bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the Validity of Digital Biomarkers in the Preclinical Screening of Cognitive Normal, Amyloid‐β‐ MCI and Amyloid‐β+ MCI
Authors: Kim Whani , Kim Jin Sung , Ko Hyun Jeong , Yun Byung Hun , Kim Yuyoung , Kim Dong Han , Kwon Ui Jun , Lim Sang Kwon , Kim Bo Ri , Lee Jee Hang , Kim Geon Ha , Kim Jinwoo 
Published: January 2025

AbstractBackgroundAmyloid‐β is widely known as a substantial biomarker in the diagnosis of Alzheimer’s disease. However, detection of amyloid‐β through neuroimaging techniques requires huge amounts of resources. There is a growing demand to detect these pathologies based on digital biomarkers. This study primarily aimed to examine the validity of a mobile‐based tool for assessment of cognitive impairment (mACI) in the prediction of cognitive normal (CN), amyloid‐β negative MCI (Aβ‐MCI), and amyloid‐β positive MCI (Aβ+MCI).MethodsWe recruited 102 participants from Gwangju Alzheimer’s and Related Dementia (GARD) cohort containing K‐MMSE v2, SNSB v2, MRI, PET‐CT, and clinical diagnosis data. 48 participants, who were still in the process of receiving a clinical diagnosis, were excluded. We then collected mACI data, which examined nine cognitive functions proposed in Kim et al. (2023), resulting in 54 participants’ full dataset. Medical doctors labeled the participants into CN (n = 27), Aβ‐MCI (n = 14), and Aβ+MCI (n = 13). We subsequently analyzed the data using machine learning (ML) techniques to see whether the mACI is a successful tool for preclinical screening between them.ResultsWe built a predictive model to classify the participants into CN, Aβ‐MCI and Aβ+MCI using the Catboost ML algorithm. To see the result, we performed Recursive Subtest Elimination Cross Validation (RSECV). In doing so, we measured the delta‐AUC indicating the degree of contribution of the eliminated subtest in the preclinical screening of CN, Aβ‐MCI and Aβ+MCI. As shown in Table 1, there are clearly distinctive sets of subtests when screening the participants into CN, Aβ‐MCI and Aβ+MCI. Specifically, the subtest in relation to working memory is likely to be crucial in classifying CN and MCI, and the additional subtest related to executive function plays an important role in classifying Aβ+MCI and others.ConclusionIn this study, we found that mACI was able to successfully classify CN, Aβ‐MCI and Aβ+MCI. Our work serves as foundational work to reduce screening time and expenses to identify amyloid‐β accumulation using a mobile‐based application.
Cerebral Blood Flow in Midlife Obesity: Associations with Visceral and Subcutaneous Abdominal Adipose Tissue
Authors: Dolatshahi Mahsa , Commean Paul K. , Dai Weiying , Nguyen Caitlyn , Lloyd LaKisha , Kasani Sara Hosseinzadeh , Sirlin Claude , Mittendorfer Bettina , Benzinger Tammie L.S. , Ippolito Joseph E. , Morris John C. , Raji Cyrus A. 
Published: January 2025

