bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging longitudinal, multi‐site diffusion MRI data in conjunction with free‐water analysis to characterize patterns of white matter neurodegeneration in aging
Authors: Archer Derek B , Shashikumar Niranjana , Jasodanand Varuna , Moore Elizabeth E. , Pechman Kimberly R. , Bilgel Murat , Beason‐Held Lori L , An Yang , Shafer Andrea T , Risacher Shannon L. , Landman Bennett A. , Jefferson Angela L. , Saykin Andrew J. , Resnick Susan M. , Hohman Timothy J. ,   Alzheimer's Disease Neuroimaging Initiative
Published: December 2022

AbstractBackgroundSeveral prior studies have used diffusion MRI to investigate the relationship between white matter microstructure and aging; however, many of these studies used conventional diffusion MRI measures and single site data. The goal of the study is to leverage multi‐site harmonized diffusion MRI data in conjunction with a novel post‐processing technique [i.e., free‐water (FW) correction] to quantify the aging related tract‐specific changes in white matter microstructure.MethodThe dataset used in this study was collated using several well‐established longitudinal cohorts of aging [Alzheimer’s Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)]. In total, this dataset included 1,909 participants (mean age at baseline: 72±9 years, 59% female) and 4,844 imaging sessions (mean number of visits: 4 ± 2 years, interval range: 1–12 years). Data was processed using standard approaches and uncorrected fractional anisotropy (FAU) was quantified with seven white matter tractography atlases (see Figure 1A). Data was then post‐processed using the FW correction technique and FW and FW‐corrected FA (FAT) values were quantified. Data were then harmonized using the ComBat technique and linear mixed‐effects regression was conducted on each microstructural measure, covarying for age at baseline, sex, cognitive status, education, APOE‐ε4 carrier status, and APOE‐ε2 carrier status. The effect of aging was modelled using an Age_at_Baseline x Interval interaction term.ResultAge was associated with lower FAU in all seven tracts (pFDR range: 4.77x10‐10 to ‐0.01). In the FW analysis, age was associated with higher FW in all seven tracts (pFDR range: 7.81x10‐12 to 1.33x10‐6). For FAT, however, age was only associated with lower FAT in the limbic tracts (pFDR=0.024) in addition to the occipital (pFDR=1.19x10‐8), parietal (pFDR=2.32x10‐4), and prefrontal (pFDR=0.024) TC tracts. Figure 1B‐D illustrates our findings.ConclusionThis study suggests that while there are global associations with FAU and age, these associations are attenuated once correcting for partial volume effects. Leveraging FW analysis, we found a global association with FW and age, whereby age is associated with higher FW. Further, we found that age is associated with reductions in FAT in the limbic and occipital/parietal/prefrontal TC tracts.
Automated method for segmenting enlarged perivascular spaces
Authors: Bown Corey W. , Khan Omair A. , Liu Dandan , Pechman Kimberly R. , Remedios Samuel , Davis L. Taylor , Houston Michelle , Gifford Katherine A. , Hohman Timothy J. , Landman Bennett A. , Jefferson Angela L. 
