bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physio‐markers based on predictive models of cerebral hemodynamics yield accurate diagnosis of cognitive impairment and differentiate MCI from AD
Authors: Marmarelis Vasilis , Chui Helena C , Billinger Sandra A , Joe Elizabeth B , Shin Dae , Hashem Suhaib , Rizko Jasmin , Hazen Emily , Cardim Danilo , Zhang Rong 
Published: January 2025

AbstractBackgroundA multi‐center study in Los Angeles (USC), Kansas City (KUMC) and Dallas (UT‐SWMC) quantified via predictive modeling the dynamics of cerebral perfusion regulation (CO2 vasoreactivity and cerebral autoregulation) in MCI/AD patients and cognitively normal controls under resting conditions. The goal was to develop model‐based physio‐markers for accurate diagnosis of MCI and pre‐clinical AD, motivated by our previous findings of significant impairment of cerebral perfusion regulation in MCI and mild AD patients.MethodContinuous spontaneous changes in arterial blood pressure, end‐tidal CO2, cerebral blood flow velocity in middle cerebral arteries and cortical tissue oxygenation at lateral prefrontal cortex were recorded over two 6‐8 min sessions, separated by session of slow‐paced breathing (6 breaths/minute), in 53 MCI (28 APOE4 non‐carriers and 25 APOE4 carriers), 33 mild AD patients (13 APOE4 non‐carriers and 20 APOE4 carriers) and 74 age/sex‐matched cognitively normal controls (50 APOE4 non‐carriers and 24 APOE4 carriers). Using our novel modeling methodology, we obtained predictive dynamic models of cerebral perfusion regulation (dynamic CO2 vasoreactivity and cerebral autoregulation) that were used to compute a composite diagnostic index as physio‐marker of cerebral perfusion regulation dynamics under resting conditions for each participant. ROC curves were computed for differentiating MCI/AD patients from cognitively normal controls, and MCI from mild AD patients (separately for APOE4 carriers and non‐carriers).ResultThe ROC curves for differentiating MCI/AD patients from controls are shown in Figure 1, for APOE4 carriers and non‐carriers separately, and had Area Under the Curve (AUC) of 0.95 and 0.92, respectively. The ROC curves for differentiating MCI from mild AD patients are shown in Figure 2, for APOE4 carriers and non‐carriers separately, and had AUC of 0.96 and 0.92, respectively. The p‐values of mean‐difference t‐tests for all four cases were less than 10‐8
(highly significant).ConclusionQuantitative analysis of cerebral perfusion regulation (dynamic CO2 vasoreactivity and cerebral autoregulation), using predictive dynamic modeling of cerebral hemodynamics under resting spontaneous conditions, yielded a Composite Diagnostic Index that differentiated MCI or AD patients from controls, and MCI from AD patients (p < 10‐8 for mean‐difference t‐test). The respective ROC curves had AUC in the range of 0.92‐0.96 (see Figures 1 & 2).
There is no quick, easy, or cheap way to recruit older African Americansto aging and brain health research: Ten evidence‐based strategies for investing in community engagement
Authors: Gluck Mark A. , Fausto Bernadette A. , Thornton‐Hammonds Delores , Wright Glenda , Wilson Glenn B. 
Published: January 2025

AbstractBackgroundWith African Americans having two to three times the prevalence of Alzheimer’s disease (AD) as compared to white Americans, a critical challenge for reducing health disparities is overcoming long‐standing barriers to recruiting African Americans into aging and brain health research. Here, we describe strategies that we have found successful for recruiting over 500 older African Americans from Greater Newark, New Jersey, into brain health and AD research studies.Method(1). Build trust through long‐term investment in community health.(2). Hire a large and varied engagement team with deep connections to community.(3). Formalize community relationships through a Community Stakeholders Board.(4). Offer frequent event programming and print materials to promote brain health.(5). Be a resource: Respond to other community needs, even if unrelated to brain health.(6). Empower, facilitate and recognize community members who embody brain healthy lifestyles.(7). Recruit older men with programming that addresses men’s interests and affiliations.(8). Support longitudinal retention through a Very Important Participants (VIP) program.(9). Recognize current research participants as ambassadors for future recruitment.(10). Communicate scientific results to participants and community members.ResultThese strategies require a sustained and substantial long‐term investment of time, effort, and money, towards building trust and partnerships with local community organizations and community members, with a primary emphasis on creating value for the community and local community‐based and faith‐based organizations, and a secondary consequence of encouraging research participation.ConclusionThese strategies are readily implementable by other universities doing brain health and Alzheimer’s disease research in underrepresented communities, although they require considerable staffing and financial resources.
