bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing Asian Americans’ and Pacific Islanders’ representation in research: Updates from the CARE research recruitment registry
Authors: Park Van Ta , Meyer Oanh L. , Tsoh Janice Y. , Nam Bora , Tzuang Marian , Vuong Quyen , Chun Heather , Hinton Ladson , Gallagher‐Thompson Dolores , Kanaya Alka , Grill Joshua D. 
Published: June 2023

AbstractBackgroundThe underrepresentation of Asian Americans and Pacific Islanders (AAPIs) in Alzheimer’s disease and related dementias (ADRD) research is a significant concern given that they are the fastest growing racial group in the US. The Collaborative Approach for AAPIs Research and Education (CARE) research recruitment registry is a collaboration among multiple academic and community partners aimed at creating a sustainable research recruitment source.MethodsBetween October 15, 2020 and January 17, 2022, 7,455 AAPIs enrolled in the CARE registry. The enrollment survey and outreach materials are available in 7 languages: English, Chinese (Simplified/Traditional), Hindi, Korean, Samoan, and Vietnamese. With input from CARE’s community advisory board, CARE was strategically promoted with a focus on health research across the lifespan, including ADRD. Participants can enroll online, by phone, or in‐person. A protocol for CARE‐supported recruitment requests was developed and was presented at four Brain Trust Meetings to promote CARE to the research community.ResultsThe mean age of participants is 53.4 years, including 2,130 middle‐aged (50‐64 years old) and 2,373 older (≥65 years old) participants who may be targeted groups for ADRD research. Overall, 11% (n = 819) reported having ADRD (mean age = 62.8; SD = 15.2). Among the 810 caregivers (mean age = 51.2; SD = 14.6), 37% were ADRD caregivers. Most participants who had self‐reported ADRD (96.2%) and caregivers (78%) were foreign‐born. Most participants with ADRD were Vietnamese (83.6%), followed by Chinese (12.5%). The major cultural groups among ADRD caregivers were Chinese (47.7%), Vietnamese (29%), Korean (10%), Asian Indian (7.7%), and Japanese (7%). Participants from several AAPI cultural groups were smaller in numbers (e.g., Filipino, Native Hawaiians and Pacific Islanders), however, we anticipate they will grow following targeted outreach efforts. Of the 32 recruitment referral requests, 21 were aging‐related, including 18 ADRD or ADRD‐caregiving studies. 798 CARE participants had been referred to participate in 20 requesting studies.ConclusionsCARE has successfully recruited over 7,400 participants despite limitations to conduct in‐person outreach during the COVID‐19 pandemic. The registry is poised to be a valuable recruitment source and a resource for fostering meaningful engagement of AAPIs in ADRD‐related research.
The impact of version update of an automated brain volumetry software: Possibility of mixed use and repeatability of clinical findings
Authors: Zhao Lei , Luo Yishan , Mok Vincent C.T. , Shi Lin ,   the Alzheimer Disease Neuroimaging Initiative
Published: June 2023

AbstractBackgroundAs a tool of automated brain volumetry, AccuBrain has been widely used to identify brain structural changes in different neurological diseases with the older version (IV1.2). As AccuBrain underwent a substantial revision update (IV2.0) for segmentation algorithms recently, a comparison of the two versions would be necessary to identify and characterize any differences that could affect the interpretation and clinical translation of the older research findings.MethodWe included 200 Alzheimer’s disease (AD) patients (75.3±7.6 years old, 44.0% women) and 200 normal control (NC) subjects (75.2±5.6 years old, 41.5% women) with 3D T1‐weighted scans processed with AccuBrain IV1.2 and IV2.0. To measure the volumetric difference or agreement of the two versions, we calculated the mean relative absolute error (MRAE, i.e., the mean of |(V2‐V1)/V1| for each volumetric measure) and intraclass correlation coefficient (ICC) between two versions regarding the volumes of typical brain structures, lobar atrophy indices and the quantitative medial temporal lobe atrophy (QMTA) score. In addition, we investigated the difference of the two versions regarding volumetric associations with age using ANCOVA, with the volumetric measures as the dependent variable, the version as fixed variable and age as the covariate. An interaction term between version and age was additionally included in the model to determine whether these two versions were statistically different in this respect.ResultThe ICC between the volumetric measures of the two versions were >0.85 for absolute volumes of typical brain structures (e.g., hippocampus) and >0.60 for lobar atrophy indices and QMTA (Table 1), indicating moderate to good agreement between versions. Furthermore, the MRAE indicated substantial difference between versions with >5% for half of the measures, and >10% for QMTA and most lobar atrophy indices, where the MRAE was slightly larger in AD than NC. There were no significant differences between versions regarding their volumetric associations with age (Table 2) for either NC or AD group (regression lines shown for NC in Figure 1∼2).ConclusionThe two versions of AccuBrain are not suggested for a mixed use. Previous research findings with older version may be repeatable with the new version of AccuBrain.
Resting‐State Connectivity Changes in Older Adults with Sleep Disturbance
Authors: Kim Hyun , Zhu Xi , Zhao Yiming , Bell Sophie A. , Cohen Daniel E. , Lee Seonjoo , Goldberg Terry E. 
Published: June 2023

