bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Relationship of Neuropsychiatric Symptoms and ADRD Pathologies
Authors: Bacci Julia R. , Rudolph Marc D. , Mielke Michelle M. , Craft Suzanne , Bateman James R. , Lockhart Samuel N. 
Published: January 2025

AbstractBackgroundNeuropsychiatric symptoms (NPS) in the Alzheimer’s Disease (AD) clinical spectrum are common, yet the pathological underpinnings are unclear. Prior research has been inconsistent, attributed in part to concomitant co‐pathologies. Additionally, prior modeling approaches have disregarded the distributional properties of right‐skewed NPS data and utilized predominantly racially homogenous cohorts. Thus, we examined the relationship between NPS and markers of vascular injury and neurodegeneration using generalized linear models (GLM) in a diverse community‐based sample. Of additional interest was whether these relationships differed by cognitive status or race.MethodsWe evaluated cross‐sectional relationships of brain white matter hyperintensity volume (WMHv) and plasma neurofilament light chain (pNfL) to NPS (NPI‐Q total severity scores) in 588 Wake Forest ADRC Clinical Core study participants. Analyses included participants with consensus diagnoses of cognitively unimpaired (CU; N = 348) and mild cognitive impairment (MCI; N = 240). WMHv and pNfL were log‐transformed prior to model entry. GLMs included age, sex, education, race, and cognitive status as covariates and pathologies as predictor variables. Secondary models included aforementioned covariates and pathology by (a) cognitive status and (b) race interaction terms to investigate how these associations differed.ResultsWMHv was not significantly associated with NPS (N = 561; ß = 0.203; p = 0.053); further, we did not observe an interaction between cognitive status and WMHv (N = 561; ß = ‐0.055; p = 0.800). However, a significant race by WMHv interaction on NPI‐Q was demonstrated (N = 561; ß = ‐0.414; p = 0.016). In White participants, elevated WMHv was significantly related to elevated NPS (N = 434; ß = 0.325; p = 0.006); whereas in Black/African American participants elevated WMHv was significantly related to lower NPS (N = 119; ß = ‐0.239; p = 0.049). pNfL was not significantly associated with NPS (N = 506; ß = 0.149; p = 0.576). A significant pNfL by cognitive status interaction on NPI‐Q was found (N = 506; ß = ‐1.055; p = 0.029; Figure 2), where elevated pNfL was related to elevated NPS in MCI participants (N = 198; ß = 1.656; p = 0.004) but not CU participants (N = 308; ß = ‐0.316; p = 0.260). However, we did not observe an interaction between race and pNfL (N = 506; ß = 0.185; p = 0.678).ConclusionConsistent with previous work we demonstrate associations of pNfL and WMHv with NPS. Future analyses with this cohort will examine additional biomarkers, including amyloid‐beta and tau measured in CSF, plasma, and PET.
Association of APOE/TOMM40 Haplotypes and Limbic System White Matter Microstructure in Black and White Individuals
Authors: Mooney Katelyn Elizabeth , Archer Derek B. , Hohman Timothy J. , Sathe Aditi , Kadiri Ose , Barnes Lisa L. , Deters Kacie 
Published: January 2025

AbstractBackgroundAPOE is in linkage disequilibrium with the length of poly‐T repeats at the rs10524523 (‘523) locus of the TOMM40 gene. APOE‐e3 is associated with short (S) and (VL) variants of ‘523 in white and Black individuals. In white individuals, APOE‐e4 is associated with the long (L) ‘523 variant, but is associated with ‘523‐S, ‘523‐L, and ‘523‐VL variants in Black individuals. Black e3‐’523‐S carriers have faster rates of cognitive decline while Black e4‐’523‐S carriers have slower rates of cognitive decline. Little is known about the association of these haplotypes with white matter integrity. This study aims to determine the association between APOE/TOMM40 haplotypes and white matter microstructure (WMM) in tracts important for cognition and risk