bluuebunny/crossref_metadata_2025_split huggingface dataset:
Specific damages to olfactory‐related structures and their relation to episodic memory in Individuals at Risk of Alzheimer’s Disease
Authors: Jobin Benoît , Frasnelli Johannes , Boller Benjamin 
Published: December 2023

AbstractBackgroundOne of the major challenges in the diagnosis of Alzheimer’s disease (AD) is to increase the specificity of the early diagnosis. While episodic memory impairment is a sensitive marker of AD, other markers are needed to improve diagnostic specificity. A promising biomarker might be a cerebral atrophy of the central olfactory processing areas in the early stages of the disease since an impairment of olfactory identification is present at early clinical stages of AD. Our goal was to evaluate whether reduced grey matter volume (GMV) in the central olfactory processing regions could be observed in early and preclinical stages of AD. We also aimed to verify if GMV of central olfactory processing regions is associated with episodic memory performance.Method166 participants from the Consortium for the Early Identification of Alzheimer’s Disease‐Quebec (CIMA‐Q) (92 with subjective cognitive decline ‐ SCD, 40 with mild cognitive impairment ‐ MCI and 34 cognitively healthy controls) were included. We performed regions of interest (ROI) analysis using a mask of the regions that are activated during olfactory stimulation. We also extracted GMV outside ROIs, representing non‐olfactory areas of these regions, i.e., regions which do not respond to olfactory stimulation. Verbal episodic memory was assessed using a free word recall task from Memoria Word Recall test.ResultCompared to controls (p = .019) and participants with SCD (p = .003), participants with MCI exhibited a smaller total GMV of central olfactory processing regions, with a significant interaction effect between region and group (p = .004). Specifically, the piriform cortex, amygdala, entorhinal cortex, and left hippocampus were significantly smaller in individuals with MCI (p = .05, corrected). In contrast, when comparing GMV outside ROIs between the three groups, there was no such interaction between region and group (p = .428). Additionally, GMV in the olfactory areas of the piriform cortex, amygdala, and left hippocampal gyrus was correlated with episodic memory performance, while GMV in the non‐olfactory areas of the left hippocampus and left parahippocampal gyrus was correlated with episodic memory performance (p = .05, corrected).ConclusionThere is a specific neurodegeneration of limbic and medial‐temporal olfactory‐structures in MCI, GMV of these regions being related to cognitive performance.
Structural brain network degeneration associated with agitation in dementia
Authors: Jenkins Lisanne M , Gupta Sonya M , Kouchakidivkolaei Maryam , Sridhar Jaiashre , Rogalski Emily J , Weintraub Sandra , Popuri Karteek , Rosen Howard J. , Wang Lei 
Published: December 2023

AbstractBackgroundAgitation is a behavioral syndrome involving increased motor activity, restlessness, aggressiveness and emotional distress. Its has a 30% prevalence across multiple types of dementia and is associated with negative outcomes, including reduced quality of life, caregiver distress, and mortality. Pharmacological treatment risks serious side effects, including mortality. Understanding brain network topology could provide insights into novel treatment methods.MethodParticipants comprised 600 subjects from 3 existing databases: the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Frontotemporal Lobar Degeneration Neuroimaging Initiative (NIFD) and the Mesulam Center for Cognitive Neurology and Alzheimer’s Disease at Northwestern University. Participants were clinically diagnosed with either behavioral variant frontotemporal dementia (bvFTD), mild cognitive impairment (MCI), dementia of the Alzeheimer type (DAT) or cognitively normal (CN). The Neuropsychiatric Inventory Questionnaire (NPI‐Q) caregiver rating was used to determine whether individuals were agitated or not. Morphometric similarity networks (MSNs) were generated from Freesurfer statistics calculated from T1‐weighted MRIs. 7 surface‐based cortical metrics (e.g. gray matter volume, surface area) were calculated for each of 360 parcels. Pairwise inter‐parcel Pearson correlations of feature vectors were calculated to produce a morphometric similarity matrix for each individual. We calculated sub‐matrices for salience (SN) cognitive control (CCN) and default mode networks (DMN). Brain Connectivity Toolbox calculated transitivity and global efficiency of each network. Metrics were calculated at different thresholds to ensure the results were not threshold‐dependent. We calculated 2 (Agitation present/absent) x 4 (Diagnosis) repeated measures ANCOVAS for transitivity and global efficiency for each network. Covariates were age, sex, race, database, education, ICV, CDR‐SB and days MRI‐NPI‐Q.ResultFor the SN, people with Agitation had significantly lower global efficiency than people without Agitation (Figure 1). There were no significant effects of diagnosis or interaction. For the CCN, people with agitation had significantly lower transitivity than people without Agitation (Figure 2). There were no significant effect of diagnosis or interaction.ConclusionAcross different forms of dementia, Agitation is associated with reduced integration (global efficiency) of the salience network, and reduced segregation (transitivity) of the cognitive control network. Interventions that alter these topological network features may be effective in reducing agitation in dementia, regardless of clinical diagnosis.