AbstractBackgroundSleep and related disorders could lead to changes in various brain network connectivities, but little is known about the role of Aβ burden—a key Alzheimer’s disease (AD) biomarker—in the relationship between sleep disturbance and altered functional connectivity in older adults. This study examined the association between sleep disturbance, Aβ positivity, and with‐in and between resting‐state functional connectivity networks using a large‐scale dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).MethodSample was consisted of 413 individuals (mean age 76.56±7.20; 57.5% cognitively normal, 30.3% mild cognitive impairment, and 12.1% AD) who had completed sleep measures (Neuropsychiatric Inventory), CSF‐Aβ42 data, and resting‐state fMRI scans at baseline. Functional connectivity within Salience (SN), Default Mode (DMN) and Frontal Parietal networks (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance were evaluated controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension.ResultSleep disturbance was associated with reduced connectivity in the SN (β = 0.04, P = 0.006) but not with DMN or FPN. Additionally, sleep disturbance interacted significantly with Aβ positivity in altered with‐in connectivity of SN (β = 0.10, P = 0.003), DMN (β = 0.07, P = 0.0048), and FPN (β = 0.09, P = 0.03) networks.ConclusionSleep disturbance may lead to altered connectivity in the SN and further change various within and between functional networks in the presence of amyloid burden.
‘Some dance to remember’: Exploring the introduction of an adaptive Irish Céilí dance programme for people living with dementia and their carers in Ireland
Authors: Stritch Jennifer Moran , McKenna Carmel ,   Loss and Grief Research Group at TUS
Published: June 2023

AbstractBackgroundThis presentation reflects on a two‐year interdisciplinary arts‐based Masters by Research project which explored the psychosocial effects of a pilot adaptive Irish Céilí dance programme for people living with dementia and their carers. The Céilí dance activity was adapted to reflect participants’ levels of mobility, agility, ability, and cognitive skills.MethodBetween October 2019 and February 2020 field work involving people living with dementia and professional carers was conducted in a day care/respite centre based in the mid‐west region of Ireland. A phenomenological approach was adopted to investigate the lived experience of participants. Semi‐structured interviews with people living with dementia and professional care staff were conducted before, during and after the dance programme. All interviews were transcribed, and a thematic analysis lens applied to the data to facilitate analysis of emerging themes, commonalities and differences.ResultKey research themes include: enhanced reminiscence for the participant living with dementia, a greater sense of inclusion, and authentic mutual connectivity for both people with dementia and their carers who took part in the dance activity.ConclusionAn adaptive Irish Céilí dance programme can enhance the quality of life for people living with dementia and care staff. The research suggests that this dance programme warrants expansion to other dementia care facilities throughout Ireland and potentially internationally in areas with significant Irish cultural connections.
Discordance in treatment effects on clinical and imaging outcomes in recently published amyloid removing trials
Authors: Kate Mara ten , Barkhof Frederik , Schwarz Adam J. 
Published: June 2023

