bluuebunny/crossref_metadata_2025 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

Background

One 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.

Method

166 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.

Result

Compared 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).

Conclusion

There 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

Background

Agitation 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.

Method

Participants 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.

Result

For 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.

Conclusion

Across 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

Background

Age‐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.

Method

We 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)

Result

The 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).

Conclusion

Our 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

Background

Recent 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.

Method

Forty‐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.

Result

APOEe4 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.

Conclusion

Microstructural 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

Background

The 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.

Method

Data 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.

Result

APOE 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.

Conclusion

We 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

Background

Alzheimer’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.

Method

Four 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.

Result

The 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.

Conclusion

DenseNet 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

Background

The 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.

Method

Thirty‐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).

Result

All 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.

Conclusion

We 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

Background

The 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.

Method

We 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.

Result

Four 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.

Conclusion

Our 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

Background

Tar 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).

Method

Participants 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.

Result

There 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.

Conclusion

High 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.
Longitudinal sleep instability predicts cognitive decline and is associated with increased MRI‐visible perivascular space burden
Authors: Keil Samantha A , Schindler Abigail G , Piantino Juan , Lim Miranda , Willis Sherry L , Iliff Jeffrey J
Published: December 2023

Background

Although emerging data suggest a direct link between sleep duration, aging, and cognitive performance, the impact of longitudinal sleep patterns have on Alzheimer’s disease‐associated pathology and cognitive decline remains unclear.

Method

Utilizing longitudinal data on self‐reported sleep duration collected within the Seattle Longitudinal Study, we used a Cox proportional hazard (CPH) regression to evaluate the relationship between longitudinal sleep factors on the development of cognitive decline. Additional analysis in a sub‐cohort utilized multivariate linear regression prediction analyses to evaluate the predictive value of these longitudinal sleep factors on the incidence of developing cognitive impairment over an interval of 10 years. A cohort within the study received MRI and FLAIR neuroimaging, enabling the assessment of the impact these longitudinal sleep factors have on subcortical white matter MRI‐visible perivascular space burden (PVS). A semi‐automated segmentation algorithm accounted for PVS total burden and volume, as well as average PVS width, length, and median volume across participants, blinded by group.

Result

CPH analysis found years of education (HR 1.12, 95% CI 1.02, 1.22), APOE4 status (HR 2.18, 95% CI 1.37, 3.49), higher depression scores (HR 1.08, 95% CI 1.04, 1.13), short sleep phenotype (HR 1.78, 95% CI 1.03, 3.08) and increased sleep variability (HR 3.10, 95% CI 1.66, 5.80) were significantly associated with cognitive impairment. Further, when including these factors into our linear regression prediction analyses, age (p<0.0001), depression (p = 0.01) and sleep variability (p = 0.042) were significant predictors of cognitive impairment over a 10‐year period. Preliminary analysis showed significant association between high sleep variability and increased whole‐brain PVS volume (p = 0.04) and length (p = 0.03), with a significant correlation between sleep variability and median PVS volume (p = 0.04). Follow‐up analysis evaluated PVS features within the wider cohort.

Conclusion

These findings suggest that variability in longitudinal self‐reported sleep duration exerts a previously unappreciated influence on downstream cognitive performance and pathological processes, potentially including glymphatic dysfunction. These findings elaborate the link between sleep instability, aging, cognitive decline and neuropathologic disease state. Future studies should evaluate these findings on an independent cohort to assess whether sleep variability of different time scales (weeks, years, decades) exerts similar effects on these outcomes.
Increased neural activity relates to greater neuropsychiatric symptoms and beta‐amyloid plaque load in cognitively normal older adults
Authors: Oh Hwamee , Razlighi Qolamreza R , Rogers Annika , Sharp Elizabeth
Published: December 2023

Background

Epidemiological studies have shown that individuals predisposed to experiencing psychological stress, and those affected with diseases associated with chronic stress such as depression and anxiety have an increased risk of developing Alzheimer’s disease (AD). These findings may imply that poor resilience to psychological stress is not simply a characteristic of dementia, but may reflect mechanisms involved in disease etiology. In this study, we examined the level of neural activity as a potential mechanism of linking individual susceptibility to psychological stress and AD‐related neuropathology across the spectrum of AD.

