bluuebunny/crossref_metadata_2025 huggingface dataset:
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

Background

Alzheimer’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.

Methods

We 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.

Results

We 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).

Conclusion

Our 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

Background

Positron 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.

Method

We 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.

Result

Table‐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.

Conclusion

Longitudinal 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

Background

Several 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.

Method

We 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.

Result

Automated 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.

Conclusion

Altogether, 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

Background

Vascular 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.

Methods

We 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.

Results

Whole 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).

Conclusion

We 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

Background

Different 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.

Method

From 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.

Results

Three 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.

Conclusion

We show that atrophy subtypes can already be detected in non‐demented individuals. Progression of atrophy within subtypes is determined by network‐based mechanisms.
White matter abnormalities in association with amyloid and tau deposition in a diverse cohort with increased risk for Alzheimer’s disease
Authors: Blujus Jenna K , Rego Eliza , Bica Sarah , Demos Kathryn , Lee Athene KW , Riddle Meghan C. , Wing Rena R. , Salloway Stephen , Maillard Pauline , Fan Audrey P. , Decarli Charles , Vemuri Prashanthi , Lockhart Samuel N. , Baker Laura D , Landau Susan M. , Oh Hwamee
Published: January 2025

Background

Neuritic plaques with fibrillar beta‐amyloid (Aß) peptides and tau‐protein neurofibrillary tangles, hallmark features of Alzheimer’s disease (AD) pathology, have been concomitantly associated with white matter (WM) integrity loss, while a unique effect of each pathology on WM integrity in a more demographically diverse population remains unknown.

Method

To examine the degree to which each pathology affects WM integrity in a more diverse non‐demented cohort, Aß and tau PET, diffusion‐weighted imaging (DWI), and cognition (memory and executive function composites) were examined from the U.S. POINTER neuroimaging participants (N = 608; age = 68.34±5.2; 61.8% females; 29% Aß+) and a subset of Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants (N = 291; age = 72.85±7.3; 50% females; 39% Aß+) (Table). Aß‐positivity was determined using tracer‐specific standardized cut‐offs. Tau SUVR was estimated for each Braak stage. For WM integrity, voxel‐based GLMs were applied to FSL‐processed fractional anisotropy (FA) maps using Braak stage tau SUVR and Aß‐positivity status, along with covariates of age, sex, and b‐value profiles.

Result

In U.S. POINTER, independent from Aß‐positivity status, greater tau burden in Braak stages I and II was related to lower FA across the tracts including the superior longitudinal fasciculus, fornix (cres), corpus callosum, and anterior thalamic radiation (Figure). Average FA from supra‐threshold clusters for Braak I and II significantly predicted executive function but not episodic memory. No association between FA and tau burden in Braak stages III/IV or V/VI was found. In the ADNI sample, greater tau burden in Braak I was related to lower FA mostly in left inferior longitudinal fasciculus and left uncinate fasciculus, while negative associations with FA became more diffuse with tau load in Braak III/IV and V/VI. Average FA from supra‐threshold clusters significantly predicted both episodic memory and executive function scores. Across both samples, after accounting for tau burden in each Braak stage, there were no association between Aß‐positivity status and WM integrity.

Conclusion

Distinct associations between tau burden, WM integrity, and cognition were found across the studies, indicating greater impact of early tau burden on WM integrity in U.S. POINTER, accounting for Aß‐positivity status. Factors contributing to the distinct associations across studies need further investigation.
Longitudinal multicenter head‐to‐head harmonization of tau‐PET tracers: an overview of the HEAD study cohort
Authors: Lussier Firoza Z , Povala Guilherme , Bauer‐Negrini Guilherme , Amaral Livia , Cehula Juli , Fine Devin J , Lemaire Peter , Bloomquist Madeleine , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Rosa‐Neto Pedro , Tudorascu Dana , Jagust William J. , Klunk William E , Baker Suzanne L. , Pascoal Tharick Ali
Published: January 2025

Background

Standardizing tau pathology quantification in vivo is challenged by differences in binding characteristics between tau‐PET tracers. The HEAD study aims to generate a leading, longitudinal head‐to‐head dataset of MK‐6240, Flortaucipir, RO948, and PI‐2620 tau‐PET to harmonize these tracers' outcomes and develop tools allowing for the generalization of findings across large studies and trials. Here, we present current advancements in building the HEAD study cohort and dataset.

