bluuebunny/crossref_metadata_2025_split huggingface dataset:
Depression and anxiety during the two waves of the COVID‐19 pandemic in two large, prospective, aging cohorts in rural and urban India.
Authors: Sundarakumar Jonas S. , Lingegodwa Abhishek Mensegere , Hameed Shafeeq K Shahul , Ravindranath Vijayalakshmi ,   SANSCOG & TLSA Study Teams
Published: December 2022

AbstractBackgroundIndia was severely impacted by both the first and second waves of COVID‐19 in 2020 and 2021. We aimed to estimate proportions of depression and anxiety disorder during both waves, among rural and urban Indians, and to compare depression trends during four distinct periods before and after the pandemic.MethodAging adults (≥45 years) from two, parallel, harmonized cohorts in rural (SANSCOG) and urban (TLSA) sites in India, underwent telephonic assessments for depression (GDS‐7) and anxiety (GAD‐7) during both waves of COVID‐19. Utilizing prior data from depression assessments (GDS‐30) during regular evaluations pre‐ pandemic and during an interim period between the two waves, we compared trends in overall proportions of depression between the two cohorts during four periods: pre‐COVID (684 rural, 317 urban); post‐COVID first wave (733 rural, 297 urban); post‐COVID interim period (458 rural, 204 urban); post‐COVID second wave (611 rural, 305 urban).ResultOverall proportion of depression among rural subjects during both waves was 28.8%. Corresponding numbers for anxiety disorder were 5.5% and 3.9%. Among urban subjects, 6.5% and 15.1% were depressed, whereas 1.7% and 0.66% had anxiety disorder, during the first and second waves, respectively. Depression trends during the four periods mentioned above were starkly different between rural and urban Indians. Sub‐analysis of the same subset of rural subjects with pre‐COVID and post‐COVID (both waves) data, revealed that subjects ≥ 65 years and those with comorbidities had significantly higher depression (36.8% vs. 25.3% and 32% vs. 15.7%, respectively) during the first wave only.ConclusionMulti‐fold increase in depression among aging, rural Indians during both waves, with alarmingly high depression among subjects ≥ 65 years and those with comorbidities during first wave, is seriously concerning. Urgent public health measures are needed to address this added mental health burden and prevent further potential adverse consequences.
Problems using structural MRIs from the oldest‐old, and some solutions: Lessons learned from The 90+ Study and ADNI
Authors: Woodworth Davis C. , Nguyen Hannah L. , Li Janice X. , Nguyen Katelynn M. , Greenia Dana E. , Kawas Claudia H. , Corrada Maria M. , Sajjadi S. Ahmad 
Published: December 2022

