bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial Similarity of Person‐Specific Resting State Topography in Cognitive SuperAgers
Authors: Diamond Bram R , Martersteck Adam , Rogalski Emily J 
Published: January 2025

AbstractBackgroundMemory decline in late life is a common hallmark of aging, yet SuperAgers are individuals age 80+ with episodic memory performances at least as good as cognitively average 50‐to‐60‐year‐olds. Recent work, combining anatomical and functional MRI, has shown the precise boundaries of large‐scale resting state networks vary at the individual level. Further, the use of person‐specific rather than standard parcellations has led to more behaviorally meaningful associations, and has not been explored in SuperAgers. The current project examines whether the topography of person‐specific resting state networks differ between SuperAgers and older‐aged controls (OACs).MethodsTwenty‐four SuperAgers and 16 OACs were included in the study. SuperAger/OAC phenotype was determined based on measures of episodic memory, executive functioning, verbal fluency, and picture naming across two visits, separated by at least 18 months. Person‐specific network parcellations were derived for each participant using their first visit resting state fMRI connectivity, constrained by anatomical priors, with a Multi‐Session Hierarchical Bayesian Model (MS‐HBM; Kong et al., 2021). Sørensen‐Dice spatial similarity coefficients (Dice) were calculated to determine the within‐group spatial similarity of each network. Dice was defined as the number of overlapping vertices between two participants’ network segmentation, multiplied by two, and divided by the sum of vertices in both network segmentations. Dice was calculated for each participant compared to all other within‐group participants and averaged to create a Dice score per participant per network. Dice scores for each of the 17 person‐specific networks were compared between SuperAgers and OACs using Mann‐Whitney tests, Bonferroni‐corrected.ResultsDemographics did not differ significantly between groups. Person‐specific network topography varied between participants (Figure 1). SuperAgers had significantly lower Dice scores than OACs in six of 17 networks (Figure 2; p‐value = 0.0029).ConclusionCompared to OACs, SuperAgers demonstrated greater within‐group variability in resting state network topography. Greater spatial variability may reflect unique patterns of functional or structural topography that support SuperAgers’ exceptional memory abilities. Future investigations will include further examination of the functional connectome of SuperAgers, leveraging the precision approach employed here.
Clinical utility of 123I‐Ioflupane SPECT striatal binding for evaluating parkinsonism: a retrospective study of a dementia with Lewy bodies cohort
Authors: Maly Emily F , Leverenz James B , Lapin Brittany , Li Yadi , DiFilippo Frank A 
Published: January 2025

AbstractBackgroundThis study set to determine if 123I‐ioflupane SPECT striatal binding ratio (SBR) correlated with parkinsonian symptoms measured on Movement Disorder Society – Unified Parkinson’s Disease Rating Scale Part III (UPDRS‐III) in a dementia with Lewy bodies (DLB) cohort and if SBR measured at baseline could predict progression of parkinsonian symptoms over 2 years.MethodsThis is a retrospective cohort study using the U.S. Dementia with Lewy Bodies Consortium (DLBC) dataset. Sample group included 54 individuals with probable DLB or mild cognitive impairment with Lewy bodies (MCI‐LB). Participants had baseline 123I‐ioflupane SPECT scan analyzed with DaTQUANT and baseline UPDRS‐III examination; a subset of 25 participants had a 24‐month UPDRS‐III examination. Mean of the left and right SBR Z‐scores for the striatum, putamen, posterior putamen, and caudate were analyzed. A subset of 45 participants had CSF tested with [Amprion] a‐synulcein seed amplification assay (SAA).ResultsMultivariable linear regression models were used to predict 54 participants’ UPDRS‐III at baseline; this showed baseline SBRs are significant predictors of baseline UPDRS‐III scores with the caudate SBR having the strongest correlation (p=0.005). Multivariable linear regression models were used to predict 25 participants’ UPDRS‐III score at 24‐months; this showed baseline SBRs are significant predictors of 24‐month UPDRS‐III scores with the caudate SBR having the strongest correlation (p=0.009). When adjusting for baseline UPDRS‐III scores, SBRs are no longer significant predictors of 24‐month UPDRS‐III scores (p=0.36). When a multivariable logistic regression model was used to predict meaningful worsening in UPDRS‐III from baseline to 24‐months (defined as worsening by = +5 points) the relationship was not significant (AUC=0.53). A sub‐analysis of the 45 participants with a‐synulcein SAA showed that presence a‐synulcein was associated with higher UPDRS‐III scores and lower SBRs.ConclusionFindings reveal a significant relationship between 123I‐ioflupane SPECT SBRs and motor parkinsonism in DLB as measured on UPDRS‐III. In DLB, 123I‐ioflupane SPECT scan, at time of diagnosis, could be used to confirm underlying dopamine deficiency in the context of clinical parkinsonism. Findings suggest baseline 123I‐ioflupane SPECT SBRs do not add value beyond baseline UPDRS‐III in predicting clinical progression of parkinsonism in 2 years.