Differential Association of Frailty Types with Cognitive Functional Impairment
Authors: Arora Sakshi , Prasad Raghav , Sundarakumar Jonas S. , Rai Pooja 
Published: January 2025

AbstractBackgroundThe phenotype model of frailty, initially proposed by Fried, is primarily confined to the physical dimension. This study seeks to expand this model by integrating the psychological dimension. We hypothesize that this psychological frailty model is strongly associated with cognitive functional impairment (CFI) in an aging Indian population.MethodWe used baseline cross‐sectional data (n = 3943) from the ongoing Srinivaspura Aging, Neuro Senescence, and COGnition (SANSCOG) study. Physical frailty was evaluated using a modified version of Fried’s criteria, encompassing hand grip strength (HGS), gait speed (timed up and go, TUG), physical activity levels, self‐reported exhaustion, and weight loss (self‐reported or a BMI < 18.5). Depression/ anxiety symptoms were assessed using the Generalized Depression Scale (GDS‐30) and Generalized Anxiety Disorder (GAD‐7) scale, respectively. Participants were classified into four groups – non‐frail, only physically frail, individuals with depression/anxiety symptoms (GDS>10/ GAD>10), and psychologically frail (physical frailty components + depression/anxiety). CFI was assessed using the Instrumental Activities of Daily Living (IADL‐E) for elderly (cognitive disability index, CDI >16). We performed logistic regression to test the association of frailty groups with cognitive functional impairment.ResultIn this study, 8.6% exhibited CFI, 4.5% were physically frail and 3.7% were identified as psychologically frail. Adjusted logistic regression analysis indicated that risk of cognitive functional impairment was 5.9 times (95% CI: 4.0 ‐ 8.8, p<0.001) higher for psychologically frail, 3.1 times (95% CI: 2.1 ‐ 4.6, p<0.001) higher for physically frail, and 2.46 times (95% CI: 1.82 ‐ 3.3, p<0.001) higher for those with depression or anxiety symptoms, respectively. On performing logistic regression for individual components of psychological frailty, we found significant association of lower HGS (OR = 1.80, 1.39‐2.31, p<0.001), delayed TUG (OR = 1.74, 1.35‐2.24, p<0.001), exhaustion (OR = 2.40, 1.58‐2.90, p<0.001), underweight i.e., BMI <18.5 (OR = 1.51, 1.09‐2.05, p<0.05) and GAD (OR = 1.65, 1.08‐2.50, p<0.05) with CFI.ConclusionPsychological frailty showed increased risk of cognitive functional impairment. This highlights the importance of a comprehensive frailty assessment in clinical practice. Therefore, while designing interventions, both physical as well as psychological health should be addressed to improve functional ability in aging population.
Cross‐Culturally Translating and Validating a Dementia Attitudes Scale in Arabic, Vietnamese, Cantonese, Mandarin, and Greek
Authors: Karamacoska Diana , Jasim Nibras , Tran Mai , Caballero Gabriela E , Tsouros Emy , Chan Sonia , Shatnawi Eman , Steiner‐Lim Genevieve Z , Siette Joyce , Chan Eliza , Nguyen Kim‐Huong , Tran Hanh Dao 
Published: January 2025

AbstractBackgroundDementia is highly stigmatised, misperceived as a mental illness, and considered a normal part of ageing by people from culturally and linguistically diverse backgrounds in Australia. There is a lack of valid and reliable scale to measure their dementia attitudes. This study aimed to cross‐culturally translate and validate a dementia attitudes scale in Arabic, Vietnamese, Chinese, and Greek communities as they represent the main languages spoken throughout Western Sydney, Australia.MethodA 12‐item Australian dementia attitudes scale, initially adapted from the PRISM‐PC–Dementia Screening Subscale, underwent forward and backward translation in the Arabic, Vietnamese, Cantonese, Mandarin, and Greek languages with certified translators and bilingual project team members. The translated surveys were also piloted with native speaking older community members to resolve comprehension issues. The final version of each scale was distributed online and at community events. Scale data (Arabic N = 197; Vietnamese N = 121; Cantonese N = 107; Mandarin N = 219; Greek N = 1,050) underwent reliability testing (Cronbach’s α) and exploratory factor analysis (EFA) with principal axis factoring and Promax rotation.ResultThe translated scales demonstrated high reliability across all five language groups (Cronbach α ≥ .77). The EFAs revealed distinct factor solutions for the Arabic, Vietnamese, Cantonese, and Mandarin scales, with ‘fear of labelling’ emerging as a common stigma‐related factor. Ten of the twelve items in the Greek scale did not meet retention criteria, limiting the scale’s validity.ConclusionThe cross‐cultural translation procedures yielded reliable scale outcomes across the five languages. The distinct factor solutions for each scale highlight the impact of culture on the stigma toward dementia. These scales can help researchers and community organisations efficiently explore dementia attitudes in under‐served populations and tailor education programs to combat misperceptions. However, a more robust scale for the Greek speaking community needs to be developed.
