bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine learning enrichment strategy for presymptomatic cohorts in Alzheimer’s disease clinical trials
Authors: Tam Angela , Laurent César , Noriega de la Colina Adrián , Gauthier Serge , Dansereau Christian 
Published: December 2021

AbstractBackgroundIt is challenging for Alzheimer’s disease trials to enroll presymptomatic individuals who are likely to decline cognitively. We propose using a multimodal machine learning approach to discriminate between cognitively normal individuals who progressed to mild cognitive impairment (MCI) and those who remained stable over 48 months.MethodPatterns of gray matter distribution, derived from structural MRI, associated with either healthy aging or Alzheimer’s disease were extracted from AIBL [1] (n=401). We processed images from 823 individuals deemed cognitively normal at baseline from NACC [2] (n=433), ADNI [3] (n=260), and OASIS‐3 [4] (n=130) and generated scores representing the spatial similarities between the gray matter distribution of each individual to the patterns produced from AIBL. Gray matter scores, MMSE, CDR‐SB, FAQ, APOE4 status, education, age, and sex were used to train a machine learning prognostic pipeline using the Foresight platform (Perceiv Research Inc.) to distinguish individuals who received a MCI diagnosis within 48 months from baseline (progressors) from those who remained stable. The model was trained and tested with 5‐fold inner‐loop cross‐validation.ResultThe model achieved a mean (± std) AUC of 0.752±0.045, accuracy of 70.72±2.44, sensitivity of 62.51±12.12, and specificity of 71.82±3.87. The predicted progressors experienced a steeper cognitive decline, tended to be older, and contained a higher proportion APOE4 carriers and amyloid positive cases, compared to stable individuals. Of the predicted progressors, 33.3% were true progressors. This represents a nearly two‐fold enrichment of progressors over the prevalence of the entire sample where only 17.7% were true progressors.ConclusionAn automated algorithm can successfully identify presymptomatic individuals with impending cognitive impairment. This tool can enhance trial enrollment by targeting individuals who are at the highest risk of cognitive decline and potentially reduce trial costs by minimizing the need for prohibitively large sample sizes.[1] Australian Imaging Biomarkers and Lifestyle Study of Ageing (aibl.csiro.au).[2] National Alzheimer’s Coordinating Center (naccdata.org). [3] Alzheimer’s Disease Neuroimaging Initiative (adni.loni.usc.edu). [4] Open Access Series of Imaging Studies (oasis‐brains.org).
Significance of the in vivo endocannabinoid level to predict effectiveness of lifestyle multidomain intervention: The SUPERBRAIN study
Authors: Lee Sun Min , Park Sun Ah , Kim Joonseok , Kim Sue Min , Han Song Mi , Song Hong‐sun , Chun Buong‐O , Choi Muncheong , Hong Chang Hyung , Park Yoo Kyoung , Na Hae Ri , Kim Byeong C. , Park Kyung Won , Park Hee Kyung , Jeong Jee Hyang , Choi Seong Hye , Moon So Young 
Published: December 2021

AbstractBackgroundIn the South Korean study to prevent cognitive impairment and protect brain health through lifestyle intervention in at‐risk elderly people (SUPERBRAIN), we explored changes of in endocannabinoid after 24‐week intervention and impact of baseline endocannabinoid on cognitive and physical effects of intervention.MethodA total of 152 participants, aged 60‐79 years without dementia but with ? 1 modifiable dementia risk factor, were randomly assigned to the facility‐based multidomain intervention (FMI), and home‐based MI (HMI), or control groups. Among them, 125 participants (43 FMI, 44 HMI, and 38 control) took measurement for their levels of cortisol, anandamide (N‐arachidonoylethanolamine; AEA), and 2‐AG (2‐arachidonoylglycerol). Plasma levels were determined by liquid chromatography‐selected reaction monitoring quantification using a QTrap5500 mass spectrometer (ABSciex, Foster City, CA, USA). We compared changes of compound levels between intervention and control groups. In addition, we analyzed whether the baseline level of the compound was independent predictor for changes in clinical measures after intervention.ResultNeither the ratios, cortisol to AEA + 2‐AG, cortisol to AEA, and cortisol to 2‐AG nor the levels in AEA, 2‐AG, and cortisol showed noteworthy differences before and after the SUPERBRAIN program, between control and intervention groups. Some changes in the physical fitness and cognitive function variables were associated with the baseline AEA and cortisol, especially in the intervention group: Figure‐8‐walks (p<0.05),and ‘pre‐contemplation stage’ score of the readiness to change questionnaire for motivational enhancement (p<0.05) for cortisol; Prospective Retrospective Memory Questionnaire (PRMQ) by caregiver (p<0.05), and total scale index score of Repeatable Battery for the Assessment of Neuropsychological Status (RBANS, p<0.05) for AEA; ‘Confirmed control’ score of the questionnaire for motivational enhancement (p<0.05) for both. Among them, intervention status and baseline AEA seemed to be possible independent variables for changes in two cognitive function items, PRMQ by caregiver and total scale index score of RBANS. However, further analysis showed no interaction between intervention status and baseline AEA level on cognitive function.ConclusionBaseline level of in vivo endocannabinoids may predict the cognitive change after a multidomain dementia prevention intervention program, though its modulation on multidomain dementia prevention intervention for cognitive effects needs to be more revealed.
Using motion‐based technology to measure movement confidence among people with dementia and mild cognitive impairment
Authors: Dove Erica , Zabjek Karl , Wang Rosalie , Astell Arlene J. 
Published: December 2021