Methods

The HEAD study is managed at the University of Pittsburgh. HEAD comprises several sites across the US and Canada in which 620 subjects (young, cognitively unimpaired, mild cognitive impairment, and Alzheimer’s disease (AD)) will undergo tau‐PET with at least two tracers, amyloid‐PET with PiB or NAV4694, MRI, blood collection, and standardized neuropsychological testing at baseline and at 18‐month follow‐up. PET and MRI acquisition parameters are based on ADNI4 protocols and neuropsychological testing employs the NACC Uniform Data Set. The National Centralized Repository for AD serves as the biorepository for blood samples and the Laboratory of Neuroimaging provides a centralized database for imaging and neuropsychological archiving. PET data is reconstructed to maximize cross‐scanner harmonization and is processed uniformly similarly to ADNI4 PET.

Results

In one year of active enrollment (Jan 2023‐Jan 2024), 362 participants were enrolled at six active sites; over 80% of participants completed neuropsychological testing and MRI, and over 70% completed Flortaucipir, MK‐6240, and amyloid‐PET, with a mean tau‐PET acquisition window of 29.1 days. RO948 and PI‐2620 tau‐PET are additionally acquired in a subset currently including 41 participants (Fig.1). Current HEAD cohort demographics including age, sex, underrepresented populations, and group distributions, APOEe4 carrier status, and amyloid positivity are shown in Fig.2. A case of a subject with AD with all 4 tau‐PET tracers acquired head‐to‐head within 49 days is shown in Fig.3.

Conclusion

The HEAD study represents a continued effort in the optimization of AD imaging biomarkers. Baseline data collection is projected to be completed in 2024; results being generated by multiple groups from this dataset will provide novel and crucial guidance on the use of tau‐PET tracers in research, clinical trials, and prospectively in clinical practice.
Associations between BDNF Val66Met and tau‐PET and episodic memory performance in sporadic AD
Authors: Thomson Diny , Rosenich Emily , Maruff Paul , Lim Yen Ying
Published: January 2025

Background

In the presence of abnormally high amyloid (Aß+), carriage of the brain‐derived neurotrophic factor (BDNF) Val66Met polymorphism Met allele (Met66) is associated with faster clinical disease progression, greater neuronal loss and faster rate of CSF total‐tau and p‐tau181 compared to matched Val66 Aß+ homozygotes. Aß levels are unaffected by carriage of Met66. This suggests reduced neurotrophic support may accelerate Aß‐related neuronal dysfunction and cognitive decline. We aimed to clarify the role of BDNF Val66Met in moderating region‐specific neurofibrillary tangle (NFT) formation in the brain in sporadic Alzheimer’s disease (AD).

Method

Data from 26 Aß+ older adult Met66 carriers and 68 Val66 homozygotes enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were included in the analysis if they had at least one tau‐PET scan, Aß‐PET scan, and neuropsychological assessment available. Participants were not excluded based on disease stage. ANCOVAs were conducted to determine, cross‐sectionally, whether levels of tau‐PET tracer retention at each Braak stage, episodic memory performance (measured on ADNI’s memory composite), and Aß levels differed between Met66 carriers and Val66 homozygotes at the time of their first tau‐PET scan. Aß levels, APOE e4 status, sex, age, baseline diagnosis, and years of education were included as covariates.

Result

Aß+ Met66 carriers showed significantly greater tracer retention in the entorhinal cortex (i.e., Braak 1) compared to Val66 homozygotes (p=.03), with the magnitude of this difference moderate (d=0.39; Table 1). There were no significant differences between Met66 carriers and Val66 homozygotes in tracer retention across all other Braak stages, episodic memory performance or Aß levels (Table 1).