AbstractBackgroundObesity and higher adiposity in midlife are recognized as contributors to Alzheimer disease (AD). Neurodegeneration in AD is at least partly mediated by vascular compromise and brain hypoperfusion. In this study, we aimed to investigate the associations between BMI and abdominal visceral and subcutaneous adipose tissue (VAT, SAT) and brain cerebral blood flow (CBF) in cognitively normal midlife individuals.MethodA total of 66 middle‐aged cognitively normal adults (age: 49.86±5.99 years, females: 66.7%, obesity (BMI of 30 kg/m2 or higher): 51.5 %, BMI: 31.72±6.96 kg/m2) underwent abdominal and brain MRI. Using an in‐house Matlab program, abdominal VAT and SAT were automatically segmented followed by manual editing. A 3D Pseudo‐Continuous Arterial Spin Labeling (pCASL) sequence, with a single post‐labeling delay of 2.025 s, was used for assessing CBF. SPM12 was used to generate ASL absolute CBF (aCBF) maps with a single compartment model, co‐registered to the gray matter segmentations, and normalized to MNI space, followed by spatial smoothing. Using AAL3 atlas and Matlab, region of interest masks were created for amygdala, hippocampus, posterior cingulate, precuneus, parahippocampal, medial orbitofrontal, and middle temporal cortices and applied to absolute CBF (aCBF) maps. The aCBF differences between the obese vs. non‐obese, high‐VAT vs. low‐VAT, and high‐SAT vs. low‐SAT was assessed, with age and sex as covariates. Also, BMI, VAT, and SAT as separate predictor variables, with age and sex as covariates, were used for voxel‐wise analysis.ResultThere was a lower whole‐brain aCBF in the high‐VAT (p=0.004) group and obese (p=0.005) individuals, more prominently in the left middle temporal lobe (p=0.002). No significant difference was observed in global and regional aCBF in the high‐SAT vs. low‐SAT groups. Voxel‐wise analyses showed significantly lower aCBF in association with BMI in temporal, occipital, and frontal lobe clusters after false discovery rate correction.ConclusionObesity and increased visceral abdominal fat are associated with a lower cerebral blood flow, with a more prominent decrease in the middle temporal cortex, as an AD‐signature area, in cognitively normal midlife individuals. These findings highlight the role of obesity, especially visceral obesity, in brain hypoperfusion and potentially Alzheimer disease risk, as early as midlife.
Wearable Frontal EEG for Screening Cognitive Impairment
Authors: Ryoo Nayoung , Kim SangYun , Lee Young Gyu , Chae Yongwook 
Published: January 2025

AbstractBackgroundAlzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline. Early detection of AD is essential for timely intervention and treatment. The objective of this study is to explore the potential usefulness of virtual reality (VR) tasks combined with frontal EEG recordings for early detection of cognitive impairment in individuals with SCD (subject cognitive decline), MCI (mild cognitive impairment), and AD (Alzheimer's disease). We aimed to analyze the results and compared them with those of a control group with normal cognition.MethodResting‐state EEG was recorded in the awake‐resting state with closed eyes, and task‐induced EEG recordings were obtained during VR tasks from 108 participants. The participants included those with SCD, MCI, and AD, and they were compared with 18 subjects with normal cognition. Alpha reactivity was determined by measuring the decrease in relative alpha power over frontal electrodes.ResultThis study observed a significant decrease in alpha reactivity in the order of SCD, MCI, and AD compared to the control group with normal cognition in EEG recordings (P‐value < 0.05). Additionally, the decibel power ratio of the EEG recorded during cognitive tasks exhibited a reversed order of decrease compared to the resting state across the same diagnostic groups.ConclusionThis study shows that when performing cognitive tasks with a virtual reality (VR) device on the forehead, distinct features for Alzheimer's disease are observed compared to the healthy control group. While larger and longer‐term studies are necessary, these findings suggest that cost‐effective digital biomarkers using measurable EEG could be valuable for early Alzheimer's diagnosis.
Bone morphogenetic protein levels relate to osteoarthritis and neurobehavioral outcomes in cognitively unimpaired older adults
Authors: Diaz Valentina E. , Paolillo Emily W. , Chen Coty , VandeBunte Anna M. , Cadwallader Claire J. , Schurman Charles A. , Schiling Birgit , Miller Bruce L. , Kramer Joel H. , Casaletto Kaitlin B. , Saloner Rowan 
Published: January 2025