AbstractBackgroundMovement confidence is defined as “a person’s feeling or sense of adequacy in a movement situation.” It is proposed that those who are ‘movement confident’ are more likely to partake in movement situations (e.g., exercise) and enjoy doing so. However, the concept and measurement of movement confidence has not been explored among people with dementia and MCI, who can benefit from participating in activities involving physical movement, such as exercise.MethodParticipants with dementia and MCI (n=28; 53.6% female) were recruited from four community‐based adult day programs to participate in a 10‐week Xbox Kinect bowling intervention to see whether the intervention impacted their balance, movement confidence, and cognition. As part of the data collection procedure, video recordings were taken during the first, middle, and final week of the intervention and coded using video analysis software, to measure movement confidence. Count and percentage data were examined, and the coding scheme used to create a categorical measure of movement confidence. Count, percentage, and categorical data were analyzed descriptively and also compared across the study using a series of related‐samples Wilcoxon signed rank tests.ResultAmong those who completed the study, movement confidence was high at the start and did not significantly decline over time (Z‐score=‐0.359, p=0.719), suggesting a potential maintenance effect of the intervention. Various behaviours signifying movement confidence during the motion‐based activity, such as hip shifting, knee bending, change in base of support, and willingness to move were captured using both the movement confidence coding scheme and categorial measure. The coding scheme, categorical measure, and implications will be further described.ConclusionThis study is the first to examine the complex construct of movement confidence among people with dementia and MCI, paving the way for future investigations. This study is also the first to create an observational, categorical measure of movement confidence which could potentially be used by clinicians (e.g., physiotherapists) to quickly score the movement confidence of people with dementia and MCI in various movement situations.
Effect of CSF biomarkers on cortical thickness in males and females
Authors: Sangha Oshin , Lee Sieun , Ma Da , Popuri Karteek , Wang Lei , Beg Mirza Faisal 
Published: December 2021

AbstractBackgroundThe level of elevated Tau, phosphorylated Tau, and aggregated Amyloid β in the cerebrospinal fluid (CSF) are markers of Alzheimer’s pathology in the brain. In this study, we analyzed how these CSF biomarkers are related to the cortical thickness in males and females, for subjects who are cognitively normal (CN), with mild cognitive impairment (MCI), and diagnosed as Alzheimer’s disease (AD).MethodWe studied the CN (305), MCI (264) and AD (230) subjects from the ADNI dataset at baseline. We first studied the CSF biomarker level differences between males and females in all three groups. The effect of age was controlled using general linear models (GLM) We also looked at the effect of the CSF biomarkers on cortical thickness maps generated separately for males and females for all three groups, also with GLM‐based covariate regression to control the effect of age, ICV, and field strength of the scan.ResultFor the CSF biomarker levels, we observed Tau to be significantly higher in females in the AD group. No other significant sex difference in the biomarker levels were observed. We found MCI males [Figure 1] and AD [Figure 2] females showing a negative relationship between Tau and thickness. When comparing CSF pTau levels to cortical thickness, a negative correlation was found only in males [Figure 3] for the AD group. When comparing Aβ and cortical thickness, negative correlations were found for males in the CN [Figure 4] and AD group [Figure 5], and for females [Figure 6] in the MCI group.ConclusionThe results suggest that the relationship between cortical thickness and CSF biomarkers is different in males and females in CN, MCI, and AD groups. We found that there is a negative relationship between CSF biomarkers and cortical thickness.
Alzheimer’s disease‐like brain atrophy patterns after mild traumatic brain injury can be predicted based on acute cognitive deficit
Authors: Rostowsky Kenneth A. , Amgalan Anar , Irimia Andrei 
Published: December 2021