Conclusion

The greater tau‐PET tracer retention in the entorhinal cortex in Met66 carriers may reflect their greater NFT pathology relative to Val66 homozygotes during early stages of AD. This is consistent with previous observations of higher levels of CSF total‐tau and p‐tau181 in Aß+ Met66 carriers, both in sporadic AD and autosomal dominant AD. Together, these findings support the hypothesis suggesting that loss of neurotrophic support, associated with Met66 carriage, may confer greater vulnerability to Aß‐related neurodegeneration compared to Val66 homozygosity.
Utility of plasma p‐tau217 as a secondary outcome for clinical trials across AD continuum
Authors: Ferreira Pamela C.L. , Bellaver Bruna , Povala Guilherme , Aguzzoli Cristiano Schaffer , Ferrari‐Souza João Pedro , Leffa Douglas Teixeira , Lussier Firoza Z , Madeiros Marina Scop , Zalzale Hussein , Rohden Francieli , Soares Carolina , Abbas Sarah , Bauer‐Negrini Guilherme , Karim Helmet T. , Hong Chang Hyung , Roh Hyun Woong , Tudorascu Dana , Karikari Thomas K , Snitz Beth E. , Son Sang Joon , Pascoal Tharick A.
Published: January 2025

Background

Blood‐based biomarkers offer a cost‐effective and simple alternative for clinical use in the context of Alzheimer’s disease (AD). It has already been shown that plasma phosphorylated tau at threonine 217 (p‐tau217) is associated with amyloid (Aß), neurofibrillary tau tangles, and cognitive decline. Longitudinal studies confirmed its ability to track AD progression. Therefore, the aim of this study is to evaluate the potential utility of changes in plasma p‐tau217 as secondary outcome in clinical trials across the AD spectrum.

Method

We included 189 individuals with available plasma p‐tau217 measurements at two time points (24 months follow‐up) across two cohorts:[MYHAT‐NI, population‐based(USA): 51 Cognitively Unimpaired(CU); BICWALZS, memory clinic(South Korea): 135 Cognitively Impaired(CI) individuals], all with baseline Aß‐PET. Plasma p‐tau217 was quantified using the ALZpath assay. We used linear regression to investigate p‐tau217 association with cognitive decline. Effect size was determined by biomarker mean change divided by the standard deviation. We also estimated the sample size required to detect a 25% drug effect on p‐tau217 reduction with 80% power at a significance level of 0.05.

Result

Baseline and longitudinal changes in p‐tau217 were significantly associated with cognitive decline independently of Aß status in both CU and CI individuals (Table 1). Functionally, individuals classified with mild dementia(CDR‐SB>4.5) showed greater and pronounced annual changes in p‐tau217 compared to the other groups (Figure 1A). Notably, Aß+ individuals presented a higher effect size for p‐tau217 changes in both CU(0.79) and CI(0.74) groups, compared to the whole population (Figure 2B). The sample size required for a clinical trial including of Aß+ individuals were 1,276 for CU and 940 for the CI. Cost analysis revealed that in trials recruiting CU Aß+ individuals targeting tau pathology using p‐tau217 as a secondary outcome was 1.5, 3.7, and 3.9 times more cost‐effective than 18F‐MK‐6240 tau‐PET, 18F‐Flortaucipir tau‐PET, and p‐tau181, respectively (Figure 2). Similarly, in trials with CI Aß+ participants, p‐tau217 was 1.5 times less expensive than [18F]‐MK‐6240 tau‐PET, and 3.7 times less than [18F]‐Flortaucipir tau‐PET.

Conclusion

Our results demonstrated that changes in plasma p‐tau217 is associated with cognitive decline across the AD continuum. Furthermore, p‐tau217 shows promise as a secondary outcome in AD clinical trials.
The role of biofluid markers in predicting near‐term cognitive impairment
Authors: Yakoub Yara , Gonzalez‐Ortiz Fernando , Ashton Nicholas J. , Karikari Thomas K , Strikwerda‐Brown Cherie , St‐Onge Frédéric , Ourry Valentin , Schöll Michael , Geddes Maiya R. , Ducharme Simon , Rosa‐Neto Pedro , Soucy Jean‐Paul , Breitner John C.S. , Zetterberg Henrik , Blennow Kaj , Poirier Judes , Villeneuve Sylvia
Published: January 2025

Background

PET biomarkers have proven valuable for identifying cognitively unimpaired (CU) individuals at‐risk of near‐term clinical progression. Given the increasing interest in plasma biomarkers to detect Alzheimer’s pathology, we assessed levels of amyloid (Aß42/40) and tau (p‐tau217 and p‐tau181) biomarkers in plasma (A+T+plasma) in CU individuals as predictors of clinical progression to mild cognitive impairment (MCI). We then repeated these analyses using cerebrospinal fluid (CSF) and PET biomarkers.

