bluuebunny/crossref_metadata_2025_split huggingface dataset:
Residual reserve index modifies the effect of amyloid pathology on FDG metabolism: implications for efficiency and capacity in cognitive reserve
Authors: McKenzie Cathryn , Bucks Romola S , Weinborn Michael , Bourgeat Pierrick , Salvado Olivier , Gavett Brandon E 
Published: December 2022

AbstractBackgroundCognitive functioning may be protected against AD pathology via cognitive resilience (conferred by cognitive reserve) or brain resilience (conferred by brain reserve or maintenance). The residual approach to measuring cognitive reserve (i.e., using the residual reserve index) aims to capture cognitive resilience, but may be confounded by unmeasured brain factors representing brain resilience. We sought to distinguish between brain and cognitive resilience by comparing the interactions between the residual reserve index and amyloid, tau, and neurodegeneration (AT(N); Jack et al., 2018) biomarkers when predicting executive function. We hypothesized that the residual reserve index would moderate at least one path from an AT(N) biomarker to executive function (consistent with cognitive resilience), as opposed to moderating a path between two AT(N) biomarkers (suggestive of brain resilience).MethodParticipants were 332 older adults from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). AT(N) biomarkers were measured as follows: amyloid = CSF Aβ42/Aβ40; tau = plasma p‐tau181; neurodegeneration = FDG metabolism in AD‐specific regions. AT(N) biomarkers were measured at consecutive time points and entered in a sequential mediation model testing the indirect effects from amyloid to executive function intercept and slope, via tau and/or FDG metabolism. The residual reserve index was entered as a moderator of paths between AT(N) biomarkers, and between AT(N) biomarkers and executive function.ResultThe only significant interaction was between the residual reserve index and amyloid when predicting FDG metabolism, such that the indirect effect of amyloid → FDG metabolism → executive function intercept and slope varied as a function of the residual reserve index. With lower amyloid pathology, a higher residual reserve index predicted better executive function via lower FDG metabolism. With higher amyloid pathology, a higher residual reserve index predicted better executive function via higher FDG metabolism.ConclusionAlthough the residual reserve index moderated a path between two AT(N) biomarkers, the net effect was consistent with cognitive rather than brain resilience. Our results suggest the residual reserve index captures variation in cognitive reserve; specifically, neural efficiency and neural capacity to upregulate metabolism to enhance cognitive resilience in the face of more severe amyloid pathology.
Social Determinants Influencing the Severity of Dementia on Screening: An Observational Study in the Indian Population
Authors: Kainth Tejasvi , Singh Gagandeep , Prasanna Prateek , Manjila Sunil , Rao Anitha 
Published: December 2022

AbstractBackgroundWith increased longevity and decreased fertility rate, the percentage of population over 65 years of age is growing in India. Literacy rates, family size, socioeconomic status, and comorbidities are rapidly changing due to the increased migration from rural to urban areas. Data‐driven studies are required to determine the influence of social factors and comorbidities on the distribution of Alzheimer’s disease and related dementias (ADRD) and neurological care resources. We demonstrate results from a feasibility study that uses state‐of‐the‐art AI, data analytics, and a HIPAA‐compliant Telehealth platform to screen patients over 65 years in India for ADRD.MethodA primary care provider used a telemedicine platform, Artificial Intelligence (AI), and a standardized cognitive test to screen every consenting patient aged 65 years and older. The screening used an algorithm‐based intake tool, baseline Mini‐Mental Status Exam (MMSE), and clinical judgment of the primary care physician. We documented sociodemographic data and comorbidities: age, gender, education, living situation (family size), geographical location (urban/rural), the number and types of comorbidities.ResultNine patients (4 females, 5 males) over 65 years of age, consented and enrolled in this study. 55% (5 in 9 patients) had a bachelor’s degree or higher, 22% (2 in 9 patients) were high school graduates, 22% (2 in 9 patients) were 8th grade and below. 44% (4 in 9 patients) were from rural backgrounds, and 55% (5 in 9 patients) lived in urban backgrounds. 44% (4 in 9 patients) had one comorbidity, 11% (1 in 9 patients) had two comorbidities, 44% (4 in 9 patients) had three and more comorbidities. Out of four patients screened as mild dementia by AI (44%), three patients (75%) had two or more underlying comorbidities.ConclusionOur results demonstrate that medical comorbidities and social determinants may influence India’s ADRD severity scores and neurocognitive screening. We can use the results to address foreseeable gaps for ADRD screening and ensure equitable resource distribution via telemedicine in India. The data captured in this AI and telemedicine collaboration may provide the foundation for identifying new biomarkers and developing targeted treatments that work for ethnically diverse patients.