Impact of TBI on AD‐Associated Proteins in Neuron‐Derived Small Extracellular Vesicles from the Vietnam Era Twin Study of Aging
Authors: Cullum‐Doyle Michaela , Panizzon Matthew S. , Risbrough Victoria , Sukreet Sonal , Yang Haoyi , Elman Jeremy A. , Franz Carol E. , Kremen William S. , Rissman Robert A. 
Published: January 2025

AbstractBackgroundAlzheimer's Disease (AD) and traumatic brain injuries (TBI) are frequently associated in medical literature, with a significant prevalence of TBI history observed among individuals diagnosed with AD. Our investigation focuses on this intersection, explicitly examining the risk of AD in individuals with a history of TBI. While current targets in cerebrospinal fluid and plasma can effectively detect acute TBI, the challenge lies in identifying biosignatures associated with TBI long after injury. Neuron‐derived small extracellular vesicles (NEVs) from plasma offer potential biomarkers linked to neuronal dysfunction. Prior research has demonstrated that the AD‐associated protein amyloid‐beta (Aβ) is sequestered in NEVs, making them more sensitive biomarkers than free proteins in native plasma. To evaluate the effectiveness of NEV cargo proteins in predicting TBI exposure, we used plasma samples from the third wave of the Vietnam Era Twin Study of Aging (VETSA3). We hypothesized that previous exposure to TBI is associated with abnormalities in AD‐related proteins in circulating NEVs.MethodParticipants in the VETSA3 study, comprising a community‐based sample of male twins aged 61‐73 (average 68), self‐reported a 40% history of mild to moderate TBI. We precipitated NEVs from biobanked VETSA3 plasma samples and enriched them for the neuronal‐specific protein L1CAM using magnetic immunocapture and fluorescence‐activated cell sorting. Following the International Society of Extracellular Vesicles’ guidelines, we characterized NEVs for size, integrity, and homogeneity using NanoSight and ELISA. We quantified AD neuropathogenic proteins Aβ40–42, tau, p‐tau, and Nf‐L in NEVs using SIMOA assays. Our analyses explored the influence of TBI characteristics (number, age at occurrence, severity) on NEV cargo compared to non‐TBI individuals, assessing their utility as potential biomarkers.ResultNEVs derived from VETSA3 plasma demonstrated similar size distributions and shape characteristics required for cargo analysis. The outcomes of the ELISA validated the presence of the NEV marker protein Flotillin‐1. A significant variation was observed in several neuropathogenic proteins, demonstrating the relationship between TBI exposure and AD.ConclusionOur findings give insight into TBI as a risk factor for AD and the role of NEV cargo proteins as potential clinical biomarkers of neurodegeneration.