Hippocampal subfield volumes and memory performances: associations with stimulus modality and free recall or recognition
Authors: Aumont Etienne , Bussy Aurelie , Bezgin Gleb , Therriault Joseph , Savard Melissa , Arias Jaime Fernandez , Poltronetti Nina Margherita , Pallen Vanessa , Thomas Emilie , Vitali Paolo , Chakravarty Mallar , Bedard Marc‐Andre , Rosa‐Neto Pedro 
Published: December 2023

AbstractBackgroundAge‐related memory decline is well associated with hippocampal atrophy, although the specific role of hippocampal subfields in memory function has not been thoroughly investigated yet. In this study, we investigated the associations between hippocampal subfield volumes and free recall and recognition performances in verbal and visual memory tasks in older adults without dementia.MethodWe selected 97 right‐handed participants without dementia aged 60 to 85, 42 males, from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. From T2‐weighted MRIs with 0.7*0.7*1mm voxel size, the hippocampi were segmented five subfields: 1) DG (DG); 2) CA2 with CA3 (CA2/CA3); 3) CA1; 4) strata radiatum, lacunosum and moleculare (SRLM); and 5) subiculum by using the MAGeT‐Brain algorithm. Memory was assessed with Rey Auditory Learning test for verbal free recall (RAVLT7) and recognition (RAVLT‐R), and with Aggie Figure Learning test for visual free recall (AFLT7) and recognition (AFLT‐R). Linear models were used to test the association between hippocampal subfield volumes and memory performances with age, sex and total intracranial volume as covariates (p<0.05, corrected for false discovery rate)ResultThe volumes of bilateral CA1 and SRLM were significantly associated with RAVLT7 and RAVLT‐R. The right DG volume was significantly associated with AFLT7 and RAVLT7. AFLT7 was also associated with the volume of right CA2/CA3 while AFLT‐R was not associated with any hippocampal subfield (see Figures 1 & 2).ConclusionOur results are consistent with the view that hippocampal subfields contribute differently to memory traces: CA1 for recollection that requires contextual information; the DG for pattern separation (creating new distinct representations of each stimulus); and CA3 for pattern completion (the recollection of a stimulus from a partial memory). Contextual information is more important when recollecting known words, while distinct and efficient encoding may be especially useful for search strategies inherent to free recall. Pattern completion could be particularly useful to efficiently recollect visual abstract figures based on visual features during free recall. Overall, this shows that hippocampal subfield segmentation offers a better understanding of their distinctive roles in cognition.
Impairment of the locus coeruleus‐transentorhinal cortex pathway in persons at risk of Alzheimer’s disease
Authors: Quattrini Giulia , Saglia Silvia , Marizzoni Moira , Mega Anna , D'Aprile Ilari , Cattaneo Annamaria , Gasparotti Roberto , Bortoletto Marta , Pievani Michela 
Published: December 2023

AbstractBackgroundRecent studies reported microstructural alterations in the locus coeruleus ‐ transentorhinal cortex (LC‐TEC) pathway in patients with Alzheimer’s disease (AD) but data in subjects at risk of AD (i.e., cognitively intact APOEe4 carriers) are missing. In this study, we apply in‐vivo diffusion weighted images (DWI) to study the effect of APOEe4 on the LC‐TEC pathway in cognitively unimpaired subjects.MethodForty‐five participants (14 APOEe4 carriers: age = 68±7 years, 45% females, MMSE score = 29±0.9; 31 non‐carriers: age = 68±6 years, 57% females, MMSE score = 30±0.6) underwent multimodal 3T MRI and multidomain neuropsychological exams. DWI were corrected for distortions with topup and eddy tools (part of FMRIB’s Software Library – FSL). Microstructural measures as fractional anisotropy (FA), mean (MD), axial (AxD), and radial (RD) diffusivities maps were estimated using the FMRIB’s Diffusion Toolbox (part of FSL) after the exclusion of cerebrospinal fluid voxels. Microstructural integrity of LC‐TEC was assessed using a thresholded probabilistic atlas non‐linearly warped on native maps with FNIRT (part of FSL). A Bonferroni multivariate generalized linear model, corrected for age and sex, was conducted to compare the diffusivity indexes between APOEe4 carriers and non‐carriers. Association with memory functioning (immediate and delayed recall) was also tested using Spearman’s rank correlations test.ResultAPOEe4 carriers and non‐carriers were comparable for cognitive performance (p>.246). Compared to non‐carriers, APOEe4 carriers showed lower FA (p = 0.048) and higher RD (p = 0.036) in the left LC‐TEC. In APOEe4 carriers, left RD negatively correlated with both immediate (rho = ‐0.808, p<0.001) and delayed (rho = ‐0.673, p = 0.025) memory recall.ConclusionMicrostructural alterations of the LC‐TEC pathway are detectable in subjects at‐risk for AD and correlate with lower memory performance. These preliminary results support the view that LC‐TEC impairment may play a role in AD pathophysiology since its early stages.