Dyadic retention in a phase 3 mild cognitive impairment clinical trial
Authors: Hakhu Navneet R , Gillen Daniel L. , Grill Joshua 
Published: December 2022

AbstractBackgroundExiting a study early (dropout) may bias treatment effect estimates, while dropout and missing visits reduces study power. Simply increasing planned sample sizes cannot remove bias due to non‐ignorable missingness (Fleming, 2011). Preventing missing data is best (National Research Council, 2010). Hence, quantifying associations with missingness may identify ways to improve retention. Alzheimer’s disease (AD) clinical trials require study participation by a participant and study partner. Previous research examined dyadic retention in AD dementia trials (Grill et al., 2013; Bernstein, Grill & Gillen, 2021), yet less is understood in mild cognitive impairment (MCI) trials. Here, we examined MCI trial dropout rates and missingness patterns by dyad type.MethodWe performed retrospective analyses of the Alzheimer’s Disease Cooperative Study phase 3 MCI trial of donepezil and vitamin E. Scheduled study visits occurred at baseline, month 3, and semi‐annually until month 36. Study completion included the progression to a possible or probable AD diagnosis or month 36 visit. Dropout was withdrawal of consent or lost‐to‐follow‐up. Deaths and study completions were censored. Dyad types were spousal, adult child, or other. We estimated Kaplan‐Meier‐based dropout rates and summarized frequencies of on‐study missing visit patterns by baseline dyad type and stratified by randomized treatment (placebo, donepezil, vitamin E).ResultFigure 1 displays cumulative dropout rates by dyad type and treatment (panels A, B, C). Among 259 participants randomized to placebo, estimated study dropout rates were 24% for spousal, 16% for adult child, and 14% for other dyads. Table 1 summarizes on‐study missing visit patterns by dyad type and treatment; Figure 2 displays placebo data for specific patterns of missing data. While on study, 21% of spousal, 23% of adult child, and 27% of other dyads missed at least one scheduled visit, primarily monotonic missingness.ConclusionDyad type may be associated with some types of missingness in MCI clinical trials. Implementing dyad‐type‐specific strategies that encourage staying on study and attending all scheduled visits may improve retention, thus reducing bias, in future MCI trials.
Diverse Ancestral Populations and the ADSP
Authors: Kunkle Brian W. ,   Alzheimer’s Disease Sequencing Project (ADSP)
Published: December 2022

AbstractBackgroundA major goal of the ADSP is to fully reveal the genetic architecture of AD/ADRD across diverse ancestral populations with the hope that new discoveries and the therapeutic or prevention strategies they enable will benefit all ancestral groups.MethodWhile the project’s ‘Discovery Phase’ (2012‐2017) sequenced predominantly non‐Hispanic White individuals of European ancestry (NHW‐EA) [whole‐exome sequencing: N = 10,061; whole‐genome sequencing (WGS): 197 NHW‐EA and 351 Hispanic/Latino (HL) familial individuals], the ‘Discovery‐Extension Phase’ of the project added WGS on 1,183 NHW‐EA, 1,141 HL, and 1,070 non‐Hispanic Black individuals with African ancestry (NHB‐AA). The ADSP’s current phase, the Follow‐Up Study (FUS) (2018‐2023) has targeted existing ancestrally diverse and unique cohorts with clinical AD/ADRD data. Over 40,000 individuals have been ascertained and ∼32,000 sequenced to date (ancestry distribution: 9,192 NHB‐AA; 9,952 HL; 13,531 NHW‐EA, 4,600 East Asian, 2,760 Indian, 89 Amerindian).ResultDespite relatively small sample sizes, important instances of unique AD/ADRD genetic variation have been identified in HL and NHB‐AA studies, including population‐specific rare/low‐frequency variants, and evidence of the importance of ancestral background in conferring risk for genetic factors such as APOE ε4. Power studies show ∼16,100 cases and ∼16,100 controls are needed per ancestry for discovery of risk/protective variants with minor allele frequency (MAF) of 0.5% and odds ratios (OR) of 2.0 at genome‐wide significance (P = 5×10−8). Using region‐based testing ∼10,000 cases and ∼10,000 controls are needed for finding variants with MAF = 0.005% and ORs = 1.4. To this end, the next phase of the ADSP, the “ADSP‐FUS 2.0: The Diverse Population Initiative” NIH_PAR‐21‐212 aims to ensure there are enough study participants to achieve statistical power for rare variant analysis in the largest US populations, with a particular focus on HL, NHB‐AA, and Asian populations. Initiatives such as the Asian cohort for Alzheimer’s disease (ACAD), focusing on increasing recruitment of Asians in AD/ADRD studies, are also in development.ConclusionThese datasets, some of which will include data for assessing social and environmental influences of AD/ADRD, will be an invaluable resource for the AD research community and will enhance ongoing efforts for the identification of shared and novel genetic risk factors for AD/ADRD across populations.