Joint Contribution of NfL and PSMD for Improved Risk Stratification of VCID
Authors: Luckey Alison M. , Beiser Alexa S , Himali Jayandra J. , Gaona Carlos A. , Zeynoun Joy , Rodriguez Luis A. Mendez , Habes Mohamad , Kautz Tiffany F. , Seshadri Sudha , Aparicio Hugo J. , Satizabal Claudia L 
Published: January 2025

AbstractBackgroundAdvancing therapeutic and prevention strategies for vascular contributions to cognitive impairment and dementia (VCID) warrants identifying novel biomarkers. However, due to the high heterogeneity underlying dementia pathology, a single marker may not fully risk‐stratify for VCID. A blood‐based biomarker of neuroaxonal injury, neurofilament light chain (NfL), and a neuroimaging‐based biomarker of white matter microstructural damage on diffusion weighted imaging, peak width of skeletonized mean diffusivity (PSMD), have been related to worse general cognition and proposed as robust biomarkers for cerebral small vessel disease (cSVD). We investigated the joint contribution of NfL and PSMD for improved specificity/sensitivity to identify persons at risk for VCID.MethodDementia‐free participants from the Framingham Offspring Study with cognitive, neuroimaging, and NfL data were included (N = 969). NfL was measured in plasma, and PSMD was derived from MRI diffusion weighted imaging. Executive function and general cognitive function were assessed from a neuropsychological battery. NfL and PSMD were dichotomized by the top quartile and combined to indicate a high cSVD burden. The high NfL‐PSMD risk category was related to cognitive function using linear regression adjusting for age, age‐squared, sex, education, renal function (eGFR), and total intracranial volume. Additional analyses incorporating amyloid PET uptake in 64 participants were performed to discern Alzheimer’s disease pathology from VCID.ResultHigher NfL‐PSMD was significantly associated with worse executive (Beta±SE, ‐0.06±0.02, p = 0.002) and general cognitive function (‐0.15±0.07, p = 0.02). Additionally, amyloid PET over‐predicted NfL levels in those with PSMD below the median (observedpredicted, 0.06 (0.33)). Although results were not significant (p = 0.15) due to the limited sample, they suggest that amyloid pathology does not explain cSVD burden measured with NfL and PSMD.ConclusionOur findings suggest combining NfL and PSMD can better risk‐stratify those with VCID and poorer cognitive function. This NfL‐PSMD multi‐biomarker has potential to discriminate vascular dysfunction from Alzheimer’s pathology, improving identification of persons better suited for VCID clinical trials. Utilizing a multi‐biomarker approach may improve accuracy for risk stratification of persons bearing covert cerebral vascular injury. Further studies are underway to confirm these findings in larger, diverse samples.
Unravelling the role of subcortical brain volumes in the conversion to dementia: a multi‐cohort analysis
Authors: Rosbergen Mathijs T. , van der Veere Pieter J. , Claus Jacqueline Josephine , Evans Tavia E , Venkatraghavan Vikram , Barkhof Frederik , van Harten Argonde C. , Ikram M. Arfan , van der Flier Wiesje M. , Vernooij Meike W. , Wolters Frank J. 
