bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing a novel brain‐based biomarker of mild cognitive impairment using time‐domain functional near‐infrared spectroscopy
Authors: Dubois Julien , Field Ryan M , Jawhar Sami , Koch Erin M , Aghajan Zahra M. , Miller Naomi , Perdue Katherine L , Taylor Moriah 
Published: January 2025

AbstractBackgroundMild cognitive impairment (MCI) is largely under‐diagnosed by primary care physicians. There is an urgent need to develop new objective screening tools to assist with early detection of MCI. Time‐domain functional near‐infrared spectroscopy (TD‐fNIRS) can be used to measure brain function in clinical settings and may fill this need.MethodMCI patients (n=21) and control older adults (HC; n=24) participated in brain recordings using TD‐fNIRS during rest and cognitive tasks implicated in MCI: 1) Verbal fluency task (VFT) consisting of interleaved blocks reciting words (control: weekdays; semantic: words from a given category; phonological: words starting with a given letter); 2) N‐back task targeting working memory by testing memory for patterns with specific memory loads (0‐, 1‐ and 2‐backs) in a block‐design manner. Raw data, i.e. the distributions of the times of flight (DToFs) of photons at two wavelengths (690 and 905nm), underwent standard preprocessing to obtain moments of DToFs and corresponding changes in the concentrations of oxygenated/deoxygenated hemoglobin. Features related to brain function, systemic physiology, and head optical properties were extracted. For tasks, behavioral metrics were also computed.ResultFirst, we looked for features that significantly differentiated between MCI and HC groups during a resting state session (watching a 7‐minute audiovisual segment; Figure 1A). Multiple features, including head optical properties and prefrontal fractional Amplitude of Low Frequency Fluctuations (fALFF) were statistically different between MCI and HC (Figure 1B). Next, we explored the tasks both in terms of behavior and neural features. In VFT, behavior was significantly different between groups (Fig. 2A), which is expected from prior literature. Additionally, whole‐brain hemodynamic activation maps, as computed using Generalized Linear Models (GLM) revealed areas with significant differences between the two groups (Fig. 2B). Similarly, for the N‐back task, multiple behavioral metrics were separated between the groups (Fig. 3A) and group‐level GLM showed brain regions with significantly different activations between groups, specifically medial prefrontal cortex (Fig. 3B).ConclusionWe demonstrated significant group‐level differences between MCI vs healthy controls using TD‐fNIRS. As such, with ongoing data collection, we seek to validate these findings and employ classification techniques for MCI detection.
Diffusion Basis Spectrum Imaging in Midlife Obesity: Associations with Abdominal Adipose Tissue
Authors: Dolatshahi Mahsa , Commean Paul K. , Rahmani Farzaneh , Nguyen Caitlyn , Lloyd LaKisha , Kasani Sara Hosseinzadeh , Mittendorfer Bettina , Sirlin Claude , Song Sheng‐Kwei , Benzinger Tammie L.S. , Ippolito Joseph E. , Morris John C. , Raji Cyrus A. 
Published: January 2025

