACE1 and PSEN1, as well as levels of Aβ40, Aβ42 and between Aβ42/Aβ40 ratio.

Results

Results demonstrated increased APPr for both DS groups compared to euploids. Lower expression of the APP130 and 110kDa fragments was observed in both DSNC and DSAD, and both fragments showed levels between 6 and 7 times lower in DSAD compared to DSNC. A reduction in the expression of ADAM10, BACE1 and PSEN1 was observed in individuals with DS compared to euploids, with no difference between DSNC and DSAD. AD subgroup had higher levels of BACE1 when compared to the Control. A higher plasma level of Aβ40 and a lower Aβ42/Aβ40 ratio were identified for both DSNC and DSAD groups, in relation to the Control. Using CART model, the combination of APP130kDa biomarkers and the Aβ42/Aβ40 ratio proved to be relevant for separating groups in terms of cognitive impairment, through the classification APP130kDa < 0.9, Aβ42/Aβ40 ≥ 0.409 and APP130 ≥ 0.77 or APP130kDa < 0.9, Aβ42/Aβ40 < 0.409, with a diagnostic accuracy of 79.9% (sensitivity: 30.6%; specificity: 98.5%; Kappa concordance coefficient: 0.365).

Conclusion

The results of this study demonstrate that people with DS can show different patterns of expression of the proteins involved in the amyloid cascade, detectable even in the absence of cognitive decline, suggesting DS as a good predictive model of AD.
A Phase Ib/II Study of BXCL501 in Agitation Associated with Dementia
Authors: Risinger Robert , Rajachandran Lavanya , Robinson Heather
Published: January 2025

Background

BXCL501, a sublingual film formulation of dexmedetomidine, a highly selective α2 adrenoceptor agonist, is currently being studied for the acute treatment of agitation associated with dementia.

Method

This was a Phase 1b/2 study assessing efficacy and tolerability of BXCL501 for treatment of acute agitation associated with dementia. Subjects were randomized to active treatment with BXCL501 (30, 40, or 60µg) or placebo. The main efficacy measure was PANSS Excited Component (PEC) score.

Result

A total of 100 patients were enrolled in the study. Most subjects had moderate agitation at baseline based on the PEC score.

At 2 hours post‐dose (primary endpoint), a significant improvement from baseline in PEC total score was observed in the 60µg group compared with placebo (LS mean difference: ‐4.2, P = 0.0011). Significant improvements from baseline in PEC total scores were also observed at 1, 4, and 8 hours. In the 40µg group, significant improvements from baseline in PEC total score compared with placebo were observed at 1, 2, and 4 hours. No significant differences from placebo were observed in the 30µg group.

BXCL501 doses of 30, 40, and 60 µg were well tolerated in this patient population. None of the observed TEAEs were severe and no subjects discontinued the study due to an AE. The most frequently reported TEAE in the BXCL501 30, 40, and 60 µg treatment groups was somnolence (56.3%, 34.8%, and 60.0%, respectively); the incidence was 5.4% with placebo. Other adverse events of interest were hypotension (2 subjects each in 40µg and 60µg groups), orthostatic hypotension (one patient each in the 30 µg and 60 µg groups) and bradycardia (one patient in the 60 µg group). No cases of syncope or falls were reported in any of the groups.

Conclusion

There are currently no FDA‐approved treatments for acute management of agitation in elderly patients with dementia. In this study, BXCL501 60 µg and 40 µg significantly reduced the symptoms of agitation at 2 hours after administration in this patient population, as measured by PEC. At those doses, the treatments were relatively well tolerated.
The EEG spectral power ratio as a cognitively relevant marker of preclinical AD
Authors: Fried Peter J. , Morse Christie , Northrop Andrew , Patel Rushali , McKinney Eliza L , Shah Keya , Cabral Danylo Ferreira , Buss Stephanie S. , Benwell Christopher , Ozdemir Recep , Shafi Mouhsin
Published: January 2025

Background

Alzheimer’s disease (AD) is associated with cerebral slowing on electroencephalography (EEG), or a shift in oscillatory power from higher to lower frequencies. This change can be captured as the spectral power ratio (SPR) of alpha and beta over delta and theta: (α+β)/(δ+θ). Prior studies have shown that compared to cognitively unimpaired older adults, the SPR was lower in persons with a clinical diagnosis of dementia due to probable AD and those with a biomarker‐confirmed diagnosis of amnestic mild cognitive impairment (aMCI) due to AD, and a lower SPR was associated with worse executive functions scores. Moreover, the SPR was unaffected in individuals who had amyloid‐negative aMCI, suggesting cerebral slowing may result from AD‐associated pathology. We sought to test this hypothesis in a cognitively unimpaired population using plasma Aβ42/Aβ40 levels as a surrogate biomarker of brain amyloid.

Methods

Eyes‐closed resting‐state EEG, neuropsychological testing, and plasma Aβ42/Aβ40 levels were obtained from 34 adults (18 women, aged 65‐89 years), as part of an ongoing study. EEG data were cleaned and analyzed using custom scripts built around EEGLAB and TESA toolboxes in Matlab. Aβ42/Aβ40 <0.1 was used as a cutoff to indicate a high risk of brain amyloid (Rissman et al., 2023, Alzheimer’s and Dementia, DOI: 10.1002/alz.13542). An executive functions composite score was created by averaging age‐normed z‐scores from the digit symbol substitution, digit span backwards, semantic fluency, verbal fluency, and trail making tests.