Method

We studied 218 participants from the PREVENT‐AD cohort with cognitive follow‐up (mean 5.34 years, range 1–10 years) and plasma biomarkers available while CU. Cognition was assessed annually using the RBANS. Plasma biomarkers were measured using IP‐MS for Aß42/40 and in‐house single molecular arrays for p‐tau217 and p‐tau181. An overlapping 71 participants had Aß42/40 (Mesoscale Discovery assay) and p‐tau181 (Innotest immunoassay) CSF data available, and 135 participants had Aß (18F‐NAV4694) and tau (18F‐florbetapir) PET data. We also performed receiver operating characteristic (ROC) curves to compare the performance of plasma (Aß42/40 and p‐tau217; Aß42/40 and p‐tau181), CSF (Aß42/40 and p‐tau181) or PET (Aß‐ and tau‐PET) biomarkers in predicting progression to MCI. We examined an additional model including only Aß‐PET, given the importance of this technique as a stand‐alone marker for recruitment in anti‐Aß trials.

Result

The proportion who progressed from CU to MCI was 62% in individuals with A+T+plasma217; and 41% with A+T+plasma181; 56% with A+T+CSF181 and 100% with A+T+PET (Figure 1). Cox proportional hazard models indicated a faster progression rate in all A+T+ groups compared with their matched A‐T‐ biomarker groups (Figure 2). Considering longitudinal RBANS scores, all A+T+ groups declined faster than the other groups, except for the plasma181 group. Finally, the PET (Aß and tau‐PET) and CSF models were superior to the plasma or Aß‐PET alone in identifying progressors, with no meaningful difference between the Aß‐PET and the biofluid models (Figure 3).

Conclusion

CU individuals with A+T+ based on plasma biomarkers are at increased risk of cognitive decline and clinical progression. Nevertheless, the proportion who progressed to MCI in individuals classified with plasma was lower than that found using PET. Thus, the latter should remain the gold standard to identify presymptomatic pathological changes.
The Role of ApoE4 in The Acceleration of Tau Aggregation
Authors: Steward Anna , Biel Davina , Roemer Sebastian Niclas , Zhu Zeyu , Pescoller Julia , Wagner Fabian , Gross Mattes , Dichgans Martin , Ewers Michael , Dehsarvi Amir , Brendel Matthias , Franzmeier Nicolai
Published: January 2025

Background

Understanding modulators of Alzheimer's disease’s (AD) progression is crucial for determining optimal treatment windows and targets. Apolipoprotein E e4 (ApoE4), i.e. a key AD risk factor, is associated with earlier tau accumulation at lower Aß levels (Steward et al. 2023), yet, the mechanisms driving this connection remain unclear. Thus, we assessed whether ApoE4 accelerates initial Aß‐related tau secretion measurable in CSF or subsequent tau aggregation as determined via PET (Figure 1A).

Method

We combined cross‐sectional CSF measures of phosphorylated tau (p‐tau181) and Aß‐PET in 287 APOE genotyped non‐demented (cognitively normal [CN]; mildly cognitively impaired [MCI]) ADNI participants. P‐tau181 was adjusted to Aß40 to account for inter‐individual variability in CSF protein concentrations. Using linear regression, we investigated i) whether ApoE4 was related to accelerated Aß‐related p‐tau secretion (i.e., Aß‐PET by ApoE4 interaction on p‐tau181), ii) whether ApoE4 accelerated the p‐tau‐induced fibrillisation of tau (i.e. p‐tau181 by ApoE4 interaction on tau‐PET) and iii) whether regional effects of ApoE4 on p‐tau‐related tau fibrillisation were associated with ApoE4 mRNA expression levels.

