bluuebunny/crossref_metadata_2025 huggingface dataset:
Data‐driven progression patterns of Aβ, tau, α‐synuclein and vascular pathology in a clinical population
Authors: Mastenbroek Sophie E. , Collij Lyduine E. , Vogel Jacob W. , Young Alexandra L. , Strandberg Olof , Smith Ruben , Palmqvist Sebastian , Mattsson‐Carlgren Niklas , Barkhof Frederik , Ossenkoppele Rik , Hansson Oskar
Published: January 2025

Background

With the development of disease modifying therapies targeting specific pathologies, accurate in vivo biomarkers have become increasingly important for disease classification. Recently, tests for neuronal a‐synuclein (Lewy body) pathology have become available, complementing pre‐existing tests for Alzheimer’s disease (AD) pathology (Aß and tau fluid and PET biomarkers) and vascular disease (MRI). Here, we aimed to identify and characterize data‐driven pathology‐based subtypes using these biomarkers.

Method

We included 1677 subjects from a prospective memory clinic cohort (BioFINDER‐2; age[mean±SD]=68.5±12.1; female=50.3%) ranging from cognitively unimpaired (CU) to dementia and including a variety of clinical diagnoses. We applied the data‐driven Event‐Based Subtype and Stage Inference (SuStaIn) model to dichotomized biomarkers of Aß‐pathology (CSF‐Aß), tau pathology (tau‐PET), neuronal a‐synuclein pathology (CSF‐a‐synuclein seeding aggregation assay) and vascular burden (MRI white matter lesions) to determine whether different biomarker sequences emerge within a clinical cohort based on the presence of different brain pathologies. Further, regional atrophy patterns (MRI) were included in the models.

Results

Four disease‐trajectories best explained the data; 998 subjects with a confident assignment (mean probability=70%) were classified as “AD” (44.0%), “Mixed AD and Vascular” (15.9%), “Vascular” (22.9%), or “a‐synuclein” (17.2%) based on early‐stage pathology (Figure‐1). 579 subjects were not classified and grouped as “No subtype” (mainly biomarker‐negative). The “Vascular” trajectory demonstrated early‐stage central and global atrophy, while “a‐synuclein” exhibited atrophy in late stages (Figure‐1). Subjects in “Vascular” had higher levels of vascular risk factors and were more often APOE‐e2 carriers. Subjects in “Vascular” and “a‐synuclein” were older and more frequently male, while those in “AD” and “Mixed” more frequently had a dementia diagnosis and APOE‐e4 carriership (Table‐1). Compared to unclassifiable subjects, “AD”, “Mixed”, and “a‐synuclein” showed faster widespread longitudinal Aß accumulation and “AD” and “Mixed” demonstrated faster widespread longitudinal tau accumulation. “AD” and “Mixed” declined faster in global cognition over time compared to “Vascular” and “a‐synuclein” and “Mixed” and “a‐synuclein” in attention compared to “Vascular” (Figure‐2).

Conclusion

In a heterogenous clinical population, we identified four common pathology‐based disease trajectories resembling established clinico‐pathological relationships. Future analyses will compare disease‐patterns on longitudinal biomarkers. Disease classification might contribute to personalized medicine approaches in trial and clinical settings.
Comparison of [18F]MK6240 and [18F]Flortaucipir standardized uptake values (SUVs): the HEAD study
Authors: Tissot Cécile , Tsai Hsin‐Yeh , Tudorascu Dana , Lussier Firoza Z , Rahmouni Nesrine , Servaes Stijn , Therriault Joseph , Stevenson Jenna , Gordon Brian A. , Pascual Belen , Lowe Val J. , Soleimani‐Meigooni David N. , Oh Hwamee , Klunk William E , Rosa‐Neto Pedro , Jagust William J. , Pascoal Tharick Ali , Baker Suzanne L.
Published: January 2025

Background

Differences between on‐ and off‐target retention characteristics between [18F]MK6240 and [18F]Flortaucipir (FTP) complicate the harmonization across tracers. Our objective here was to separate the impact of the reference region by evaluating correlations between [18F]MK6240 (MK) and [18F]FTP standard uptake values (SUVs).

Method

Participants (Figure 1, n=90) received an amyloid‐β (Aβ) PET scan ([11C]PIB or [18F]NAV4694) and two tau‐PET scans: [18F]MK (90‐110 minutes post‐injection) and [18F]FTP (80‐100 minutes post‐injection). For all PET scans, the individual frames were realigned, averaged, and co‐registered to a Freesurfer 7.1‐segmented T1‐MPRAGE. SUVs were calculated in the reference region (inferior cerebellar gray), on‐target regions (entorhinal cortex, hippocampus, Braak III, Braak IV, Braak V, Braak VI) and off‐target regions (caudate, pallidum, putamen, thalamus, cerebellar white matter, choroid plexus, meninges, eroded white matter). We examined correlations between [18F]MK and [18F]FTP SUV values as a function of Aβ status, as well as their associations with age.

Result

All correlations (Figure 2) were significant at p<0.001. The interaction with Aβ status was significant for hippocampus, BraakIII‐V and the metatemporal region. In Aβ+ participants, [18F]FTP and [18F]MK6240 have similar SUVs in on‐target regions with a slope close to 1 except for in hippocampus and Braak VI. However, [18F]FTP SUVs, on average, were greater than [18F]MK SUVs in Aβ+ and Aβ‐ subjects in the reference region and all off‐target regions except for meninges, and in Aβ‐ subjects in the on‐target regions. Age correlated with [18F]FTP SUVs in Aβ‐ subjects in all regions (except the reference region, Braak VI and meninges) and [18F]MK SUVs in putamen and pallidum, but this correlation was only significant (p<0.01) when young and old subjects were included.