AbstractBackgroundLongitudinal changes in volumetric MRI (vMRI) are correlated with longitudinal changes in cognition and function in subjects with Alzheimer’s disease (AD). In clinical trials, vMRI has been used as an exploratory outcome measure with the assumption that an effective treatment would slow down brain atrophy, in addition to slowing down cognitive decline. We have recently shown that in clinical AD trials published up to November 2020, treatment effects on clinical outcomes were associated with treatment effects on vMRI measures1. Here, we assess these relationships in three more recently published trials (Donanemab2, Lecanemab3, Lanabecestat4,5), and compared it to our previous findings.MethodTreatment effects were computed as the percent slowing in change from baseline in the active group relative to the control group for clinical (ADAS‐Cog, MMSE, CDR‐SB) and imaging (whole brain volume [WBV], ventricular volume [VV], hippocampal volume [HV]) outcomes. We assessed the concordance in directionality and magnitude of treatment effects between variables.ResultIn trials published up to November 2020, treatment effects on ADAS‐Cog and CDR‐SB were directionally concordant and significantly associated with treatment effects on WBV and VV. The trials with Donanemab and Lecanemab, amyloid‐removing antibodies, showed a clear discordance between treatment effects on all three cognitive scales and global brain atrophy (WBV and VV), with decreased cognitive decline being accompanied by an increase in atrophy (illustrated for ADAS‐Cog and WBV in Figure 1). In contrast, results from the trials with Lanabecestat, a BACE inhibitor, were more consistent with the historical relationship.ConclusionBoth Donanemab and Lecanemab, two monoclonal antibodies with amyloid‐removal properties, showed a discrepancy in treatment effects on cognition and brain atrophy. Possibly, the atrophy reflects acute reductions in brain volume related to the removal of amyloid from the brain (“pseudo‐atrophy”). Further regional analyses and follow‐up imaging studies may help elucidate the mechanism and temporal evolution.References:1. Ten Kate M et al., submitted2. Mintun MA et al. N Engl J Med 2021;384:1691:3. Swanson CJ et al. Alzheimers Res Ther 2021;13:80.4. Zimmer JA et al. Alzheimers Dement 2021;7:e12123:5. Wessels AM et al. JAMA Neurol 2020; 77(2):199
Understanding the impact of social stigma on the patient journey in Alzheimer’s disease through social media narratives
Authors: Monfared Amir Abbas Tahami , Stern Yaakov , Doogan Stephen , Farid Nardin , Karahan Esra , Zhang Quanwu 
Published: June 2023

AbstractBackgroundPatients living with Alzheimer’s disease (AD) and their caregivers/health care providers (HCP) recognize the importance of social stigma; however, traditional surveys do not capture nuances of experienced stigma. We sought to systematically study stigma in AD using social media narratives.MethodOnline narratives posted by patients with AD, caregivers, and HCPs (ie, stakeholders) were collected from 84 public social media sites from 1998‐2021. Using RLS Reveal’s Natural Language Processing (NLP) platform, we identified stakeholder narratives containing ‘stigma’‐related terms. NLP algorithms and manual curation, alongside subject matter expert review, were used to analyze the narratives. Data were examined by stages of the patient journey: pre‐diagnosis, diagnosis, and post‐diagnosis.ResultA total of 112,464 online narratives from AD stakeholders were screened; 4,392 (4%) that specifically mentioned stigma‐related terms were identified and are the focus of this analysis. Most narratives were by caregivers (n = 1917), followed by patients (n = 342) and HCP (n = 306). The majority of narratives (n = 3968; 90.3%) were in the post‐diagnosis phase of the patient journey, followed by diagnosis (n = 304; 6.9%), and pre‐diagnosis (n = 120; 2.7%). In the pre‐diagnosis phase, 78% of the narratives were posted by caregivers, 11% by HCPs, and 11% by patients. Lack of support was the most common theme identified in 73/120 (60.8%) of pre‐diagnosis narratives – mostly by caregivers (38/73; 52.1%). During the diagnosis phase, 47% of the narratives were posted by caregivers, 28% by HCPs, and 25% by patients. A feeling that support/advocacy is lacking was a common theme, and identified in 128/304 (42.1%) of the diagnosis phase narratives. In the post‐diagnosis phase, 78% of the narratives were posted by caregivers, 10% by HCPs, and 12% by patients; the fear/worry caused by stigma was the most common theme and identified in 2467/3968 (62.2%) of these narratives. In addition, stakeholders discussed the feeling of shame related to the AD diagnosis – a theme identified in 1,017/3,968 (25.6%) of post‐diagnosis narratives.ConclusionWe found that social media narratives by various AD stakeholders identified a negative impact of stigma throughout the patient journey.
Assessment of myelin in Alzheimer’s by a R1 and the relationship to amyloid burden
Authors: Bolaños Alfredo D , Kohli Akshay , Kecskemeti Steven R , Alexander Andrew L , Betthauser Tobey J , Pasquesi Mary‐Elizabeth , Nair Veena A. , Prabhakaran Vivek , Li Shi‐Jiang , Bendlin Barbara B 
Published: June 2023