AbstractBackgroundThe neurological events that follow traumatic brain injury (TBI) can include cognitive decline, personality changes, and long‐term structural and functional effects. At the microscale, the neuropathological changes following TBI overlap partially with those seen in Alzheimer’s disease (AD). Nevertheless, our understanding of how mild TBI (mTBI) can lead to AD remains inadequate. The predictive potential of acute mTBI degeneration patterns in prognosticating the risk of AD‐like structural changes is also largely unexplored.MethodIn 66 AD patients, 33 mTBI patients and 72 healthy controls (HCs), diffusion‐weighted imaging (DWI) was used to calculate the fractional anisotropy (FA) of white matter (WM) connections and T1
‐weighted magnetic resonance imaging (MRI) was used to estimate gray matter (GM) thickness. Support vector machines (SVMs) then leveraged acute mTBI data to predict the severity of AD‐like neurodegeneration measured six months after mTBI.ResultIn both AD and mTBI, WM degeneration patterns and their extent are indistinguishable, in a statistical sense, within the fornix, corpus callosum, and corona radiata. In these structures, 78%, 35%, and 56% of their respective voxels have mean FAs which differ significantly from those of HCs for both mTBI and AD cohorts (p < 0.05). The mean FAs of these same sets of voxels are statistically equivalent across the mTBI and AD groups (p < 0.05, two one‐sided tests of statistical equivalence). mTBI and AD participants exhibit statistically significant similarities in their GM degeneration patterns, particularly within temporal poles (memory) and orbitofrontal cortices (executive function). 47% and 75% of voxels in these structures, respectively, exhibit statistical equivalence of mean FA across mTBI and AD (p < 0.05); these sets of voxels’ mean FAs are also statistically significantly different from those of HCs. SVM predictions suggest that acute post‐traumatic cognitive assessments contain information that accurately predicts AD‐like neurodegeneration patterns and severity observed chronically after mTBI (sensitivity: 0.87±0.09, specificity: 0.93±0.09; precision: 0.88±0.2).ConclusionOur findings suggest that mTBI‐induced atrophy can relegate the brain onto AD‐like neurodegeneration trajectories and that post‐mTBI cognitive assessments may provide early indications of AD risk after TBI.
Association of ambient air pollution and retinal layer thickness with cognitive impairment in community‐dwelling older adults: A two‐year cohort study
Authors: Fu Shin‐Syuan , Chen Jen‐Hau , Chen Ta‐Fu , Yeh Su‐Ling , Lai Liang‐Chuan , Chiou Jeng‐Min , Chen Jia‐Kun , Chen Yen‐Ching 
Published: December 2021