of AD.MethodsData comes from participants without cognitive impairment from the Rush Memory and Aging Project and the Minority Aging Research Study who self‐identified as non‐Hispanic white (N=500) and non‐Hispanic Black (N=144). WMM was measured using diffusion MRI (dMRI). dMRI was preprocessed using PreQual and microstructural metrics were calculated in DTIFIT and MATLAB. Data was harmonized using Longitudinal ComBat. We assessed free‐water (FW; higher values are abnormal) and FW‐corrected fractional anisotropy (FAFW‐corr; lower values are abnormal) in five limbic tracts that are associated with AD: the inferior longitudinal fasciculus, cingulum, fornix, inferior temporal gyrus, and uncinate fasciculus. The effect of 0, 1, or 2 copies of ‘523‐S on FW and FAFW‐corr was assessed using linear regression models, controlling for age, sex/gender, and education.ResultsWhite e3/e3 participants with two copies of ‘523‐S had lower FAFW‐corr in the cingulum (ß=‐0.006, SE=0.003, P=0.031) and inferior temporal gyrus (ß=‐0.007, SE=0.003, P=0.042) (Table). Black e4+ participants with one‐‘523‐S had lower FW in cingulum (ß=‐0.024, SE=0.01, P=0.020) and inferior longitudinal fasciculus (ß=‐0.0304, SE=0.013, P=0.026) (Table).ConclusionsThis is the first study examining APOE/‘523 variation on WMM in Black participants, and the first to examine this association using FW‐corrected metrics. These results support prior findings that ‘523‐S copy‐number is deleterious in White‐e3/e3 participants, but protective in Black‐e4+ participants. These findings suggest a differential effect by racialized background of APOE on brain microstructural integrity in older adults.
Aging, beta‐amyloid deposition, and brain functional connectivity decline
Authors: Yi Dahyun , Chumin Evgeny J. , Byun Min Soo , Cha Woo‐Jin , Ahn Hyejin , Kim Yu Kyeong , Kang Koung Mi , Sohn Chul‐Ho , Risacher Shannon L. , Sporns Olaf , Nho Kwangsik , Saykin Andrew J. , Lee Dong Young 
Published: January 2025

AbstractBackgroundChanges in brain network organization are influenced by aging. Accumulation of amyloid‐beta (Aß) and neurodegeneration in the neocortex are also expected to alter neuronal networks. Therefore, we examined the relationship between aging and brain functional connectivity (FC), as well as the effect of brain Aß on this relationship.MethodResting state functional MRI (rsfMRI) from 594 participants spanning age and diagnostic severity of AD from the Korean Brain Aging Study for the Early Diagnosis and Prediction of AD (KBASE) was preprocessed as previously described in studies conducted at the Indiana AD Research Center (Chumin 2021, 2023). Cortical FC data from 200 regions (Schaefer 2018) grouped into 7 canonical resting state networks (RSN; Yeo 2011) was used to compute a network segregation measure (ratio of within‐ to between‐network connectivity (Chan 2014); here used as an index of FC) across all RSNs. Additionally, a subsample of older participants was classified as Aß positive or negative based on global amyloid in Centiloid units (Klunk 2015).ResultIntrinsic network connectivity was reduced with increasing age beginning in young adulthood (Fig, left), resulting in a dedifferentiated, or less segregated, network architecture (t = ‐4.79, p = 0.000002). The relationship between age and network segregation was significant in the Aß negative group (t = ‐4.09, p = 0.00005); however, such relationship was not found in the Aß positive group (Fig, right). Fitted Aß values were significantly different (Welch Two Sample t‐test: p < 2.2e‐16).ConclusionThis preliminary study elucidates age‐related decline of brain FC, quantified as network segregation, from young adulthood to late‐life, wherein RSN communication become less coherent, manifesting as a degeneration of FC structure. Such age‐related reduction pattern of brain connectivity appears disappear under the presence of pathological Aß deposition in brain.