Conclusion

Despite [18F]MK’s higher affinity for tau and SUVR dynamic range being twice that of [18F]FTP, the SUVs in on‐target regions are similar. The higher [18F]FTP signal in the reference region appears to be the contributing factor to the lower dynamic range. The higher [18F]FTP signal in on‐target regions for Aβ‐ subjects may reflect the presence of off‐target signals in these subjects. Taking off‐target signals into account should improve correlations between the two tracers, especially when measuring the earliest deposition of tau.
Unraveling the Early Trajectory of Cortical Tau Accumulation Using 18F‐MK6240
Authors: Dore Vincent , Krishnadas Natasha , Bourgeat Pierrick , Leuzy Antoine , Feizpour Azadeh , Cox Timothy , Huang Kun , Haeberlein Samantha Budd , Fripp Jurgen , Villemagne Victor L , Rowe Christopher C.
Published: January 2025

Background

Tau PET is instrumental in tracking the longitudinal progression of Alzheimer’s disease (AD). 18F‐MK6240 is a high affinity tracer targeting the 3R/4R paired helical filaments of tau in AD. We aimed to evaluate the early phase of the natural progression of tau accumulation using 18F‐MK6240.

Method

231 participants: 100 cognitively unimpaired (CU) Aß‐ (Centiloid<25CL), 58 CU Aß+, 73 cognitively impaired Aß+ (41 with mild cognitive impairment (MCI) and 32 with dementia) from the AIBL cohort were followed‐up with 18F‐MK6240 PET over one to four years (median 2.2years). Meta‐Temporal CenTauR (CTR) were generated using CapAIBL and CU CL<15, N = 120 and AD (typical AD tau pattern, MMSE>24, CL>50 & age<75, N = 39) as 0 and 100CTR anchored points. Abnormal level of tau was defined at 2 standard deviations above the CU Aß‐ (13CTR). Linear ordinary differential equations (ODE) were employed to model the mean natural history of CTR based on tau accumulators (CTR>13 or CTR rate>0) only. Given the limited numbers of individuals with CTR>100, our analysis concentrated on the early phase of tau accumulation (CTR<100, N = 204).

Result

Figure1A illustrates a linear relationship between the average and the rate of CTR, with a R of 0.72. Tau accumulation spanned from 0.5CTR/yr at 13CTR to 12.2CTR/yr at 100CTR, with a standard deviation of the residuals at 2.4CTR/yr. Figure1B displays the individual’s trajectories projected on the ODE model. We estimated that, on average it takes 15.1 (CI:[12.6‐17.9]) years for an individual crossing 13CTR to reach 100CTR.

Conclusion

Longitudinal 18F‐MK6240 is a robust tool for estimating natural progression of tau accumulation. Our findings indicate that it typically takes around 15 years to reach the tau levels associated with mild AD once tau starts aggregating in the neocortex. These findings shed light into the initial stages of cortical tau accumulation, relevant for early diagnosis and therapeutic interventions in AD.
Plasma N‐terminal tau fragment is associated with cognitive status and AD biomarkers of tau and neurodegeneration in older adults
Authors: Rao Yiwen , Ostaszewski Beth L. , Anderson Amirah K. , Shirzadi Zahra , Liu Lei , Yang Hyun‐Sik , Chhatwal Jasmeer P. , Selkoe Dennis J. , Schultz Stephanie A. ,   ADNI
Published: January 2025

Background

The emergence of blood‐based biomarkers offers a cost‐effective and less invasive alternative to established neuroimaging and cerebrospinal fluid biomarkers. Newly developed fluid biomarkers, including N‐terminal tau fragment (NT1), have shown promise for identifying individuals at risk for Alzheimer’s disease (AD). Evidence has shown NT1 may be more abundant than full‐length tau across the AD continuum and has high sensitivity and specificity to separate cognitively normal (CN) individuals from those with mild cognitive impaired (MCI) and AD in discovery and replication cohorts. Here we quantify plasma NT1 in a large, well‐characterized cohort and examine the association between plasma NT1 and cross‐sectional clinical and biomarkers measures.

Methods

Seven hundred and seventeen individuals enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) who have plasma NT1, Aß‐PET, MRI, and clinical (Clinical Dementia Rating; CDR) measures were included in this study (Table 1). NT1 was assessed using Quanterix Simoa HD‐X platform. PET, MRI, clinical, and other plasma measures were derived using previously described procedures in ADNI. Linear regressions were performed to assess the cross‐sectional association of NT1 with clinical and biomarkers measures, after adjusting relevant covariates.

Results

NT1 levels were elevated in cognitively impaired (MCI/AD; CDR>0) relative to CN (CDR=0) individuals (p=0.008, Figure 1A). Specifically, NT1 is elevated in the MCI group (CDR=0.5, MCI vs Aß‐ CN group: p=0.005), but not the AD group (CDR>0.5, AD vs all other groups: p’s >0.206, Figure 1B). NT1 was associated with plasma phosphorylated (p)Tau‐181 (p=1.27x10‐9, Figure 2A) and plasma neurofilament light chain (NfL; p=5.68x10‐6, Figure 2B) but not hippocampal volume (p=0.239).

Conclusion

Plasma NT1 differentiated CN from MCI/AD individuals and was elevated particularly in the early symptomatic phase of disease. Plasma NT1 was associated with plasma markers of tau and neurodegeneration. Together these results suggest that plasma NT1 may be a useful biomarker of AD‐related tau pathology and neurodegeneration.
Longitudinal association between synaptic dysfunction and Alzheimer's disease pathology in preclinical Alzheimer's disease
Authors: Ourry Valentin , Valdez Alfonso Fajardo , Soucy Jean‐Paul , Ashton Nicholas J. , Nilsson Johanna , Brinkmalm Ann , Zetterberg Henrik , Blennow Kaj , Breitner John C.S. , Poirier Judes , Villeneuve Sylvia
Published: January 2025

Background

Synapse loss in Alzheimer’s disease (AD) is correlates closely with cognitive impairment. Recent evidence suggests that synapse loss is promoted by amyloid‐beta, leading in turn to the spread of tau pathology. We sought to assess: 1) the association in positron emission tomography (PET) between several cerebrospinal fluid (CSF) synaptic biomarkers and amyloid and tau burden, as well as their annual change; and 2) the potential clinical utility of these synaptic biomarkers in preclinical AD.