AbstractBackgroundThe oldest‐old (≥85 years) have the highest rates of dementia. However, because of pronounced brain atrophy, standard neuroimaging programs face unique challenges in this cohort. Here, using data from both The 90+ Study and Alzheimer’s Disease Neuroimaging Initiative (ADNI), we report the prevalence of errors when processing brain MRIs from oldest‐old participants using standard approaches and present some strategies for ameliorating these issues.MethodFirst, we analyzed image quality issues and segmentation errors (FreeSurfer) for the last available scans by age‐groups (oldest‐old, ≥85 years, vs younger‐old, 55 to 85 years) in ADNI. Second, we evaluated the utility of an age‐specific template (the 90+ T1w Template) for realigning MRIs from the oldest‐old compared to a standard template (Montreal Neurological Institute T1w template, MNI) using linear and nonlinear registration (FSL) and evaluating alignment quality using visual and deformation (Jacobian) measures for oldest‐old participants (≥90 years) in both The 90+ Study and ADNI. Lastly, we evaluated whether stringent preprocessing (bias field removal, denoising, brain extraction, intensity normalization using Computational Anatomy Toolbox (CAT12)) helped reduce FreeSurfer segmentation errors in frontal, parietal, and temporal regions in MRIs from the oldest‐old. Comparisons were performed using Chi‐square tests.ResultIn ADNI data (Table‐1), MRIs from oldest‐old participants (∼10% of cohort) were around twice as likely to have image quality issues (20% vs 13%, P<0.001) and brain segmentation errors (45% vs 29%, P<0.001) compared to younger‐old participants. Figure‐1 shows a histogram of image quality issues and segmentation errors, which become more common with greater age. Compared to the MNI template, MRIs from participants aged 90 and older from both The 90+ Study (N=163, Table‐2) and ADNI (N=75) had fewer registration errors (∼5% vs ∼23%, P<0.001 for all) and less severe deformation when using the 90+ T1w Template (Figure‐2). Our proposed preprocessing pipeline (see Figure‐3 for example) roughly halved segmentation errors in the oldest‐old (P<0.001 for all regions, Figure‐4).ConclusionOur results show that adapting pipelines specifically for processing brain MRIs of oldest‐old participants minimizes errors, enabling more effective use of neuroimaging to study neural correlates of neurodegeneration and dementia in this important portion of our aging population.
Associations between a biological marker of resilience, brain pathology, and cognitive functioning
Authors: Marseglia Anna , Dartora Caroline , Skoog Johan , Mårtensson Gustav , Muehlboeck J‐Sebastian , Ferreira Daniel , Kern Silke , Zettergren Anna , Skoog Ingmar , Westman Eric 
Published: December 2022

AbstractBackgroundDementia is the end‐product of decades of accumulating neuropathology. Resilience mechanisms can help sustaining the brain structure (brain maintenance, BM) and/or compensating for neuropathology (cognitive reserve, CR), preserving cognition. Measuring such mechanisms, however, has been challenging with traditional approaches as they fail to capture the complex biological dimension. Using deep learning (DL), we recently developed a biological measure of brain age from raw brain MRI images. Here, we tested whether differences between predicted brain age and the chronological age (PBA‐CA) can be used as marker of BM/CR following the latest framework from the NIH‐supported Collaboratory on Research Definitions for Reserve and Resilience.MethodWithin the Gothenburg H70‐Birth cohort 1944, we included 728 septuagenarians with available brain MRI and without cognitive impairments/neuropsychiatric disorders. We applied the DL algorithm (developed in 15115 healthy individuals from four other cohorts) to the participants’ MRI images to predict brain age and compute PBA‐CA, which was categorized in 4 groups according to distribution: Q1 (younger‐appearing brain) to Q4 (older‐appearing brain). Brain pathology included measures of Alzheimer‐neurodegeneration (average cortical thickness in signature areas), small vessel disease (SVD, i.e. presence of lacunes, microbleeds, white‐matter lesions, perivascular spaces), and microstructural white‐matter changes. A global cognitive score was generated by averaging z‐scores from ten tests. Sex‐adjusted regressions were used in data analysis.ResultParticipants with younger‐appearing brains (reference=older‐appearing) were more likely to have less SVD burden (reference: ≥2 SVD; OR=2.75 [95% CI 1.41–5.37] for no‐SVD; OR=2.55 [95% CI 1.20–5.45] for one‐SVD), white‐matter microstructural alterations, or AD‐related atrophy. Younger‐appearing brains were also associated with better cognitive performance (β‐coefficient=0.19 [95% CI 0.04–0.30]).ConclusionPreliminary findings indicate that negative differences between PBA and CA (PBA<CA) were associated with less AD‐ and cerebrovascular pathology, and better cognitive functioning. This suggests that PBA<CA indicate preserved brain structure and could be used as marker of BM.
Prevalence and longitudinal clinical outcomes of negative, moderate, and advanced [18F]flortaucipir PET visual patterns across the Alzheimer's disease spectrum
Authors: Moscoso Alexis , Heeman Fiona , Camacho Valle , van Essen Martijn , Grothe Michel J. , Lin Li , Mainta Isminni , Ribaldi Federica , Devous Michael D. , Pontecorvo Michael J. , Frisoni Giovanni B , Garibotto Valentina , Schöll Michael 
Published: December 2022