Method

A total of 166 participants (mean age = 74.21; 90 Females) spanning diagnostic spectrums along cognitively normal (CN) individuals and AD patients was selected for analysis from the ADNI2 database based on the availability of resting state fMRI and AV45 PET data. Neural activity was quantified by applying the amplitude of low frequency fluctuations (ALFF) method to time series of fMRI blood oxygenation‐level‐dependent signals (in the frequency range of 0.01‐0.08 Hz) obtained during resting‐state fMRI (rsfMRI) scan. Amyloid pathology was quantified by AV45‐SUVR measures that were normalized to the cerebellum. Mini‐Mental State Exam (MMSE) and the total Neuropsychiatric Inventory Questionnaire (NPI‐Q) scores were used as cognitive and stress susceptibility measures.

Result

Behavioral measures of stress were significantly associated with brain Aß indices and neural activity across the entire cohort, spanning from CN older adults to AD patients (ps<0.05). Relationships between the neural activity, stress responses, and Aß deposition, however, differ by diagnostic groups. As stress indicators increased, CN subjects exhibited increased activity in several brain regions including the regions within the default mode network (DMN), while AD participants exhibited decreased activity across the brain. Moreover, as brain Aß load increased, CN participants experienced DMN hyperactivity, while AD participants experienced hypoactivity.

Conclusion

These results indicate a potential link between heightened stress responses and increased susceptibility to the development of AD pathologies through neuronal hyperactivity, especially in the preclinical stage of AD. Alleviating stress and regulating stress responses may be important modifiable factors and intervention strategies that could help prevent and intervene the development of AD pathology.
Association between physical function and neuroimaging measures in a 2‐year multidomain lifestyle randomized controlled trial
Authors: Stephen Ruth , Kulmala Jenni , Antikainen Riitta , Kemppainen Nina , Lehtisalo Jenni , Mangialasche Francesca , Ngandu Tiia , Rinne Juha O. , Soininen Hilkka , Strandberg Timo , Kivipelto Miia , Solomon Alina , Hall Anette
Published: December 2023

Background

This exploratory study investigated associations between physical function and neuroimaging biomarkers: brain magnetic resonance imaging (MRI) and Pittsburgh compound B‐positron emission tomography (PiB‐PET) measures during the 2‐year Finnish Geriatric Intervention Study to prevent cognitive impairment and disability (FINGER).

Method

FINGER targeted 60–77‐year‐old general population at‐risk and without dementia or substantial cognitive impairment. Measures of physical function (activities of daily living (ADL), hand grip strength, physical performance, Fried’s frailty phenotype index and self‐rated health) from baseline and 2‐year visits were used. Baseline neuroimaging measures, MRI (hippocampus, total gray matter volumes, Alzheimer’s disease (AD) signature cortical thickness) were available for 115‐132 participants and PiB‐PET (composite score) for 44‐48 participants. Linear and logistic regressions were used to test the cross‐sectional associations and the impact of baseline imaging measures on changes in physical function. Models were adjusted for site, sex and education.

Result

Cross‐sectionally, higher ADL were associated with higher hippocampus volume (ß = 0.18 p = 0.048), total gray matter volume (ß = 0.15 p = 0.005) and AD signature cortical thickness (ß = 0.25 p = 0.006) while stronger hand grip and was associated with higher total gray matter volume (ß = 0.20 p = 0.041) significantly. Baseline imaging measures were associated with changes in physical function: higher baseline hippocampus volume was associated with maintenance/improvement in the ADL (OR = 0.56 p = 0.039) while lower hippocampus at baseline predicted poorer physical performance over time (OR = 1.66 p = 0.036).

Conclusion

Higher brain integrity is associated with better physical function while lower baseline brain integrity predicts poorer physical function over time.
Family history of dementia is associated with longer sleep duration and smaller volume of the thalamus in the PREVENT‐Dementia study
Authors: Laurell Axel AS , Shah Sita , Dounavi Maria‐Eleni , Dudas Robert B , Dauvilliers Yves , Ritchie Craig W , Koychev Ivan , Lawlor Brian A , Naci Lorina , Malhotra Paresh A , O'Brien John T
Published: December 2023

Background

The relationship between sleep and dementia risk is complex, with both longer and shorter sleep duration being associated with cognitive decline. The thalamus has an important role in regulating the sleep‐wake cycle and structural changes may be a good marker of sleep abnormalities. Our aim was to investigate the association between dementia risk, sleep and the volume of thalamic nuclei.