AbstractBackgroundAlzheimer’s disease (AD) is well known as a grey matter disorder, characterized by substantial and progressive neurodegeneration. However, less is known about myelin loss in AD, particularly as the disease progresses in severity. To gain a better insight on the role of myelin over the clinical and biologic progression of AD, we tested for differences in quantitative relaxometry R1, a metric sensitive to brain myelin, among individuals who were cognitively unimpaired (CU), diagnosed with mild cognitive impairment (MCI), and diagnosed with AD, in addition to testing for associations between R1 and amyloid PET. Understanding the course of myelin injury in disease progression is expected to address the gap in knowledge about the trajectory of myelin alterations in AD.MethodsParticipants from the Alzheimer’s Disease Connectome Project underwent T1‐weighted (T1w) MPnRAGE with motion‐correction and amyloid imaging with [11C]PiB PET. Composite T1w images and R1 maps were reconstructed at 1mm isotropic resolution. T1w scans were bias‐field corrected and denoised before undergoing tissue segmentation. R1 was sampled and bilaterally averaged across cortical‐adjacent white matter (WM). An average WM‐R1 was generated for each participant by calculating the mean of cortical regions R1. MANOVA and regression analyses were used to analyze the difference and relationship between each group’s WM‐R1 and PiB‐Index.ResultThe three groups showed an association with PiB‐Index and WM‐R1, Pillai’s Trace = 0.28, F(4, 110) = 4.56, p<0.01. Participants with AD showed higher amyloid and lower WM‐R1. In contrast, UC and MCI participants showed lower amyloid and WM‐R1. A significant correlation was found in individuals with AD wherein amyloid burden was positively correlated with WM‐R1 across the whole brain, R2 = 0.64, F(1, 6) = 10.99, p = 0.016.ConclusionOur findings indicate myelin differences by clinical status, in addition to relationships between amyloid and R1 indices of myelin. While AD was associated with lower myelin as indexed by R1, we unexpectedly found that higher cortical amyloid in AD was associated with higher myelin indexed by R1, suggesting an increase in myelination as AD progresses. Overall, lower myelin in clinical AD, accompanied by the higher myelin with greater amyloid burden suggests possible reparative mechanisms in response to neurodegeneration in AD.
A machine learning‐based multiple imputation method for the health and aging brain among latino elders study
Authors: Zhang Fan , Petersen Melissa , Johnson Leigh , Hall James , O'Bryant Sid E. 
Published: June 2023

AbstractBackgroundThe Health and Aging Brain among Latino Elders Study (HABLE) project seeks to understand the biological, social and environmental factors that impact brain aging among diverse communities. HABLE, like many other NIH funded data‐sharing projects, has important data assets for various uses, including social, environmental and behavioral data, and multiple data flow pathways. A common methodological issue for data collection in such a large survey‐based, behavior, behavioral, or environmental epidemiology study is missing data. It is impossible to achieve machine learning (ML) if data contains missing values. Therefore, developing new imputation methodology has become a very urgent task for HABLE.MethodIn this study, we developed a ML‐Based Multiple Imputation method. First, we built four ML‐Based Imputation models (Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGB) and lasso and elastic‐net regularized Generalized Linear Model (GLMNET)). Then we adapted the above four ML‐Based methods to multiple imputation. Lastly, we evaluated our ML‐Based Multiple Imputation method in comparison with lowest of detection (LOD), random drawing from a lef‐censored normal distribution (ND), k‐nearest neighbors (kNN), local least squares (LLS), and random forest (RF), Singular value decomposition (SVD), Bayesian principal component analysis (BPCA).ResultOur results show that ML‐Based Multiple Imputation method can have lower Normalized Root Mean Square Error (NRMSE) in missing value imputation and higer prediciton performance in machine learning.ConclusionThe choice of missing handling methodology has a significant impact on the accompanying statistical analyses of alzheimer’s disease. The Machine Learning‐Based Multiple Imputation Method performs well for our alzheimer’s disease models. It can also be applied to other disease data analysis.
Estimating bidirectional transition and post‐reversion of mild cognitive impairment
Authors: Qin Yao , Yu Hongmei 
Published: June 2023