AbstractBackgroundOsteoarthritis (OA) is a degenerative disorder of bone aging and risk factor for cognitive decline. Bone morphogenetic proteins (BMPs) are growth factor proteins that regulate skeletal and neural development, and circulating BMPs may mediate molecular cross‐talk between bone and brain. The present study examined plasma BMP levels in relation to OA and neurobehavioral outcomes in cognitively unimpaired (CU) older adults.MethodsParticipants included 65 CU adults (mean age= 76.45, 60% female) enrolled in the UCSF Brain Aging Network for Cognitive Health (BrANCH) study who underwent cross‐sectional neurological examination, neuropsychological testing, and blood draw. Participants were classified as OA (n=31) or control (CTL; n=34) based on clinician exam (UDS Medical Conditions). Plasma was assayed for 11 different BMPs via SomaScan v4.1. Composite z‐scores were calculated for cognitive domains of memory and executive functioning. Mood symptoms were quantified with the 30‐item Geriatric Depression Scale (GDS). ANCOVA compared BMP concentrations between OA and CTL, adjusting for age and sex. Separate multiple linear regressions examined the relationship between OA‐associated BMPs and neurobehavioral outcomes across the entire sample (cognitive z‐scores, GDS total score), adjusting for age, sex, and education.ResultsOA and CTL groups did not significantly differ on demographics or neurobehavioral outcomes (ps>0.10). Five BMPs were differentially abundant (ps<.05) between OA and CTL (lower in OA: BMP5, BMP7, BMP10, BMP6; higher in OA: BMP4). In neurobehavioral models, lower BMP6 and higher BMP4 levels related to worse executive functioning (BMP6: β=0.27, p=.03; BMP4: β=‐0.28, p=.02) and higher GDS scores (BMP6: β=‐0.33, p=.02; BMP4: β=0.34, p=.01). Higher BMP10 also related to lower GDS scores (β=‐0.31, p=.02). No associations were observed between BMPs and memory z‐scores (ps>0.05).ConclusionIn a cohort of CU older adults, OA related to differential plasma abundance of BMPs. In turn, circulating BMP levels, specifically BMP4, BMP6, and BMP10, were associated with executive function and depressive symptoms. These data help provide a molecular link connecting skeletal disorders of aging (e.g., OA) to adverse neurobehavioral outcomes. Given the diverse immunovascular, metabolic, and growth regulatory functions of BMPs, additional mechanistic work is needed to identify the precise pathways by which systemic BMPs interact with the central nervous system.
The long term effect of a multidimensional comprehensive cognitive intervention training program in cognitive impairments: a longitudinal study in China
Authors: Yang Feng , Li Yatian , Zhou Zhixing , Wang Ruihan , Cai Hanlin , Xia Huanhuan , Chen Qin 
Published: January 2025

AbstractBackgroundOlder adults with cognitive impairments will benefit from multicomponent interventions include cognitive training, exercise, and lifestyle modifications. Many digital therapeutic products predominantly focus on computerized cognitive training, lacking effective approaches to other crucial interventions. This study aimed to investigate the long term effects of multidimensional comprehensive cognitive intervention training program – Brain and Body Rehab Training (BBRT), which integrates multidomain cognitive training with physical‐cognitive training and multidimensional lifestyle interventions on cognitive performance in participants with cognitive impairment after a 8‐month follow‐up.MethodAll participants (n = 351) were allocated into the cognitive unimpaired (CU) group and cognitive impaired (CI) group. Participants were evaluated by cognitive and performance test batteries before, 4 months and 8 months after the interventions. In both groups, an individualized training program is assigned consisting of completing four to five daily tasks, including cognitive training, physical‐cognitive training, lifestyle interventions, chronic disease/diet/sleep/emotion management, and traditional Chinese medicine non‐pharmacological interventions among others. The intervention duration ranges 15‐25 minutes per day, and task difficulty is dynamically adjusted based on individual task performance and periodic cognitive assessments. Participants were asked to take the intervention 3‐4 times per week for 8 months. The statistic analysis were using mixed‐effect regression model.ResultsAfter the 4 months intervention, a significant improvement on the cognitive performance was observed in the CI group compared to the CU group (p<0.001), and the improvement persistent after 8 month follow‐up (p<0.001). The change of cognitive performance were associated with frequency of training repetition and whole time of the intervention.ConclusionsThe BBRT program significantly improved the cognitive function in cognitively impaired participants after 4 months training and had a persistent effect after 8 months. The convenient home‐based multidimensional interventions provides an long term effects for the cognitive impaired participants.
Data‐driven progression patterns of Aβ, tau, α‐synuclein and vascular pathology in a clinical population
Authors: Mastenbroek Sophie E. , Collij Lyduine E. , Vogel Jacob W. , Young Alexandra L. , Strandberg Olof , Smith Ruben , Palmqvist Sebastian , Mattsson‐Carlgren Niklas , Barkhof Frederik , Ossenkoppele Rik , Hansson Oskar 
Published: January 2025