Apoe ε4 exacerbates age‐dependent decline of cortical microstructural changes in cognitively normal midlife individuals: the PREVENT‐Dementia and ALFA studies
Authors: Mak Elijah , Dounavi Maria‐Eleni , Operto Grégory , Ziukelis Elina T , Jones P Simon , Low Audrey , Swann Peter , Newton Coco , Muniz‐Terrera Graciela , Malhotra Paresh A , Koychev Ivan , Falcon Carles , Mackay Clare , Lawlor Brian , Naci Lorina , Wells Katie , Ritchie Craig W , Ritchie Karen , Su Li , Gispert Juan Domingo , O'Brien John T 
Published: December 2023

AbstractBackgroundThe APOE e4 allele is the primary genetic risk factor for the sporadic type of Alzheimer’s disease (AD). However, the mechanisms by which APOE e4 is associated with neurodegeneration are still poorly understood. Here, we applied the NODDI to characterise the effects of APOE e4 and its interactions with age and education on cortical microstructure in cognitively normal individuals.MethodData from 1954 participants were included from the PREVENT‐Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non‐carriers, 757 APOE e4 carriers). T1 MRIs were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index (ODI) maps from diffusion MRI. Primary analyses were focused on the (a) main effects of APOE e4, and the (b) interactions of APOE e4 with age and education on lobar and vertex‐wise ODI and implemented using Permutation Analysis of Linear Models.ResultAPOE e4 carriers and non‐carriers did not differ in terms of lobar ODI. However, there were APOE e4 × age interactions in the temporo‐parietal and frontal lobes (TFCE p FWE < 0.05), indicating steeper age‐dependent ODI changes in APOE e4 (Figure 1). Lobar analyses revealed decreased temporal ODI in APOE e4 carriers after age = 60 (Figure 2). There was a three‐way interaction of APOE e4 x age x education; steeper age‐related ODI declines among APOE e4 carriers with lower years of education (Figure 3, TFCE p FWE < 0.05). There were no significant main effects or interactions of APOE e4 on cortical thickness.ConclusionWe found novel evidence that APOE e4 worsened age‐related ODI decreases in brain regions typically associated with atrophy patterns of AD. This finding also suggests that APOE e4 may hasten the onset age of dementia by accelerating age‐dependent reductions in cortical ODI, although additional studies are needed to verify this hypothesis. These findings were independent of cortical thickness. While conclusions are limited due to the cross‐sectional design, our findings imply that APOE e4 related changes in ODI may precede macroscopically visible changes in cortical atrophy and may be a more sensitive marker of incipient AD.
Which Convolutional Neural Network Architecture is the Best at Detecting Alzheimer’s Disease: A head‐to‐head Comparison Using Relevance Maps
Authors: Singh Devesh , Teipel Stefan , Dyrba Martin 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is a neurodegenerative disorder which causes gradual and irreversible damage to the brain. These patterns of brain damage can be detected using T1‐weighted MRI scans by modern neuroimaging methods. Recent developments in convolutional neural networks (CNN) have achieved promising results in various computer‐vision tasks. Feature attribution methods such as layer‐wise relevance propagation (LRP) allow tracing back the information flow in CNNs to derive relevance heatmaps, which approximate the contribution of the input image regions on the model decision. We addressed the open question, which of the most common CNN architectures is best suited for medical image detection, i.e. AD classification based on MRI data.MethodFour CNN architectures are widely used in the literature: AlexNet, VGG, ResNet, and DenseNet. We adapted these CNN architectures to be used with 3D brain MRI data and trained the models on a heterogeneous dataset with N>2200 from four large studies. We applied tenfold cross‐validation and additionally evaluated the results on an independent test dataset.ResultThe more complex CNN architectures DenseNet and ResNet with ‘skip connections’, provided the best results for both group separation tasks of ‐ AD vs Cognitively Normal (CN), and Mild Cognitive Impairment (MCI) vs CN, although the overall differences in accuracy did not reach statistical significance. From the mean relevance maps obtained using the LRP relevance propagation method (see Fig. 1.), we found that DenseNet focused primarily on the medial temporal lobe and posterior cingulate cortex atrophy. ResNet’s mean relevance maps were more noisy and heterogeneous.ConclusionDenseNet provided the most focused relevance maps, best matching apriori expectations of brain regions contributing to the detection of AD. Its ‘dense connections’ between the layers enabled a highly efficient information flow at various scales. Our evaluation setup also demonstrated the value of a holistic evaluation of models, where relevance maps are used in combination with classical performance metrics.