AbstractBackgroundThe anatomical structure is close between retina and brain. Our team for the first time found a nonlinear relationship between retinal markers and cognition (Liu et al. 2019). Exposure to ambient air pollution was also known to affect cognition. However, the relationship between long‐term air pollution, retina markers and cognition remains unclear. Therefore, we aimed to clarify this association in a community‐based prospective cohort study.MethodParticipants of this study (2015‐2019) were part of the ongoing Taiwan Initiative for Geriatric Epidemiological Research. A total of 232 older adults (≥ 65 years old) were enrolled at baseline (2015‐2017) with a two‐year follow up. Ganglion cell‐inner plexiform layer (GC‐IPL) and retinal nerve fiber layer (RNFL) thickness were measured by Cirrus High‐Definition Optical Coherence Tomography at baseline. Data of air pollutants were obtained from monitors of Taiwan Environmental Protection Administration between 1993 and 2010. Global cognition and domain‐specific cognition were assessed by a battery of neuropsychological test. Generalized linear mixed model were utilized to assess the association of retinal markers and air pollution with cognition adjusted for important covariates.ResultWe found a nonlinear association between GC‐IPL and poor logical memory over 2 years (immediate theme recall: β=‐0.30×10‐2; immediate free recall: β=‐0.22×10‐2; delayed free recall: β=‐0.17×10‐2). No association was not found between RNFL and cognition. High‐level NO2 (≥ 27.23 ppb) exposure was associated with poor logical memory (immediate theme recall: β=‐0.56; immediate free recall: β=‐0.71; delayed free recall: β=‐0.67). Similarly, high‐level O3 (≥ 41.75 ppb) exposure was associated with poor logical memory (immediate free recall: β=‐0.32). No significant association was found for other air pollutants. After stratification by levels of air pollutants, association remain non‐significant.ConclusionThinning and thickening of GC‐IPL was associated with cognitive impairment over two years. Long‐term high‐level exposure to NO2 or O3 was associated with poor logical memory over the same duration. More studies are need to clarify the association between retinal markers and air pollution on the performance of cognition.
The digital mobile assessment of cognition as a quick comprehensive cognitive test for primary care
Authors: Kumar Suresh , Shah Shalin , Chalamalasetty Prasanth , Kumar Aryan 
Published: December 2021

AbstractBackgroundThe uniform standardized neuro‐cognitive test is a challenge for the primary care physician due to time constraints, interpretation, and clinical use in the daily practice for dementia care.MethodThe DMAC was given to 318 patients presenting with memory loss in the disease group and 33 patients in the control group. The DMAC was given between 35‐55 minutes after the pre‐screening test. Each domain test was bundled to give a comprehensive average score of each domain in percentage: as the person’s ability to recruit neurons in the neural circuit to perform the cognitive task. The test was given individually. The domains tested include visual, auditory, delayed recall, attention, executive, number recall, disinhibition, and working memory.ResultsStatistical analysis with a series of t‐Tests showed the diseased group (n‐318) had significantly lower scores than the control group (c‐33) with confidence interval of 95% in the following domains: visual (p < 0.001), auditory (p < 0.001), delayed recall ( p < 0.001), disinhibition (p < 0.001), attention (p < 0.001), executive function (p < 0.001), numerical recall ( p < 0.001), and working memory (p < 0.001). The average sensitivity of the DMAC across these eight domains was 84.75% while the average specificity was 59.56%.DiscussionNeuropsychological test batteries have limitations as it takes 4 to 6 hours, which is not possible for the dementia group due to a short attention span and score interpretation is a challenge due to t‐score and z‐score reporting and selection bias of test battery. In an effort to create a comprehensive, reliable, and simple test for cognitive evaluation by a primary care physician under a controlled environment, we have created a digital mobile cognitive assessment test (DMAC) for memory loss patients with 8 common domains with simple interpretation and guidance to cognitive therapy within one software package. The DMAC has an inbuilt prescreening questionnaire to eliminate and standardize the patient selection.ConclusionThe DMAC is an ideal cognitive test in an outpatient primary care setting as the results are also translated into cognitive therapy & training in simple digital media.
Cerebrospinal fluid and brain PET measures of synaptic density glycoprotein 2A: Biomarkers of synaptic density in Alzheimer’s disease
Authors: Mecca Adam P. , Ashton Nicholas J. , Chen Ming‐Kai , O'Dell Ryan S. , Naganawa Mika , Toyonaga Takuya , Zhao Wenzhen , Nabulsi Nabeel B. , Brinkmalm Ann , Kvartsberg Hlin , Schöll Michael , Arnsten Amy F.T. , Huang Yiyun , Blennow Kaj , Zetterberg Henrik , Carson Richard E. , van Dyck Christopher H. , Nilsson Johanna 
Published: December 2021