Robust Symptomatic Subtypes of Typical Alzheimer's Disease Characterized by Differential Neuropathological Patterns and Functional Decline
Authors: Zalzale Hussein , Ferreira Pamela C.L. , Lemaire Peter , Madeiros Marina Scop , Soares Carolina , Bellaver Bruna , Bauer‐Negrini Guilherme , Lussier Firoza Z , Povala Guilherme , Ferrari‐Souza João Pedro , Abbas Sarah , Aguzzoli Cristiano Schaffer , Rodrigues Matheus Scarpatto , Rohden Francieli , Amaral Livia , Leffa Douglas Teixeira , Oliveira Markley , Tudorascu Dana , Tissot Cécile , Rahmouni Nesrine , Ashton Nicholas J. , Blennow Kaj , Hong Chang Hyung , Son Sang Joon , Rosa‐Neto Pedro , Cohen Ann D , Lopez Oscar L. , Villemagne Victor L , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is classically viewed as a predominantly amnestic syndrome, with other cognitive and neuropsychiatric symptoms (NPS) being non‐integral associations. Emerging Evidence suggests that within typical AD, these symptoms are core features from the onset.MethodsWe employed K‐modes clustering on 2483 cognitively impaired (CI) individuals (CDR >= 0.5), excluding participants diagnosed with atypical AD, non‐amnestic MCI, or CI due to non‐AD dementias from five cohorts: TRIAD, ADNI, BICWALZS, OASIS‐III, and Pittsburgh. Cluster‐specific clinical and pathological profiles were established through comparison with 2670 cognitively unimpaired (CU) participants across plasma biomarkers (Ptau‐181, Ptau‐217, GFAP, Nfl, AB42/40 ratio) and neuroimaging (amyloid and tau PET, white matter hyperintensity, MRI‐derived degeneration maps). The rate of functional decline, modeled by increase in CDR‐SB, was assessed using a Cox‐proportional hazards model and a linear mixed‐effect model.ResultsWe identified five distinct clinical phenotypes within typical AD: 'Pure Amnestic' (30.2%), 'Linguistic‐Hyperactive' (14.7%), 'Visuospatial‐Affective' (14.7%), 'Frontal' (27.6%), and 'Global' (19.3%) (Figure 1, Figure 3). These phenotypes demonstrated consistency regardless of amyloid status or cohort. Each phenotype exhibited a unique neuropathological signature and a distinct pattern of neurodegeneration (Figure 2). A critical aspect of our findings is the differential rate of functional decline across these phenotypes. The 'Pure Amnestic' group showed the slowest decline, followed by 'Linguistic‐Hyperactive' (HR = 1.39; B = 0.2), 'Visuospatial‐Affective' (HR = 2.13; B = 1), 'Frontal' (HR = 2.23; B = 1.53), and the 'Global' phenotype showing the fastest decline (HR = 3.52; B = 2.66) (Figure 2, Figure 3).ConclusionOur results challenge the concept of “typical” AD by uncovering five robust clinical phenotypes with divergent neuropathological profiles and clinical characteristics. These results mark an important advancement toward personalized medicine in the landscape of emerging AD treatments.
Choosing wisely: Evaluating reference regions for improved longitudinal 18F‐AV‐1451 tau PET consistency
Authors: Saguer Isaac Llorente , Oxtoby Neil P 
Published: January 2025

AbstractBackgroundPositron emission tomography (PET) can facilitate precise spatial and temporal measurement of Alzheimer’s disease pathology in the brain. The default quantification measure is the standardized uptake value ratio (SUVR) of radiotracer uptake in a target region of interest normalised by uptake in a reference region. Evaluations of new radiotracers commonly assess test‐retest consistency in scans with no pathological changes, but rarely question the SUVR paradigm. Notably, even the Centiloid/CenTauR scales depend on SUVR. This study aims to quantitatively assess the impact of different reference regions on 18F‐AV‐1451 tau‐PET scans.MethodWe analysed SUVR data from 399 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) having at least two 18F‐AV‐1451 tau‐PET scans (199 CU, 149 MCI, 51 AD). Across multiple target regions of interest and common reference regions we compared SUVR longitudinal consistency for this radiotracer using median percent test‐retest (PTRT), average intraclass correlation coefficient (ICC), and average within‐subject coefficient of variation (WSCV). Target regions considered: cerebellum, brainstem, eroded subcortical white‐matter. Reference regions considered: inferior cerebellum grey‐matter, composite (cerebellum, eroded subcortical white‐matter, brainstem), and a data‐driven linear combination of these regions. Four‐fold cross‐validation stratified by diagnostic group was used to train the linear model (optimizing the three metrics factored), using 75% of data for training and 25% for testing.ResultTable‐1 presents test‐retest performance across reference regions. The inferior cerebellum gray‐matter was the worst‐performing reference region with only 2.2% test‐retest consistency. The composite reference region produced 26% lower (better) PTRT, 33% lower (better) WSCV and 5% higher (better) ICC. Our data‐driven linear combination of reference regions outperformed inferior cerebellum gray‐matter by 32% PTRT, 37% WSCV and 3% ICC.ConclusionLongitudinal consistency varied based on the reference region chosen. The composite reference region and the linear model both outperformed the inferior cerebellum grey‐matter. This study emphasizes the importance of selecting an appropriate reference region for accurate assessment and tracking of Alzheimer’s disease pathology in 18F‐AV‐1451 tau PET scans, in line with other studies (Young et al. 2021).