Longitudinal age effects in microstructures of the hippocampal subfields
Authors: Zia Ghina , Shahid Syed Salman , Risacher Shannon L , Saykin Andrew J. , Wu Yu‐Chien 
Published: December 2023

AbstractBackgroundThe human brain undergoes considerable morphologic change with age, which is one of the primary risk‐factors for Alzheimer’s disease (AD). Age‐related microstructural changes in the brain may be quantified by advanced diffusion MRI (dMRI) with compartment modeling. In this longitudinal study, we aimed to investigate the effects of age on the hippocampal subfields, one of the brain regions vulnerable to the early stages of AD.MethodThirty‐seven cognitively normal older adults (70.6 ± 6.7 years) were recruited from the Indiana ADRC. Participants received a baseline and a follow‐up MRI scan over 24 ± 11.7 months with a Siemens 3T Prisma scanner using a 64‐channel head coil. We applied grey‐matter‐specific multi‐compartment diffusion model (cortical‐neurite orientation dispersion and density imaging) to derive diffusion microstructural metrics, namely orientation dispersion index (ODI), volume fractions of fast isotropic diffusion (VFISO), and intracellular‐space (VFIC) in the hippocampal‐subfields (CA1‐3, CA4 and dentate gyrus (CA4‐DG), and subiculum) [1]. To study the longitudinal age effects, we investigated the rate of change in the diffusion metrics and the association between the rate of change and age. Linear regression analysis was performed using SPSS software and adjusted for sex, education, APoE e4 status, and subfield volumes (Table 1).ResultAll subjects had normal cognition (i.e., MoCA and MMSE, Table 1). The volumes of CA1‐3 and subiculum significantly decreased between the baseline and follow‐up MRI scans, (p<0.05, Table 1). During this period, while significantly increased ODI within subject was observed in CA4‐DG, significantly decreased VFISO in all the subfields and increased VFIC in the subiculum were noted (Figure 1). The decreasing rate of VFISO in CA4‐DG was significantly associated with age (Table 2), suggesting the reduction in VFISO accelerated over age.ConclusionWe demonstrated that diffusion metrics are sensitive to microstructural alterations in the hippocampal subfields of cognitively normal older adults. The cornu ammonis region 4 and dentate gyrus is the most vulnerable region affected by aging with increased tissue dispersion and age‐accelerated reduction in fast isotropic diffusion. Future studies will focus on the effects of the initial microstructural condition to its rate of change with aging. References: 1. Shahid, et al., Brain,2022
Pathophysiological mechanisms of grey matter morphometry changes in preclinical Alzheimer’s disease
Authors: Pelkmans Wiesje , Cacciaglia Raffaele , Salvadó Gemma , Falcon Carles , Minguillón Carolina , Fauria Karine , Kollmorgen Gwendlyn , Carboni Margherita , Molinuevo Jose Luis , Grau‐Rivera Oriol , Zetterberg Henrik , Blennow Kaj , Suarez‐Calvet Marc , Gispert Juan Domingo 
Published: December 2023

AbstractBackgroundThe biological mechanisms underlying structural brain changes in early Alzheimer’s disease (AD) are not well understood. Combining a wide selection of biomarkers of AD pathology, synaptic dysfunction, neuroaxonal injury, and neuroinflammation, and examining their effects on grey matter (GM) changes may provide a deeper understanding of the multifactorial nature of AD. We aimed to identify biological components of key fluid biomarkers predictive of longitudinal GM changes in cognitively unimpaired adults.MethodWe studied 322 cognitively unimpaired individuals from the ALFA+ cohort (Table1) with available longitudinal MRI and cerebrospinal fluid (CSF) biomarkers of ß‐amyloid (Aß42/40), phospho‐tau (p‐tau181), neurogranin, neurofilament light chain (NfL), total‐tau, a‐synuclein, glial fibrillary acidic protein (GFAP), chitinase‐3‐like protein‐1 (YKL‐40), soluble triggering receptor expressed on myeloid cells‐2 (sTREM2), S100 calcium‐binding protein B (S100B), and interleukin‐6 measured using the Roche NeuroToolKit immunoassays. Pairwise longitudinal registration analysis was performed