Neflamapimod treatment reduces plasma glial fibriallary acidic protein levels in patients with pure dementia with Lewy bodies (DLB)
Authors: Alam John J , Koel‐Simmerlink Marleen JA , Conway Jennifer , Verberk Inge M.W. , Teunissen Charlotte 
Published: January 2025

AbstractBackgroundIn a 16‐week, 91‐patient placebo‐controlled clinical study in DLB (“AscenD‐LB”;NCT04001517), neflamapimod improved outcomes on the CDR Sum‐of‐Boxes (p = 0.023 vs. placebo) and Timed Up and Go test (p = 0.044 vs. placebo). Further, at the higher of two dose levels in the study neflamapimod also improved (p = 0.049 vs. placebo) outcomes in a cognitive test battery, particularly with respect to attention (p = 0.023 vs. placebo). The results were most prominent in patients with pure DLB (i.e., without Alzheimer’s disease‐related co‐pathology, assessed by plasma ptau181). While no validated biomarkers for treatment effects in DLB were available when the study was conducted, with a recent report that plasma GFAP and neurofilament‐light‐chain (NfL) discriminated MCI‐DLB from healthy controls, with GFAP being more discriminant, we evaluated the effects of neflamapimod in AscenD‐LB on plasma GFAP and NfL, both overall and in pure DLB patients.MethodGFAP and NfL levels (pg/mL) in stored plasma samples from AscenD‐LB were determined using Simoa® platform. Design and overall results (Jiang et.al. Nature Communications, 2022), and analysis after stratification for baseline plasma ptau181 (Alam et.al. Neurology, 2023) are published.ResultAt baseline, GFAP was higher (p = 0.02) in DLB with AD co‐pathology [282(SD = 120, n = 29] versus in pure DLB [215(SD = 91), n = 28]; NfL was not. In the overall population, a reduction in GFAP levels were seen in neflamapimod‐treated participants (n = 30, ‐12.3±6.8, baseline‐to‐week16) and not in placebo‐recipients (n = 27, +3.7±7.8; p = 0.13); p = 0.13 for the difference. In pure DLB participants, the change from baseline to week 16 in GFAP was significantly different (p = 0.04) in neflamapimod‐treated participants (n = 15, ‐10.6±6.4) compared to placebo‐recipients (n = 13, +14.1±10.2). For NfL, no neflamapimod‐placebo differences were evident in either population. In the pure DLB population, the change in GFAP levels from baseline was significantly correlated to change in CDR‐SB (r = 0.54, p = 0.036; increased GFAP associated with worsening CDR‐SB, reduction in GFAP associated with improvement on CDR‐SB) among neflamapimod recipients, but not in placebo‐recipients.ConclusionThe beneficial effects on GFAP further support that neflamapimod is clinically efficacious in patients with DLB. The results also demonstrate the potential of GFAP as biomarker to assess treatment effects in DLB, though treatment effects may be masked in patients with AD co‐pathology.
The Evaluation of Telehealth Provider Payment Parity on Health Service Utilization among Adults with High Risk Factors for Dementia in the US
Authors: Zhang Zhang 
Published: January 2025

AbstractBackgroundCardiometabolic diseases and mental health disorders, which are high‐risk factors for dementia and cognitive decline, are associated with higher mortality and morbidity with age. Interventions before age 60 may lessen the burden of cognitive and physical function in later life. Telehealth offers early intervention and solutions for their complex demands in continuous behavior monitoring and medication refilling. Telehealth has been catalyzed by the COVID‐19 pandemic and become a new norm in healthcare. One of the important factors driving this transformation is governments’ temporary modifications and policies. Our study aims to evaluate the impact of telehealth payment parity mandates, which require an equal payment rate for telehealth vs. in‐person outpatient visits, on overall health service utilization among populations with high‐risk factors for dementia.MethodUsing the IBM MarketScan dataset from 2019 to 2021, we leverage a policy shock using a quasi‐experiment by a two‐way fixed effect difference‐in‐differences (DiD) estimation. Our sample includes adults with cardiometabolic risks (diabetes, hypertension, or dyslipidemia) or mental health disorders. We compare the differences between the control and treated states in changes in the outcomes of interest after the onset of the pandemic.ResultOn average, the treated group had 0.18 more telehealth visits by patient by month than the control (p<0.05). Compared to the control group, the treated group had 7 percentage points higher probability of having at least one telehealth encounter by patient by month (p<0.1) and 5 percentage points increase in the proportion of outpatient visits via telehealth by patient by month (p<0.1). In addition, the payment parity did not lead to a significant increase in in‐person outpatient visits.ConclusionOur results suggested that the telehealth payment parity, driven by supply‐side incentives, has effectively increased telehealth adoption during and post‐pandemic. The findings addressed the public concerns that telehealth expansion policies could induce and trigger excess demand for in‐person office visits. Our study provides evidence for policymakers to establish sustainable telehealth reimbursement policies and payment models and improve equitable telehealth access for populations with high‐risk factors for dementia in the US.
