bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements
Authors: Kothapalli Satya V.V.N. , Benzinger Tammie L.S. , Gordon Brian A. , Eldeniz Cihat , Hildebolt Charles F , Goyal Manu S. , Morris John C. , Yablonskiy Dmitriy A.
Published: January 2025

Background

The 18F‐AV‐1451 radioligand enables in‐vivo identification of tau neurofibrillary tangles that are considered as biomarkers of neurodegeneration in Alzheimer Disease (AD). However, off‐target radioligand binding is also observed in basal ganglia, known as an iron‐rich region. Hence, it is important to distinguish between radioligand‐identified tissue neurodegeneration and iron‐related radioligand binding effects. Our aim is to answer this question by using previously developed quantitative Gradient Recalled Echo (qGRE) MRI technique sensitive to morphological and microstructural tissue neurodegeneration, as well as to iron deposition.

Methods

Sixty‐eight participants (ages: 72.1y ± 8.2y; 15 with amyloid status (Aß) positive and cognitive dementia rating (CDR®)>0; 16 with Aß‐positive and CDR® = 0; and 37 with Aß‐negative and CDR® = 0) recruited by Knight ADRC underwent 18F‐AV‐1451 PET imaging and qGRE MRI imaging (3T Siemens MRI scanners). As previously demonstrated, the R2t* metric of qGRE signal is sensitive to both, pre‐atrophic neuronal loss (low R2t*, a.k.a. Dark Matter (DM), and nonheme iron accumulation (High R2t*). The histogram characterizing distribution of R2t* values across the brain (Figure 1) allows the quantification of DM (R2t*<5.8s‐1) and Iron Deposition Score (IDS, R2t*>28s‐1). 18F‐AV‐1451 binding was characterized in terms of Standardized Uptake Value Ratio (SUVR). All results were summarized in brain regions segmented using FreeSurfer.

Results

(Figures 2 and 3): Tissue volumes exhibited moderate negative associations with 18F‐AV‐1451 SUVRs in MTL (R2 = 0.21), temporal lobe (R2 = 0.17), and parietal lobe (R2 = 0.11). The linear model that includes IDS and DM exhibited positive association with 18F‐AV‐1451 SUVRs only in MTL (R2 = 0.18). The linear mixed model that includes volume, IDS and DM metrics showed the improved association between predicted and actual 18F‐AV‐1451 tracer retention in the MTL (R2 = 0.34), the temporal lobe (R2 = 0.23), and the parietal lobe (R2 = 0.12).

Conclusion

Our results suggest that the 18F‐AV‐1451 binding is modulated not only by neurodegeneration but also by elevated levels of iron deposition. More detail studies are required to answer the question whether the iron effect is concomitant or contributes to neurodegeneration through ferroptosis. The qGRE‐based multiparametric approach allowing simultaneous identification of pre‐atrophic neurodegeneration and iron deposition has a potential to contribute to understanding of this intricate relationship.
A brain MRI estimate of whole‐body aging in midlife predicts late life risk for Alzheimer's disease
Authors: Whitman Ethan T. , Elliott Maxwell L. , Knodt Annchen R. , Moffitt Terrie E. , Caspi Avshalom , Hariri Ahmad R.
Published: January 2025

Background

Aging is the strongest risk factor for Alzheimer’s disease (AD). Accordingly, identifying biomarkers of accelerated aging is a major focus of AD prevention research. Current MRI‐based “aging clocks” (i.e., brain age) derive from cross‐sectional associations with chronological age. However, chronological age differs fundamentally from biological aging. We introduce a novel brain MRI proxy for biological aging in midlife developed in the Dunedin Study, a population‐representative longitudinal birth cohort, and demonstrate its ability to differentiate and predict AD in the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Method

The pace of whole‐body aging was determined by tracking physiological decline of 6 organ systems over 20 years in Dunedin Study members. An elastic‐net regression model was trained to estimate this pace of aging using a single T1‐weighted scan collected at age 45 from 860 Study members. We call this measure the Dunedin Pace of Aging Calculated from NeuroImaging or “DunedinPACNI.” We exported DunedinPACNI to ADNI and tested its association with current and future AD. Lastly, we compared DunedinPACNI to “brain age” using brainageR.

Result

DunedinPACNI estimated whole‐body aging with a cross‐validated accuracy of r=0.43 in Dunedin Study members. Derived in 6,199 T1‐weighted ADNI scans, DunedinPACNI was on average 0.40 standard deviations higher in MCI patients and 1.13 standard deviations higher in AD patients compared to healthy participants (MCI 95% CI:[0.36‐0.45]; AD 95% CI:[1.08‐1.19]). DunedinPACNI outperformed brainageR in differentiating MCI and AD patients from controls (MCI: b=.25; 95% CI:[.14‐.35]; AD: b=.68; 95% CI:[.56‐.80]). In 1,326 ADNI participants followed up to 16 years, baseline DunedinPACNI was associated with a higher probability of AD conversion (HR=1.58, 95% CI:[1.36‐1.84]) as was brainageR (HR=1.61; 95% CI:[1.42‐1.84]). DunedinPACNI and brainageR together predicted conversion more accurately than either measure alone (combined HR=2.10, 95% CI:[1.76‐2.51).