Result

ApoE4 did not moderate the relationship between Aß‐PET and p‐tau181 (Figure 1B, p=0.76) but strengthened the effect of p‐tau181 on global Tau‐PET increase (Figure 1C, ß=0.7, p<0.001). At the regional level, this ApoE4 x p‐tau181 interaction on tau‐PET was correlated with regional APOE mRNA expression in CN (Figure 2B, r=0.5, pspin<0.001), but not in MCI (p=0.141), suggesting that ApoE4 drives earliest p‐tau‐induced tau aggregation. Supporting this further, we found that the regional effect of p‐tau181 on Tau‐PET was more strongly correlated with APOE mRNA expression in CN ApoE4 carriers (Figure 2C, r=0.54, pspin<0.001) than in CN non‐carriers (r=0.4, pspin=0.05). Lastly, we confirmed that the effect of Aß on tau aggregation is mediated by p‐tau increases (Figure 1D, ACME: B=0.28; p<0.001; ADE: B=0.206; p=0.008) which is strengthened in ApoE4 carriers (B=0.21, p=0.006).

Conclusion

ApoE4 promotes p‐tau‐induced tau aggregation, particularly in early disease stages and in regions that express high APOE. This suggests that ApoE4 can trigger earlier Aß‐related tau spreading most likely due to facilitated p‐tau induced tau aggregation. This suggests that preventing soluble p‐tau increases may attenuate tau aggregation and therefore dementia.
Support for transmission of tau pathology in humans using individualized epicenters and structural connectomes
Authors: Brown Christopher , Das Sandhitsu R. , Nasrallah Ilya M. , Detre John A. , Yushkevich Paul A. , McMillan Corey T , Wolk David A
Published: January 2025

Background

Population‐based functional connectomes help explain heterogeneity in tau spread in Alzheimer’s disease by demonstrating spread among connected neurons from canonical epicenters. However, if the hypothesis of cell‐to‐cell transmission of tau is correct, individual structural connectomes seeded from individual‐specific epicenters of PET‐tau pathology should improve prediction of regional tau patterns.

Method

86 participants from the Penn Aging Brain Cohort and 158 participants from ADNI with multi‐shell diffusion MRI and AV1451 Tau PET within 18 months of each other were included. A schematic of methods is shown in Figure 1. Tau PET standard uptake value ratios were converted to Tau Pathology Indices (TPI) based on Gaussian‐mixed models. Regions > 2.5 standard deviations above the mean TPI within an individual were used as individualized epicenters, while entorhinal cortex (ERC) was used as a canonical group epicenter. Probabilistic tractography generated individual connectomes and a group connectome in amyloid‐negative participants. Network‐analysis calculated structural connectivity distances from epicenters for each region. Data were re‐arranged by tau pathology rank to average across all participants using each combination of individualized and group epicenters and connectomes. The model of Regional TPI = ß*Distance + e was tested in the training dataset using each of the 4 approaches: 1) Group canonical epicenter and group connectome (GE‐GC), 2) Group canonical epicenter and individual connectome (GE‐IC), 3) Individualized epicenters and group connectome (IE‐GC), and 4) Individualized epicenters and connectomes (IE‐IC). The resulting models were then applied to the validation dataset to predict regional TPI and compare to actual TPI.

Result

The fully individualized model demonstrated a significantly stronger relationship between connectivity and regional tau burden (ß = ‐0.95[‐1.03, ‐0.87]) compared to all other models (Z = ‐5.81, p < .001, Figure 2). When the four trained models were applied to the validation dataset, the fully individualized model explained 80% of regional TPI variance, while the other models explained = 52% (Figure 3).