AbstractBackgroundThe advent of positron emission tomography (PET) imaging with tracers such as [18F]flortaucipir (FTP) has allowed in‐vivo visualization of aggregated tau in Alzheimer’s disease (AD). Recently, a clinically applicable visual interpretation method for FTP PET yielding negative, moderate, and advanced AD visual patterns was developed, leading to its subsequent approval by the US Food and Drug Administration (FDA). Yet, the prevalence and longitudinal clinical outcomes of the different AD‐associated visual patterns, in particular the moderate AD pattern, have not been investigated systematically across the clinical spectrum of AD.MethodWe included cognitively normal individuals and patients with mild cognitive impairment and AD dementia from five observational cohort studies — Alzheimer’s Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain study (HABS), A4 study, AVID’s A05 study and Geneva Memory Clinic cohort — all of which had available FTP PET scans. Furthermore, Aβ status, established with Aβ PET, was available in 1924 participants (98%), and longitudinal clinical and cognitive data was obtained for 968 participants over an average follow‐up time of 2.2 years. Three readers, blinded to clinical and imaging information, will independently evaluate each FTP PET scan, and an individual’s FTP uptake pattern will be interpreted as negative, moderate, or advanced AD tau pattern, based on the majority read of the three readers. Multinomial generalized additive models (GAM) will be fitted to provide prevalence estimates of each FTP AD pattern. Mixed models for repeated measures (MMRM) will be used to estimate cognitive decline trajectories.ResultA total of 1963 participants had available FTP PET scans. We will investigate the prevalence of the different FTP AD patterns as a function of age per diagnostic group, stratifying participants by β‐amyloid status and APOE genotype. Further, in the subset of participants with available longitudinal clinical data, we will explore how the different FTP patterns associate with clinical decline across the aforementioned diagnostic groups.ConclusionOur large‐scale study will contribute significantly to elucidating the clinical relevance of FTP visual reads across the AD spectrum, potentially widening its applicability and promoting its use in patient assessment and in clinical prevention trials.
Role of APOE ε gene in cognitive performance among cognitively healthy participants of TLSA cohort
Authors: Lingegodwa Abhishek Mensegere , Kommaddi Reddy Peera , Giridhar Varsha , Ravindranath Vijayalakshmi ,   TLSA Collaborators
Published: December 2022

AbstractBackgroundAPOE ε4 is a major genetic risk factor for Alzheimer’s Disease (AD), however, effect of APOE ε4 on cognitive decline is not well understood. TATA Longitudinal Study of Aging (TLSA) is a longitudinal study in healthy aging individuals in Bangalore, India.MethodWe analyzed the performance on global cognition, processing speed, working memory, auditory attention, verbal short‐term memory, and visuospatial skills, to ascertain between APOE ε4 carriers and non‐carriers among healthy participants of TLSA.ResultGeneralized linear models were constructed which showed that APOE ε4 carriers showed a faster cognitive decline in auditory attention and verbal short‐term memory as measured by digit forward test (B = ‐0.79; p = 0.001) compared to non‐carriers at two years of follow up. The presence of APOE ε4 allele didn’t affect the rate of cognitive decline on other cognitive domains.ConclusionThe presence of specific cognitive deficits in APOE ε4 carriers could potentially be a composite biomarker for early cognitive decline in people carrying this allele.
Transcriptomic Analysis of Whole Blood in Admixed Latinx Alzheimer Disease Cohorts
Authors: Griswold Anthony J. , Gu Tianjie , Van Booven Derek , Whitehead Patrice L. , Hamilton‐Nelson Kara L. , Contreras Maricarmen , Sanchez Jose Javier , Tejada Sergio , Adams Larry D. , Mena Pedro Ramon , Bush William S. , Silva‐Vergara Concepcion , Cornejo‐Olivas Mario , Illanes‐Manrique Maryenela , Cuccaro Michael L. , Vance Jeffery M. , Feliciano‐Astacio Briseida E. , Beecham Gary W. , Pericak‐Vance Margaret A. 
Published: December 2022