Conclusion

DunedinPACNI, a novel MRI proxy for longitudinal whole‐body aging during midlife, offers advantage over “brain age” in detecting neurodegenerative disease and predicting AD conversion in late life. DunedinPACNI can be applied to existing neuroimaging datasets to estimate whole‐body aging to better gauge early AD risk.
Association of Objective Sleep Measures and White Matter Limbic System Integrity in Community‐Dwelling Cognitively Unimpaired Older Black and White Adults
Authors: Bubu Omonigho Michael , Gills Joshua L , Cesar Oliver , Kovbasyuk Zanetta , Sogade Anamarie , Dominguez Joanna , Browne Laurel Y , Valkanova Elena , Mbah Alfred , Figueredo Luisa F , Kam Korey , Mullins Anna E , Parekh Ankit , Masurkar Arjun V. , Varga Andrew , Osorio Ricardo
Published: January 2025

Background

We examined racial differences between measures of limbic white matter tracts and objective sleep parameters in cognitively unimpaired older‐adults.

Method

This cross‐sectional study included 170 community‐dwelling cognitively unimpaired older‐adults (mean±SD: age = 67.2±5.2y) participating in NYU studies of sleep, aging, and memory. Subjects completed polysomnography (NPSG) and brain MRI. Sleep measures of interest included total sleep time (TST), NREM stages 2, 3 and REM sleep duration, sleep latency and fragmentation, slow sleep spindles (SSP), sleep spindle density (SPD), AHI4% and REM AHI4%. Microstructural properties of the cingulum, uncinate fasciculus (UF), and fornix were estimated using diffusional tensor imaging (DTI) metrics including radial kurtosis (RK), radial diffusivity (RD), and fractional anisotropy (FA). Adjusted Linear mixed‐effects regression models examined associations between race, sleep, race*sleep and DTI metrics.

Result

Participants were 44.1% Black with 16.8±2.5y of education. Subjects were relatively matched on AHI4%, age, BMI and educational level. In the cingulum, increased fragmentation was associated with higher RD ß[Left] = 0.0026, p = 0.022), decreased RK (ß[Right] = ‐0.0069, p = 0.039) in Blacks. Additionally, increased sleep latency was associated with reduced FA (ß[Right] = ‐0.0010, p = 0.019), higher RD (ß [Right] = 0.0010, p = 0.008) in Blacks. In the UF, increased fragmentation was associated with higher RD(ß[Left] = 0.0052, p = 0.019) and lower RK (ß[Right] = ‐0.0010, p = 0.039) in Blacks; increased AHI4%REM was associated with reduced FA ß[Left] = 0.0007, p = 0.041), higher RD (ß[Right] = ‐0.0007, p = 0.027) and lower RK (ß[AHI4%, Left] = ‐0.0029, p = 0.001) in Blacks. Furthermore, higher SSP (ßRight] = 0.00031, p = 0.045 and SPD (ß[Right] = 0.045, p = 0.025) was associated with higher RK in Blacks. In the cingulum of white participants, higher AHI4%REM was associated with reduced FA ß[right] = ‐0.0006, p = 0.013), higher RD ß[Left] = 0.0005, p = 0.051), and reduced RK ß[Right] = ‐0.00198, p = 0.008). Additionally, NREM stage‐2 sleep duration was associated with higher FA ß[Right] = 0.0010, p = 0.037) and higher RK ß[Right] = 0.0031, p = 0.040). In the UF, increased fragmentation was associated with reduced RK ß[Left] = ‐0.017, p = 0.047) in Whites.

Conclusion

Cognitively‐unimpaired Black and White older‐adults showed sleep disruption associations with limbic white matter integrity, with race‐specific associations observed across various microstructural properties of the cingulum, UF, and fornix. Thus, highlighting possible sleep‐related underpinnings of racial differences in Alzheimer disease‐risk.
Amyloid burden and APOE modify sex differences in estimated meta‐temporal region tau onset age
Authors: Heston Margo B. , Cody Karly , Teague Jordan P , De Chavez Elena Ruiz , Morse Jacob , Deming Yuetiva , Engelman Corinne D. , Chappell Richard J , Langhough Rebecca E. , Gleason Carey E. , Clark Lindsay R. , Zuelsdorff Megan L. , Betthauser Tobey J.
Published: January 2025

Background

Recent advances in Alzheimer’s disease (AD) temporal biomarker modeling have revealed considerable heterogeneity in age at amyloid onset, and recently we and others identified sex and APOE differences in tau onset age and subsequent dementia development. Here we assessed whether amyloid burden, APOE‐e4 dose, and sex interact to predict estimated T+ onset age (ETOA).

Methods

Alzheimer’s Disease Neuroimaging Initiative participants (N = 911, Table 1) underwent serial PET imaging to quantify global cortical amyloid ([18F]Florbetapir SUVR50‐70, [18F]Florbetaben SUVR90‐110) and meta‐temporal tau ([18F]Flortaucipir SUVR80‐100) burden. Cortical amyloid SUVRs were harmonized using linear transformation to Centiloids (CL). Sampled iterative local approximation (SILA) was used to model ETOA and, separately, to estimate amyloid CL burden at ETOA. Kaplan‐Meier survival curves and Cox regression were used to test CL*APOE‐e4*sex interaction effects on ETOA. Event time was ETOA for T+ individuals and age at last tau PET scan (right censored) for T‐ individuals who could become T+.

Results

We observed a significant CL*APOE‐e4*sex interaction on ETOA (p = 0.013, Table 2). APOE‐e4 was associated with earlier ETOA in a dose‐dependent manner and effects were greater in females compared to males. ETOA differences between sexes and across APOE‐e4 were attenuated at higher amyloid burden, largely due to the increased presence of T+ across all APOE‐e4 statuses and both sexes (Figure 1). Main effects also revealed that higher cortical amyloid burden at ETOA was associated with earlier ETOA and greater T+ risk, as was greater APOE‐e4 dose (Table 2).