Conclusion

Individualized structural connectomes and tau epicenters capture the heterogeneity of Alzheimer’s disease and provide strong support for the cell‐to‐cell transmission of tau pathology in vivo.
Metabolic Hyperconnectivity in Underrepresented Individuals with long‐COVID
Authors: Machado Luiza Santos , Silveira Maiele Dornelles , de Bastiani Marco Antônio , Povala Guilherme , Borelli Wyllians Vendramini , Senger Joana Emilia , da Silva Ana Paula Bornes , da Ros João Pedro Uglione , de Mello Guilherme Bastos , Jotz Arthur Viana , Kadan Matheus Fakhri , Peixoto Guilherme G. Schu , Radaelli Graciane , Pascoal Tharick A. , Rosa‐Neto Pedro , Matushita Cristina Sebastião , Soder Ricardo Benardi , Schumacher‐Schuh Artur Francisco , Souza Diogo O. , Lourenco Mychael V , Faria Daniele de Paula de Paula , Coutinho Artur Martins , da Costa Jaderson Costa , de Souza Débora Guerini , Zimmer Eduardo R.
Published: January 2025

Background

Long‐COVID is characterized by persistent symptoms post‐infection with SARS‐CoV‐2. This condition includes neurological manifestations and has been proposed as a potential risk factor for the development of dementia. Individuals presenting with dementia due to Alzheimer's disease have dysfunctional brain metabolism, including metabolic brain network (MBN) hypoconnectivity. However, whether long‐COVID alters brain metabolic architecture remains elusive. Here, we aimed to evaluate the brain metabolic connectivity in a Brazilian cohort of individuals presenting with long‐COVID.

Method

[18F]FDG‐PET images were acquired from 52 community‐dwelling Brazilians above 50 year old. Standardized uptake value ratio (SUVr) parametric maps were processed to a common 8 mm FWHM and generated using the pons as the reference region (Figure 1). We extracted the mean values of regions of interest using the ICBM152 atlas. [18F]FDG‐PET MBNs were constructed using a novel multiple sampling scheme, which assembles a stable group representative MBN based on bootstrap (n = 2000). Adaptive Synthetic Sampling Approach for Imbalance (ADASYN) was used to account for group imbalance and generated the ADA‐MBNs. Graph measures, including density, global efficiency, average degree, and assortativity coefficient were computed. Data were corrected for multiple comparisons using the False Discovery Rate (FDR) method (p<0.05).

Result

41 individuals with long‐COVID and 11 healthy controls (HC) were included (Table 1). We observed that long‐COVID individuals present PET hyperconnectivity in both MBN and ADA‐MBN. (Figure 2a‐b). The long‐COVID group presented increased density, global efficiency and average degree whereas assortativity coefficient were reduced in both MBN and ADA‐MBN.

Conclusion

Our findings showed that individuals with long‐COVID presented a brain metabolic hyperconnectivity, which is supported by increased density and average degree and may indicate a potential compensatory mechanism within the brain. In addition, the increase in global efficiency indicates that the brain of long‐COVID individuals exchanges metabolic information more efficiently, but the decreased assortativity coefficient suggests vertices with different properties connect to each other. Further longitudinal studies should follow these individuals for assessing microstructural and cognitive changes.
Association between Tau and Cognition as a Function of Age
Authors: Ackley Sarah F , Wang Jingxuan , Decarli Charles , Fletcher Evan , La Joie Renaud , Corrada María M. M. , Glymour M. Maria
Published: January 2025

Background

The relationship between tau pathology and cognition as a function of age and whether these relationships are consistent across samples is unknown. A growing number of studies now perform positron emission tomography with tau ligands (tau‐PET), making it possible for an improved understanding of the dynamics of tau and cognition in relation to other biomarkers.

Method

We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (ages 55‐90) and The 90+ Study (Table 1) to cover a broad age range. We examined the association between region‐specific tau uptake by composite Braak stage and cognitive outcomes at the visit at which tau‐PET was performed (ADNI) or the closest visit (90+). We examined two cognitive outcomes: the mini mental status exam (MMSE) and clinical dementia rating sum of box scores. Spearman‐rank correlation coefficients between tau‐PET standardized uptake value ratios (SUVRs) with cerebellar cortex normalization and cognitive outcome are calculated for four distinct age ranges in ADNI: <60, 60‐70, 70‐80, and 80+ and among the 90+ study participants. Associations adjusted for age and age‐squared, race/ethnicity, number of APOE‐e4 alleles, educational attainment, and gender are determined using bootstrapped linear regression.