AbstractBackgroundThe natural trajectory of reversion from MCI to normal cognition (NC) and the cognitive pattern post‐reversion have been poorly explored in the existing literature. The main goals of this study were as follows: (1) to quantitatively predict bidirectional transitions of MCI (reversion to NC and progression to dementia); (2) to explore patterns of future cognitive changes post‐reversion; and (3) to estimate the effects of selected covariates on transition probabilities in the course of cognitive loss.MethodThe National Alzheimer’s Coordinating Center database was funded by a National Institute on Aging/National Institutes of Health grant (U24 AG072122). Data for this study comprised 24,220 observations from 6,651 participants with an MCI diagnosis at study entry during at least two visits between June 2005 and February 2021. Defining NC and MCI as transient states and dementia as an absorbing state, we explored the fate of MCI and future cognitive changes post‐reversion using the continuous‐time, multi‐state Markov model, which provides information on the transition probability between multiple states, hazard ratio, mean sojourn time, and total length of stay over 15 years.ResultTransition intensity of re‐progression to MCI for post‐reversion was 0.3168, 2.48 times greater than the progression from MCI to dementia or reversion from MCI to NC. For the post‐reversion participants, the chance of progressing to dementia increased by 2% per year. participants who re‐progressed to MCI had an approximately 40% probability of reversing to NC again over the 15‐year period. participants stayed in the post‐reversion NC state for 3.2667 years (range 2.9349–3.6360) and in the MCI state for 1.7605 years (range 1.5134–2.0480) before progressing to dementia. Age, cognitive function, daily activity ability, and depressive symptoms were significant predictors of progression to dementia.ConclusionThere were distinct transition dynamics between amnesic MCI (aMCI) and nonamnesic (naMCI). The post‐reversion participants remained at increased risk of re‐progression to MCI or progression to dementia in the long term. Findings in this study can serve as valuable references for relevant research and healthcare professionals to help understand the natural history of cognitive loss and create proactive plans and targeted interventions.
Positive effect of moderate alcohol intake for AD
Authors: Wu Xinxing , Nelson Peter T , Cheng Qiang 
Published: June 2023

AbstractBackgroundAlzheimer’s disease (AD) is one most common forms of dementia, and it slowly gets worse over time and progresses at different rates. At present, the factors affecting AD are largely unclear. Finding effective ways to prevent and lower the potential risk of dementia is important and necessary.MethodFirst, we adopted the statistical method, chi‐square test, to analyze alcohol factors differentiating subjects with AD from Control with healthy cognition, as well as the relationship between alcohol intake and APOE, on a large‐scale data, National Alzheimer’s Coordinating Center (NACC); then, we used logistic regression analysis to analyze the factorsincluding APOE e4 carrier and alcohol intake‐related variables for the group of Control and AD; further, we used another dementia, limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), which was a recently defined common neurodegenerative disease mimicking the clinical symptoms of AD to do an adjusted analysis. The rules used to label subjects on NACC were given in Table 1.ResultWe focused on the association analysis of five alcohol intake‐related variables, including ALCOHOL, ALCOCCAS, ALCFREQ, ALCDEM, and ALCDEMIF, with APOE and AD on NACC (a detailed description of these variables and their corresponding demographics were given in Table 2). We found that there existed significant associations of alcohol‐related variables, such as ALCDEM and ALCDEMIF, with AD and APOE, respectively (see Tables 3 and 4); further, considering APOE as a potential covariable with alcohol‐related variables, we analyzed their association with AD subpopulation and control subpopulation, and discovered that APOE aggravated AD, while moderate alcohol intake had a potentially positive effect on AD (see Table 5). Also, we performed adjustment analysis by LATE and noted that the relationship between AD and alcohol intake was closer than that between LATE and alcohol intake (see Table 6).ConclusionWe discovered that moderate alcohol intake positively affected AD, and was much more obvious than LATE. Our study will potentially contribute to understanding the different alcohol factors of AD (or LATE) and support the development of effective intervention strategies for AD.