Conclusions

These results suggest that amyloid burden, APOE‐e4, and sex may influence when temporal tau deposition becomes abnormal. Smaller sample size among APOE‐e4 carriers, and especially e4 homozygotes, limits the estimates in this cohort. Future extensions of this work will expand to a multicohort sample, to attempt replication of these findings and to investigate how these factors and their interaction predict time from amyloid and tau onset to dementia.
Addressing the gaps of the functional neuroimaging in young APOEe4 carriers: A systematic review and Graph Theoretical analysis of brain connectivity
Authors: Kucikova Ludmila , Brass Adam , Xiong Xing , Zeng Jianmin , Ritchie Craig , Muniz‐Terrera Graciela , O'Brien John T , Su Li
Published: January 2025

Background

In the last decade, extensive research has emerged into understanding the impact of risk factors for Alzheimer’s Disease (AD) on brain function in pre‐symptomatic stages. Here, we focused on the apolipoprotein e4 (APOEe4) gene, the major genetic risk factor for sporadic AD, and its effect on brain function in early adulthood.

Method

In the first part of the study, we systematically reviewed the multimodal functional neuroimaging literature, exploring its relationship with cognition, and the potential effects of other variables including the demographics, other risk factors, and methodological and analytical choices. While the studies demonstrated consistent alterations of APOEe4 carriers in brain connectivity and activity; the results of fMRI studies covered mostly the differences in the directionality using standard connectivity and activity measures. In the second part of this study, we aimed to address this gap by using the graph theory analysis to explore the dynamic behaviour of the six resting‐state networks of interest in young APOEe4 carriers versus non‐carriers (n = 129, aged 17‐22).

Result

Average Path Length and Closeness Centrality were consistently disrupted, pointing to network reorganisation in multiple resting‐state networks, albeit using different mechanisms.

Conclusion

This study is the first to demonstrate the restructuring of multiple resting‐state networks in young adults modulated by the APOE genotype.
Synapse loss in early‐ and late‐onset Alzheimer’s Disease assessed by 18F‐SynVest‐1
Authors: He Kun , Xie Fang , Huang Qi
Published: January 2025

Background

We aimed to investigate the loss of synaptic density in early‐onset and late‐onset Alzheimer’s Disease.

Method

One hundred and eighty‐two participants underwent synaptic density PET with 18F‐SynVesT‐1. Including 23 early‐onset Alzheimer‘s Disease (EOAD), 58 late‐onset Alzheimer’s Disease (LOAD), 16 EOnonAD, 28 LOnonAD, 31 younger normal control (age < 65) and 26 older normal control (age ⩾ 65). We analyzed the synaptic density loss in EOAD and LOAD relative to their control group respectively. Associations between age and synaptic loss were evaluated in different groups.

Result

EOAD and LOAD groups both displayed significant synaptic density across most areas of cerebrum cortex. Relative to LOAD group, EOAD group showed severer synaptic loss in Lateral Parietal lobe. In EOAD group, synaptic density in occipital lobe had positive association with age. While, in LOAD group, synaptic density in most areas of the cerebrum cortex had a negative association with age.

Conclusion

Our study suggested that the areas of synaptic loss were different between EOAD and LOAD.
Elevated iron levels in the older adult brain are associated with higher R2 relaxation rate in gray matter and more white matter hyperintensities: An ex‐vivo MRI, pathology and mass spectrometry study
Authors: Yasar Md Tahmid , Bush Ashley I. , Ayton Scott , Agarwal Puja , Agrawal Sonal , Bennett David A. , Schneider Julie A. , Arfanakis Konstantinos
Published: January 2025

Background

Elevated iron in brain is a source of free radicals that causes oxidative stress which has been linked to neuropathologies and cognitive impairment among older adults. The aim of this study was to investigate the association of iron levels with transverse relaxation rate, R2, and white matter hyperintensities (WMH), independent of the effects of other metals and age‐related neuropathologies.

Method

Cerebral hemispheres from 437 older adults participating in the Rush Memory and Aging Project study (Table 1) were imaged ex‐vivo using 3T MRI scanners. R2 maps were generated from multi‐echo spin‐echo data and then registered to an ex‐vivo brain template. WMH were segmented based on T2‐weighted images. WMH volume was normalized by the total hemisphere volume and then log‐transformed. Following ex‐vivo MRI, all hemispheres underwent neuropathologic assessment including Aß plaques, neurofibrillary tangles, LATE‐NC, hippocampal sclerosis, Lewy bodies, cerebral amyloid angiopathy, gross infarcts, microscopic infarcts, atherosclerosis, and arteriolosclerosis (Table 1). Inductively coupled plasma mass spectrometry was used to measure brain trace metal levels. The assessed metals included iron, boron, titanium, manganese, copper, zinc, selenium, rubidium, molybdenum, and mercury (Table 1). Linear regression was used to test the association of R2 and WMH burden with iron levels. All models were controlled for all other metals and neuropathologies listed above, demographics (age at death, sex, years of education), the presence of the APOE‐e4 allele, postmortem interval to fixation and to imaging, and scanner. Statistical analysis was performed using PALM, with tail‐accelerated 5,000 permutations. Statistical significance was set at p<0.05 after family wise error rate correction.

Result

The voxel‐wise analysis revealed a spatial pattern of higher R2 for higher iron levels, particularly in gray matter (Fig. 1). The pattern included basal ganglia structures such as the globus pallidus and putamen, and cortical regions including the precentral, postcentral and cuneus cortex (Fig. 1). Higher lobar and total WMH burden were also associated with higher iron levels (Fig. 2). No negative associations were observed.