Incentives to increase willingness to undergo research lumbar puncture
Authors: Witbracht Megan G. , Baumgartner Morgan , Gillen Daniel L. , Grill Joshua 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) research increasingly relies on biomarker testing to understand longitudinal biological contributions to clinical disease progression. The collection of cerebrospinal fluid (CSF) through a lumbar puncture (LP) is an efficient method to obtain reliable AD biomarkers; however, most people are unwilling to participate in the procedure for research. This study aimed to understand what incentives could be offered to increase the propensity for people to consider a research LP.MethodAs part of a previous study testing an educational intervention to increase willingness to consider the research LP (Witbracht et al, 2020), we asked participants an open‐ended question about incentives that could be offered to change their mind about undergoing a research LP. One reviewer assessed a subset of responses to establish preliminary categories of independent themes. A second reviewer assessed these themes and then a consensus exercise was used to create final themes for coding. Two reviewers then coded all responses and discordant assignments were resolved by a third rater.ResultOf 851 participants who enrolled in the study, 467 answered the open‐ended question. Among those who responded, 72.8% were female; 87.6% were white; 86.7% were non‐Hispanic. The mean age of respondents was 57.9 (15.2) years and the mean years of education was 18 (9.0). Responses deemed valid incentives were provided by 205 (44%) participants, while 121 participants (26%) indicated that nothing could be offered to make them more likely to consider the procedure and 30% provided a non‐incentive response. The top 3 themes identified accounted for 60% of the total coded incentives: financial compensation (n=69), diagnostic value (n=30), and more information (n=26). Other themes identified included assurance of no adverse events, post procedure care, performance by a qualified clinician, improved techniques, mitigated fear, first person testimonies of procedure, evidence of research value, providing logistical support, approval from personal doctor, anda guarantee of no biomarker disclosure.ConclusionBarriers to recruitment are significant for research involving LP. Participants in this study identified several feasible (and some infeasible) incentives that could increase willingness to consider a research LP.
Contribution of modifiable dementia risk factors to cognitive performance and subjective cognition in middle‐aged adults
Authors: Bransby Lisa , Rosenich Emily , Buckley Rachel F. , Yassi Nawaf , Maruff Paul , Pase Matthew P , Lim Yen Ying 
Published: December 2022

AbstractBackgroundCharacterization of the contribution of modifiable risk factors (MRF) to dementia generally consider MRFs individually, despite strong evidence that MRFs co‐occur. In a large group of middle‐aged adults, the prevalence and co‐occurrence of MRFs for dementia was determined, spanning five broad domains (mood, lifestyle behaviours (e.g., physical inactivity), cardiovascular health, cognitive/social engagement, and sleep). We then investigated relationships between MRFs, both individually and combined, to cognitive performance and subjective cognition.MethodMiddle‐aged adults (n = 1610), most (70%) with a family history of dementia, enrolled in the Healthy Brain Project, completed an extensive set of questionnaires about their physical and psychological health and lifestyle. Participants also completed the Cogstate Brief Battery (CBB), and the Cognitive Function Instrument (CFI), a measure of subjective cognition. Participants were classified according to the number of domains (mood, lifestyle behaviours, cardiovascular health, cognitive/social engagement, and sleep, ranging from 0‐5) in which they reported at least one MRF. Age, sex, education and ethnicity were adjusted for in analyses.ResultMost participants (65%) reported at least one MRF in two or more domains (Fig 1A). Compared to participants reporting no MRFs, participants who reported at least one MRF in 3‐5 domains showed worse memory performance and reported greater subjective cognitive concerns, with magnitudes of differences moderate to large (d = 0.30‐0.93; Fig 1B). Participants who reported at least one MRF in five domains also showed worse attention than those reporting no MRFs (d = 0.58). When individual MRFs were considered simultaneously, MRFs in the mood (e.g., anxiety symptomatology) and cognitive/social engagement domains (e.g., leisure activities) were associated with worse attention and memory performance. Individual MRFs reflecting mood and sleep symptomatology were associated with greater subjective cognitive concerns.ConclusionIn middle‐aged community dwelling adults, multidomain MRFs for dementia are highly prevalent and co‐occur, and are associated with poorer cognitive outcomes. This suggests that the presence of multiple MRFs as early as midlife may have negative neurological outcomes, however, this will need to be explored in future neuroimaging studies. These findings indicate that multidomain lifestyle prevention trials in middle‐aged adults may be useful to delay or prevent future cognitive impairment or dementia.