AbstractBackgroundSynaptic loss is linked with Alzheimer’s disease (AD) progression and provides a novel target for exploration with fluid and imaging biomarkers. Studies using [11C]UCB‐J–PET have shown significant reductions in synaptic glycoprotein 2A (SV2A) specific binding as a marker of synaptic density in early AD. The extent of these reductions indicates widespread neocortical synaptic loss that corroborates previous postmortem studies. This study examined the association between a SV2A measured with brain [11C]UCB‐J–PET and cerebrospinal fluid (CSF) levels of SV2A.MethodUsing [11C]UCB‐J binding to SV2A, synaptic density was measured in 21 participants with early AD (CDR=0.5‐1.0, PiB+) and 7 cognitively normal (CN) participants (CDR=0, PiB–). PET scans were performed on a HRRT after a bolus injection of [11C]UCB‐J. Synaptic density was calculated as the distribution volume ratio (DVR) using SRTM2 with a cerebellum reference region. CSF SV2A was measured by an in‐house ELISA method.ResultAs previously demonstrated, synaptic density measured with SV2A PET was significantly lower in AD participants in the hippocampus, entorhinal cortex, lateral parietal cortex, lateral temporal cortex, and lateral occipital cortex. CSF SV2A was also reduced in participants with AD (762 ± 148) pg/mL) compared to CN participants (935 ± 134 pg/mL, P = 0.01, Figure 1). Within the AD group (n = 21), CSF SV2A was significantly correlated with synaptic density measured with [11C]UCB‐J–PET in a composite of AD‐affected regions (r = 0.65, P = 0.001, Figure 2). A regional analysis showed that CSF and PET measures of SV2A were significantly correlated broadly in the neocortex, but not in medial temporal regions such as the hippocampus, entorhinal cortex, and amygdala.ConclusionThis study supports a previous report of decreased CSF SV2A in AD. In the primary analysis, SV2A measured in CSF and SV2A measured with brain PET were strongly correlated within a group of individuals with AD, indicating that decreases in both measures may reflect synaptic loss during disease progression. Further studies will focus on longitudinal changes in CSF and PET measures of SV2A, as well as other CSF measures of synaptic and neuronal damage to investigate the neurobiology of AD.
Alzheimer’s disease medication utilization patterns: Disparities in treatment initiation, non‐adherence, and discontinuation
Authors: Lin Paige , Daly Allan , Olchanski Natalia , Zhu Yingying , Cohen Joshua T , Neumann Peter J , Faul Jessica D , Fillit Howard M , Freund Karen M 
Published: December 2021

AbstractBackgroundAlthough currently there is no disease‐modifying treatment for Alzheimer’s disease (AD), several FDA‐approved prescription drugs may ameliorate AD symptoms. This study analyzed AD‐targeted medication utilization patterns in a representative US population overall and by race and ethnicity.MethodWe analyzed use of cholinesterase inhibitors and memantine for AD, using data from the 2000‐2014 Health and Retirement Study (HRS), linked with Medicare and Medicaid claims. We examined medication initiation among newly‐diagnosed AD patients: 1) the proportion filling an AD prescription ≤90 and ≤365 days after diagnosis; 2) mean/median time from diagnosis to first AD prescription fill; and 3) AD symptom severity at treatment initiation, measured by cognitive and functional limitations. We measured AD medication non‐adherence and discontinuation rates in the year following treatment initiation. We used logistic regression to examine whether AD medication initiation, non‐adherence and discontinuation rates differed by race and ethnicity. We used HRS survey reports to compare the proportion of subjects not filling any prescription due to cost, by race and ethnicity.ResultAmong individuals with newly‐diagnosed AD (n=1,299), 26% filled an AD prescription ≤90 days and 36% ≤365 days of diagnosis. These proportions and the median time from an incident AD diagnosis to first AD prescription fill did not vary by race/ethnicity. For 3 of 4 measures, AD severity at treatment initiation did not differ across racial/ethnic groups. Of all individuals who initiated AD‐targeted treatment, 44% were non‐adherent and 24% discontinued the medication during the year following treatment initiation. Non‐Hispanic Blacks were more likely than non‐Hispanic whites to not adhere to AD medication therapy (OR: 1.50 [95% CI: 1.07‐2.09] or discontinue treatment (OR: 1.83 [95% CI: 1.27‐2.63]). More non‐Hispanic Blacks and Hispanics with AD reported ever not filling a prescription due to cost, compared to non‐Hispanic whites (42% and 40% vs. 22%, p<0.01).ConclusionInitiation of AD‐targeted medications among newly‐diagnosed patients was suboptimal in all ethnoracial groups, with nearly two‐thirds having no prescription for cholinesterase inhibitors or memantine during the first year post‐diagnosis. Rates of AD medication non‐adherence and discontinuation were substantial and may relate to cost and access to care.