bluuebunny/crossref_metadata_2025_split huggingface dataset:
123I‐Ioflupane SPECT Striatal Binding Ratio Predicts Progression of Parkinsonism in a Dementia with Lewy Bodies Cohort
Authors: Maly Emily F , Leverenz James B , DiFilippo Frank A 
Published: December 2023

AbstractBackgroundThe criteria for diagnosis of dementia with Lewy bodies (DLB) remain predominantly clinical. However, use of striatal dopamine transporter visualization is suggested as an “indicative” biomarker for DLB under the most recent published DLB criteria (McKeith, Neurology, 2017). The objective of this study is to determine if 123I‐ioflupane SPECT (DaTscan) striatal binding ratio (SBR) correlates with parkinsonian symptoms measured on the Movement Disorder Society – Unified Parkinson’s Disease Rating Scale Part III (MDS‐UPDRS‐III) in patients with either probable DLB or high‐likelihood DLB individuals with mild cognitive impairment (MCI). A secondary aim of this study is to determine if DaTscan SBR measured at baseline can predict progression of parkinsonian symptoms over 2 years in this study population.MethodsThis is a retrospective cohort study using the U.S. Dementia with Lewy Bodies Consortium (DLBC) dataset (U01 NS100610). The sample group included in this study are individuals with either probable DLB (McKeith, Neurology, 2017) or MCI‐LB (McKeith, 2020). Each participant had a baseline DaTscan analyzed with DaTQUANT software and physical examination scored with MDS‐UPDRS‐III. Participants without these data were excluded. Mixed effect models were fit with UPDRS score as the dependent variable and SBR z‐score as the primary independent variable. Data were adjusted for age, gender, diagnosis, and dopaminergic medication at time of examination.ResultsAn analysis between 53 participants’ baseline MDS‐UPDRS‐III and SBR z‐scores revealed a moderate negative correlation, indicating SBR is a significant predictor of baseline MDS‐UPDRS‐III score. An analysis between 23 participants’ baseline SBR z‐scores and 24‐month MDS‐UPDRS‐III revealed a moderate negative correlation, indicating that baseline SBR is a significant predictor of 24‐month MDS‐UPDRS‐III scores.ConclusionThese data reveal a significant relationship between DaTscan SBR and motor examination in DLB. Additionally, there is a significant relationship between baseline SBR and progression of parkinsonian features. We conclude that in DLB, DaTscan at time of diagnosis could be used to confirm underlying dopamine deficiency in the context of clinical parkinsonism and predict progression of parkinsonian symptoms in DLB. This could aid in guiding therapies and prognostication of symptom progression.
Longitudinal cognitive change in older adults with elevated tau PET signal in the absence of amyloid
Authors: Weigand Alexandra J. , Thomas Kelsey R. , Edwards Lauren C. , Bondi Mark W. 
Published: December 2023

AbstractBackgroundMost theoretical frameworks for Alzheimer’s disease (AD) pathogenesis propose amyloid as the primary pathologic process, whereas tau in the absence of amyloid (A‐/T+) is considered a “non‐AD pathologic change” (Jack et al., 2018). Previous research has demonstrated AD‐like characteristics of the A‐/T+ biomarker profile, including poorer memory and language performance and entorhinal thinning (Weigand et al., 2022; Yoon et al., 2022). Assessment of domain‐specific longitudinal cognitive decline in this group, however, has not yet been addressed. Our study sought to evaluate 1‐year memory, language, and attention/executive function trajectories of A‐/T+ older adults.MethodWe included 756 older adults at baseline across the AD clinical continuum from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), of whom 359 had 1‐year follow‐up cognitive data. Four A/T groups were classified based on cortical amyloid‐beta and medial temporal tau positron emission tomography positivity. Linear mixed effects models examined 1‐year trajectories of each baseline A/T group in domains of memory, language, and attention/executive function. Both statistical significance and effect size estimates were evaluated.ResultThe following proportions of A/T groups were observed at baseline: 47.0% A‐/T‐, 13.2% A‐/T+, 13.4% A+/T‐, and 26.4% A+/T+. Only the A+/T+ group exhibited a statistically significant decline in language and attention/executive function domains relative to the A‐/T‐ group. Examination of effect sizes, however, revealed that the A‐/T+ group had a quantitatively similar degree of decline as the A+/T+ group in memory (A‐/T+ and A+/T+ bs = ‐0.13), and an intermediate degree of decline between the A‐/T‐ and A+/T+ groups for language (A‐/T+ b = ‐0.17) and attention/executive function (A‐/T+ b = ‐0.19). Similar patterns were observed when examining cognitively unimpaired participants only.ConclusionOlder adults with the A‐/T+ biomarker profile demonstrate a degree of cognitive decline across multiple domains consistent with a possible AD trajectory. The systematic exclusion of these individuals from AD clinical trials may hinder early intervention efforts to attenuate the cognitive decline observed in this biomarker group, and an expansion of our conceptualization of the AD continuum to include A‐/T+ individuals may offer improved insight into the pathologic and cognitive changes that occur in the context of preclinical AD.
Plasma p‐tau 181 outperforms FDG‐PET and plasma‐NfL in the diagnosis of biological AD
Authors: Socualaya Kely Quispialaya , Therriault Joseph , Aliaga Antonio , Servaes Stijn , Tissot Cécile , Rahmouni Nesrine , Macedo Arthur C. , Arias Jaime Fernandez , Hosseini Seyyed Ali , Vitali Paolo , Soucy Jean‐Paul , Gauthier Serge , Rosa‐Neto Pedro 
Published: December 2023