Method

We analysed baseline data from PREVENT‐dementia, a multicentre, prospective cohort study of cognitively intact participants aged 40 to 59 years, who were stratified according to presence of the ApoE4 allele and parental family history of dementia (FH+). Sleep data was collected using the Pittsburgh Sleep Quality Index (PSQI) which measures subjective sleep quality, latency, duration, efficiency, disturbances, medication use and daytime dysfunction. T1‐weighted 3T MRI images were analysed using Freesurfer (version 7.1.0) to determine the volume of the thalamus and its subnuclei, controlling for total intracranial volume. The score on the centre for epidemiologic studies depression scale and the number of analgesic medications, were also used as covariates in the analysis to control for mood and pain. The data was analysed in R Studio using robust logistic regression.

Result

Complete data was available for 594 participants. The total PSQI score was lower in FH+ subjects (p = 0.046) but was not associated with ApoE4 status. FH+ subjects had smaller volumes of mediodorsal medial (p = 0.03) and lateral (p = 0.03) nuclei, longer sleep duration (p = 0.02), and counterintuitively less sleep‐related daytime dysfunction (p = 0.01) compared to controls. In the FH+ group, larger pulvinar nucleus was associated with better sleep quality (r = ‐0.17, p = 0.002). In apoE4 non‐carriers, a larger thalamus (r = ‐0.12, p = 0.02) and larger centromedian nucleus (r = ‐0.13, p = 0.01) were both associated with a lower total PSQI score. They also had an association between larger pulvinar (r = ‐0.11, p = 0.04) and centromedian (r = ‐0.14, p = 0.007) nuclei and increased sleep efficiency.

Conclusion

Middle‐aged subjects with a FH+ had longer sleep duration and smaller thalamic volumes which may represent early neurodegenerative changes. Furthermore, we found an association between larger thalamic nuclei and better sleep variables, especially in ApoE4 non‐carriers, indicating that the thalamus may be an important imaging correlate of sleep quality.
Characteristics of cerebrospinal fluid biomarkers/imaging findings in ptaients with amyloid PET‐negative dementia
Authors: Takenoshita Naoto , Yamamoto Ryo , Hanyu Haruo , Kasuga Kensaku , Ikeuchi Takeshi , Ishii Kenji , Shimizu Soichiro
Published: December 2023

Background

In daily clinical practice, we often encounter cases with atypical clinical symptoms and imaging findings, even amoung those diagnosed with Alzheimer’s disease.

Method

Forty‐nine cases of undiagnosed patients with atypical clinical symptoms or imaging findings underwent both amyloid PET and cerebrospinal fluid(CSF) examinations.They were divided into amyloid‐positive group(n = 25) and amyloid‐negative group(n = 24).The cerebrospinal fluid findings,neuropsychological examination findings,MRI findings,and SPECT findings were compared between the two groups.

Result

CSF findings showed significant differences in amyloid‐ß42,amyloid‐ß42/40, and P‐tau between the two groups.There was no significant difference in MRI findings.SPECT findings showed a significant difference in decreased blood flow in the right parietal lobe and bilateral precuneus.

Conclusion

In dementia patients with atypical clinical symptoms and imaging findings, CSF findings and decreased blood flow in the right parietal lobe and bilateral precuneus are suggested to be useful indicators to distinguish whether amyloid is involved in the back ground pathology.
Functional connectivity changes of the Locus Coeruleus in Alzheimer’s Disease
Authors: Hou Ruihua , Ali Mobeen , Brown Matthew
Published: December 2023

Background

Growing evidence indicates neurone loss in the Locus Coeruleus(LC) in patients with Alzheimer’s Disease(AD). The widespread projection and rich connectivity of the LC with multiple brain regions and its interaction with different neural networks suggests the importance of investigating the functional connectivity of the LC, an area of research which has been less studied. Aims: The primary aim of this study was to test for differences in functional connectivity of the LC between AD subjects and matched controls using neuromelanin‐sensitive MRI(NM‐MRI). The secondary aim of this study was to test for the effects of AD on the resting state networks.

Method

Pre‐processing of the fMRI and structural MRI data from 23 AD subjects and 23 controls was completed using the FMRIB Software Library(FSL). The images were skull‐stripped, registered, and normalised to the MNI152_t1_2mm_brain template. LC masks were created from the NM‐MRI scans also using FSL. The subsequent data was processed using the CONN toolbox. Seed‐to‐voxel and ROI‐ROI analysis were used to produce connectivity maps and comparisons were conducted between AD and controls, left and right LC, mild and moderate AD, and resting state networks.