Published: January 2025

AbstractBackgroundHippocampal volume is an acknowledged biomarker of neurodegenerative disease, including Alzheimer’s disease (AD). However, the relationship between other subcortical brain structures and dementia risk is uncertain and may differ by disease stage. We aimed to assess the prognostic value of subcortical volumes for dementia risk across different disease stages by investigating memory clinic‐based populations and community‐dwelling individuals.MethodWe included 9613 dementia‐free participants from a population‐based cohort (Rotterdam Study [n=5442, MCI:4.2%]) and two memory clinic‐based cohorts (Amsterdam Dementia Cohort [n=1964, MCI:36.1%] and the Alzheimer's Disease Research Centers of NACC: National Alzheimer’s Coordinating Center, funded by NIA/NIH Grant U24 AG072122 [n=2207, MCI:32.7%]). Mean age ranged from 62 to 65 years, and 40 to 61% were women. We performed automated segmentations of the nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus on T1‐MRI using Freesurfer. We determined the association between volumes of each subcortical structure and 5‐year risk of dementia in each cohort, using Cox proportional hazard models adjusted for various confounders and the other subcortical volumes.ResultDuring 5 years of follow‐up, dementia was diagnosed in 371 individuals in NACC, 249 in ADC, and 321 in the Rotterdam Study. Consistently across all cohorts (Figure 1), smaller hippocampal volume was significantly associated with an increased dementia risk, driven by the progression to AD dementia rather than non‐AD dementia. Smaller amygdala volume was associated with an increased dementia risk in both memory clinic cohorts, with similar effect estimates in the population‐based cohort. Smaller thalamic volume was associated with dementia risk only in the population‐based cohort, driven by the progression from normal cognition to dementia (HR: 1.73 [95%CI:1.14‐2.63]), rather than from mild cognitive impairment to dementia (HR 0.83 [0.45‐1.54]). The association between the amygdala and dementia risk was similar for AD and non‐AD dementia in both memory clinic‐based populations, while in the population‐based cohort the association was only evident in progression to AD dementia.ConclusionVarious subcortical structures play a role in the conversion to dementia. While the hippocampus and amygdala show consistent associations across populations, variation between populations for the thalamus and accumbens suggest differences in their role with underlying pathophysiology and disease stage.
Links between cognition and multivariate brain white matter differences in individuals with family history of Alzheimer's disease
Authors: Tremblay Stefanie A , Spreng R. Nathan , Wearn Alfie , Alasmar Zaki , Pirhadi Amir , Tardif Christine L , Chakravarty M. Mallar , Villeneuve Sylvia , Leppert Ilana R , Carbonell Felix , Medina Yasser Iturria , Steele Christopher J , Gauthier Claudine J 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is thought to result from a complex cascade of events involving several pathological processes. Recent studies have reported alterations in white matter (WM) microstructure in the early phase of AD, but WM remains understudied. We used a multivariate approach to capture the complexity and heterogeneity of WM pathologies and its links to cognition and AD risk factors in a more holistic manner.MethodThe MRI data of 134 cognitively unimpaired older adults with a family history of AD from the PREVENT‐AD cohort were analysed. Diffusion‐weighted imaging and multi‐echo magnetization transfer, proton density and T1‐weighted data were used to compute several WM metrics (see Fig. 1b‐c). We used the Mahalanobis distance (D2) to summarize the MRI metrics into a single score, indicative of the degree a voxel’s microstructure differs relative to a reference. Voxel‐wise D2 was computed for each subject relative to the group average of all other subjects using the MVComp tool and D2 maps were residualized for age (Fig. 2). Partial Least Squares (PLS) analyses were then performed to relate WM D2 with cognition (RBANS) and AD risk factors, separately in each sex.ResultIn males, there was only one significant latent variable (LV 1). There were extensive brain WM regions associated with this LV pattern: higher white matter D2, was associated with higher BMI, lower total cholesterol (likely due to lower HDL) and worse cognitive performance in all cognitive domains except attention (Fig. 2a‐b). In females, only the first LV was significant. Higher D2 in several WM tracts, including the inferior and superior longitudinal fasciculus, and the parahippocampal cingulum, was associated with lower education, and worse cognitive performance in all cognitive domains except attention and visuospatial construction. Higher WM D2 was also associated with several metabolic risk factors in females including higher SBP, higher BMI, higher glycated hemoglobin (HbA1c) and lower cholesterol (Fig. 2c‐d).ConclusionThe different patterns of associations observed suggest there are sex‐specific risk profiles associated with WM microstructure differences in this population of older adults at risk of AD. The WM tracts affected in each sex were also associated with specific cognitive profiles.