Conclusion

This investigation combined ex‐vivo MRI, neuropathology and mass spectrometry in a community‐based older adults and showed that higher iron levels were independently associated with higher R2 in gray matter and higher WMH burden.
An explainable framework for convolutional neural networks detecting dementia in MRI scans
Authors: Singh Devesh , Grazia Alice , Dyrba Martin , Teipel Stefan
Published: January 2025

Background

With a global ageing population, there is an increasing demand for fast and reliable early diagnosis of individuals. Convolutional neural networks (CNNs) have an immense potential in assisting clinicians in diagnosing dementia. Regional atrophy patterns, which are visible in T1‐weighted MRI scans, have been consistently identified by the CNNs with high accuracy. However, there is still hesitation in the clinical adoption of CNNs, due to their black box nature. To alleviate these issues, we propose a framework for explainable CNN models to detect neurodegenerative diseases.

Method

Using data from multiple data cohorts (N>3000) we trained a robust DenseNet CNN model and utilised the feature attribution method ‘layer‐wise relevance propagation’ (LRP) to highlight image features found useful by the model. The FastSurfer tool was utilised to segment individual brain scans into various anatomical region of interests (ROIs). We created an ontology model for encoding the hierarchy of and relationships between neuroanatomical structures. Using linear regression models, controlling for common covariates such as age and sex, we quantified the volumetric deviance from normal levels (w‐scores) for all ROIs. These findings were visualised as summary plots. We integrate two different sources of information about pathology in the MRI scans, 1) the CNN predictive models and 2) the volumetric atrophy analysis. An algorithmic framework was developed to combine both of them and to select the information to be included in textual explanations for the CNN’s predictions (Figure 1).

Result

Our framework results in a modular pipeline where each component – attribution method, segmentation tool, ontology model, could be altered due to advancements or changes in the requirements. Our framework implements a plug‐and‐play functionality for interpreting trained CNN models. It assists an easy understanding of CNN’s prediction by generating textual and visual explanations for its findings, with variable degree of detail, focusing on specific ROIs or lobes.

Conclusion

Our study provides a proof‐of‐concept of utilizing a‐priori neuroanatomical information for explaining CNNs. This prototypical implementation for generating explainable AI is going to be tested by clinicians to evaluate its utility for assisting the diagnosis of dementia. We also plan to extend our framework to other neurodegenerative diseases.
Microstructural assessment of the locus coeruleus‐entorhinal cortex pathway and association with ATN markers in patients with cognitive impairment
Authors: Aiello Marco , Borrelli Pasquale , Cavaliere Carlo , Marizzoni Moira , Ribaldi Federica , Garibotto Valentina , Scheffler Max , Jelescu Ileana O , Jovicich Jorge , Salvatore Marco , Frisoni Giovanni B. , Pievani Michela
Published: January 2025

Background

This study investigated microstructural features of the locus coeruleus to entorhinal cortex pathway (LC‐EC) in relation to amyloid (A), tau (T), neurodegeneration (N) markers and cognitive impairment in memory clinic patients.

Method

124 participants were recruited from the Geneva Memory Clinic (n=30 cognitively unimpaired – CU; n=80 MCI and n=14 dementia ‐ CI) and underwent clinical assessment, 3T MRI scan including diffusion weighted imaging, amyloid PET, and tau PET. Diffusivity indices (fractional anisotropy ‐ FA, mean, axial and radial diffusivities ‐ MD, AxD, RD) were assessed in the LC‐EC pathway using a probabilistic atlas. A, T, N markers were assessed both as continuous and dichotomous measures. Differences in LC‐EC microstructure according to ATN markers and diagnosis were assessed with ANOVA models (FDR correction). Linear regression models were used to test whether LC‐EC pathway microstructure predicted cognitive impairment independently of ATN markers.

Result

Lower FA (p=0.020) and higher MD, RD and AxD (p<0.005) was observed in participants with tau positivity in the EC (TEC+, Braak stage >1) compared to tau negative subjects (TEC‐). Higher MD, RD and AxD was observed in neurodegeneration positive (N+, medial temporal atrophy) versus negative (N‐) participants (p<0.001), and CI versus CU (p<0.016). There was no difference in LC‐TE microstructure between amyloid positive (A+) and negative (A‐) subjects (p>0.05) nor between tau positive (T+; Braak stage >4) and negative (T‐) subjects (p>0.05). The regression model showed that RD of the LC‐EC tract was associated with clinical diagnosis and mini mental state examination score independently of ATN markers (p<0.05).

Conclusion

Our results indicate that LC‐EC microstructural measures, specifically RD, are sensitive in detecting CI and provide complementary information over ATN biomarkers. Associations with T suggest that LC‐TE microstructural alterations show regional specificity in the EC.
Intracranial atherosclerosis is linked to lower volume in the posterior portion of the hippocampus
Authors: Chowdhury Gulam Mahfuz , Tazwar Mahir , Evia Arnold M , Kapasi Alifiya , Agrawal Sonal , Bennett David A. , Schneider Julie A. , Arfanakis Konstantinos
Published: January 2025

Background

Intracranial atherosclerosis is a common age‐related neuropathology that has been linked to cognitive decline and dementia and often mixed with Alzheimer’s and other neuropathologies. But the association of atherosclerosis with brain morphometric abnormalities has not been explored. This work combined Deformation‐based morphometry on ex‐vivo MRI with detailed neuropathological examination in a large number of community‐based older adults to investigate the association.