Translating network activity in an Alzheimer mouse model to human Alzheimer's disease mutation carriers
Authors: van Nifterick Anne M , van Heusden Fran C , Stam Cornelis J , Scheltens Philip , van Kesteren Ronald E. , Gouw Alida A 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) mouse models allow for the identification of cellular and molecular processes underlying neuronal network imbalance. In order to interpret these processes in a disease context, we need to link network changes in AD animals to those in human patients. Brain oscillations reflect neuronal network (im)balance and offer a tool to translate findings from mice to men. In this preliminary study, we investigate and compare cortical and hippocampal oscillatory activity using magnetoencephalography (MEG) in human patients and longitudinal electrophysiology recordings in AD mice.MethodsSource reconstructed resting state whole‐brain MEG of ten APP and PSEN1 mutation carriers and ten age‐ and gender‐matched control subjects were acquired. Carriers did not show objectively impaired cognitive functioning on any of the composite scores after extensive neuropsychological testing. Longitudinal local field potential recordings were obtained by implanted electrodes in APP/PS1 transgenic and wildtype controls from 3 until 10 months of age in different brain regions of the left hemisphere: hippocampus, prefrontal and parietal cortex. MEG analyses were constrained to similar brain regions. We estimated peak frequency, total (absolute broadband) and relative power across canonical frequency bands and compared these between human or mice mutation carriers and controls.ResultsHuman APP and PSEN1 mutation carriers showed lower peak frequency in the hippocampus and lower relative alpha 2 power in the precuneus and frontal cortex compared to controls (Fig1.). APP/PS1 mice also showed specific network alterations compared to wildtype control mice, but these seem to have more faster oscillations instead.ConclusionIn cognitively unimpaired human APP and PS1 mutation carriers we find oscillatory activity changes in the cortex and hippocampus, indicating network imbalance. However, opposite network changes are observed in the APP/PS1 AD mouse model compared to human mutation carriers using spectral measures. Future studies should explore other measures of network imbalance to identify potential cross‐species mechanistic links of early stage AD.
Best combination of CSF biomarkers for predicting cognitive decline and clinical progression: A multi‐cohort study
Authors: Salvadó Gemma , Larsson Victoria , Cody Karly Alex , Cullen Nicholas , Jonaitis Erin M. , Stomrud Erik , Kollmorgen Gwendlyn , Wild Norbert , Palmqvist Sebastian , Janelidze Shorena , Mattsson‐Carlgren Niklas , Zetterberg Henrik , Blennow Kaj , Johnson Sterling C. , Ossenkoppele Rik , Hansson Oskar 
Published: December 2022

AbstractBackgroundAmyloid‐β (Aβ) and tau markers have very good prognostic value for Alzheimer’s disease (AD); however, novel neurodegeneration and glial‐related cerebrospinal fluid (CSF) biomarkers may help further improve prognosis. Using multiple CSF biomarkers from a single multi‐panel, we explored the combination of biomarkers that best predicts cognitive decline and clinical progression in three separate cohorts with relevance for clinical practice and trials.MethodIn this study, we included 1,991 participants (cognitively unimpaired [CU], n=1,462; mild cognitive impairment [MCI], n=529) from three separate cohorts (BioFINDER‐1, BioFINDER‐2 and Wisconsin’s: Wisconsin Registry for Alzheimer’s Prevention [WRAP] & Wisconsin Alzheimer’s Disease Research Center [WADRC]; Table 1) with longitudinal cognitive and clinical measurements. CSF was measured in all participants using the NeuroToolKit panel (a panel of automated Elecsys® and robust prototype immunoassays, Roche Diagnostics International Ltd) for biomarkers of AD pathology (p‐tau/Aβ42 ratio), neurodegeneration (neurofilament light chain [NfL], neurogranin, and α‐synuclein), and glial function (sTREM2, GFAP, YKL‐40, IL‐6, and S100b). Linear mixed