Methods

Mass spectrometry assays quantified cerebrospinal fluid (CSF) markers of synaptic dysfunction (GAP43, SYT1, SNAP25 and Neurogranin) on 75 older adults (age 67.1 ± 4.8 years, 69.3% female) from the PREVENT‐AD cohort. These persons also had longitudinal amyloid ([18F]‐NAV4694) and tau ([18F]‐AV1451) PET scans performed over approximately 4.5 years. All were cognitively unimpaired (CU) at baseline, but 19 developed mild cognitive impairment (MCI) during follow‐up. We examined: 1) the association between these synaptic dysfunction biomarkers and global Aß and entorhinal tau burden as well as their annual change, adjusting for age and sex; and 2) synaptic biomarker differences across those with Aß at baseline vs. those who subsequently developed such pathology, and between individuals who remained CU vs. those who developed MCI during follow‐up. Analyses were considered significant at p=0.05/5=0.01 to account for multiple comparisons.

Results

Amyloid burden was positively associated with increased SNAP25long, while tau burden was associated with all 5 synaptic biomarkers (Figure 1). No association was found between these markers and amyloid and tau annual change. GAP43 and SNAP25 differed in Aß‐ and Aß+ groups but showed no difference across amyloid accumulators’ groups (Figure 2). Finally, MCI individuals had higher SNAP25long and GAP43 concentration than CU individuals (Figure 3).

Conclusions

GAP43 and SNAP25, being markers associated with neuronal growth and synaptic vesicle fusion, appear closely related to amyloid and tau burden, but only at baseline, even in preclinical AD. These biomarkers of synapse loss appear also to have clinical relevance, with differences observed in MCI compared to CU individuals. Future studies should explore these biomarkers, alongside pathology reduction, as potential targets for AD prevention to confirm these preliminary findings.
Genetic Analysis of an Amyloid PET‐Negative Autopsy‐Confirmed Alzheimer's Pedigree
Authors: Talozzi Lia , Peña‐Tauber Andrés , Jensen Tanner D. , Wilson Edward N. , Young Christina B. , Stewart Ilaria , Cobos Inma , Vallejo Kristen , Hefti Marco M , Guen Yann Le , Williams Kennedy , Vossler Hillary , Gorzynski John , Andreasson Katrin I. , Mormino Elizabeth , Ashley Euan , Greicius Michael D
Published: January 2025

Background

Alzheimer's disease (AD) is the most common form of dementia. Neuropathologically, AD stands out as a mixed proteinopathy. Beta‐amyloid and tau biomarkers can now add in‐vivo support to the AD diagnosis. Rarely, a patient with AD confirmed at autopsy may have a negative amyloid PET. Here we describe a pedigree in whom the index case was amyloid PET‐negative. We performed genetic sequencing of two affected siblings to identify a set of candidate single nucleotide variants (SNVs) and structural variants (SVs) associated with disease and rare in healthy older controls from several large genetic databases.

Method

We performed long‐read sequencing (LRS) to comprehensively evaluate both SNVs and SVs. The index case, an APOE3/E4 male, developed memory trouble at 68 that progressed to probable AD at 72. Notably (Figure 1) his amyloid‐PET scan, which was confirmed to be of high technical quality, was negative. His tau PET scan was positive and his plasma Abeta42/40 was in the expected range for Stanford AD patients. His family history is extensive and suggestive of an autosomal dominant pattern of late‐onset AD (Figure 2). The patient's sister was diagnosed with AD at 62. We filtered their shared heterozygous SNVs keeping those with a minor allele frequency < 0.01 in gnomAD and that were not present in any ADSP healthy controls (HC) over 70y.o. (N=19771;62.1%females;81±6.4y.o). Shared SVs were kept as candidates if they were not seen in any Stanford LRS HC (N=95;59%females;72±1.5y.o.)

Result

Neuropathological analysis revealed that both siblings met the A3B3C3 criteria for AD and had cerebral amyloid angiopathy. Among rare mutations on genes expressed in the brain (Table 1), a novel missense in ADNP (Activity‐Dependent‐Neuroprotector‐Homeobox), and a 267bp deletion on TET1 (Tet‐Methylcytosine‐Dioxygenase) were identified. The 3426bp insertion on ATP8A2 (ATPase‐Phospholipid‐Transporting‐8A2) was the longest, rare insertion found. Additionally, a large duplication (∼20Kbp) and inversion (∼160Kbp) were observed.

Conclusion

This study highlights an unusual AD pedigree and emphasizes the potential utility of LRS in identifying causal SNVs and SVs. In future work we plan to perform additional amyloid stains to understand why the index case PET was amyloid‐negative. We are also assessing additional family members to improve our ability to identify a causal mutation.
Data‐driven analysis of 10,361 amyloid‐PET scans from the IDEAS study reveals two primary axes of variation
Authors: Giorgio Joseph , Mundada Nidhi S , Blazhenets Ganna , Mejía‐Perez Jhony Alejandro , Schonhaut Daniel R. , Carrillo Maria C. , Hanna Lucy , Gatsonis Constantine , March Andrew , Apgar Charles , Siegel Barry A. , Hillner Bruce E , Whitmer Rachel A. , Jagust William J. , Rabinovici Gil D. , La Joie Renaud
Published: January 2025

Background

The variability in the regional distribution of Aß‐PET signal and its relation to clinical features is debated. We used data‐driven approaches to uncover heterogeneity in cortical Aß‐PET signal from a large representative sample collected through the IDEAS study.