Published: December 2022

AbstractBackgroundEnlarged perivascular spaces (ePVS) on magnetic resonance (MR) imaging are difficult to quantify due to their small size, diffuse distribution, and often, high prevalence. We present a method for automating ePVS volume quantification in the basal ganglia.MethodVanderbilt Memory and Aging Project participants (n=327, 73±7, 41% female) underwent MR imaging and serial neuropsychological assessment. Fifty T1‐weighted MR scans were manually coded for basal ganglia ePVS and used to train and test a deep learning U‐net. The model was then used to segment 277 remaining scans. Dice similarity coefficient (DSC), volume Pearson correlation, and mean symmetric surface distance (MSSD) were used to compare ground‐truth segmentations to predicted segmentations. In head‐to‐head regressions using pseudo‐conditional R2, basal ganglia ePVS volume and count were compared to two existing ordinal scores (Patankar et al., 2005; Hansen et al., 2015) to assess which method best predicted longitudinal cognition. Models adjusted for demographic, genetic, and risk factors.ResultThe basal ganglia deep learning model attained a mean DSC of 0.76 on testing images (n=10) with an ePVS volume correlation of 0.95 and MSSD of 1.16 mm. Next, to assess the utility of automated measures derived from the model, ePVS volume and count were compared to commonly used ordinal scores on cognitive trajectory over a mean follow‐up time of 5.2±1.7 years. All automated and ordinal ePVS predictors achieved comparable pseudo‐conditional R2 values (e.g., 0.893 to 0.894 for episodic memory, 0.829 to 0.831 for executive function) on the longitudinal cognitive outcomes. ePVS volume had the highest or identical to the highest pseudo‐conditional R2 value on four of seven outcomes, including episodic memory (0.894), information processing (0.559), executive function (0.831), and visuospatial skills (0.743).ConclusionWe present a deep learning model that reliably segments ePVS in the basal ganglia of T1‐weighted brain MR scans, creating regional volume measures of ePVS. Automated basal ganglia ePVS volume measures perform comparably to existing validated manual methods when predicting longitudinal cognition. Automated methods are less time‐consuming and produce a continuous measure, providing a more robust way to quantify longitudinal ePVS change.Funding: F31‐AG066358, IIRG‐08‐88733, R01‐AG034962, R01‐AG056534, K24‐AG046373, P20‐AG068082
Data‐Driven Methods Highlight Early Signals of Tau in Patients Lacking Global Uptake: Facilitating Enrollment in Clinical Trials
Authors: Rathore Saima , Southekal Sudeepti , Kennedy Ian Andrew , Kotari Vikas , Pontecorvo Michael J. 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) patients showing neocortical Flortaucipir (FTP) tau levels above predetermined cutoffs based on the likelihood of disease progression are enrolled in Lilly trials. However, patients below the cutoffs can also exhibit disease progression, and clinical decline. These patients might be earlier in the course of disease progression and may benefit the most from therapy. The objective of this study is to apply data‐driven methods on regional tau measurements at baseline to identify a relatively homogeneous patient population showing earlier signals of tau.MethodA standardized uptake value ratio (SUVr) from a weighted composite region (MUBADA;Devous et al,JNM,2017) with respect to cerebral white matter reference signal intensity (Southekal et al,JNM,2018) was calculated using baseline FTP (n=1093) images from AVID FTP development studies (AV1451‐A05:NCT02016560) and Lilly clinical trials (EXPEDITION‐3:NCT01900665, NAVIGATE‐AD:NCT02791191, and AMARANTH:NCT02245737). Using the cutoff of 1.11, we identified a cohort of 431 subjects that were negative by MUBADA. Diagnostic breakdown included 67 cognitively‐normal, 135 mild‐cognitive‐impairment, and 229 AD subjects. Within this cohort, we calculated reference‐region independent, min‐max scaled regional tau measurements in 68 regions from FreeSurfer FsAverage template. An affinity propagation clustering analysis was applied to detect homogeneous subgroups showing patterns of similar tau uptake. Two distinct subgroups—FTPEarly (n=151), and FTPUndetected (n=280), names reflecting their tau uptake levels— emerged in the cohort. The groups were compared on clinical, cognitive, and genetic characteristics using Analysis‐Of‐Covariance.ResultFTPEarly group demonstrated relatively higher baseline plasma‐tau levels (p‐tau217) and pattern of elevated FTP uptake in inferior‐temporal, fusiform, entorhinal, and para‐hippocampal regions (P<0.01 for all) compared to FTPUndetected group. In FTPEarly group, 98% were MCI or AD, 90% were amyloid+, and 69% were APOE4‐carriers, whereas in FTPUndetected group, the prevalence of MCI or AD, amyloid positivity, and APOE4‐carriers dropped to 76%, 43%, and 37%, respectively. When evaluated on longitudinal sub‐population, FTPEarly patients progressed faster than FTPUndetected patients on FTP SUVr (P<0.01) and cognitive measures (ADAS; P<0.01).ConclusionData‐driven methods identify visually difficult to recognize FTPEarly group characterized by distinct neuroimaging patterns and paralleled by relatively homogeneous clinical, genetic, and cognitive profile. These methods hold promise for targeting enrollment of FTPEarly patient populations into clinical trials.