AbstractBackgroundIdentifying the genes and biological pathways involved in Alzheimer disease (AD) is critical in the effort to develop effective therapies. Significant work has identified genetic variants conferring risk and protection for AD in individuals of diverse ancestries, but identification of downstream functional effects including modulation of gene regulation is lacking, particularly in individuals of diverse ancestries. Therefore, to explore transcriptional changes between clinically diagnosed AD and cognitively intact age‐matched controls, herein we analyzed RNA sequencing data from peripheral blood collected from individuals of admixed genetic backgrounds.MethodTotal RNA was extracted from peripheral whole blood stored in PAXGene tubes from 47 Cubans (22 AD and 25 controls), 85 Peruvians (41 AD and 44 controls), and 168 Puerto Ricans (88 AD and 80 controls). PolyA selected mRNA was sequenced to more than 40 million paired end read per sample on the Illumina NovaSeq 6000. The bioinformatic pipeline included mapping to the human reference genome (GRCh38), gene quantifications against the GENCODE v35 annotation set, and differential expression was calculated using DESeq2 with sex, age at blood draw, and count of APOEe4 alleles as covariates. Functional categorization was performed by gene set enrichment of gene ontology and KEGG pathways.ResultAcross the cohorts, a total of 358 protein‐coding genes (FDR ≤ 0.05, Fold change ≥ 1.25) were differentially expressed with 238 down‐regulated and 120 up‐regulated in AD relative to controls. Despite the few genes overlapping between ethnicities, pathway analysis revealed common pathways including up‐regulation of genes involved in inflammation and RNA processing and down‐regulation of genes involved in cellular detoxification and lipid transport, among others. Interestingly, while few specific genes overlap in differential expression overlap with a published set of genes from non‐Hispanic Europeans and African Americans (Griswold et al, 2018), the pathways identified are similar.ConclusionOur analysis reveals a signature of gene expression that implicates increased inflammation and decreased cellular detoxification based on gene expression analysis in admixed Latinx AD. Convergence of pathways across these and African American and European cohorts supports the idea of distinct genes but similar underlying pathological processes contributing to AD across individuals of diverse ancestries.
Multidisciplinary collaboration to develop a digital health solution for early detection of cognitive decline in primary care
Authors: Hilsabeck Robin C. , Keller Jeffrey N. , Henry Maya L , Toprac Paul , Rathouz Paul , Sreekanth Varshinee , Largent Avery , Chang Joshua , Li Jessy , Pugalenthi Lokesh , Parsons Thomas , Cuevas Heather E , Schmitz Suzanne 
Published: December 2022

AbstractBackgroundDeveloping digital healthcare solutions that facilitate rapid identification and effective management of patients with Alzheimer disease and related disorders (ADRD) is an area of intense study. A critical juncture for these efforts involves the early detection of cognitive decline. Because primary care providers (PCPs) are the first line of medical care, they are often the first to hear concerns about cognitive decline. However, under‐diagnosis of ADRD in primary care settings is widely recognized, as are the many barriers to routine cognitive screening. While information about brief cognitive screening tools for detecting ADRD is plentiful, PCPs remain uncertain about which patients to assess, which tools to use and how to use them, and how to communicate results. The goal of this project was to design a risk assessment and cognitive screening (RACS) application that specifically addressed the needs and concerns of PCPs to facilitate identification of cognitive decline in primary care settings.MethodWe employed a multi‐modal assessment approach in designing the RACS app, which first assesses risk for cognitive impairment and then assesses cognitive functioning using a working memory/processing speed task in combination with four speech/language tasks. We assembled a multidisciplinary team with the following expertise to develop and test the app: biostatistics, computational linguistics, computer science, computerized cognitive assessment, gaming/app development, engineering, neurology, neuropsychology, neuroscience, primary care, psychometrics, and speech‐language pathology.ResultProgramming of app features and pilot testing with people with ADRD was completed in 3 months. Initial development of the connected speech analysis pipeline was completed in 4 months with ongoing testing. Data collection of 50 cognitively normal, 50 mild cognitive impairment, and 50 mild dementia participants is approximately 50% completed within 6 months. Preliminary results based on cognitive performance alone show good ability to discriminate groups. Reduction of speech‐language variables for inclusion in a final cognitive performance score is underway using a variety of machine learning techniques, including the elastic net and random forests.ConclusionThe RACS app shows promise as a digital health solution to facilitate early detection of cognitive decline in primary care and may prove useful in other busy clinical settings.
Development and Co‐Design of a Digital Intervention for People Affected by Dementia who are Fearful of Disclosing the Diagnosis to Their Social Networks
Authors: Kohl Gianna , Bhatt Jem , Scior Katrina , Charlesworth Georgina 
Published: December 2022