Methods

We analysed cross‐sectional Aß‐PET collected from 10,361 patients with MCI or mild dementia scanned in 295 PET facilities using one of the 3 FDA‐approved tracers. Central image processing resulted in template‐space SUVR images (reference: whole cerebellum) and centiloid (CL) values. Spatial independent component analysis was used to decompose SUVR volumes into 40 independent components. After excluding noise components, participants’ scores were extracted for each of the remaining 11 grey matter (GM) components describing cortical and subcortical binding. K‐means clustering was used on these GM component scores to assign each participant to different Aß‐PET clusters based on GM binding (Figure1).

Results

Three informative clusters of PET binding were estimated. Cluster 1: Aß‐(n = 4729, CL mean = 2±23) with low GM binding, and two Aß+ clusters; Cluster 2(n = 2484, CL mean = 76±34) and Cluster 3(n = 3148, CL mean = 86±32). Subtracting average SUVR of Clusters 2 and 3 showed they differed along a posterior‐anterior gradient with Cluster 2 showing an occipital predominant pattern. Principal component analysis conducted on the GM scores confirmed two dominant axes of variation separated the clusters, a Aß‐ to Aß+ axis and, an anterior‐posterior axis (Figure2). Statistically significant but weak differences were observed between the two Aß+ Clusters (2 vs. 3); Visual Read (positive: 95% vs. 92%); Clinical Stage (dementia: 47% vs. 41%); Age (76.9±6.4 vs. 75.9±6.2), however, most clinical variables showed no differences (Figure3a). 48 ADNI participants with Aß‐PET and post‐mortem neuropathology data (11 Female, Age mean = 79.7±7.4, PET‐Death mean = 2.3±1.7years; Aß‐CL mean = 71.2±55.5; APOE4(0/1/2) = 22/21/5; Diagnosis(CN/MCI/AD) = 6/8/32) were applied to the model fit on IDEAS data. Qualitatively, no differences in neuropathology were observed between the two Aß+ Clusters (Figure3b).

Conclusion

Data driven classification of Aß‐PET reveals two primary axes reflecting Aß load and anterior‐posterior binding, with the later not clearly related to clinical or pathological variation. Future work will apply new data to this model and investigate if this spatial variation in Aß‐PET is related to longitudinal changes in pathology.
A clock model of regional tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer's disease
Authors: Schonhaut Daniel R. , Insel Philip S. , Soleimani‐Meigooni David N. , Zeltzer Ehud , Windon Charles , Maiti Piyush , Yballa Claire , Zhang Jiaxiuxiu , Mundada Nidhi S , Shankar Ranjani , Amuiri Alinda , Koeppe Robert A. , Dickerson Bradford C. , Carrillo Maria C. , Apostolova Liana G. , Rabinovici Gil D. , Joie Renaud La
Published: January 2025

Background

The timing of tau‐PET accumulation and cognitive decline in sporadic early‐onset Alzheimer’s disease (eoAD, age‐at‐onset<65) has not been established and is needed to optimize tau‐PET as an outcome measure in clinical trials. Here we leverage large‐sample, longitudinal data from the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS) to model tau‐PET accumulation in three regions relative to cognitive decline.

Method

Longitudinal [18F]Flortaucipir‐PET (FTP) and CDR‐SB scores were acquired in 195 amyloid‐PET‐positive, sporadic eoAD patients with MCI or mild dementia due to AD at baseline (Table 1). FTP scans were referenced against inferior cerebellar GM, and mean SUVRs calculated in three meta‐ROIs comprising temporal, parietal, and frontal association cortices (Figure 1A). Generalized additive models estimated nonlinear relations between: (1) baseline SUVRs and annualized rates‐of‐change in each meta‐ROI, and (2) baseline CDR‐SB and annualized rates‐of‐change in cognition. Integrating these baseline‐by‐change functions yielded regional FTP and CDR‐SB trajectories over time. An exhaustive search algorithm identified optimal time‐shifts between each regional tau trajectory and CDR‐SB progression that minimized the error between model‐predicted and observed data at baseline. This time‐shifting procedure was repeated in a held‐out dataset of 184 eoAD patients to assess out‐of‐sample reproducibility (Table 1).

Result

FTP SUVRs and CDR‐SB scores increased longitudinally in most patients (Figure 1B, C). Baseline SUVR by rate‐of‐change associations were inverted U‐shaped in each meta‐ROI (Figure 1D), and similar associations were found for CDR‐SB progression (Figure 1E). Time‐shift estimation in the training dataset converged on a single, best‐fitting model in which temporal and parietal FTP accumulation led clinical onset by 4.5 years, while frontal FTP accumulation began 0.5 years before clinical onset (Figure 2A). The replication dataset yielded nearly identical results (Figure 2B). We estimate that the full timecourse of FTP accumulation and cognitive decline occurs over ∼16 years from earliest detectable change in FTP.