Alzheimer's Disease Genotype Frequencies Differ in Top Risk Alleles Between Mexican Americans and Non‐Hispanic Whites in HABLE Cohort
Authors: Housini Mohammad , Rao Sumedha R , Phillips Nicole , O'Bryant Sid E. , Barber Robert 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) and/or other related dementias remain a significant burden on our aging population. Here we evaluate the top 10 AD risk alleles previously reported by Kunkle et al. (2018) in Mexican Americans and non‐Hispanic whites enrolled in the Healthy Aging Brain in Latino Elders Study (HABLE) cohort to see if allele frequencies vary based on ethnicity.MethodDNA was extracted from buffy coat samples (n = 1635) on the Hamilton robotic system with the Mag‐Bind Blood & Tissue DNA HDQ 96 Kit. Genotyping was performed per manufacturer’s protocol using the Illumina Infinium Global Screening Array (GSA) and analyzed with Genome Studio 2.0. Samples with call rates less than 98% were repeated or excluded.Allele and genotype frequencies were calculated using standard statistics by compiling the top ten AD risk alleles from Kunkle et al. (2018) and measuring their frequencies in the HABLE cohort.ResultOur data suggest varying degrees of allele and genotype frequencies among the top 10 risk conferring SNPs between Mexican Americans and Non‐Hispanic Whites. In particular, we show some instances (BIN1, PTK2B) where the heterozygotes are in higher frequency than homozygotes. 8 of our evaluated SNPs show a difference greater than 5% between the two ethnicitiesConclusionIt may be beneficial to further study the top AD risk alleles among different ethnicities to determine if there are variable frequencies in those populations. We plan to expand and continue this work in other ethnicities and further elaborate on these differences to promote ethnicity targeted diagnostics and help reduce health disparities in medicine and science.
Longitudinal trajectory of microglial activation and astrocyte activation
Authors: Edison Paul 
Published: December 2022

AbstractBackgroundNeuroinflammation plays a significant role in the pathogenesis of AD. Here, we evaluate neuroinflammation, the interrelationship between neuroinflammation, amyloid and tau pathologies, and the impact of neuroinflammation in disease trajectory. We specifically focus on microglia as a major player in neuroinflammation and spatial and temporal variation of microglial phenotypes and novel methods of evaluation of astroglial activation.HypothesisMicroglial activation is the driver of neuronal dysfunction and tau aggregation in neurodegenerative diseases, and that levels of microglial activation will correlate with tau aggregation.Astrocyte activation could be detected by novel astrocyte marker [11C]BU99008 PETMethodsWe evaluated AD, MCI and cognitively normal subjects using amyloid ([18F]Flutemetamol), tau ([18F]AV1451 and neuroinflammation using [11C]PBR28 PET scans. A separate group of AD, MCI and control subjects were evaluated using novel astrocyte marker [11C]BU99008 PET along with [18F]FDG PET and amyloid PET. [11C]PBR28 and [11C]BU99008 PET scans were analysed using two tissue compartmental model, while [18F]Flutemetamol was analysed using target to cerebellar ratio. [18F]FDG PET was analysed using pons as a reference region. We performed regional and voxel wise analysis for all the tracers.ResultsMicroglial activation was elevated in different cortical regions in both AD and MCI subjects. There were areas of increased astrocyte activation in both AD and MCI. Higher microglial activation was associated with increased tau formation and neuronal damage in later stages of the disease. Interestingly, there was increased astrocyte activation in the early stages of the disease.ConclusionWhile microglial activation in the late phase of the disease is associated with neuronal damage, activation of the astrocytes is prominent in the early stage of the disease and may be associated with neuroprotection. This suggests that in targeting glial activation as a therapeutic strategy, we must target astrocyte and microglia separately and in different stages of the disease.