AbstractBackgroundObesity and abdominal adiposity in midlife are shown to increase the risk of Alzheimer disease. However, it is not clear whether midlife adiposity is associated with increased neuroinflammation. We aimed to investigate the associations of obesity, BMI of 30 kg/m2 or higher, and abdominal visceral and subcutaneous adipose tissue (VAT and SAT) with brain histology, using diffusion basis spectrum imaging (DBSI) analysis;MethodIn total, 54 cognitively normal middle‐aged subjects (50.46±6.19 years, male: 21 (38.9%), obesity: 32 (59.3%), BMI: 32.18±6.99 kg/m2) underwent brain and abdominal 3T MRI. Abdominal VAT and SAT were semi‐automatically segmented using VOXel Analysis Suite (Voxa). A DBSI scheme with a total of 98 diffusion samplings was acquired followed by movement and eddy current correction and brain tissue extraction in FSL. DBSI maps including fractional anisotropy (FA, overall integrity), axial diffusivity (AD, axonal injury), radial diffusivity (RD, myelin loss), restricted fraction (RF, inflammation cellularity), hindered fraction (HF, extracellular edema), and fiber fraction (FF, axonal density) were generated using in‐house software scripted in MATLAB. DBSI‐derived maps were processed using a tract‐based spatial statistics (TBSS) pipeline for whole‐brain white matter voxel‐wise analyses. Using the Randomize tool from FSL, the difference between obese vs. non‐obese, high‐VAT vs. low‐VAT, and high‐SAT vs. low‐SAT groups were investigated for each DBSI‐derived skeleton, with age and sex as covariates, and a threshold of 0.05 for false‐discovery rate. The sex differences were further investigated;ResultLower FF and AD and higher RF in widespread white matter areas were observed in the obese vs. non‐obese group, and in the high‐SAT vs. low‐SAT group. Lower AD and higher RF were observed for the high‐VAT vs. low‐VAT group. All of these differences were only significant in females, not males, but higher RF in obese vs. non‐obese was observed both in males and females;ConclusionOur data support lower axonal density and fiber integrity, as well as higher inflammation cellularity in cognitively normal, middle‐aged obese individuals, and those with high VAT and high SAT, especially in females. Overall, our data suggest the differential role of visceral and subcutaneous abdominal fat in promoting neuroinflammation and axonal damage.
Markers of Interstitial Fluid Dynamics from Diffusion MRI Reveal Association with Amyloid Deposition in Cognitively Normal Older Adults
Authors: Chen Chang‐Le , Jin Hecheng , Schweitzer Noah , Minhas Davneet S , Villemagne Victor L , Yang Shaolin , Aizenstein Howard J , Wu Minjie 
Published: January 2025

AbstractBackgroundGlymphatic clearance dysfunction within the perivascular space has been implicated in Alzheimer’s Disease (AD) pathology. Diffusion MRI‐based techniques such as DTI‐ALPS can quantify perivascular interstitial fluid (ISF) dynamics, yet their links with other early AD markers in the cognitively normal elderly population remain underexplored. Here, we investigated associations between DTI‐ALPS and cerebral ß‐amyloid (Aß) burden measured with Pittsburgh Compound B (PiB)‐PET. We also evaluated an augmented version of DTI‐ALPS to enhance sensitivity and better reflect the ISF diffusivity potentially associated with glymphatic function.MethodsDiffusion tensor images (DTI) and PiB‐PET images were collected from 40 cognitively normal older adults (age: 74.8 [5.8] years, sex: 18 males, mini‐mental state examination (MMSE): 28.8 [1.4], APOE‐e4%: 23%). Based on the DTI (acquired on a 3T MRI scanner with 12 diffusion directions, b‐value = 1000, and voxel size in 2 mm cubic), we estimated DTI‐ALPS index that evaluates the perivascular ISF movement along the medullary conduits and also developed an algorithm to generalize the definition of the traditional DTI‐ALPS by automatically localizing the periventricular space as the target area and calculating transverse tensor ratios as the primary measure (Figure 1). PiB‐PET analysis followed our previous validated approach, and the regional standardized uptake value ratios (SUVR) representing PiB retention relative to the cerebellar gray matter were averaged to determine global cerebral Aß burden. Linear regression analysis was applied to investigate the relationship between DTI‐ALPS and global PiB‐PET SUVR.ResultsThe baseline model with the predictors of age, sex, MMSE and APOE4 status significantly explained the logarithmic global SUVR of PiB‐PET (Figure 2). When incorporating DTI‐ALPS indices, the baseline models were significantly improved (Likelihood‐ratio test: both p < 0.01); the explained variance increased by 15.3% and 19.3% by adding traditional and proposed augmented DTI‐ALPS indices, respectively. The models indicated that the DTI‐ALPS indices were significantly negatively associated with the global Aß burden after adjusting the covariates (Figure 2).ConclusionWe observed that higher ISF diffusivity (likely better glymphatic clearance) corresponds to lower PiB‐PET retention (lower Aß burden) in the cognitively normal older adults, suggesting the potential utility of ISF measures as a putative AD biomarker.
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

AbstractBackgroundWith 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.MethodWe 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.ResultsFour 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).ConclusionIn 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

AbstractBackgroundDifferences 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).MethodParticipants (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.ResultAll 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.ConclusionDespite [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

AbstractBackgroundTau 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.Method231 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).ResultFigure1A 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.ConclusionLongitudinal 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

AbstractBackgroundThe 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.MethodsSeven 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.ResultsNT1 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).ConclusionPlasma 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

AbstractBackgroundSynapse 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.MethodsMass 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.ResultsAmyloid 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).ConclusionsGAP43 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.