Conclusion

Tau‐PET accumulation in the frontal meta‐ROI immediately precedes cognitive decline and tracks closely with clinical progression in eoAD, while temporoparietal tau‐PET is prominent at clinical onset and plateaus as dementia worsens. For clinical trials in symptomatic patients, temporal and parietal tau‐PET may therefore aid staging and inclusion criteria, while frontal tau‐PET is likely superior for monitoring longitudinal change.
Medial temporal lobe subregional atrophy patterns in presymptomatic and symptomatic genetic frontotemporal lobar degeneration
Authors: Gaynor Leslie S , Yballa Claire , Cobigo Yann , Mejía‐Perez Jhony Alejandro , Wuestefeld Anika , Wisse Laura E.M. , Forsberg Leah K. , Heuer Hilary W. , Rosen Howard J. , Boxer Adam L. , Boeve Brad F. , Kantarci Kejal , Staffaroni Adam M. , La Joie Renaud
Published: January 2025

Background

Medial temporal lobe (MTL) atrophy is an early feature of multiple neurodegenerative diseases. In genetic frontotemporal lobar degeneration (FTLD, i.e. individuals carrying GRN, MAPT, or C9orf72 mutations), MTL atrophy can occur 10‐15 years before symptom onset. We aimed to better characterize MTL atrophy patterns in presymptomatic and symptomatic genetic FTLD using a multi‐atlas segmentation pipeline that allows precise measurement of MTL subregions.

Method

Participants included a diagnostically mixed sample of familial FTLD mutation carriers (MAPT: N = 87; C9orf72: N = 117; GRN: N = 65) and 142 non‐carrier family member controls from the ALLFTD study cohort (Table 1). T1‐weighted MRIs were preprocessed using a multi‐atlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS]) to segment the amygdala, anterior and posterior hippocampus, and MTL cortices: entorhinal cortex (ERC), perirhinal cortex or Brodmann areas (BA) 35 and 36, and parahippocampal cortex (PHC). Following rigorous quality control and manual correction (Figure 1), we assessed bilateral volume differences in mutation carriers compared to controls, adjusted for age, sex, and total intracranial volume. Analyses were conducted separately for symptomatic (FTLD‐Clinical Dementia Rating Global Score≥0.5) and presymptomatic (Global Score = 0) mutation carriers.

Result

Out of 413 scans, 317 (76.8%) segmentations passed quality control while 94 (22.8%) needed some manual edits—this was more common in symptomatic than presymptomatic carriers (32% versus 15%, p = 0.001). Three scans were excluded (<1%; 2 complete scans, 1 for selected subregions) due to insufficient landmark visibility in symptomatic GRN and MAPT carriers. In symptomatic carriers, all MTL subregions demonstrated reduced volume compared to controls, although MAPT carriers exhibited particularly marked atrophy, especially in anterior MTL subregions (Table 2; amygdala, ERC, BA35, hippocampus). Presymptomatic MAPT and C9orf72 carriers also exhibited significant atrophy of primarily anterior MTL cortices, while presymptomatic GRN carriers only exhibited significantly smaller ERC volume compared to controls.

Conclusion

MTL atrophy is present in genetic FTLD across mutation carriers, even at the presymptomatic stage. Anterior MTL subregions, which are also susceptible to neuropathologic accumulation in early Alzheimer’s disease and Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), tend to be more vulnerable than posterior subregions. Unsurprisingly, MAPT carriers show the greatest MTL atrophy compared to controls across groups.
Plasma phospho‐tau 217 rises with and not before early tau aggregation measured by MK6240 PET
Authors: Feizpour Azadeh , Dore Vincent , Doecke James D. , Masters Colin L , Rowe Christopher C.
Published: January 2025

Background

Rise in plasma phospho‐tau (pTau) is hypothesized to reflect a physiological response to brain Aß plaques, preceding the formation of neurofibrillary tangles (NFT). An alternate explanation is poor sensitivity of tau PET for detection of early NFT formation. The tau tracer MK6240 has very low background “off‐target” binding and may better detect early tau aggregation. Choice of tau PET regions for analysis may also influence early detection of tau.

Method

Participants included 105 cognitively unimpaired (CU) and 178 cognitively impaired (CI), with plasma pTau217 Lumipulse® assay, 18F‐NAV4694 Aß PET and 18F‐MK6240 tau PET data. The entorhinal, amygdala and meta temporal (MT) ROI 18F‐MK6240 SUVR and pTau217 levels were modelled as a function of Centiloid (CL).

Result

Rise in plasma pTau217 slightly lagged the rise in amygdala MK6240 binding and paralleled the rise in the meta temporal ROI (Figure 1), consistent with our previous report using Janssen p217+Tau measured by Simoa®1. Our findings also suggest that amygdala and meta temporal ROI were more robust for early detection of aggregated tau than the entorhinal cortex possibly related to PART and small ROI volume producing wide variance in the entorhinal normal range in Ab‐ CU.

Conclusion

This data suggests that the amygdala is a robust region for detecting early tau aggregation by MK6240 PET and that a rise in plasma pTau217 is associated with early formation of NFT rather than a direct physiological response to brain Aß plaques prior to NFT formation. Figure 1 legend: Modeling of 18F‐MK6240 quantification and pTau217 as a function of Centiloid. Biomarker values Z‐scored using the results from Aß‐ cognitively unimpaired to define the normal range for p217+tau level and each tau PET ROI SUVR. The horizontal line is +2 standard deviations (SD). 1Doré V, Doecke JD, …, Rowe CC. Plasma p217+tau versus NAV4694 amyloid and MK6240 tau PET across the Alzheimer’s continuum. Alzheimers Dement (Amst). 2022 Apr 5;14(1):e12307. https://doi.org/10.1002/dad2.12307. PMID: 35415202; PMCID: PMC8984092.
Data‐driven analysis of Aβ peptide ratios in iPSC models of familial Alzheimer’s disease for diagnosis and prediction of symptom onset
Authors: Saguer Isaac Llorente , Gabriele Rebecca , Wray Selina , Oxtoby Neil P , Arber Charlie
Published: January 2025

Background

Familial Alzheimer’s disease (fAD), arising from mutations in amyloid‐precursor‐protein (APP) and presenilin (PSEN1/2) genes, leads to the production of longer, aggregation‐prone amyloid‐beta (Aß) peptides—a hallmark of Alzheimer’s disease. Age‐at‐onset (AAO) varies among carriers of different mutations. Recent evidence challenges the Aß42:40 ratio as the leading and predictor of AAO between different pathogenic variants, prompting exploration of peptide combinations as potential biomarkers for these tasks.