using SPM12 to calculate Jacobian determinant maps. Next, we performed partial least‐squares analysis to determine the optimal number of CSF biomarker components and tested their association with GM volume changes by AT (Amyloid‐Tau) stage.ResultFour distinct biomarker components (C1‐4) were identified (Figure1). C1 was driven by moderate contributions from several biomarkers, particularly markers of core AD pathology and neurodegeneration, which were strongly associated with temporal lobe atrophy in A+T‐ individuals. C2 represented mainly Aß pathology and, to a lesser extent, axonal damage and astrogliosis that contributed to a decrease in GM volume, especially in the hippocampus in A‐T‐ participants, while showing strong correlations with volume increases in medial frontal regions in A+T+ participants. C3 loading was associated with greater frontoparietal atrophy, especially in A+T+ individuals, and consisted of microglial activation together with Aß pathology but in the absence of reactive astrogliosis. Lastly, C4, reflecting mostly microglial activation alone, was also strongly associated with frontoparietal atrophy, particularly in A+T+ participants.ConclusionOur results suggest important contributions of Aß pathology, neuroaxonal damage, and microglial activation to GM morphometry changes in the earliest stages of the AD continuum. Atrophy patterns differed depending on the underlying pathological drivers and on A and T positivity, showing stronger correlations with increasing disease severity; however, volumetric increases were also observed.
Plasma TDP‐43 Levels are Associated with Neuroimaging Measures of Temporal Lobe Structure
Authors: Gold Brian T. , Bauer Christopher E. , Zachariou Valentinos , Sudduth Tiffany L , Van Eldik Linda J. J. , Nelson Peter T , Jicha Gregory A , Wilcock Donna M. 
Published: December 2023

AbstractBackgroundTar DNA binding protein of 43kDa (TDP‐43) proteinopathy is a pathological hallmark of limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), with or without comorbid Alzheimer’s disease neuropathologic change (AD‐NC). At present, the diagnosis of LATE neuropathologic change (LATE‐NC) can only be made at autopsy. There is thus an urgent need for a clinical biomarker for LATE and a blood‐based method would be optimal for clinical and economic reasons. Here, we assessed the relationship between plasma TDP‐43 levels with imaging measures of neurodegeneration (volume and cortical thickness).MethodParticipants were 72 nondemented older adults (47 women, age range 60‐94 years). Immunoassays for TDP‐43, phosphorylated threonine‐181 tau (p‐tau181), total tau (t‐tau), amyloid beta‐42 (Aß42), and amyloid beta‐40 (Aß40) were quantified (pg/mL) in duplicate for each participant using the Quanterix Simoa HD‐X instrument. Neuroimaging was conducted using a 3 Tesla MRI Siemens Prisma scanner with a 64‐channel head coil. A T1‐weighted MPRAGE sequence with 1 cubic mm voxels covering the entire brain was acquired. FreeSurfer software was used to estimate intracranial volume (ICV) and volumes of the entorhinal cortex (ERC), amygdala, and subiculum of the hippocampus, regions known to harbor TDP‐43 pathology in early stages of LATE‐NC. Multivariate linear regression models controlling for age, sex, and ICV were conducted in SPSS using plasma TDP‐43 as the predictor and volumetric or cortical thickness measurements as dependent variables.ResultThere was a negative association between plasma TDP‐43 concentration and ERC volume, a relationship that remained significant after controlling for plasma markers of AD‐NC (the Aß42/Aß40 ratio, p‐tau181/Aß40 ratio or t‐tau/Aß40 ratio). Results from subsequent exploratory analyses indicated a negative association between TDP‐43 and cortical thickness in the inferior temporal lobe, a finding which also remained significant after controlling for AD‐NC plasma biomarkers.ConclusionHigh plasma TDP‐43 levels were associated with in vivo imaging measures of neurodegeneration in multiple temporal lobe structures. Plasma TDP‐43 assays may prove useful in clinical trials seeking to enroll individuals at risk for LATE‐NC.