Method

Hemispheres from 891 community‐based older adults from four cohort studies of aging: the Rush Memory and Aging Project, Religious Orders Study, Minority Aging Research Study, and African American Clinical Core of the Rush Alzheimer’s Disease Research Center were imaged ex‐vivo on 3T clinical MRI scanners using a multi‐echo spin‐echo sequence with a voxel size = 0.6×0.6×1.5 mm3. All images were non‐linearly registered to an ex vivo brain hemisphere template using ANTs. The logarithm of the Jacobian determinant of the deformation fields was calculated in each voxel and the resulting maps were smoothed using a Gaussian filter with a FWHM = 4mm. All hemispheres underwent detailed neuropathologic examination. The assessed pathologies included atherosclerosis, arteriolosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts, Alzheimer’s pathology, Lewy bodies, limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change, and hippocampal sclerosis. Voxel wise linear regression was used to test the association of atherosclerosis with deformations shown in the smoothed LogJ maps, controlling for other age‐related neuropathologies, demographics (age at death, sex, years of education), postmortem interval to fixation, postmortem interval to imaging, and scanner (Fig. 1,2). The FSL PALM tool with 1000 permutations, threshold‐free cluster enhancement, and tail acceleration was used for the statistical analysis. Associations were considered significant at p<0.05 after family‐wise error rate correction for multiple comparisons.

Result

Voxel‐wise linear regression showed that intracranial atherosclerosis was significantly associated with lower volume in the posterior body and tail of the hippocampus (p<0.05), independently of the effects of other age‐related neurodegenerative and vascular pathologies (Fig.3). No part of the brain showed significantly higher volume with atherosclerosis.

Conclusion

This work demonstrated that intracranial atherosclerosis is associated with lower volume of the posterior body and tail of the hippocampus. This finding is of great interest due to the important role of the hippocampus in cognition.
Aberrant resting‐state functional connectivity of the default‐mode network relates to cognitive decline in the earliest Alzheimer’s continuum
Authors: Lizarraga Aldana , Kassinopoulos Michalis , González‐de‐Echávarri José María , Huguet Jordi , Sánchez‐Benavides Gonzalo , Brugulat‐Serrat Anna , Suarez‐Calvet Marc , Milà‐Alomà Marta , Blennow Kaj , Zetterberg Henrik , Kollmorgen Gwendlyn , Quijano‐Rubio Clara , Molinuevo Jose Luis , Gispert Juan Domingo , Cacciaglia Raffaele
Published: January 2025

Background

Amyloid‐ß (Aß) pathology affects resting state functional connectivity (RSFC), even in cognitively unimpaired (CU) individuals. However, the impact of such an aberrant RSFC on cognitive decline is yet to be determined. Moreover, most prior research focused on fibrillary Aß deposition to predict RSFC, while early Aß dysmetabolism as reflected by cerebrospinal fluid (CSF) concentrations has received less attention. We assessed RSFC as a function of both CSF Aß and p‐tau in CU individuals, and further analyzed the impact of biomarker‐dependent RSFC on the longitudinal cognitive performance.

Method

Analyses were conducted in 328 CU individuals from the ALFA cohort (mean age = 60.8, SD = 4.74) with available CSF Aß, p‐tau, resting‐state fMRI and longitudinal cognitive assessment (average follow‐up time = 3.35 years, SD = 0.53). CSF Aß42 and Aß40 were assessed with the exploratory NeuroToolKit, while p‐tau181 was measured with the Elecsys® Phospho‐Tau (181P) CSF immunoassay (both Roche Diagnostics International Ltd). RSFC was computed amongst 246 brain regions of the Brainnetome atlas using the CONN toolbox, selecting a cluster threshold of p<0.005. The effects of CSF biomarkers on RSFC were adjusted by age, sex, years of education and APOE‐e4 status.

Result

Of the entire sample, 38.4% had positive CSF Aß42/40 markers. Low CSF Aß42/40 ratios were associated to a higher RSFC between visual areas and anterior as well as posterior subdivisions of the default‐mode network (DMN) (Fig. 1). These results survived a family‐wise error rate p‐value<0.005. High levels of CSF p‐tau were related to a higher RSFC between inferior temporal areas and the anterior DMN, as well as a reduced RSFC between visual and the somatomotor network. The Aß‐related higher RSFC significantly predicted longitudinal cognitive decline in PACC, episodic memory (EM) and executive control (EC), in models adjusted by CSF biomarkers (Fig. 2), and further modulated the association between CSF Aß42/40 and PACC longitudinal decline (Fig. 3)

Conclusion

In CU individuals, CSF Aß and p‐tau affect RSFC in networks relevant for cognitive performance. Low CSF Aß42/40 was related to hyperconnectivity between the DMN and the visual system. Lack of DMN segregation as a function of CSF Aß42/40 may represent a driving mechanism of cognitive decline in the earliest Alzheimer’s continuum.
The relationship between sex‐steroid hormones and brain volume variation in aging
Authors: Magalhães Thamires Naela Cardoso , Jackson Trevor Bryan , Gonzales Ivan Herrejon , Bernard Jessica A
Published: January 2025

Background

Older females, particularly susceptible to Alzheimer's disease (AD), may be affected by hormonal fluctuation during life. We aim to investigate the relationship between changes in brain volume and sex steroid hormones over time. We hypothesize that levels of sex hormones (17ß‐estradiol, progesterone, and testosterone) relate to changes in brain volume, especially in the hippocampus (HPC) and cerebellum (CB). The growing relevance of the CB in cognitive functions supports the exploration of potential associations in AD.