AbstractBackgroundReceiving a diagnosis of dementia can affect all aspects of an individual’s life, including their sense of identity. As a consequence, some people with dementia may socially withdraw due to stigma, embarrassment or fear of what might happen if other people were to find out about the diagnosis. The “Who to tell, how and when” intervention, a group‐based face‐to‐face intervention, has been developed for people affected by dementia who are fearful of disclosing the diagnosis to others. This study aims to adapt the existing intervention for online delivery, in light of the ongoing COVID‐19 pandemic.MethodsA co‐created, user‐centred design in three phases is applied. In phase 1, focus groups conducted with people with dementia and informal caregivers will inform the platform, features and adaptation of pre‐existing material. Phase 2 consists of the development of the digital prototype. In phase 3, the feasibility and usability are tested with end users to inform prototype v. 2.0.ResultsResearch has indicated that peer support in the disclosure decision‐making process is especially important for participants. Results from phase 1 and 2, including findings from the discussions with the focus groups and options appraisals for the peer support elements of the digital intervention will be discussed. We will discuss general principles of adaptation from paper manual to digital intervention.ConclusionOnline access to this intervention may be especially valuable for people who wish to maintain anonymity and privacy, for example people from cultural or ethnic groups where the stigma of dementia is high. Online versions of face‐to‐face interventions improve overall accessibility by providing choice.
Feasibility of Intentional Technology Pairing in Fostering Connections Among Dementia Caregivers
Authors: Fields Julie A. , Forsberg Leah K. , Knutson Matthew , Seifert Sara J. , Melius Jodi L. , Kramer Kevin M. , Lunde Angela 
Published: December 2022

AbstractBackgroundTo gather user input iteratively to develop a matching algorithm for peer‐to‐peer support and to assess the feasibility and usability of a web‐based program to conduct matching.Method32 caregivers of persons with dementia (PwD) participated in semi‐structured focus groups and completed surveys to provide input regarding characteristics deemed valuable in someone they would choose to be connected with for emotional support. Through an iterative process as new information emerged, a web‐based prototype and matching algorithm were developed. Caregivers interacted with the prototype and provided feedback indicating ease of accessibility and use, initial impression, and comfort/satisfaction with profile content.ResultAll 32 caregivers (age 40‐90, education 12/GED‐20, sex 88% female, 31% Black/African‐American) completed online profiles. Of those who interacted with the prototype, 23 completed the feedback survey, on which 87% had no or only mild difficulty accessing the site, 91% had no difficulty with technology once there, 86% had a very or quite positive initial impression, 91% found it very or quite easy to navigate, 87% rated a very or quite high level of comfort with completing the personal profile questions, and 82% felt very or quite confident the questions asked would lead to a good match.ConclusionA large majority of caregivers of PwD demonstrated the web‐based platform was easy to access and navigate, provided a positive experience, and gathered information that would lead to a good supportive relationship with another caregiver. Phase II will optimize the design and algorithm and evaluate the matching process in 350 caregivers.