AbstractBackgroundWith the development of disease modifying therapies targeting specific pathologies, accurate in vivo biomarkers have become increasingly important for disease classification. Recently, tests for neuronal α‐synuclein (Lewy body) pathology have become available, complementing pre‐existing tests for Alzheimer’s disease (AD) pathology (Aβ and tau fluid and PET biomarkers) and vascular disease (MRI). Here, we aimed to identify and characterize data‐driven pathology‐based subtypes using these biomarkers.MethodWe included 1677 subjects from a prospective memory clinic cohort (BioFINDER‐2; age[mean±SD]=68.5±12.1; female=50.3%) ranging from cognitively unimpaired (CU) to dementia and including a variety of clinical diagnoses. We applied the data‐driven Event‐Based Subtype and Stage Inference (SuStaIn) model to dichotomized biomarkers of Aβ‐pathology (CSF‐Aβ), tau pathology (tau‐PET), neuronal α‐synuclein pathology (CSF‐α‐synuclein seeding aggregation assay) and vascular burden (MRI white matter lesions) to determine whether different biomarker sequences emerge within a clinical cohort based on the presence of different brain pathologies. Further, regional atrophy patterns (MRI) were included in the models.ResultsFour disease‐trajectories best explained the data; 998 subjects with a confident assignment (mean probability=70%) were classified as “AD” (44.0%), “Mixed AD and Vascular” (15.9%), “Vascular” (22.9%), or “α‐synuclein” (17.2%) based on early‐stage pathology (Figure 1). 579 subjects were not classified and grouped as “No subtype” (mainly biomarker‐negative). The “Vascular” trajectory demonstrated early‐stage central and global atrophy, while “α‐synuclein” exhibited atrophy in late stages (Figure 1). Subjects in “Vascular” had higher levels of vascular risk factors and were more often APOE‐ε2 carriers. Subjects in “Vascular” and “α‐synuclein” were older and more frequently male, while those in “AD” and “Mixed” more frequently had a dementia diagnosis and APOE‐ε4 carriership (Table 1). Compared to unclassifiable subjects, “AD”, “Mixed”, and “α‐synuclein” showed faster widespread longitudinal Aβ accumulation and “AD” and “Mixed” demonstrated faster widespread longitudinal tau accumulation. “AD” and “Mixed” declined faster in global cognition over time compared to “Vascular” and “α‐synuclein” and “Mixed” and “α‐synuclein” in attention compared to “Vascular” (Figure 2).ConclusionIn a heterogenous clinical population, we identified four common pathology‐based disease trajectories resembling established clinico‐pathological relationships. Future analyses will compare disease‐patterns on longitudinal biomarkers. Disease classification might contribute to personalized medicine approaches in trial and clinical settings.
Blood‐based biomarkers of systemic inflammation, metabolic function, and vascular injury are elevated in patients with rapid progressive neurodegenerative disease
Authors: Kuchenbecker Lindsey A , Tipton Philip W , Brier Matthew R , Satyadev Nihal , Piura Yoav D , Dunham S Richard , O'Bryant Sid E. , Graff‐Radford Neill R , Day Gregory S 
Published: January 2025

AbstractBackgroundPatients with rapid progressive Alzheimer disease and related dementias (rpAD/ADRD) develop dementia within 1 year or incapacitation within 2 years of symptom onset. We previously showed that selected CSF biomarkers of neuronal injury (NfL, VILIP‐1), AD neuropathology (p‐tau181), and neuroinflammation (GFAP, MCP‐1, sTREM2) measured at presentation associated with etiologic diagnoses and reliably differentiated patients with treatment‐responsive causes of rapid progressive dementia. However, no differences were identified between CSF biomarkers in patients with rapid and typical progressive forms of AD/ADRD, leaving key questions unanswered concerning the mechanisms that drive rpAD/ADRD. Blood‐based biomarkers may inform the systemic factors that contribute to rpAD/ADRD, including the systemic inflammation, metabolic function, and vascular injury.MethodsBiomarkers of systemic inflammation (Eotaxin‐3, IFN‐γ, IL‐1b, IL‐2, IL‐4, IL‐6, IL‐8, IL‐10, IL‐12p70, IL‐13, TARC, TNF‐α), metabolic function (A2M, B2M, FABP‐3, FVII, I‐309, IL‐18, PPY, TNC, TPO), and vascular injury (CRP, SAA, sICAM‐1, sVCAM‐1) were measured in plasma obtained at presentation from patients with rpAD/ADRD (n=29) and age‐ and sex‐ similar participants with typical progressive AD/ADRD (n=39) enrolled in prospective studies of memory and aging at Mayo Clinic in Florida. Biomarker measures were completed at the University of North Texas Institute for Translational Research using Meso Scale Discovery multiplexed assays. Biomarker concentrations were compared between groups using univariate analyses; potential predictors (p<0.05) were further evaluated via step‐wise multivariate logistic regression.ResultsMarkers of vascular injury (SAA, CRP, sICAM‐1), metabolic function (I‐309, TPO), and systemic inflammation (Eotaxin‐3, TARC, TNF‐α) were increased in patients with rapid versus typical progressive AD/ADRD (p<0.05). Eotaxin‐3, I‐309, and SAA were independently associated with rpAD/ADRD in multivariable model after controlling for age and sex. The overall model correctly characterized 86.8% of patients, with an area under the curve of 0.864 (95%CI: 0.777‐0.950; p<0.001).ConclusionBlood‐based biomarkers of systemic inflammation, metabolic function, and vascular injury were elevated at presentation in patients with rapid vs typical AD/ADRD. These findings may provide additional insights into the mechanisms that drive rpAD/ADRD. Longitudinal measures from larger cohorts are needed to decipher the relationship between candidate biomarkers and rpAD/ADRD.
Navigating the Challenges of Community Supports Services: A Focus Group for Black Family Caregivers
Authors: Johnson Florence U 
Published: January 2025