Left frontoparietal control network connectivity moderates the effect of amyloid on cognitive decline in preclinical Alzheimer’s disease
Authors: Boyle Rory , Shirzadi Zahra , Coughlan Gillian T , Seto Mabel , Properzi Michael J , Klinger Hannah M , Townsend Diana L , Yuan Ziwen , Scanlon Catherine E , Jutten Roos J , Papp Kathryn V , Amariglio Rebecca E , Johnson Keith A , Rentz Dorene M , Chhatwal Jasmeer P. , Sperling Reisa A , Schultz Aaron P , Buckley Rachel F 
Published: January 2025

AbstractBackgroundStronger default mode (DMN) and bilateral frontoparietal control network (FPCN) resting‐state functional connectivity are associated with reduced ß‐amyloid (Aß)‐related cognitive decline in cognitively unimpaired older adults, who were predominantly Aß negative. This suggests that these networks might support cognitive resilience in the face of early AD pathology but it remains unclear whether these effects are apparent in preclinical AD. We investigated whether left‐FPCN, right‐FPCN, and DMN connectivity moderated the effect of Aß on cognitive decline using a large multi‐site dataset from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study.MethodCognitively unimpaired participants with elevated Aß on screening amyloid‐PET (n = 1,062, mean age = 71.9 years, 60% women, see Table1), underwent functional MRI (3T) at baseline. We obtained connectivity estimates of the left‐FPCN, right‐FPCN, and DMN using template‐based rotation (Fig.1). Cognition was measured using the Preclinical Alzheimer’s Cognitive Composite (PACC; average follow‐up including open‐label extension period = 280 weeks [SD = 115]). We examined three‐way linear and quadratic interactions between functional connectivity and Aß burden with time in mixed effects models (model 2 = DMN, 3 = left‐FPCN, 4 = right‐FPCN). 1. PACC∼time + covariates×time 2‐4A. PACC∼FC×time + covariates×time 2‐4B. PACC∼FC×Aß×time + covariates×time 2‐4C. PACC∼FC×Aß×time + FC×Aß×time2 + covariates×time Covariates included age, education, APOEe4 status, ICV‐adjusted gray matter volume, treatment group (Solanezumab vs placebo), and head motion. We modeled random effects of intercept and slope for each participant and included scanner as a random effect.ResultThe three‐way quadratic interaction of connectivity and Aß burden with time was statistically significant for the left FPCN (p‐value corrected for multiple comparisons = .047, Fig.2), with a moderate effect size. That is, stronger left FPCN connectivity was associated with less cognitive decline in those with elevated Aß. The pattern of effects were similar, but not statistically significant once all covariates were included, for the right FPCN and DMN.ConclusionIn a very large multi‐site clinical trial dataset, individuals with stronger left FPCN connectivity showed reduced Aß‐related cognitive decline. This effect was specific to the left‐FPCN, in line with previous cross‐sectional findings. Our finding demonstrates that this protective effect of left FPCN connectivity can be observed in preclinical AD.