Results

A Shapiro‐Wilk test indicated SPR values were not normally distributed, so data were log10‐transformed. 18 participants (53%) were classified as “high‐risk of brain amyloid.” An independent‐samples t‐test showed the SPRlog10 (mean ±SD) was lower in this group (0.23 ±0.2) than those with “low‐risk of brain amyloid” (0.39 ±0.2), which was significant, t(32) = ‐2.6, p = 0.015. Pearson’s correlation coefficients showed that executive functions were significantly correlated with SPRlog10 in the high‐risk group, R(16) = 0.57, p = 0.013, but not in the low‐risk group, R(14) = 0.24, p = 0.370.

Conclusions

Cerebral slowing is an early feature of amyloid‐associated pathophysiology. The EEG SPR (α+β)/(δ+θ) is a sensitive and cognitively relevant marker of preclinical AD.
Large‐scale Plasma Proteomic Profiling Identifies a Robust Set of Biomarkers for Detection of Clinical Alzheimer's Disease
Authors: Heo Gyujin , Ali Muhammad , Timsina Jigyasha , Liu Menghan , Cruchaga Carlos , Sung Yun Ju
Published: January 2025

Background

While several non‐invasive plasma biomarkers are rapidly developing, they still have lower accuracy than the established CSF biomarkers. This study therefore comprehensively examined 6,905 plasma proteins in over 3,000 individuals to identify novel biomarkers for predicting clinical Alzheimer’s disease (AD) and monitoring disease progression.

Method

To identify and validate plasma biomarkers, we performed difference abundance analysis of 6,905 plasma proteins in a total of 3,366 cases and controls from three different datasets (Knight‐ADRC discovery, Knight‐ADRC replication and Stanford ADRC). Enrichment analysis with Gene Ontology and DisGeNet were performed to understand biological significance of the identified proteins. Machine learning model was used to create prediction models for AD risk, which were replicated on the Knight ADRC replication and Stanford datasets.

Result

We identified and replicated 257 plasma proteins (including NEFL, SMOC1, SPON1, and NEUROG1) associated with clinical AD status. Machine learning model identified 89 proteins with strong prediction power for AD (AUC=0.843 in Knight ADRC; AUC=0.771 in Stanford ADRC), but not for Parkinson's disease (AUC< 0.6 in two independent datasets), frontotemporal dementia (AUC=0.726), and dementia with Lewy bodies (AUC=0.712), indicating AD specificity. This proteomic signature also predicted AD individuals with faster progression (clinical dementia rating sum‐of‐boxes changes per year; P=4.7∗10‐5). Furthermore, this model identified a subset of cognitive normal individuals at 201 times higher risk of developing AD individuals (hazard ratio =201.3; P=1.95∗10‐2). Pathway analysis highlighted proteins (APOE, SPP1, and PLTP) related to lipid transport pathways (FDR=2.7∗10‐2). DisGeNet indicated the relevance to senile cardiac amyloidosis (APOE, CRP, and NEFL; FDR=1.1∗10‐4), highlighting transthyretin, that was found to be potentially protective against amyloid beta deposition.

Conclusion

This large‐scale plasma proteomic study identified proteins associated with AD, developed a robust prediction model that accurately predicted AD status, examined differences between predicted groups in progression and conversion, and revealed pathways and diseases relevant to AD. These findings from extensive analysis provides the potential of plasma proteins as biomarkers for routine clinical uses in early detection of AD and guiding AD treatment decisions. They provide valuable insights into the relevance of specific pathways and diseases in the context of AD.
Integration of a Digital Cognitive Assessment Tool in a Primary Care Setting
Authors: Doerr Adam J. , Orwig Taylor A. , Melkonyan Mark N. , Leung Robert P. , Showalter John , Jannati Ali , Purkey Sage , Mullavey Judy , Erban Stephen B. , Weinstein Bruce R. , McManus David D. , Lin Honghuang
Published: January 2025

Background

Almost all primary care providers (PCPs) believe screening for mild cognitive impairment (MCI) and dementia in older patients is important. However, there are significant barriers in primary care, including low provider confidence in their assessment skills, time constraints, competing priorities, and poor financial incentives. Consequently, PCPs report conducting cognitive assessments for less than half of patients over 60 years of age. We evaluated the feasibility of integrating Linus Health’s Core Cognitive Evaluation (CCE), a tablet‐based digital cognitive assessment, into the workflow of a primary care practice at UMass Memorial Medical Center.

Method

A convenience sample was recruited from six participating PCPs’ upcoming schedules. Eligibility criteria included age >65 years, ability to read, write, and speak English or Spanish, no prior diagnosis of cognitive impairment, and no known hearing or vision impairment. Patients were contacted for inclusion by phone one month prior to their scheduled visits and were instructed to arrive at their appointments one hour early. Participants were consented in person and were asked to perform the cognitive assessment on a tablet. PCPs reviewed the report during the visit and shared the results at their discretion. A report was uploaded to each participant’s REDCap record and linked to the encounter in the electronic health record.