Result

The association between region‐specific tau uptake by composite Braak stage and cognition appears consistent for ages 60‐80 (figures 1 and 2), with worse cognition with higher tau. Over age 80, tau does not appear to be associated with cognition. Based on point estimates, some associations appear to be reversed over age 80 in ADNI, which is not the case in the 90+ study, although these differences between cohorts are not statistically significant.

Conclusion

Tau‐PET association varies with age, becoming less reliably associated with cognition over age 80. This is likely due to increased incidence of co‐occurring pathologies and selective survival. Associations may further depend on features of the source population.
Characterization of pulsations in the brain and cerebrospinal fluid using ultra‐high field magnetic resonance imaging
Authors: de Almeida Bruno , Martins Tiago Amaro , Wu Minjie , Wilckens Kristine A , Minhas Davneet S , Ibinson James W , Aizenstein Howard J , Santini Tales , Ibrahim Tamer S
Published: January 2025

Background

Brain fluid flow plays a crucial role in maintaining brain health by eliminating potentially harmful waste products like amyloid‐beta and tau [1‐2]. This process is potentially facilitated by pulsations in the perivascular space, influenced by the neurovascular unit and autonomic nervous system, which may vary in brain diseases such as Alzheimer’s disease (AD) [3‐4]. Using a 7 Tesla MRI scanner and ultrafast echo‐planar imaging (EPI), we developed a non‐invasive neuroimaging methodology to characterize the in‐vivo frequency and amplitude responses of pulsations of cerebrospinal fluid (CSF) flow.

Method

Brain images from six volunteers were acquired using a 7T MRI Scanner and an in‐house developed 16‐channel Tic‐Tac‐Toe transmit array with a 32‐channel receive coil. The human‐connectome EPI multiband MR sequence was optimized to present a real‐time visualization of the CSF flow in the brain. For the first volunteer, two axial and one sagittal slices were obtained, while whole‐brain coverage was acquired for the remaining volunteers, where the acquisition was divided into 19 slabs, each consisting of 3 axial slices. A spectral analysis based on Fast Fourier Transform (FFT) was conducted for the whole brain and grey matter, white matter, and CSF regions.

Result

Figure 1 presents the processed axial and sagittal slices acquired from the first volunteer, demonstrating the presence of a periodic variation of the CSF signal. Figure 2 presents the identification of peaks in the spectrum acquisitions of whole‐brain segments for one volunteer, which exhibited similar frequencies, magnitudes and bandwidths among different volunteers. Quantitative results of this analysis are summarized in Table 1.

Conclusion

This project developed a real‐time visualization of CSF pulsations based on a non‐invasive ultrafast EPI obtained with a 7T MRI scanner. The identification of similar frequency peaks (around 0.3, 0.8, 1.1, 2.3 and 3.1 Hz) and magnitudes among healthy volunteers suggests its potential as a feasible biomarker. Future work will examine this technique’s potential to identify changes in brain fluid dynamics associated with AD progression and pathology. Funding: NIH R01AG063525, R01MH111265, University of Pittsburgh CRC’s RRID:SCR_022735.

References:

• Nedergaard, 2013

• Xie et al., 2013

• Peng et al., 2016

• Ramanathan et al., 2015
Development of AI‐4‐AD tools for evaluation and prognosis of AD conversion: multi‐branch network and multi‐task deep learning algorism
Authors: Han Liang , Pang Ran , Ren Qing , Pu Xiujuan , Liu Yuan , Tan Yuanfan , Yang Qing X
Published: January 2025

Background

AD prevention and early interventions require tools for evaluation of people during aging for diagnosis and prognosis of AD conversion. Since AD is a complicated continuum of neurodegenerative processes, developing of such tools have been difficult because it needs longitudinal and multimodal data which are often complicated and incomplete. To address this challenge, we are developing AI4AD framework using ADNI data.