Comparing de‐facing software MiDeFace and mri_reface according to privacy protection and effects on downstream measurements
Authors: Schwarz Christopher G. , Prakaashana Carl M. , Kremers Walter K. , Gunter Jeffrey L. , Senjem Matthew L. , Vemuri Prashanthi , Kantarci Kejal , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. 
Published: January 2025

AbstractBackgroundSeveral programs are available for automatically “de‐facing” brain images. These are designed to prevent the potential use of face imagery to re‐identify research participants. Previous works have compared available software and mri_reface is frequently among the top methods. The “Minimally Invasive DeFacing of MRI images” (MiDeFace) program was more recently added to FreeSurfer, but minimal validation of MiDeFace has been published.MethodWe ran mri_reface 0.3.3 and MiDeFace 7.3.2 on two datasets: A) 207 participants with face photographs and 3D T1‐weighted and 3D T2‐weighted‐FLAIR MRI from the Mayo Clinic Study of Aging (all unimpaired, Siemens); and B) 300 participants from ADNI3 with 3D T1‐weighted MRI (50 unimpaired + 50 with clinical AD, from each of 3 vendors). For dataset A, we tested the rate at which Microsoft Azure face recognition matched each participant’s photographs with the correct MRI, comparing unmodified images, those from mri_reface, and those from MiDeFace. For dataset B, we compared measured regional brain volume and cortical thickness from original vs. de‐faced images with SPM12, FreeSurfer 7.4.1, and the FSL‐UK Biobank pipeline. For both datasets, images were visually rated to assess removal of the face and retention of brain tissue.ResultAutomated face recognition match rates were lower with mri_reface (17/207 8.2%) than with MiDeFace (24/207 11.6%), indicating stronger identity protection with mri_reface, but both were greatly reduced vs. unmodified images (203/207 98.1%). Example images with both programs are shown in Figure 1. From visual ratings (Table 1), rates of complete success (modification of the entire face while retaining the entire brain) were much higher with mri_reface, but the great majority of failures from MiDeFace were subtle and occurred in relatively less recognizable face regions. The effects of both programs on downstream imaging measurements (Figure 2) were small and very comparable, but MiDeFace was favored mildly for SPM12 and for FSL, while mri_reface was more favored for FreeSurfer.ConclusionAltogether, mri_reface more reliably removed the complete face, leading to smaller rates of potential re‐identification (8.2% vs 11.6%). Effects on downstream image measurements were small and comparable with both methods.
Cerebrovascular and Metabolic Alterations in a Mouse Model of Familial Alzheimer’s Disease Carrying the Notch3 C456R Mutation
Authors: Letica Leila , Choi Sang‐Ho , Dubberley Lauren R , Szczupak Diego , Park Jung Eun , Schaeffer David J , Silva Afonso C 
Published: January 2025

AbstractBackgroundVascular pathology associated with small vessel disease (SVD), such as microinfarcts and microbleeds, are common in elderly populations and significant contributors to cognitive impairment and dementia. Autosomal dominant cerebral arteriopathy with subcortical infarctions and leukoencephalopathy (CADASIL), caused by mutations in the Notch3 gene, is the most prominent inheritable SVD, with a common etiology of subcortical strokes and dementia. This study aimed to investigate additive or synergistic effects of CADASIL‐related vascular alterations and familial Alzheimer’s disease (FAD)‐related amyloid pathology on cerebral metabolism of glucose and disease progression in a novel FAD‐CADASIL mouse model.MethodsWe bred 5xFAD mice to CADASIL mice carrying the Notch3 C456R mutation to create the novel FAD‐CADASIL mouse model. To investigate progressive alterations in cerebral glucose metabolism, 18F‐FDG was delivered to awake mice via a tail vein injection, with an average dose of 18.5 MBq. The mice were fasted for a minimum of 2 hours before 18F‐FDG administration. PET and CT acquisitions were completed after a 30‐minute 18F‐FDG circulation period using a Bruker Si78 instrument. Static datasets were analyzed for standard uptake values relative to the brainstem (SUVr) and corrected for glucose levels (SUVglc). Statistical tests included unpaired t‐tests and 1‐ & 2‐way ANOVA using GraphPad Prism 9.ResultsWhole brain SUVr values were decreased across age groups in 5xFAD, Notch3C456R, and 5xFAD/Notch3C456R mice compared to age‐matched WT controls. Blood glucose levels collected before ligand injection indicated an age‐dependent decrease in glucose levels across all genotypes. 