AbstractBackgroundTo compare the performance of plasma p‐tau181, plasma‐NfL and FDG‐PET in the diagnosis of biological AD.MethodWe included 787 participants (cognitively unimpaired (CU, n = 251), mild cognitive impairment (MCI, n = 412), and Alzheimer’s dementia (AD, n = 124) from the ADNI database. Participants underwent measures of plasma p‐tau181, plasma‐NfL, CSF P‐tau181, [18F]FDG‐PET, amyloid‐PET and cognitive screening tests. ROC analyses were used to determine diagnostic accuracy of plasma P‐tau181, NfL and [18F]FDG‐PET using clinical diagnosis and core AD biomarkers (amyloid‐PET and CSF P‐tau181) as reference standards. We assessed whether plasma P‐tau181 and [18F]FDG‐PET diagnostic accuracies were significantly different with a bootstrap‐based test (pROC package in R). Second, correlations of [18F]FDG‐PET, plasma‐NfL, plasma P‐tau181 with P‐tau181 CSF, Aβ‐PET, and cognitive performance were evaluated. Correlation coefficients were compared via Cocor package, a statistical framework for comparing associations between intercorrelated measurements.ResultAcross the total sample we observed that plasma P‐tau181, plasma‐NfL, and [18F]FDG‐PET were able to identify individuals with CSF evidence of AD as well as participants who are amyloid‐PET+. In the MCI group, plasma P‐tau181 outperformed [18F]FDG‐PET and plasma‐NfL in identifying AD pathophysiology measured via CSF P‐tau181 (p = 0.0007), and amyloid‐PET (p = 0.001). We also observed that both plasma P‐tau181, plasma‐NfL and [18F]FDG‐PET were associated with AD pathophysiology measured by core AD biomarkers (CSF and amyloid‐PET). However, [18F]FDG‐PET was more closely associated with cognitive outcomes than plasma P‐tau181 and plasma NfL (MoCA: p < 0.0001; MMSE: p< 0.0001; CDR‐SB: p < 0.0001)ConclusionThis study investigated the diagnostic properties of plasma P‐tau181 and two neurodegenerative biomarkers (plasma‐NfL and [18F]FDG‐PET) as well as their to identify biological AD. While plasma P‐tau181, plasma‐NfL concentrations and [18F]FDG‐PET were associated with AD pathophysiology measured by core AD biomarkers (CSF and amyloid‐PET), plasma P‐tau181 outperformed [18F]FDG‐PET and plasma‐NfL in identifying individuals with AD pathophysiology. However, we also observed that [18F]FDG‐PET was more strongly associated with neuropsychological assessments than plasma P‐tau181 and plasma‐NfL. Taken together, our study suggests that plasma P‐tau181 may aid in the evaluation of individuals by identifying those with underlying AD pathophysiology.
Preliminary Data on the Rural‐Urban Commuting Area Codes for the ALLFTD Cohort
Authors: Forsberg Leah K. , Brushaber Danielle , Heuer Hilary W. , Rosen Howard J. , Boxer Adam L , Boeve Brad F. 
Published: December 2023