Cholinergic drug downregulates annexin A3 in platelets of Alzheimer’s Disease patients
Authors: Park Lucas Yongsoo , Gattaz Wagner Farid , Joaquim Helena Passarelli Giroud , Talib Leda Leme 
Published: December 2022

AbstractBackgroundInvestigation of the expression of annexin A3 (ANXA3) platelets of Alzheimer´s Disease patients pre and post three‐month treatment with cholinesterase inhibitors and compared to healthy controls.MethodThe sample consisted of healthy controls (n=24) and AD drug‐naïve patients (n=34), diagnosed according to DSM‐IV and specificized according to NINCDS‐ADRDA diagnostic criteria. After three months of treatment with cholinesterase inhibitors, platelets were extracted from blood samples of the same AD patients (n=34). The Cambridge cognitive test (CAMCOG) was used as a measure of global cognitive performance, however, scores on both tests were not used to establish the patients' diagnosis. The method of Western Blotting sample analysis was performed through primary antibodies against ANXA3 and secondary antibody, anti‐rabbit IgG‐HRP peroxidase. Student's t‐test or Mann‐Whitney, Pearson's Chi‐square tests were used for numerical variables, Kolmogorov‐Smirnov test were used to analyze a normal distribution and Wilcoxon test to longitudinal variables. Spearman’s rank correlation coefficient was performed for association between ANXA3 levels and clinical parameters.ResultThere was no difference in ANXA3 expression between AD patients before treatment and healthy controls (p=0.926). However, after three months with anticholinergic treatment the AD patients present a decrease in ANXA3 expressions (p=0.012).ConclusionANXA3 levels on platelets samples of patients diagnosed with AD decrease before an evident improvement of the clinical manifestation of the disease.
Hyperacusis in Frontal Variant Alzheimer’s Dementia ‐ an unrecognized symptom?
Authors: Taiwo Tolulola O 
Published: December 2022

AbstractBackgroundDisruptive behaviors are common in individuals living with Alzheimer’s dementia. The identification of the factors that contribute and exacerbate these behaviors is important.MethodRetrospective Chart Review of Patients with Frontal Variant Alzheimer’s dementia seen by the Specialized Geriatric Services in Red Deer between 2019 and 2022. Demographic and clinical data, cognitive assessments and behavioral assesssment tools were used in assessing patients.ResultHyperacusis was reported in 8 of the 42 patients with frontal variant AD. The hypersensitivity to sound was associated with restlessness and agitation. Patients with hyperacusis had poor functional status and had prominent language disturbances.ConclusionHyperacusis may be an underrecognized condition in patients living with Alzheimer’s dementia. It may also be indication of disease severity in patients with frontal variant Alzheimer’s dementia.
Smart Home Tech: an interface to provide feedback to caregivers of persons living with cognitive impairment
Authors: Thomas Neil W. , Bhati Divya K , Ault Laura , Lariviere‐Chartier Julien , Petriu Mihaela D , Wallace Bruce , Knoefel Frank , Kaye Jeffrey A , Goubran Rafik 
Published: December 2022

AbstractBackgroundHome‐based sensor technologies can detect information on daily activities, such as sleep, activity level, and time spent together. This is relevant information for care partners of individuals with cognitive impairment as it can detect early changes in daily activities and cognition. The challenge is how to present thousands of data points to care partners in real‐time, allowing them to make adjustments in their daily routine to help reduce burden.MethodThe Collaborative Aging Research using Technology (CART) sensor platform was installed in 4 Ottawa homes of persons with cognitive impairment and their care partner. This system includes contact and motion sensors to assess home activity, a smart watch to record steps and sleep patterns, a bed sensor, and medication tracking pillboxes. Questions regarding areas of stress, the types of information that caregivers would like to receive, and how to receive their data were posed in focus group discussions involving caregivers with and without the sensor platform. An interface was designed based on participant input.ResultEight care partners (75% female) aged 30 to 81 participated in focus groups that obtained their opinions on the usefulness of a feedback system, its content, layout, and frequency in which care partners would like to receive their sensor information. The majority of participants wished to be sent their sensor information on a weekly basis in easy to interpret graphical formats that summarized information for them. An algorithm that collects sensor data, parses appropriate measures; steps, sleep, time together in a room, and displays it in graphical representation, was developed. The user interface displays the daily summary compared to the weekly average, with the ability to navigate between day and weekly views.ConclusionSensor‐based data needs to be displayed in an efficient and convenient manner if it is going to be used by care partners to help guide changes in behavior to reduce stress. This project designed an interface, based on user feedback. This system also has the potential to be used by clinicians to evaluate longitudinal cognitive decline. Next, we will provide participants with the CART system with sample visual reports and gather their feedback.