5xFAD/Notch3C456R mice showed distinct reductions in whole brain SUVglc values compared to aged‐matched 5xFAD and Notch3C456R mice. ROI analysis of 3‐month‐old 5xFAD/Notch3C456R shows significantly decreased SUVglc levels in several cortical regions such as the striatum, cortex, hippocampus, hypothalamus, and thalamus when individually compared to WT, 5xFAD, and Notch3C456R mice (Figure 1).ConclusionWe observed a significant synergistic effect of CADASIL on accelerating increased amyloid accumulation and reducing cerebral glucose metabolism in the novel FAD‐CADASIL mouse model. These results provide further key evidence of an association between cortical vascular pathology and Alzheimer’s Disease progression. This research was funded by NIH/NINDS grant RF1NS117486.
Differential network‐based propagation of cortical thinning in atrophy subtypes in non‐demented individuals
Authors: Lorenzini Luigi , Tranfa Mario , Pieperhoff Leonard , ten Kate Mara , Pontillo Giuseppe , Alves Isadora Lopes , Shekari Mahnaz , Altomare Daniele , den Braber Anouk , Ritchie Craig W , Boada Mercè , Marquié Marta , Vandenberghe Rik , Luckett Emma S. , Hanseeuw Bernard J , Visser Pieter Jelle , Schöll Michael , Frisoni Giovanni B. , Birck Cindy , Mett Anja , Stephens Andrew W. , Gismondi Rossella , Buckley Christopher , Farrar Gill , Jessen Frank , Gispert Juan Domingo , Mutsaerts Henk‐Jan , García David Vállez , Wink Alle Meije , Collij Lyduine E. , Barkhof Frederik 
Published: January 2025

AbstractBackgroundDifferent patterns of atrophy exist in the dementia stage of AD. However, little is known about the heterogeneity of atrophy patterns and the mechanisms that drive subsequent propagation of the disease in the preclinical stages.MethodFrom the AMYPAD‐PNHS cohort, we included a total of 1323 non‐demented individuals, including 1094 amyloid‐negative, and 229 amyloid‐positive participants (Table 1). Gray matter thickness in 100 regions of interest was measured using FreeSurfer. Global cortical amyloid burden was derived from amyloid PET scans in Centiloids (CL). Individuals were assigned to atrophy subtypes based on cortical thickness measures using Non‐Negative Matrix Factorization (Figure 1). Multinomial regression models were used to study differences between subtypes in age, sex, global CL and APOE E4 carriership. Linear regression models were used to investigate the effect of time on atrophy within each subtype. Coordinated deformation models (Figure 1, Shafiei et al. 2023) were used to estimate network‐based thickness changes in each region, by multiplying the effect of time in connected regions by the strengths of their connections. Connectivity strength was based on templates of functional, structural and morphometric similarity networks, and allowed us to evaluate differential mechanisms. Significance was tested using a permutation approach.ResultsThree significant subtypes of regional GM atrophy were identified:‘limbic predominant’, ‘typical AD’, and ‘diffuse cortical’ (Figure 2). Individuals assigned to the limbic predominant subtype were significantly older, while the typical AD subtype had more APOE E4 carriers compared to the others (all p<0.001). Both limbic predominant and typical AD subtypes had higher CL compared to the diffuse cortical atrophy subtype (all p<0.001). Significant longitudinal thickness changes per subtype are shown in Figure 2. In the typical AD subtype, all network architectures constrained longitudinal GM changes (p<0.001), while in the diffuse atrophy subtype, propagation was mostly determined by morphometric similarity (p<0.005). No significant prediction model was found for the limbic predominant subtype.ConclusionWe show that atrophy subtypes can already be detected in non‐demented individuals. Progression of atrophy within subtypes is determined by network‐based mechanisms.