AbstractBackgroundThe rural‐urban commuting area (RUCA) codes classify communities using measures of population density, urbanization, and daily commuting from U.S. Census Bureau information. The ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study generated RUCA codes for enrolled participants to better understand our cohort demographics. The rural‐urban distribution of participants may provide important insights for clinical trial planning.MethodsThe current RUCA codes are generated from the 2010 decennial census and the 2006‐10 American Community Survey data. The codes are numbers (1‐10) that describe metropolitan, micropolitan, small town, and rural commuting areas based on the size and direction of the primary (largest) commuting flows.ResultsRUCA codes were generated on 784 ALLFTD participants. At their most recent visit, participant median age was 60, 51.1% female, and a median education of 16 years. Participants were classified as clinically normal (39.1%), behavioral variant FTD (25%), nonfluent PPA (6.7%), semantic variant PPA (6.6%), PSP (4.7%), MBCI (4.8%), corticobasal syndrome (5.9%), and the remaining 7% of participants had other dementia‐related diagnoses. For participants with sporadic disease, 87.4% live in a metropolitan area, 6.7% a micropolitan area, 3.2% a small‐town area, and 3.2% live in a rural area. In familial FTLD, a larger percentage of participants live in micropolitan or small town/rural community (18.8% combined; p = 0.029), driven largely by MAPT family participants (n = 101). 10% of those with a familial MAPT mutation live in a rural area; with an additional 18% in micropolitan (12.9%) or small‐town areas (5%). Among those with a familial C9orf72 expansion, 83.3% live in a metropolitan area, 8.9% micropolitan area, 5.6% in a small‐town area, and 2.2% in a rural area. Participants with a familial GRN mutation show a similar distribution: 84.7% live in a metropolitan area, 5.6% micropolitan, 6.9% small‐town, 2.8% rural.ConclusionsAdditional analyses to better understand if FTD families are disproportionately living in rural communities are underway. These analyses will better characterize sporadic and familial FTD demographics to assist with clinical trial design.
Interaction between DNA methylation and neighborhood disadvantage may impact risk for cognitive decline among Mexican Americans enrolled in the Health and Aging Brain Study – Health Disparities (HABS‐HD) Cohort
Authors: Housini Mohammad , Zhou Zhengyang , Kind Amy J. , Reid Danielle M , Daniel Ann Abraham , Silzer Talisa , O'Bryant Sid E. , Phillips Nicole , Barber Robert , Pathak Gita 
Published: December 2023

AbstractBackgroundLiterature continues to indicate that social exposome factors such as neighborhood disadvantage, measured by the area deprivation index (ADI), is associated with cognitive decline, total brain volume, hippocampal volume and AD neuropathology. We hypothesize that epigenetic markers are implicated in the effect of neighborhood disadvantage on neurodegenerative biomarkers among Mexican Americans. We used existing Illumina EPIC Methylation chip and ADI data from 32 Mexican American participants enrolled in the Heath & Aging Brain Study ‐ Health Disparities (HABS‐HD) cohort to test whether differentially methylated sites and regions moderate a portion of the effect of ADI on risk for implicated AT(N) biomarkers.MethodThis study included Mexican American participants with information on DNA methylation, ADI, and Neurofilament Light (NfL), who were part of the Health and Aging Brain Study – Health Disparities (HABS‐HD). We considered 25 targeted epigenetic markers, which were previously identified to be associated with MCI or NfL from our group. We conducted preliminary analysis to assess associations between ADI and NfL using whole data (n = 812), and whether such association is moderated by one of the aforementioned targeted epigenetic markers using data with DNA methylation information (n = 32). Linear regression models were conducted to test the above effects and adjust for covariates.ResultResults of the linear regression models showed that ADI was significantly positively associated with NfL among Mexican Americans (p = 0.007) using whole data, but the moderation analysis revealed no significant moderating effects on such association for any of the targeted epigenetic markers. However, one CpG site, cg07413251, showed marginally significant interaction effects with ADI on the association with NfL (p = 0.056). The cg07413251 site maps to a CpG island located at chr3p24.1. The biological implications of differential methylation at this site are unknown and remain under investigation.ConclusionThe lack of significant results for moderation effects of the targeted epigenetic markers in our pilot study were likely due to the small sample size. In our future work, we will expand samples size significantly, improving power to better understand the role of disadvantaged neighborhoods in influencing cognitive function. Investigations into other biomarkers are underway.
Prognostic prediction of the longitudinal cognitive trajectory of amyloid‐positive patients with mild dementia
Authors: Devanarayan Viswanath , Charil Arnaud , Sachdev Pallavi , Ye Yuanqing , Koyama Akihiko , Reyderman Larisa , Hampel Harald , Irizarry Michael C. , Dhadda Shobha , Kramer Lynn D 
Published: December 2023