models and generalized linear mixed models were used in each cohort to identify biomarker combinations most predictive of clinical progression (to Alzheimer’s dementia or all‐cause dementia) or cognitive decline (Preclinical Alzheimer’s cognitive composite [PACC] for CU and Mini‐Mental State Examination [MMSE] for MCI). Best performing models were compared to single‐predictor (p‐tau/Aβ42) models using Akaike information criterion (AIC) and areas under the curve (AUC), respectively.ResultOnly p‐tau/Aβ42 ratio was selected as predictor in the parsimonious models for predicting conversion to Alzheimer’s dementia in all cohorts and conversion to all‐cause dementia in the Wisconsin’s cohort (Table 2, Figure 1). In the other two cohorts, model performance was significantly improved by the addition of NfL and neurogranin (BioFINDER‐1) and NfL alone (BioFINDER‐2). For predicting cognitive decline, parsimonious models included p‐tau/Aβ42 ratio alone (MMSE in BioFINDER‐1 and PACC in the other cohorts) or together with NfL (rest) as predictors.ConclusionThe CSF p‐tau/Aβ42 ratio is sufficient for prediction of AD progression, showing very high accuracy in three separate cohorts. The addition of NfL to p‐tau/Aβ42 can be applied to a clinical setting to further improve the prediction of all‐cause dementia and cognitive decline.
Medial temporal lobe subregional atrophy patterns in early‐ and late‐onset amnestic Alzheimer’s disease
Authors: Wuestefeld Anika , Wutt Hmon , Berron David , Baumeister Hannah , Binette Alexa Pichet , Stomrud Erik , Mattsson‐Carlgren Niklas , Strandberg Olof , Smith Ruben , Palmqvist Sebastian , van Westen Danielle , Hansson Oskar , Wisse Laura EM 
Published: December 2022

AbstractBackgroundThe medial temporal lobe (MTL) is hypothesized to be relatively spared in early‐onset compared to late‐onset Alzheimer’s disease (AD). However, detailed examination of MTL subfields comparing amnestic early‐ and late‐onset AD is lacking. We investigate MTL subfield atrophy patterns in individuals with amnestic early‐ and late‐onset cognitive impairment (EOCI and LOCI).MethodsCognitively impaired (mild cognitive impairment and dementia) adults from the BioFINDER‐2 study with memory impairment (>1.5SD age‐ and education‐specific norms), amyloid‐beta (Aβ+ based on CSF Aβ42/40), and tau positivity were included (Table 1). [18F]RO948‐PET standardized uptake value ratios (SUVRs) were calculated for the MTL, and tau‐PET positivity was determined from a temporal meta‐ROI. EOCI individuals were <65 years, LOCI >70 years of age. Self‐reported age‐of‐onset matched with EO/LO status. Two reference groups of Aβ‐ cognitively unimpaired (CU) which were age‐matched to EOCI/LOCI were included. Hippocampal subfield volumes and thickness of entorhinal cortex, Brodmann areas (BA)35/36, and parahippocampal cortex were obtained using Automated Segmentation for Hippocampal Subfields packages for T1‐ and T2‐weighted MRI. We focused particularly on BA35, region with earliest tau accumulation. Episodic memory was determined (errors on delayed word‐list recall).ResultsCompared to CU, LOCI showed widespread atrophy across all MTL subfields, while the atrophy pattern in EOCI was slightly more restrictive (Fig. 1). Compared to EOCI, LOCI showed more severe atrophy in hippocampal subfields and entorhinal cortex.There was no difference between EOCI and LOCI for MTL tau‐PET SUVR (Fig. 2).Zooming in on BA35, there was a trend for an association between MTL tau‐PET SUVR and BA35 atrophy in LOCI. This association was stronger for EOCI but non‐significant, likely due to limited power (Fig. 2C). In both groups, smaller BA35 was associated with worse episodic memory (Fig. 3A). In LOCI, higher MTL tau‐PET SUVR was associated with worse episodic memory (Fig. 3B).ConclusionThe findings suggest that MTL tau‐PET uptake and atrophy is present in both amnestic LOCI/EOCI and is related to the observed memory impairment in these groups. The MTL atrophy pattern is more extensive in LOCI, which may be due to longer presence of tau pathology and/or the involvement of comorbid pathologies.