Result

AD subjects had connections from the LC to only 43 brain regions, compared to 80 brain regions in the controls. In comparison to controls, AD subjects had reduced LC connectivity in the subcallosal cortex(p‐FDR = 0.016417), increased LC connectivity in the right supramarginal and postcentral gyri(p‐FDR = 0.000002), and reduced connectivity in the default mode network(p‐FDR = 0.000286) and sensorimotor network(p‐FDR = 0.027524). The left LC in the AD subjects had significant connections to only 56 brain regions compared to 81 brain regions in the right LC. In particular, the left LC had decreased number of significant connections to the amygdala and vermis, compared to the right LC. The number of significant LC connections decreased with progression from controls to mild AD to moderate AD.

Conclusion

This study provides new evidence of reduced LC functional connectivity in AD patients and asymmetrical reduction in the LC skewed towards the left LC. LC connectivity reduction could indicate pathogenesis and progression of AD, aiding prediction of disease progression and development of novel intervention targets.
MRI phenotypes of the brain are related to long‐term dementia outcome in community‐dwelling older adults
Authors: Keller Jasmin Annica , Sigurdsson Sigurdur , Abecassis Bárbara Schmitz , Kant Ilse M.J. , van Buchem Mark A. , Launer Lenore J J. , Van Osch Matthias J.P. , Gudnason Vilmundur , de Bresser Jeroen H.J.M.
Published: December 2023

Background

Individual brain MRI markers only show at best a modest association with long‐term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We aimed to identify different brain MRI phenotypes by combined hierarchical clustering analysis based on neurodegenerative and neurovascular brain MRI markers in community‐dwelling individuals. Within each of these brain MRI phenotype subgroups, we determined the long‐term dementia risk.

Method

A hierarchical clustering analysis based on combined brain MRI markers in community‐dwelling individuals of the Age‐Gene/Environment Susceptibility (AGES) Reykjavik Study (n = 3056) was applied to identify different brain MRI phenotypes. Brain MRI markers used in the hierarchical clustering analysis were brain volumes for the estimation of brain atrophy, WMH markers (volume and shape), brain infarcts, microbleeds, and enlarged perivascular spaces.

Result

We identified 14 distinct subgroups of individuals with different brain MRI phenotypes (figure 1 and figure 2). The brain MRI phenotypes of the subgroups ranged from limited burden (subgroup (S) 12), mostly atrophy and infarcts (S14), mostly irregularly shaped WMH and atrophy (S3) to a multi‐burden subgroup (S2). These subgroups had a different long‐term risk for dementia (mean time to follow‐up: 9.9 ± 2.6 years; hazard ratio ranging from 4.1 (95%‐CI: 3.19‐13.40) to 13.8 (95%‐CI: 4.28‐44.37); see figure 3); especially the multi‐burden brain MRI phenotype showed an increased risk compared to the reference group (HR: 13.8 (95%‐CI: 4.28‐44.37)).

Conclusion

Our results indicate that distinct brain MRI phenotypes are related to different long‐term risks of developing dementia. Brain MRI phenotypes may assist in an improved understanding of the structural correlates of dementia predisposition. These findings may in the future be useful to determine patient prognosis and may aid in patient selection for future treatment studies.
Longitudinal white matter integrity alterations as a function of Preclinical Alzheimer’s Pathology: findings from the EPAD non‐demented cohort
Authors: Lorenzini Luigi , Tranfa Mario , Ingala Silvia , Wolz Robin , Haller Sven , Blennow Kaj , Frisoni Giovanni B , Chetelat Gael , Ewers Michael , Payoux Pierre , Martinez‐Lage Pablo , Ritchie Craig W , Gispert Juan Domingo , Brunetti Arturo , Mutsaerts Henk‐Jan , Wink Alle Meije , Barkhof Frederik
Published: December 2023

Background

Cross‐sectional diffusion tensor imaging (DTI) studies report white matter (WM) microstructural alterations, mainly involving fornix and corpus callosum (CC), in symptomatic stages of Alzheimer’s Disease (AD). Exploring these changes longitudinally in relation to preclinical and prodromal AD pathology is essential to track disease progression. We investigated trajectories of WM alterations in non‐demented individuals from the European Prevention of Alzheimer’s Dementia (EPAD) cohort and their relationship with AD biomarkers.