Result

The screened cohort consisted of 150 participants (mean age 74±6.7 years, 64% female). The CCE identified the results of 40 participants as borderline and 7 participants as indicative of cognitive impairment. Follow‐up actions taken by PCPs after positive screens included laboratory evaluations for reversible causes, referrals to neurology, and brain MRIs. As a result of taking the CCE, only 1% of patients reported feeling sad or depressed, while 5% reported feeling worried or anxious. More than two‐thirds of participants reported that taking the CCE was beneficial. All caregivers reported they would want to know if their loved ones’ brain health was declining. All PCPs reported they would continue using the CCE if made available following the study.

Conclusion

Integration of the Linus CCE into a primary care setting was feasible and impacted PCPs’ clinical decision‐making, with high patient, caregiver, and provider satisfaction.
Impact of the sars‐COV2 pandemic on cognitive frailty in older adults: The role of social support
Authors: Fabbo Andrea , Manni Barbara , Villani Emanuele Rocco
Published: January 2025

Background

Social restrictions and closures of services due to COVID‐19 pandemic had a negative impact on the social inclusion and well‐being of older people. In fact, older adults present risk factors both in terms of health ‐ such as frailty or multimorbidity ‐ and in terms of quality of life ‐ for example institutionalization ‐ and poor social support. The main objective is to evaluate whether social support had the role of an effect modifier on the incidence of cognitive frailty. Material: single‐center, cohort study, based on retrospective data collected during the emergency phase of the COVID‐19 pandemic and on a re‐evaluation performed in the post‐emergency phase. To evaluate social support, Cohen’s Social Support Scale (CSSS) was used, whose higher scores identify subjects with a low level of social support. To screen for cognitive impairment, the Mini Mental State Assessment (MMSE) was used, with an adjusted score of 26 ore less indicative of cognitive impairment. Frailty was assessed through a frailty index and cognitive frailty was defined as the co‐occurence of both cognitive impairment and physical frailty.

Methods

patients belonging to the frailty clinic of the Modena AUSL with a first evaluation carried out between October 2020 and June 2021 and with data relating to social support are re‐evaluated between october and December 2023.

Results

105 participants were enrolled. 68 (64.7%) were found to be frail at baseline. There was no statistically significant difference in mean CSSS between non‐frail and frail patients (8.7 ± 2.1 vs. 9.3 ± 2.2, p = 0.173). At December 2023, 50 patients were reevaluated. During follow‐up, 25 out of 37 patients developed cognitive frailty. The OR of cognitive frailty was higher when basal Cohen’s social support scale was higher (1.91, 95% CI 1.08‐3.25). Discussion: the impact of the pandemic, in terms of reduced social support should be assessed in the transition phase between the emergency and post‐emergency phase

Conclusions

investments should be made to implement psychosocial support interventions to reduce further incidence of cognitive frailty among older adults
Comparing Unmet Service Needs Between Rural and Urban Family Caregivers of People Living with Alzheimer’s Disease and Related Dementias: A Multi‐Site Qualitative Study
Authors: Miyawaki Christina E. , McClellan Angela , Russell David , Bouldin Erin D.
Published: January 2025

Background

The scarcity of resources and caregiving services, a higher prevalence of health conditions, and financial concerns in rural areas in the United States have been well‐documented. However, less research has compared experiences between caregivers of people with Alzheimer’s disease and related dementias (ADRD) in rural versus urban areas. This study sought to address this gap by identifying those unmet service needs, explore factors associated with service use, and propose tailored strategies for better serving the needs of both rural and urban caregivers.

Methods

Using semi‐structured interviews guided by Andersen’s theory of health service use (1968), Taylor’s theory of dependent care (2001), and Roberto’s model of service use (2022), we interviewed 20 family caregivers of people with ADRD in rural areas of Western North Carolina and 18 caregivers within the urban setting of Houston, Texas. We compared their unmet service needs and contextual factors that facilitate their service use. We conducted a thematic analysis of interview data first with rural caregivers and developed a codebook. Using the same codebook, we analyzed the urban interview data while inductively adding new codes.

Results

Rural caregivers were 56 years old (mean), working, White, and female. Urban caregivers were 63 years old, retired, White, Asian, or Black, and female. We found similar unmet service needs among rural and urban caregivers; however, the ways they approached and solved their challenges differed. Caregivers in rural areas wished for more information and caregiver support whereas urban caregivers looked for information they needed until they found the answers. Rural caregivers expressed guilt about using services because they felt they were limited and zero‐sum while urban caregivers shared available resources with others so that other caregivers could use them as well. Unmet service needs for urban caregivers included more culturally tailored services for people with ADRD in their ethnic‐specific languages and foods while rural caregivers’ cultural needs were not racially and ethnically specific but more place‐specific services.

Conclusions

Increasing options for online and virtual support groups across the United States for rural caregivers and increasing culturally tailored service options would likely increase access and use for urban ADRD caregivers.