Method

Data consisted of patient‐derived in‐vitro iPSC models of fAD and Ab measurements via enzyme‐linked immunosorbent assay (ELISA). With novel data of our own (N = 39) and published data from Liu et al. 2022 (N = 134) (table‐1), we performed a data‐driven analysis of Aß37/38/40/42/43 combinations, employing area under the curve (AUC) and coefficient of determination metrics for classification (WT vs AD) and AAO regression. A linear model optimized for these metrics was also explored. Each peptide was divided by the average of the control group of the same assay. Then, we weighted each peptide in accordance with the average profile of the control population in Liu.

Result

Data transformation using controls proved necessary for to produce comparable ratios (figure‐1). Table‐2 presents diagnostic and predictive performance for each peptide‐ratio biomarker relative to biomarkers from the literature (top 3 rows). Our new data‐driven biomarkers improved upon the literature in both diagnostic AUC (not statistically significant: DeLong’s test p>0.47) and predicting AAO (Spearman’s R^2 significant differences in UCL data; Hittner’s p<0.005; p>0.5 in Liu’s).

Conclusion

Our results do not recapitulate Liu et al. findings, as Aß37:42 did not outperform Aß42:40 in our data; one explanation could be that our lines represent a physiological model of Ab production that is free from plaque deposition. While no significant differences emerged in AD classification, specific peptide ratios demonstrated varying correlations with AAO: short‐to‐long ratio > Aß42:40, and Aß42:40 > Aß37:42, but other ratios were found to perform better in each set, suggesting mutation‐specific profiles. Data‐driven linear combination can improve the results, and notably, both optimizing for AUC or AAO found the same ratio of short/long, albeit with different weights. Standardization through control‐based data was essential for robust measures.
Longitudinal posterior‐medial functional connectivity changes with age and Alzheimer’s pathology are differentially related to memory performance depending on APOE genotype
Authors: Fischer Larissa , Molloy Eóin N. , Adams Jenna N. , Tremblay‐Mercier Jennifer , Remz Jordana , Binette Alexa Pichet , Villeneuve Sylvia , Maass Anne
Published: January 2025

Background

The posterior‐medial network is crucial for episodic memory. However, the medial temporal lobe (MTL) and posteromedial cortex (PMC) regions are vulnerable to aging and early Alzheimer’s disease (AD). Both processes might elicit distinct early functional connectivity (FC) changes which could be detrimental or protective/ compensatory regarding cognition. However, this is not well understood. We hypothesized that resting‐state FC strength between key regions (Figure 1a) would decrease with age and memory decline without AD pathology (A‐T‐) but increase with early AD pathology.

Method

We analysed longitudinal 3‐Tesla resting‐state fMRI data from cognitively unimpaired older adults (OA; PREVENT‐AD cohort). We assessed FC at baseline and after 24 months (FU24) in i) CSF or PET Aß‐ and tau‐negative OA (A‐T‐, N = 96, 63±5years, 70 female, 28 APOE4) and ii) Aß and p‐tau CSF‐characterized OA with available longitudinal p‐tau181/Aß1‐42 ratio (N = 65, 63±5years, 45 female, 22 APOE4). First, we investigated effects of age, APOE genotype and p‐tau181/Aß1‐42 ratio on FC controlling for sex and education. Second, we tested the association between baseline FC or change in FC and change in delayed memory recall in multiple regression analyses.

Result

In A‐T‐ OA, FC decreased mainly between regions within the PMC subnetwork over 24 months (Figure 1b). Higher baseline FCwithin‐PMC was related to increasing memory performance over time (p = 0.047; Figure 2a). Longitudinally, increasing FCMTL‐mPFC was associated with increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.016; Figure 2b). In CSF‐characterized OA, p‐tau181/Aß1‐42 ratio at baseline and FU24 was related to increasing FCMTL‐PMC over time (Figure 3a). Higher baseline FCMTL‐PMC was associated with longitudinally increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.028; Figure 3b).

Conclusion

Our results provide novel longitudinal evidence incorporating age, APOE, Aß and tau indicating specific memory‐related FC changes in cognitively unimpaired OA. APOE moderated the effects of FC strength on change in episodic memory performance. Higher FCMTL‐PMC and increasing FCMTL‐mPFC seem to be detrimental in APOE4 carriers but beneficial in APOE4 non‐carriers. Importantly, this effect was observed in A‐T‐ OA, hinting that APOE genotype may affect FC earlier than AD‐related pathology.
White‐matter myelin is reduced in monogenic small vessel disease and MCI: evidence from MRI source separation
Authors: Denecke Jannis , Dewenter Anna , Lee Jongho , Pirpamer Lukas , Franzmeier Nicolai , Gesierich Benno , Duering Marco , Ewers Michael
Published: January 2025

Background

The myelin sheath around axons is of fundamental importance for signal transduction. Myelin is reduced in white matter hyperintensities (WMH), which occur in both small vessel disease (SVD) and Alzheimer’s disease (AD), giving rise to the question to what extent myelin is reduced in these diseases. Here, we employed an advanced MRI based method to assess myelin independently from a major confounding factor, i.e. iron‐related signal, in monogenic small vessel disease (i.e. CADASIL) and in mild cognitive impairment (MCI) & AD dementia.