Method

Subjects underwent structural magnetic resonance imaging (MRI) in conjunction with a series of cognitive and motor tasks. Roughly 12 months later, a subgroup of 91 participants—comprising 27 individuals in early middle age (average age 41±4.7 years; 13 females), 32 in late middle age (average age 58±4 years; 19 females), and 32 older adults (average age 72±6 years; 16 females)—underwent follow‐up MRI and task assessments (such as MoCA, digit, and symbol span). Saliva samples were collected during both visits for the quantification of sex hormones.

Results

Analyzing longitudinal data with regression models that included all subjects, we found that baseline T and P levels were predictive of increased volumes in the bilateral cerebellar cortex and left HPC, respectively. In essence, individuals with higher levels of these basal hormones exhibited greater volumes over time. However, upon dividing the sample by sex, the result about P levels remained consistent in the female group. This suggests that, in females, higher baseline P levels continued to predict a greater volume in the left HPC (r = 0.351, p = 0.009; R2= 0.57, p=0.001). Upon closer examination of the groups independently, we identified positive correlations between baseline P levels and changes in volume (delta) of the left hippocampus (r = 0.441, p = 0.03) specifically in the middle‐aged group.

Conclusion

Both T and P levels show a protective effect against age‐related structural changes. Ongoing analyses will explore this phenomenon further, with a focus on observing hormonal stages within the sample for clearer understanding.
Contrast of Early Phase Amyloid PET
Authors: Kameyama Masashi , Sakata Muneyuki , Ishibashi Kenji , Tago Tetsuro , Kamitaka Yuto , Toyohara Jun , Ishii Kenji
Published: January 2025

Background

The method of obtaining pseudo‐cerebral blood flow images from the initial minutes of amyloid PET scans has been proposed. This technique proves to be highly valuable as it not only indicates the presence of amyloid accumulation but also reveals sites of neurodegeneration. However, the obtained early images represent the K1 image rather than cerebral blood flow. Consequently, the contrast in early images from amyloid PET tracers is thought to be compromised when compared to cerebral blood flow images.

Method

To enhance the contrast in early images obtained from amyloid PET tracers and thereby improve diagnostic accuracy, we developed a method for contrast recovery and established a methodology for determining the parameter involved in achieving this contrast recovery, drawing insights from a thorough literature review. Additionally, we conducted a comparative analysis involving PiB’s early images and FDG, investigating their respective contributions.

Result

Our study demonstrated a strong correlation between FDG and early images of PiB, with relatively inconspicuous underestimations in high‐blood‐flow regions.

Conclusion

While we theoretically established a method to recover the contrast in early images, our findings suggest that amyloid PET tracers may exhibit a higher permeability‐surface area product than anticipated. This observation raises the possibility that, without correction, these tracers might inherently provide sufficient contrast.
Cortical Myelination, Cognition, and Cardiovascular Fitness: New Insights using Advanced Magnetic Resonance Relaxometry
Authors: Guo Alex , Faulkner Mary E , Gong Zhaoyuan , Bae Jonghyun , Laporte John P , Bouhrara Mustapha
Published: January 2025

Background

Alterations in grey matter (GM) are known to contribute to cognitive decline in aging and dementia. Recent evidence suggests that individuals with higher cardiorespiratory fitness (CRF) may have a lower risk of GM atrophy and subsequent cognitive decline. However, the role of cortical myelination in cognitive decline and its association with CRF remains elusive. We used two microstructure MRI measures: MWF, which is a direct measure of myelin content, and R1, which is sensitive to lipids, the main constituents of myelin, to first, investigate the relationship between myelination and longitudinal changes in cognition, and second, determine whether higher CRF is associated with higher myelination in cortical regions.

Method

123 participants (55.1±20.4 years) underwent our BMC‐mcDESPOT MRI protocol for MWF and R1 mapping with mean values calculated in 6 GM regions (Table 1). Cognitive performance scores were obtained retrospectively at the time of MRI and before. VO2max, the gold standard measure of CRF, was also measured using our established treadmill protocol. The association between each MRI measure and changes in cognition was evaluated using a linear mixed‐effects model. The association between VO2max and each MRI measure was assessed using a multiple linear regression model. Relevant covariates were included in both models (Fig1. caption & Fig.2 caption).

Result

Lower myelin content in various GM regions, indicated by lower MWF and R1 values, is associated with a steeper decline in all cognitive domains (Fig. 1). These associations were prominent with processing speed and executive function (Table 1A). Moreover, higher VO2max was associated with higher myelin content in several GM regions (Table 1B). An interaction between age and VO2max revealed a steeper positive slope in the older age group, suggesting that the beneficial effect of VO2max on MWF is more pronounced at older ages; and a negative slope in the lower VO2max group, indicating that lower VO2max levels are associated with more rapid demyelination with advanced ages (Fig.2, Table 1B).

Conclusion

These original findings highlight the importance of cortical myelination in cognitive functioning, and suggest that improving CRF could represent a non‐pharmaceutical intervention toward better myelination and offset subsequent cognitive decline.
Development and Validation of Natural Language Processing (NLP)‐Based Risk Prediction Model for Cognitive Impairment in Geriatric Patients
Authors: Soleimani Laili , Cheng Fu‐Yuan , Sano Mary , Kia Arash
Published: January 2025

Background

Dementia poses a significant global crisis, yet 60% of cases go undetected, particularly among specific sub‐populations. Timely diagnosis is crucial for implementing early intervention strategies. Challenges of current screening tools (e.g., Montreal Cognitive Assessment (MOCA) and Mini‐mental Status Exam (MMSE)) include their rule‐based nature, time‐consuming administration and potential bias against individuals with lower education or different socioeconomic backgrounds.