Brain cell transcriptomics in vulnerable and resilient regions in Alzheimer’s Disease brains
Authors: Baldasso Gabriela Mantovani , Carello‐Collar Giovanna , Limberger Christian , Paes Rodrigo Sebben , Bastiani Marco De , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundNeurodegeneration is a major pathological feature of Alzheimer’s disease (AD). During this process, it is known that not only neurons are affected but also glial cells. However, the biological mechanisms driving brain cellular vulnerability and resilience to neurodegeneration in AD remain elusive. Thus, we aimed to investigate the transcriptomic profile of brain cell types in vulnerable and resilient AD regions.MethodWe searched microarray AD datasets in the Gene Expression Omnibus repository for available transcriptomics of vulnerable (hippocampus and entorhinal cortex) and resilient (cerebellum) postmortem regions. The data was downloaded using the GEOquery package. We performed gene expression deconvolution with the Population‐Specific Expression Analysis (PSEA) to obtain the differentially expressed genes (DEGs) specific for neurons, astrocytes, microglia, oligodendrocytes, and endothelial cells (FDR‐adjusted p‐value < 0.05). We then executed functional enrichment analysis to obtain Gene Ontology (GO) of Biological Processes (GOBP) terms (clusterProfiler package). All analyses were done in R.ResultWe included eight GSEs to vulnerable regions, comprising 165 cognitively unimpaired (CU) and 182 AD individuals, and two for resilient (123 CU, 179 AD). The PSEA analysis revealed an increased percentage of DEGs in neurons and oligodendrocytes in resilient regions when compared with astrocytes, microglia, and endothelial cells (Figure 1A). By contrast, the percentage of DEGs among the cell types in vulnerable regions remained similar (Figure 1B). Interestingly, resilient regions presented more DEGs related to neurons than the vulnerable ones (Figure 1C). Microglia were the cell type with the most GOBPs number in resilient regions, while astrocytes had one (Table 1). Table 2 shows that only microglia, oligodendrocytes, and astrocytes presented GOBPs in the vulnerable regions.ConclusionWe demonstrate that neurons are the only cell type presenting a higher number of DEGs in resilient regions compared to vulnerable regions. Other cells exhibit a similar percentage of DEGs in both resilient and vulnerable regions. Regarding GOBPs, all cell types show enriched terms in resilient regions; however, in vulnerable regions, neurons and endothelial cells do not exhibit any enriched terms. These findings suggest that neurons possess an exceptional ability to adapt in resilient regions, a trait not observed in vulnerable regions.
In vivo data‐driven patterns of Amyloid‐ and Tau accumulation associated with AD progression using 18F‐MK6240 and 18F‐NAV4694 PET
Authors: Fonov Vladimir S , Rosa‐Neto Pedro , Collins D Louis 
Published: January 2025

AbstractBackgroundAlzheimer’s disease is a neurodegenerative disease associated with the accumulation of Amyloid‐β and Tau neurofibrillary tangles following a pattern known as Thal and Braak stages, respectively (Thal 2002; Braak 1995,2011). Recent research (Pascoal 2020) showed the possibility of recapitulating Braak's histopathological stages in vivo using PET tracer [18F]‐MK‐6240 with manually defined regions of interest. This study analyzes the joint patterns of Amyloid‐β and Tau accumulation associated with AD in a completely data‐driven fashion.MethodWe used T1w MRI, [18F]‐NAV4694, and [18F]MK6240 PET scans from 36 young individuals (47 scans), 192 healthy elderly individuals (280 scans) in the community or outpatients at the McGill University Research Centre for Studies in Aging (97 individuals with mild cognitive impairment (140 scans) and 75 patients with AD (98 scans).T1w MRIs were pre‐processed (non‐uniformity correction, intensity normalization, stereotaxic registration, brain masking, tissue classification) and non‐linearly registered to the ADNI template using ANTs ( Avants et al 2011 ).PET scans were linearly registered to the T1w MRI, and voxel‐wise standardized uptake value ratios (SUVR) were calculated using whole cerebellum grey matter as the reference, and then non‐linearly warped into the space of the ADNI template and downsampled to 2mm3 resolution.All PET scans were concatenated to create a matrix 518x345846. This matrix was factorized into two low‐rank components (Krichene 2018) with the constraint that all matrix elements should be positive, spatial loadings constrained to be between 0 and 1, latent vectors ordered monotonously to capture the additive nature of disease progression, and the loadings aligned with MOCA scores, by minimizing cosine distance. We used spatial components to create pseudo‐probabilistic ROIs associated with the different stages of disease progression.ResultOur method revealed regional patterns of joint tau and amyloid accumulation associated with AD progression, shown in Figure 1. Associated weighted SUVR average values are shown on Figure 2. The first two components, as visible on Figure 2, have almost no relationship with MOCA score and are most likely associated with off‐target bindings for both tracers.ConclusionThis work is a stepping stone towards creation of the Tau & Amyloid AD disease staging system.