Methods

We included 62 CADASIL subjects, 11 with MCI or AD dementia, and 22 elderly controls (HC). Using 3D‐T2‐star‐weighted multi‐echo gradient‐echo MRI, we performed susceptibility source separation of diamagnetic (|χ‐negative|, e.g. myelin) and paramagnetic (χ‐positive, e.g. iron) sources (Shin et al., 2021). Mean diffusivity (MD) was calculated from diffusion tensor imaging. We extracted |χ‐negative| and MD values within WMH, normal appearing white matter (NAWM), and two ROIs including the left anterior thalamic radiation and forceps minor (genu) of the corpus callosum, i.e. two strategic tracts for processing speed. Subject‐level difference‐scores between CADASIL or MCI/dementia patients and group‐averaged HC were derived as abnormality scores. Voxel‐based WMH frequencies were mapped for each group. Group differences in |χ‐negative| and MD values were tested using linear regressions, controlled for χ‐positive scores, age, sex, and education.

Results

Voxel‐wise proportions of WMH are mapped for each group in Figure 1. For CADASIL, |χ‐negative| values were decreased, and MD values increased in each ROI compared to the HC group, with intermediate values for the MCI/dementia group (Figure 2 A&B). Worse |χ‐negative| and MD alterations were observed in WMH compared to NAWM (Figure 2 C‐F) in each disease group. Lower |χ‐negative| values were associated with higher MD in WMH (r = ‐0.57, Figure 3) and NAWM (r = ‐0.56).

Conclusion

|χ‐negative| values showed a marked decrease in WMH of CADASIL patients, suggesting myelin loss in SVD, with less pronounced myelin reduction present in MCI/AD. |χ‐negative| values were only moderately associated with MD, suggesting that each provides complimentary information. Our results encourage future studies to test the cognitive consequences of myelin loss in SVD and MCI.
Spatial Pattern of Medial Temporal Lobe Cross‐Sectional and Longitudinal Structural Change in Cognitively Normal Individuals
Authors: Xie Long , Das Sandhitsu R. , Li Yue , Wisse Laura E.M. , McGrew Emily , Lyu Xueying , DiCalogero Michael , Shah Ujashi , Ilesanmi Ademola , Denning Amanda E , Brown Christopher D. , Cohen Jesse S , Sreepada Lasya P , Dong Mengjin , Sadeghpour Niyousha , Khandelwal Pulkit , Ittyerah Ranjit , Ravikumar Sadhana , Sadaghiani Shokufeh , Hrybouski Stanislau , de Flores Robin , Gibson Eli , Yushkevich Paul A. , Wolk David A
Published: January 2025

Background

The medial temporal lobe's (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without ß‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both ß‐amyloid and tau status in a large cohort of CN individuals.

Methods

A dataset of 3036 CN (A‐/A+: 1270/1558, Table 1) individuals from ADNI, HABS, A4 and ABC were analyzed. We extracted MTL regional thickness maps from MRI using tailored pipelines, ASHS‐T1 and CRASHS. For participants with prospective longitudinal MRI (five years follow‐up), regional maps of longitudinal atrophy rate were extracted using SkelDBM. Subjects with cross‐sectional tau PET available (N=563) were further divided into A and T subgroups by tracer uptake. General linear modeling was performed on each surface point to investigate cross‐sectional and longitudinal MTL structural group differences (detailed in Figure 1) and their correlation with MTL tau burden in All/A+/A‐ CN. Age and sex were covariates and cluster‐level multiple comparison correction was performed.

Results

A+CN demonstrated a significantly faster atrophy rate than A‐CN across the whole MTL, primarily driven by A+T+CN individuals (Figure 1‐b). Notably, A‐T+CN showed significantly faster atrophy rate in the entorhinal cortex (ERC) and Brodmann area 35 (BA35), the earliest sites of tau pathology (Figure 1‐b, second column). Figure 2‐b displays an MTL‐wise significant correlation between atrophy rate and tau in All/A+/A‐ CN. In both analyses, cross‐sectional effects are consistently weaker than longitudinal ones, but have some significant clusters in ERC and BA35.

Conclusions

Pointwise analysis revealed extensive tau‐associated accelerated neurodegeneration in the MTL in preclinical AD. Furthermore, accelerated atrophy was observed in early Braak regions in A‐CN with evidence of tau pathology, potentially driven by primary age‐related tauopathy (PART). These pointwise longitudinal MTL measures provide sensitive measures that may allow for disease monitoring in preclinical AD.
Among older African Americans, high‐risk ABCA7‐80 allele carriers have lower medial temporal lobe dynamic network flexibility than APOE‐ε4 allele carriers
Authors: Budak Miray , Fausto Bernadette A. , Piaszczynska Wiktoria , White Payton G. , Gluck Mark A.
Published: January 2025

Background

Alzheimer’s disease (AD) is a progressive neurodegenerative disease characterized by amyloid plaques and neurofibrillary tangles which cause neurodegeneration and cognitive decline1. APOE‐ε4 is identified as the first common genetic risk factor with high penetrance in the early onset of AD3. ABCA7 (rs115550680) (ABCA7‐80) is associated with the development of late‐onset AD among African Americans2. The medial temporal lobe (MTL) is the first region that displays atrophy and neurofibrillary tangle involvement during AD4. However, the comparative influence of APOE‐ε4 and ABCA7‐80 on neural functions among African Americans is not yet known. The present study investigated the effect of APOE‐ε4 and ABCA7‐80 high‐risk alleles on the MTL dynamic network flexibility among cognitively unimpaired older African Americans.

Method

175 older, cognitively unimpaired African Americans drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans completed saliva collection for genotyping and underwent an MRI scan in a Siemens 3T Prisma scanner. AFNI and ANTs were used for dynamic functional MRI processing and analysis for MTL dynamic network flexibility. Gender, age, and education were used as covariates for analysis.