Method

In this study, we created a patient cohort within Mount Sinai Health System, identifying individuals at high‐risk for cognitive impairment using MMSE scores 23 and below. Extracting clinical notes from inpatient and outpatient settings, we applied specific sampling logic to select the last five notes for each patient before their MMSE. Utilizing word‐embedding techniques, we vectorized sentences and input these vectors into a deep neural network for Named Entity Recognition to extract clinical concepts (e.g diagnosis, signs and symptoms, medications). A psychiatrist reviewed and selected 337 features based on their frequency in the cohort and clinical relevance. Using these features, we created a map to generate feature vectors, and following a train‐test split, 70% of the data was used to train a classifier using the random forest algorithm. The remaining 30% of the cohort was employed for validation purposes.

Result

Out of 4,366 patients, with documented MMSE scores from 2011 to 2023, 73% had one MMSE, and 29% scored below 24. The developed model demonstrated an AUC ROC of 0.93. At a threshold of 0.5, it showed a sensitivity of 0.86 and specificity of 0.85 in the validation set. On the test set, the AUC ROC was 0.68, with a sensitivity of 0.62 and specificity of 0.63 at a threshold of 0.5.

Conclusion

The development and validation of this digital tool exemplify translational research that leverages Real‐World Data (RWD) from EMR. The tool aims to assist clinicians in efficient dementia detection across different stages of the disease. Our next phase involves optimizing the feature engineering, fine‐tune the model, and deploying it in the production environment. This will facilitate automated screening of geriatric patients during clinical encounters at Mount Sinai Hospital, allowing us to measure the tool's prospective performance.
Dynamic Changes in Quantitative MRI‐based Biomarkers and Its Association with Pathology of Alzheimer’s Disease – A Longitudinal Study
Authors: Fan Xiang , Cai Yuan , Liu Wanting , Zhao Lei , Luo Yishan , Shi Lin , Mok Vincent Chung Tong
Published: January 2025

Background

Alzheimer’s disease (AD) resemblance atrophy index (AD‐RAI) is a novel MRI‐based machine‐learning derived biomarker for AD that is valid in the detection of early AD. We aimed to investigate the association between the serial change of AD‐RAI and cognitive progression overtime among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects with and without A+T+ (i.e., Aß+ and Tau+) and to compare it with other conventional MRI biomarkers (i.e., hippocampal volume (HV), hippocampal fraction (HF), brain parenchymal volume (BPV) and fraction (BPF)), which have been used in the past as surrogate markers for AD.

Method

We selected participants from the ADNI databases and included those aged 55 to 90 years, diagnosed with CU and MCI at baseline with high‐quality volumetric MRI data and CSF at baseline, and at least once matched T1W scans and CSF during follow‐up. We define A+T+ based on the threshold value of Aß1‐42 and ptau in CSF. A total of 168 participants were recruited with serial MRI scans and corresponding CSF in total. We assessed longitudinal changes of the MRI biomarkers (i.e., AD‐RAI, HV, HF, BPV, BPF) in correlation with changes in time and conversion status with and without A+T+. We used a linear mixed‐effects model (LMM) in SPSS 26.0 to explore the serial changes of the imaging biomarkers and interaction effects with and without A+T+ over time, and further explore the association between dynamic CSF Aß1‐42 and dynamic changes in the imaging biomarkers’ interaction effects over time.

Result

AD‐RAI with A+T+ increased significantly faster than non‐A+T+ over time (P < 0.05), while HV and HF with A+T+ decreased significantly faster than non‐A+T+ over time (P < 0.05, respectively), which performed better than BPV/BPF. Serial AD‐RAI was significantly associated with changes in CSF Aß1‐42 over time, which outperforms other imaging biomarkers.

Conclusion

Serial AD‐RAI outperforms other conventional biomarkers in correlating with AD pathologies. It may be used as a surrogate marker for monitoring disease progression or treatment response in AD.
Application value of structural MRI combined with ASS1 in early diagnosis of Mild Cognitive Impairment
Authors: Chen Lele , Fan Xiang , Shan Hui , Yu Keyan , Lu Gaigai , Wei Zhuonan , Cheng Guanxun
Published: January 2025

Background

Mild cognitive impairment (MCI) refers to a transitional stage between the cognitively unimpaired (CU) and dementia, which is probable in the Alzheimer’s disease (AD) continuum. Neuropsychological assessments and structural MRI are primary clinical examinations applied for diagnosing MCI. Hippocampal volume (HV) and medial temporal lobe atrophy (MTA) as recognized AD biomarkers are the most frequently used imaging markers in clinical application. However, HV or MTA is not sensitive enough in the early stage of AD. Recently, blood‐based biomarker analysis has demonstrated great potential for early AD diagnosis because it is simple and less invasive. It has been shown that argininosuccinate synthetase (ASS1) expression is increased in Alzheimer’s disease neurons and glial cells, which also correlates with inducible nitric oxide synthase (iNOS) expression, and that there is a link between the increased NO production observed in Alzheimer’s disease brains and iNOS expression. We aim to study whether ASS1 can provide additional value compared with HV in diagnosing MCI and validate the diagnostic utility of the combined model.

Method

Twenty MCI patients and 20 CU were recruited and underwent neuropsychological assessment, MRI examinations, and the collection of blood. Protein quantification was analyzed by high‐resolution tandem mass spectrometry (MS/MS), and the ROC curve was plotted for selected biomarkers. The automated structure tool and SPSS 26.0 were used to analyze the HV and ASS1. We investigated the area under curve (AUC) of HV, and the combined model using both ASS1 and HV based on the logistic regression. The Delong test is used to compare the combined model with the single HV.

