bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractBackgroundAlthough 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.MethodUtilizing 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.ResultCPH 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.ConclusionThese 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

AbstractBackgroundEpidemiological 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.MethodA 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.ResultBehavioral 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.ConclusionThese 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

AbstractBackgroundThis 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).MethodFINGER 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.ResultCross‐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).ConclusionHigher 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

AbstractBackgroundThe 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.MethodWe 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.ResultComplete 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.ConclusionMiddle‐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

AbstractBackgroundIn daily clinical practice, we often encounter cases with atypical clinical symptoms and imaging findings, even amoung those diagnosed with Alzheimer’s disease.MethodForty‐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.ResultCSF 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.ConclusionIn 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

AbstractBackgroundGrowing 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.MethodPre‐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.ResultAD 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.ConclusionThis 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

AbstractBackgroundIndividual 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.MethodA 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.ResultWe 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)).ConclusionOur 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

AbstractBackgroundCross‐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.MethodEPAD 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.ResultAt 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).ConclusionOur 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

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