Method

EPAD inclusion criteria were age>50 years and Clinical Dementia Rating = 0.5. We selected participants with baseline CSF samples, and longitudinal DTI scans. After defining AT groups(Ingala et al. 2021), A‐T+ participants were excluded (final N = 283). MRI acquisition and preprocessing was previously described(Lorenzini et al. 2022). We extracted fractional anisotropy (FA) in 14 regions(Mori et al. 2005) from DTI as a marker of WM integrity. Site harmonization of MRI‐derived data was performed with ComBat toolbox(Fortin et al. 2018). Age‐ and sex‐corrected linear mixed models with random intercepts on participants were used to estimate time‐effect on MRI‐derived phenotypes, and their interaction with AT status. Results were corrected for multiple testing.

Result

At baseline, A+T‐ participants showed lower FA in body/columns (ß = ‐0.04, p<0.01) and crus of fornix (ß = ‐0.01, p = 0.04), and in splenium (ß = ‐0.007, p = 0.04) and body of CC (ß = ‐0.01, p = 0.03) compared to A‐T‐. In the whole group, FA decreased over time in splenium (ß = ‐0.003, p<0.01), body (ß = ‐0.002, p<0.01) and genu of CC (ß = ‐0.009, p<0.01), body/columns (ß = ‐0.004, p<0.01) and crus of fornix (ß = ‐0.005, p<0.01), and inferior longitudinal fasciculus (ß = ‐0.007, p<0.01). Compared to A‐T‐, A+T+ participants showed steeper FA reduction in superior (Interaction:ß = ‐0.004, p = 0.03) and anterior corona radiata (Interaction:ß = ‐0.006, p = 0.02).

Conclusion

Our results suggest that WM integrity in key AD regions may degenerate early in the AD continuum, showing greater impairment over short‐time intervals in individuals with higher AD‐specific pathological burden.
Associations of subcortical shapes with age‐related neuropathologies in community‐based older adults
Authors: Saifullah Khalid , Makkinejad Nazanin , Evia Arnold M , Bennett David A. A , Schneider Julie A , Arfanakis Konstantinos
Published: December 2023

Background

Age‐related neuropathologies lead to substantial atrophy of subcortical brain regions. However, the effects of age‐related neuropathologies on the shape of subcortical brain structures are not well understood because a) definitive diagnosis of most neuropathologies is only possible at autopsy and b) multiple neuropathologies often coexist in the brain of older adults. The purpose of this work was to integrate ex‐vivo MRI and detailed neuropathologic examination in a large number of community‐based older adults.

Method

Participants and Data Cerebral hemispheres from 842 older adults participating in four longitudinal, clinical‐pathologic cohort studies of aging: the Rush Memory and Aging Project (MAP), the Religious Orders Study (ROS), the Minority Aging Research Study (MARS) and the Clinical Core (CC) of the Rush Alzheimer’s Disease Research Center (ADRC)1,2 (Fig.1) were included in this work. All hemispheres were imaged at room temperature while immersed in 4% formaldehyde solution using clinical 3T MRI scanners approximately 30 days postmortem. After ex‐vivo MRI, each hemisphere underwent detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1). Ex‐vivo MRI and Shape Estimation The subcortical structures were segmented in ex‐vivo T2‐weighted MR images from all participants. Shape analysis was performed using SPHARM‐PDM3. For each subcortical structure, signed shape differences were computed from the average mesh for all vertices and all participants. Statistical Analysis Vertex‐wise linear regression was performed for each subcortical structure, modeling the signed shape difference at each vertex (dependent variable) as a function of neuropathologies (specifically amyloid‐ß plaques, neurofibrillary tangles, limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC), Lewy bodies, arteriolosclerosis, atherosclerosis, gross and microscopic infarcts, and cerebral amyloid angiopathy), and controlling for age at death, sex, years of education, postmortem interval to fixation, postmortem interval to imaging, and scanner. The statistical analysis was conducted using PALM4 with family‐wise error rate correction.

Result

The results are shown in Figure 2. These findings for tangles and LATE‐NC were in good agreement with our previous work5,6. Finally, although MRI was conducted ex‐vivo, we expect the results to translate well to in‐vivo7.

Conclusion

The differences in spatial patterns of the effects of various neuropathologies may contribute towards the development of tools for in‐vivo prediction of these neuropathologies.