Result

The AUC of diagnosing MCI by HV was 0.788 (95%CI: 0.629 ‐0.901). When combining HV with ASS1, the AUC increased to 0.938 (95%CI: 0.813‐0.989). The Delong test results indicated a significant difference between the single HV and the combined model. (P = 0.0188).

Conclusion

Combining plasma ASS1 could provide significantly additional value in detection of MCI, which also means plasma ASS1 and HV may be a potential early biomarker combination in diagnosing early AD.
GENETIC DELETION OF THE PRESINILIN‐LIKE PEPTIDASE SPPL2B SIGNIFICANTLY REDUCES NEUROINFLAMMATION AND HALTS PRODUCTION AND PLAQUE DEPOSITION IN PRE‐CLINICAL MODELS OF Alzheimer's DISEASE
Authors: Badman Jack , Chen Gefei , Garcia Sandra Pérez , Nilsson Per , Tambaro Simone
Published: January 2025

Background

Signal Peptide Peptidase‐Like 2b (SPPL2b) is relevant for AD, being a brain‐specific intramembrane protein involved in the cleavage of Alzheimer's disease (AD)‐related proteins, such as BRI2, inflammatory‐related proteins like CD74, TNFalpha, and Clec7a, and synaptic proteins Neuregulin‐1 and VAMP 1‐4. SPPL2b is specifically expressed in the hippocampus and cortex. The cleavage of TNFalpha by SPPL2b promotes the inflammatory pathway. Conversely, the SPPL2b substrate BRI2 regulates amyloid precursor protein (APP) cleavage and subsequent Aß production. This work explores the pathophysiological role of SPPL2b in AD pathogenesis and investigates the potential of inhibiting SPPL2b activity as a novel therapeutic strategy.

Method

To characterize the role of SPPL2b in the APP cleavage process and neuroinflammation, we used neurons and glia primary cell cultures from WT and SPPL2b‐deficient mice. Furthermore, we assessed the therapeutic potential of inhibiting SPPL2b by employing a new AD mouse model generated through crossbreeding state‐of‐the‐art AppNL‐G‐F knock‐in mice with SPPL2b‐deficient mice. Cells and mouse brain samples were analyzed through western blotting, immunoprecipitation, and immunofluorescence. Aß levels were quantified using ELISA kits.

Result

The results showed a significant increase in BRI2, followed by a substantial reduction in soluble APP, Aß40, and Aß42 levels in the conditioned media of SPPL2b KO neurons. Immunoprecipitation of BRI2 from the cortex of those mice revealed an increased interaction between BRI2 and APP in SPPL2b KO/AppNL‐G‐F mice. Most importantly, a notable decrease in brain Aß plaque deposition and a significant decrease in both cortical and hippocampal gliosis were observed at 4 months‐of‐age in SPPL2b KO/AppNL‐G‐F mice.

Conclusion

The results outlined in this study support a relevant connection between SPPL2b and the development of Aß pathology in AD. In a global scenario characterized by the need to identify novel strategies to prevent and counteract AD progression, this study highlights and strengthens the importance of SPPL2b as a novel therapeutic approach for AD.
Chronic Medical Conditions and Dementia Risk: Brain Age Models for Quantifying Impact and Understanding Mechanisms
Authors: Yu Xi , Przybelski Scott A. , Reid Robert I. , Gebre Robel K , Lesnick Timothy G. , Vassilaki Maria , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Vemuri Prashanthi
Published: January 2025

Background

Chronic medical conditions increase dementia risk, and the mechanism may be captured computationally by measures of accelerated brain aging. We hypothesized that quantifying the impact of chronic conditions on GM and WM aging will aid in measuring the differential impact of each condition on brain aging and shed light on the mechanisms through which they increase dementia risk. We specifically focused on microstructural brain changes with Neurite Orientation Dispersion and Density Imaging (NODDI) based on advanced diffusion MRI ‐ neurite density index (NDI), free water fraction (FWF), and orientation dispersion index (ODI).

Method

We identified 1123 participants [913 cognitively unimpaired (CU), 114 with MCI, 96 with AD] from the Mayo Clinic Study of Aging (MCSA) and Mayo ADRC with multi‐shell diffusion MRI. MCSA participants had chronic medical conditions’ diagnosis (based on US Dept of HHS) extracted from the electronic health care records. Using the BorutaSHAP algorithm on NDI, ODI, and ISOVF features from GM and WM separately, we constructed two distinct brain age models for GM and WM. First, we evaluated the usefulness of the predicted age gap (PAG), which is the difference between predicted age by model and chronological age, for both WM and GM NODDI models in CU/MCI/AD. We then developed separate GM and WM models for each condition using samples from condition‐negative participants to compare PAG of GM and WM for that condition.

Result

There was greater PAG in GM (avg = ) than WM (avg = 9.15 yrs) in MCI/AD participants (Fig. 1A). Each condition shifted the GM PAG by 0.10 to 3.56 years and WM PAG by 0.38 to 3.72 years with stroke and congestive heart failure showing the greater PAG overall for GM and WM PAD respectively (Fig. 2). COPD, stroke, chronic kidney disease, hypertension had comparatively greater GM PAG than WM PAG; while hyperlipidemia, congestive heart failure and coronary artery disease had greater WM PAG than GM PAG (Fig. 1B).

Conclusion

Chronic conditions are associated with increased GM and WM Brain aging models can aid in quantifying the impact of chronic conditions on dementia risk and understanding mechanisms.