AbstractBackgroundPrediction of longitudinal cognitive decline for patients with mild dementia using baseline characteristics will be useful for designing optimal clinical trials and real‐world patient monitoring. This can be accomplished via machine‐learning models using baseline clinical characteristics. Adding plasma pTau181 and brain region volumes may improve the predictions.MethodThe training cohort (TC) included 905 amyloid‐positive (A+) patients with mild dementia from two clinical trials. The validation cohort (VC) included 230 A+ patients from another clinical trial. Over 85% of these patients had MCI. The longitudinal cognitive decline was defined by the change from baseline in CDR‐SB at months 3, 6, 9, 12, 15, and 18. Plasma pTau181 was measured using Simoa assay in a subset of 159 patients in TC.Structural brain network (SBN) modules and hubs were derived using 207 regional volumetric MRI measures in TC via an algorithm from genomics called “multiscale embedded gene co‐expression network analysis”. A signature for predicting longitudinal cognitive trajectory for each patient was first derived using baseline cognitive assessments and demographics within TC via the Stochastic Gradient Boosting algorithm. The added value of SBNs and plasma pTau181 was then evaluated within this framework. Prediction performance was evaluated in VC via the correlation between predicted versus observed cognitive trajectory.ResultPredictions of the longitudinal cognitive trajectory using baseline cognitive assessments achieved 43.4% and 42.5% correlation with observed values at months 12 and 18 respectively. Key baseline cognitive function predictors were ADAS‐Cog‐14, CDR‐SB, and sub‐scores such as ideational praxis and word recall.Adding baseline SBNs significantly improved the correlation between predicted versus observed cognitive trajectory to 46.3% and 49.7% at months 12 and 18 respectively (p<0.05). Key baseline SBN predictors were middle and inferior temporal, inferior parietal, and superior frontal cortex, along with a module comprising the entorhinal cortex and temporal pole. Adding baseline plasma pTau181 to cognitive assessments yielded similar improvements, but adding both pTau181 and SBNs did not improve the predictions further.ConclusionLongitudinal cognitive decline of A+ patients with mild dementia can be predicted using baseline cognitive assessments. Adding specific structural brain networks or plasma pTau181 significantly improves the predictions.
Longitudinal change of plasma biomarkers with incident mild cognitive impairment or Alzheimer’s disease in a multi‐ethnic cohort
Authors: Honig Lawrence S. , Kang Min Suk , Sanchez Danurys , Reyes‐Dumeyer Dolly , Lantigua Rafael A. , Dage Jeff L. , Brickman Adam M. , Manly Jennifer J. , Mayeux Richard , Gu Yian 
Published: December 2023

AbstractBackgroundThe utility of plasma‐based Alzheimer’s biomarkers in differentiating cognitively healthy individuals from those with Mild Cognitive Impairment (MCI) or Alzheimer’s disease (AD) has been widely investigated in cross‐sectional studies. There are fewer data on longitudinal change of these biomarkers over time, particularly in multi‐ethnic cohorts.MethodBased on a community‐based, multi‐ethnic cohort study, the Washington Heights Inwood Columbia Aging Project, we included 610 cognitively normal individuals with three plasma samples collected over a mean period of 6.7 years. We used AD biomarkers, including Aβ40, Aβ42, tau, phosphorylated tau‐181 (P‐tau181), glial fibrillary acid protein (GFAP), and neurofilament light chain (NfL), and two calculated ratio measures (Aβ42/Aβ40, P‐tau181/Aβ42). During the follow‐up, 156 individuals developed MCI, 50 developed AD, and 404 remained cognitively unimpaired. We used generalized estimating equations to examine whether those who developed MCI and AD had different rates of change in plasma biomarkers than controls. Analyses were adjusted for age, years of education, sex, race and ethnicity, and APOE ɛ4 status. Similar analyses were performed to examine whether the rate of biomarker change differed by race and ethnicity, sex, and APOE ɛ4 status.ResultThe initial mean age of individuals was 73.1 (SD = 5.6) years, 419 (69%) were women, and 25.9% carried APOE e4. Individuals self‐identified as non‐Hispanic White (28.9%), non‐Hispanic Black (25.4%), or Hispanic (45.7%). Compared to controls, individuals with incident MCI had an accelerated increase in P‐tau181 (b = 0.029, p = 0.048), NfL (b = 0.027, p = 0.010), GFAP (b = 0.029, p = 0.002), and a more rapid decrease in Aβ42/Aβ40 ratio (b = ‐0.015, p = 0.033). Individuals with incident AD also had a greater increase in NfL (b = 0.041, p = 0.027) and GFAP (b = 0.04, p = 0.006) than controls. Hispanics had a faster increase in NfL (b = 0.033, p = 0.002) and GFAP (b = 0.034, p<0.001), and Black participants had a faster increase in NfL (b = 0.028, p = 0.023), compared to Whites. Neither sex nor APOE ɛ4 genotype affected rates of biomarker changes.ConclusionLongitudinal change in plasma biomarkers may have clinical utility, since incident MCI and AD are accompanied by faster increases in P‐tau181, NfL, and GFAP, and a faster decrease in Aβ42/ Aβ40 ratio. The trajectories of AD biomarker change may also vary by race and ethnicity.
History of infections is associated with smaller hippocampal volume in older women
Authors: Ukraintseva Svetlana , Popov Vladimir , Duan Hongzhe , Yashkin Arseniy , Akushevich Igor , Arbeev Konstantin , Yashin Anatoliy 
Published: December 2023