Smartphone Application Usability Test for Dementia Patients' Primary Caregivers: Pilot Study
Authors: Park Jeong Min , Kim Seong Min , Seo Jihye 
Published: December 2022

AbstractBackgroundThe increase in the prevalence of dementia is emerging as a serious social problem by increasing the physical, mental, and social burdens of family caregivers taking care of dementia patients We would like to conduct a preliminary study to evaluate the application design, development, and usability test before conducting a study on the effectiveness of the smartphone application developed for the main caregiver of dementia patients.MethodAfter approval of N university IRB, usability test will be carried out in 2 cycles. We will use the application developed for 10 family caregivers (5 people in 1 cycle) in South Korea aged 18 to 80 years old. We will then collect usability testing surveys on content, interface design, technology etc. either via online (web‐based) or telephone surveys.ResultThe application to be developed in this study will enable key caregivers caring for dementia patients at home to obtain information on dementia knowledge and coping strategies, set physical and mental goals, and monitor their physical and mental status. In addition, through communication within the app, they share information about diseases and care, maintain and improve mental and physical health through emotional support and empathy, and increase coping strategies and care effectiveness.ConclusionThis study is a usability study of a smartphone application developed for caregivers of dementia patients. The results of this study will encourage the use of applications to improve the mental and physical health of caregivers caring for dementia patients, and to improve coping strategies and caring efficacy.
Profiles of 24‐hour Activity Cycle in Older Adults with Mild Cognitive Impairment: Does it Matter for Cognition?
Authors: Balbim Guilherme Moraes 
Published: December 2022

AbstractBackgroundMild cognitive impairment (MCI) is associated with increased risk for dementia and is characterized by poorer cognitive performance. Physical activity, sedentary behaviour, and sleep constitute the 24‐hour activity cycle (24‐HAC). Each of these share an inter‐dependent relationship with each other and are associated with cognitive health in older adults. It is unclear whether differences in the 24‐HAC profiles in older adults with MCI are associated with cognitive performance. Therefore, we examined whether older adults with MCI showed differences in cognitive performance based on profiles of 24‐HAC.MethodA cross‐sectional analysis of 247 community‐dwelling older adults (aged 55+ years) with MCI (Montreal Cognitive Assessment <26). MotionWatch8© assessed 24‐HAC (5‐7 days) of physical activity, sedentary behaviour, and sleep duration and quality. We measured cognitive performance with composite z‐scores of executive function (verbal fluency test, digit span forward and backward), processing speed (trail making tests A and B), and memory (word recognition, word recall, and delayed recall). Latent profile analysis identified common profiles of the 24‐HAC. ANCOVAs compared cognitive performance between profiles, adjusted for age, biological sex, body mass index, and educational attainment.ResultWe identified four distinct profiles with acceptable fit (Table 2). Profile 1 (n = 84) showed balanced levels in the 24‐HAC and longer sleep duration. Profile 2 (n = 44) had below‐average physical activity, sleep duration and quality, and above‐average sedentary behaviour. Profile 3 (n = 37) showed the lowest physical activity levels, the highest sedentary behaviour, above‐average sleep duration and quality. Profile 4 (n = 71) had the highest physical activity, the lowest sedentary behaviour, and below‐average sleep duration and quality. ANCOVAs revealed a main effect of profile (p = 0.046) on processing speed (Table 3). Post‐hoc analysis (Estimated mean difference = 0.39, p = 0.036) showed that participants in Profile 1 demonstrated better performance (0.08 [95%CI ‐0.23; 0.39]) compared with participants in Profile 3 (‐0.31 [95%CI ‐0.68; 0.06]) (Table 3). No other statistically significant differences were noted.ConclusionOlder adults with MCI appear to have four distinct 24‐HAC profiles. Balanced levels of 24‐HAC are associated with better processing speed compared with a less physically active, more sedentary, and lower sleep quality profile.