Longitudinal Regional Flortaucipir Profiles in Preclinical Alzheimer’s Disease: Evaluation using A4 phase 3 trial with Solanezumab
Authors: Kotari Vikas , Holdridge Karen Chilcott , Yaari Roy , Schultz Aaron P , Johnson Keith A , Aisen Paul S. S. , Sperling Reisa A , Sims John R. , Shcherbinin Sergey 
Published: January 2025

AbstractBackgroundThe A4 Study (NCT02008357) was a multicenter, randomized, double‐blind, placebo‐controlled phase 3 trial, assessing the safety and efficacy of solanezumab in preclinical Alzheimer’s Disease (AD). We previously reported on the baseline regional flortaucipir (FTP) profiles in this study1. Here, we present the longitudinal tau profiles.MethodsFTP scans were acquired at baseline and weeks 84,168, and 240. All FTP scans were analyzed using an established image processing pipeline to evaluate global[2] and regional tau patterns in template space. Global tau level was measured using an AD‐signature weighted volume‐of‐interest (VOI) (tauSUVR)2. Regional tau uptake and accumulation were measured in 3 prespecified composite regions representing tau pathology in preclinical AD, ordered by hypothetical pathologic spreading: 1) “early” (amygdala, entorhinal cortex, parahippocampal gyrus), 2) “middle” (fusiform, inferior, and middle temporal, and inferior parietal gyri), and 3) “late” (lateral occipital, posterior cingulate, superior parietal, and supramarginal gyri). We evaluated associations between baseline amyloid burden, age, sex, APOE e4 carriage and longitudinal tau change within placebo group.ResultsAt baseline, a lower tau signal was observed generally in regions identified later in pathologic sequences. Longitudinal change was region‐ and visit‐specific. In both treatment groups, the early and middle regions showed the largest change from baseline at Week 84; the middle region showed the largest change at Weeks 168 and 240; the global assessment changes were smaller than the early and middle regions at each time point (figure 1; tables 1&2) and a majority of participants remained global “tau negative”3(tauSUVR<1.11 figure 2) throughout the trial. Higher baseline global amyloid level was most strongly associated with increased tau PET signal in the prespecified middle composite region at all timepoints (figure 3).ConclusionA multi‐regional composite VOI staging scheme was developed using baseline tau profiles and prespecified for analysis of longitudinal tau PET images. Results confirmed that cognitively unimpaired, amyloid positive participants demonstrate larger tau accumulation in the early and middle than late and neocortical regions. The early composite performed better at detecting tau accumulation initially and middle composite at later timepoints. This multi‐regional staging scheme appears to be useful to characterize tau progression in this preclinical AD cohort.
Diffusion‐Weighted MRI Brain Connectivity Assessment of Healthy Aging Trajectories in Marmosets
Authors: Szczupak Diego , Bhik‐Ghanie Rebecca , Zhang Bei , Papoti Daniel , Campos Vinicius , Dubberley Lauren R , Hitchens T Kevin , Yeh Fang‐Cheng , Schaeffer Lauren K Hayrynen , Carter Gregory W , Rizzo Stacey J Sukoff , Schaeffer David J , Silva Afonso C 
Published: January 2025

AbstractBackgroundThe common marmoset (Callithrix jacchus) is an important animal model in neuroscience and neurological diseases (e.g., Alzheimer’s disease ‐ AD), as they present primate‐specific evolutionary features such as an expanded frontal cortex. We established a new consortium with funding support from the National Institute on Aging to generate, characterize, and validate MArmosets as Research MOdels of AD (MARMO‐AD). This consortium develops and studies gene‐edited marmoset models carrying genetic risk for AD, comparing them against wild‐type aging marmosets from birth throughout their lifespan, using non‐invasive longitudinal assessments. Here, we aimed to characterize the structural cortical connectivity (white matter fibers) in a population of marmosets across the lifespan to establish healthy aging trajectories against which we will compare our genetically engineered marmoset models of AD.MethodWe performed high‐resolution (500 µm isotropic) diffusion‐weighted MRI (dMRI) in a cohort of 19 marmosets (13 males, 6 females) aged 8 to 89 months using a dedicated 9.4T 30cm bore MRI scanner (Bruker BioSpin Corp, Billerica). The animals were anesthetized under isoflurane and maintained at normal physiological conditions. The brain images were aligned and registered to the Marmoset Brain Mapping (MBM) V2 template. The brain was segmented using the MBM white matter atlas, and voxel‐based morphology (VBM) was used to quantify regional white matter volume in the left and right hemispheres. Furthermore, we used DSI STUDIO to perform the whole‐brain tractogram, calculate network‐based statistics (NBS), and correlate them with age.ResultWe measured decreases in the NBS properties of Assortativity, Small Worldliness, and Hierarchy with age but an increase in Efficiency, showing the maturation processes of white matter across development. We are actively working on increasing our sample size to identify the entire marmoset age trajectory and its impact on white matter connectivity.ConclusionOur work is the first to thoroughly describe the healthy aging trajectories of the marmoset brain, a valuable model for age‐related neuropathologies (e.g., AD). This research will establish normative baselines for changes in marmoset brain connectivity with aging that will be used to evaluate our genetically engineered marmoset models of AD, which is the goal of the MARMO‐AD consortium.