AbstractBackgroundAccumulating evidence suggests that infections can play a major role in Alzheimer’s disease (AD), however, mechanism is unclear as multiple pathways may be involved. One possibility is that infections might contribute to AD directly by promoting neuronal death and neurodegeneration.MethodWe investigated the relationship between history of infectious diseases (a potential AD risk factor) and brain hippocampal volume, HV (a biomarker of neurodegeneration and AD neuropathology) in a subsample of the UK Biobank participants with respective information. Infectious disease diagnoses were based on ICD‐10 codes. The left/right HV was measured by the MRI. Analysis of variance (ANOVA) and Welch Two Sample t‐test were used to examine the statistical significance.ResultThe HV was significantly lower in older women (age 65+) with prior history of infections, compared to the same age women without such history (p‐value = 0.014 and 0.029, for the left and right HV, respectively). The effect size increased with age, and this increase was faster for the right vs. left HV. The difference in HV between male subjects with and without history of infections was not statistically significant.ConclusionIn this study, prior infections were significantly associated with the lower left/right HV in women aged 65+, which supports the role of infectious diseases in neurodegeneration and preclinical AD pathology in females. The effect size increased with age, in line with the increase in brain vulnerability to stressors due to aging. The faster increase for the right vs. left HV might indicate that females’ verbal memory declines faster with age compared to visual‐spatial memory, following the exposure to infectious disease, which deserves further investigation. The observed sex differences may reflect a higher vulnerability of the female brain to infection‐related factors, which in turn might contribute to the higher risk of AD in women compared to men.
APOE ε4 and cognitive networks: Centrality of episodic memory nodes in patients with mild cognitive impairment
Authors: De Marco Matteo , Wright Laura M , Valera‐Bermejo Jose Manuel , Ferguson Cameron E 
Published: December 2023

AbstractBackgroundThe literature based on univariate models does not lead to unequivocal conclusions on the effects of APOE variability on cognition. We thus hypothesised that the impact of APOE‐ε4 on cognitive functioning can be reliably captured by graph‐theory.MethodCognitive datasets were extracted from the National Alzheimer’s Coordinating Center’s database. After the application of stringent exclusion criteria, 16,173 participants with a known APOE ε3ε3/ε4ε3/ε4ε4 genotype were retained: 8,118 controls, 3,482 MCI patients and 4,573 AD‐dementia patients. ε3ε3 individuals were classified as “non‐carriers”, while ε4ε3/ε4ε4 individuals were tagged as “carriers”. Two independent sub‐cohorts were defined based on the version of the battery used to characterise cognitive profiles. Pairwise Markov random‐field models of cognitive functioning were constructed in “R” using the “qgraph” package, following published methodological guidelines. Nine cognitive nodes were established, and partial correlations were run to calculate the statistical strength of all node‐to‐node edges. This was regularised via the LASSO penalty‐imposing method, to control graph sparsity. Differences in global and nodal metrics between ε4 carriers and non‐carriers were tested via permutation‐based Network Invariance Tests. These analyses were run separately in each sub‐cohort and within each diagnostic status. “Expected Influence” was analysed as the centrality metric of interest, to assess how influential each node is within its network.ResultA significant APOE‐dependant effect emerged from the analysis of the Logical‐Memory nodes in MCI patients in both sub‐cohorts. While non‐carriers showed equal centrality in immediate and delayed recall, the latter was significantly less central among carriers. These findings were replicated in the sub‐groups of sole amnestic‐MCI patients (n = 2,971), were independent of differences in network communities, clinical severity or other demographic factors. No effects were found in the other diagnostic groups or in global network metrics.ConclusionAPOE‐ε4 influences nodal properties of cognitive networks when patients are clinically classified as MCI. Our findings expand this area of knowledge by characterising the statistical effect of the ε4 allele in terms of its differential impact on immediate and delayed recall, and how this results in specific network effects. The study of the wider cognitive network can complement univariate approaches in characterising the effects of risk factors.