Method

As shown in Fig. 1, we used the multimodal features of subjects in the initial four time points to predict the disease status after 1.5 years. The informative feature set with available multi‐modal data (MRI, PET and cognitive score (CSs)), is extracted as a multivariate time series. Then, a multi‐scale local temporal attention network (MCLAN) is constructed to extract corresponding deep features from three categories of multivariate time series respectively. Furthermore, a set of statistical features are extracted from multivariate the time series. Subsequently, fusion of selected deep features, statistical features and background knowledge (demographics, CSF, genetics feature) at baseline are performed using a DL feature network. Finally, AD and CSs predictions are realized utilizing multi‐task DL algorism with Adam optimization algorithm and the five‐fold cross‐validation method. 190 CN subjects, 347 MCI subjects and 20 AD subjects were selected according to the first visit diagnosis from TADPOLE database (Table 1a). The longitudinal data for training and ground truth of AD conversion are shown in Table 1(b).

Result

The accuracy (ACC), accuracy (PRE), recall (REC) and F1 score of the proposed AD prediction method in the AD classification were 93.57%, 93.55%, 93.68%, and 93.59%, respectively, which is greatly improved the predictive ability of those by the conventional methods (Table 2). In addition, the root mean square error (RMSE) on the CSs prediction of CDRSB, ADAS11, ADAS13 and MMSE are 0.5863, 0.5238, 0.4747 and 0.5417 respectively.

Conclusion

Our DL method consolidates multi‐modal medical information at different visits to predict the disease's progression, which greatly improved AD prognosis from those using traditional DL algorithms (CNN, LeNet and ResNet). The AI4AD framework proposed here can also be tailored to other diseases with similar data characteristics.
Short‐term Sirolimus Treatment Restores Hippocampus and Caudate Volumes and Global Cerebral Blood Flow in Asymptomatic APOE4 Carriers Compared with Non‐carriers
Authors: Flemister Abeoseh , Xing Xin , Overschmidt Jessica , Cassani Joanne , Green Stefan J. , Beversdorf David Q. , Woods Carter , Grinstead John W. , Altes Talissa A. , Lin Ai‐Ling , Govindarajan Maalavika
Published: January 2025

Background

Apolipoprotein e4 allele (APOE4) is the strongest genetic risk factor for late‐onset Alzheimer’s disease (AD). Compared with non‐carriers, cognitively normal APOE4 individuals have shown brain atrophy and lower cerebral blood flow (CBF) decades before AD pathological and clinical symptoms appear. The goal of the study is to determine if using Sirolimus, an FDA‐approved mTOR inhibitor, could restore the brain volumes in structures related to cognitive functions and global CBF (gCBF) for asymptomatic APOE4 carriers compared with non‐carriers.

Method

The study was performed at the University of Missouri. Low dose Sirolimus (1 mg/day) was given for 4 weeks to three middle‐aged, cognitively normal APOE4 carriers (F:M = 2:1) and two female APOE3 individuals (45‐65 yrs; MOCA > 27). Oral swabs were used to determine APOE status. 3T MRI‐based structural MPRAGE and T1‐weighted images, and pseudo‐continuous arterial spin‐labeled (PCASL, 1.7×1.7×4mm resolution) were acquired at baseline (pre‐treatment) and Post‐Sirolimus (the end of treatment). FreeSurfer 7.4 was used to automatically generate segments for volumetric analysis and PCASL images were analyzed via MANGO software for perfusion weighted gCBF.

Result

APOE4 carriers had significantly increased Caudate and Hippocampal volumes (Fig. 1A) and gCBF (Fig. 1B) after 4 weeks of Sirolimus treatment. These differences were not found in the non‐carriers (APOE3 participants). The quantitative data is shown in Table 1. It also shows that APOE4 carriers had significantly lower Hippocampal volume and gCBF at baseline compared with that of APOE3 participants (indicated by “**”), and Sirolimus tends to restore the values to closer to those of the non‐carriers. No side effects were observed, and no changes in blood glucose and HbAc1 levels were found in all the participants.

Conclusion

We show that short‐term Sirolimus treatment can effectively restore brain volumes and gCBF for asymptomatic APOE4 carriers. Specifically in the caudate and hippocampus, which play many roles integral in normal cognitive functioning including memory, learning, and emotional regulation, has considerable atrophy in AD. The findings imply that Sirolimus may be useful and effective to mitigate or prevent AD developments for asymptomatic APOE4 carriers.