Result

The analysis revealed trend‐level differences in MTL Dynamic network flexibility between high‐risk and non‐risk allele carriers for ABCA7‐80 (F = 3.531, η² = 0.025, p = 0.062) and for APOE‐ε4 allele (F = 2.421, η² = 0.017, p = 0.122). Individuals with the ABCA7‐80 high‐risk allele exhibited significantly lower MTL dynamic network flexibility compared to those with the APOE‐ε4 allele (F = 4.577, η² = 0.067, p = 0.036).

Conclusion

ABCA7‐80 high‐risk allele may better capture the dynamic neural dysfunction in the MTL network rather than APOE‐ε4 among cognitively unimpaired older African Americans.
Cerebral and cognitive correlates of olfactory functioning in older adults at risk of Alzheimer’s disease: preliminary results from the CIMA‐Q Cohort
Authors: Jobin Benoît , Frasnelli Johannes , Boller Benjamin , Group CIMA‐Q
Published: January 2025

Background

Olfactory identification is impaired in the early stages of Alzheimer’s disease (AD), including mild cognitive impairment (MCI). This early sensory impairment could result from several factors such as early cognitive or structural cerebral damages caused by the disease. It is however not clear which factors are contributing the most to the olfactory impairment in older people at risk of developing AD. The aim of this study was to explore and determine the cerebral and cognitive correlates of olfactory identification functioning in a cohort of older adults at risk of developing AD.

Method

Here we report preliminary data on 16 participants with subjective cognitive decline (SCD) (mean age: 76.58, SD: 5.53) and 17 patients with MCI (mean age: 79.94, SD: 7.06) from the Consortium for the Early Identification of Alzheimer’s Disease‐Quebec (CIMA‐Q). Olfactory assessment was completed using the University of Pennsylvania Smell Identification Test (UPSIT), while episodic memory was assessed using the Logical Memory subtests of the Wechsler Memory Scale. All participants underwent a clinical examination and neuropsychological assessment. Further, grey matter volume (GMV) of olfactory‐related structures was extracted using CAT12 in a subgroup of 16 participants for whom MRI data were available.

Result

The UPSIT score was significantly correlated with the Logical Memory immediate recall score in the MCI group (r = .53, p = .03) but not in the SCD group (r = ‐.26, p = .33). No significant differences were found regarding olfactory identification between both groups (p = .75). Bilateral middle cingulate cortex (r = .51, p = .04) and caudate (r = .51, p = .04) GMV were correlated to the UPSIT score, while no significant correlation was found for other structures (p > .05).

Conclusion

These preliminary data suggest that short‐term episodic memory, as well as GMV of middle cingulate cortex and caudate are related to olfactory identification in older adults at risk of AD. Future studies to validate these findings will incorporate more participants from the CIMA‐Q cohort.
Differential association of moderate alcohol use with neurodegeneration, cerebrovascular disease, and cognition by racial, ethnic and sex/gender groups in middle age
Authors: Guzmán Diana S. , Rentería Miguel Arce , Avila Justina F , Turney Indira C. , Johnson Aubrey S. , Smith Anna C. , Okafor Amarachukwu , Houlihan Hannah M. , Heuer Lauren B. , Alshikho Mohamad J. , Morales Clarissa , Mazen Jessica , Gu Yian , Manly Jennifer J. , Brickman Adam M. , Lao Patrick J.
Published: January 2025

Background

Moderate alcohol use may be associated with brain and cognitive benefits compared to heavy alcohol use. However, results have varied. We hypothesized that the relationship between alcohol use and cognition is mediated by neurodegenerative and cerebrovascular measures in a diverse middle‐aged sample of non‐alcohol dependent community‐dwelling adults in Northern Manhattan.

Method

Participants (N = 451; age = 53±10 years; 36 Black Men (BM), 68 Black Women (BW), 95 Latinx Men (LM), 198 Latinx Women (LW), 17 White Men (WM), 37 White Women (WW)) from the Offspring study of Racial and Ethnic Disparities in Alzheimer’s Disease underwent structural and vascular MRI (total brain volume (TBV), cortical thickness in AD signature regions, hippocampal volume, white matter hyperintensities (WMH)). Moderate alcohol use was assessed by the Alcohol Use Disorder Identification Test–Concise (AUDIT‐C = 9). Mediation models tested whether the association of alcohol use on cognition (SRT total and delayed; Animal and letter fluency; Digit Span Backwards) is mediated by brain measures, stratified in sex/gender by racial and ethnic groups.

Result

Greater moderate alcohol use was associated with lower cortical thickness and hippocampal volume LM (cortical thickness: ‐0.005 mm [‐0.008, 0.001], p = 0.005; hippocampal volume: ‐25.0 mm3 [‐45.0, ‐4.7], p = 0.02), greater vascular burden in BM (temporal WMH: 0.07 cm3 [0.001, 0.121], p = 0.05), and lower TBV in WM (‐24.0 cm3 [‐27.5, ‐20.4], p = 0.01), but not associated with brain measures in women. Greater moderate alcohol use was associated with lower animal fluency for LM (ADE: ‐0.25 to ‐0.21, p = 0.04), but higher letter fluency for LW (ADE: 0.24 to 0.25, p = 0.04) and BW (ADE: 0.43 to 0.43, p = 0.05), accounting for brain to cognition associations. However, mediation pathways (ACME) were not significant.

Conclusion

Men had lower cortical thickness and brain volume, greater WMH volume, and lower cognitive measures, while women had higher cognitive measures with greater moderate alcohol use in midlife. Neurodegenerative and vascular associations with moderate alcohol use differed by race and ethnicity in men, while the directionality of associations between moderate alcohol use and fluency differed by sex/gender. Future work should explore alcohol use factors (e.g., context of use, duration of use), and the relationship to brain and cognitive changes over the life course.