AbstractThis qualitative study highlights the challenges faced by Black family caregivers who provide personal care to dementia patients without remuneration or training. Caring for a person with dementia can be stressful and negatively impact the caregiver’s health. Black family caregivers are particularly vulnerable to stress‐related mental health issues. Community support services (CSS) such as support groups, help‐seeking, respite, and dementia training can help address these issues. CSS can also help delay or avoid institutionalization and keep the person living with dementia and their community‐dwelling caregivers safe in their homes.The study used the RaDAR method to analyze and develop themes from the focus group interviews of six participants. The focus group participants validated the hypothesis that Black caregivers are less likely to use CSS, particularly respite and support groups. Financial constraints and lack of free time were reported as the main barriers to support groups and respite use.The study concludes that CSS can help address the mental health issues of Black family caregivers. However, financial constraints and lack of free time are significant barriers to CSS use. The study recommends that CSS providers consider offering flexible and affordable services that cater to the needs of Black family caregivers. The study also recommends that policymakers consider providing financial support to CSS providers to enable them to offer affordable services to Black family caregivers.
I struggle watching her diminish: Caregivers experiences of caring for loved ones with Alzheimer’s
Authors: Kamau Lucy Wambui , Bosire Edna N , Blackmon Karen , Udeh‐Momoh Chi , Nesic‐Taylor Olivera , Sokhi Dilraj , Mbugua Sylvia , Narayan Vaibhav , Merali Zul 
Published: January 2025

AbstractBackgroundAlzheimer’s disease is a neurodegenerative disease that affects patients’ ability to perform activities of daily living thus requiring assistance from their loved ones. The progressive nature of the disease unravels new and continuous challenges for the caregivers posing a huge burden on caregiving. However, there is little research in Sub‐ Saharan African countries including Kenya, on caregiver’s experiences managing patients with Alzheimer’s disease. We conducted an ethnographic study at the Aga Khan University Hospital (AKUH) to understand caregivers’ experiences and practices caring for patients with Alzheimer’s disease.MethodsWe purposively recruited 30 caregivers who have been managing patients with Alzheimer’s disease from the Neurology clinic at AKUH. We conducted semi‐structured in‐ depth interviews in English or Swahili, which lasted for about 60 minutes to completion. Interviews were audio‐recorded, transcribed, and analyzed thematically with the aid of Nvivo‐12 software.ResultsKey themes identified from data included: (a) Caregiver knowledge and skills in managing patients (b) Caregiving burden (emotional, psychological, physical, financial) (c) dealing with patient’s changing personality, moods, and loss of self‐identity (d) fulfilment and privilege taking care of loved ones (e) navigating through self‐chores and caregiving roles. Overall, most caregivers lacked knowledge and skills for managing patients with Alzheimer’s. Given the limited resources, awareness and support of Alzheimer’s in Kenya, we found that caregivers carried the burden of taking care of their loved ones with some reporting mental health issues related to caregiving burden. In addition, lack of skills and training on how to manage patients’ changing personalities and patients’ loss of identity left many caregivers frustrated and worn out. Despite the challenges, caregivers had a sense of fulfilment taking care of their loved ones.ConclusionCaregivers of Alzheimer’s disease in Kenya require support from healthcare providers and other stakeholders in terms of trainings and capacity building skills to enable them to provide optimal care for the patients. They also require psychosocial support to maintain a healthy balance between their daily life activities and those of caregiving.