bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroanatomical predictors of progression to dementia in primary progressive aphasia
Authors: Quimby Megan , Hochberg Daisy , Katsumi Yuta , Carvalho Nicole , Brickhouse Michael , Flaherty Ryn , Dickerson Brad C. , Touroutoglou Alexandra 
Published: February 2022

AbstractBackgroundPatients with Primary Progressive Aphasia (PPA) have a prominent, isolated language deficit during the initial phase of the illness, with other cognitive and affective functions being affected later on (Gorno‐Tempini et al. 2011; Mesulam, 2001). Based on evidence that executive, memory and socioaffective functions are associated with functional independence (De Paula et al. 2015), we hypothesized that greater atrophy in cognitive or affective brain networks outside language networks is predictive of dementia in PPA. The development of quantitative neuroanatomical prognostic biomarkers for loss of independent functioning would be valuable in research and clinically (e.g. treatment recommendations, family education).Method50 PPA patients (17 agrammatic, 14 semantic, and 19 logopenic variant), who underwent a clinical and MRI evaluation at baseline and had at least 6 months of follow‐up, were selected. For each patient we measured the time between the first visit and the progression to dementia or last observation. We estimated individual network atrophy using surface‐based analyses described in our previous studies and using large‐scale cortical cognitive and affective networks derived from the Yeo et al. 2011 parcellation. We performed Cox regression models to test the hypothesis that greater baseline atrophy in cortical networks subserving non‐language cognitive or affective functions predicts time to dementia, but that greater atrophy in the visual association network (serving as a control) does not.ResultUnivariate Cox regression analysis showed that patients with greater atrophy outside the language network, in left hemisphere heteromodal association and paralimbic areas, including the default mode, frontoparietal, salience and ventral frontotemporal networks, had the highest risk of progression to dementia within a shorter time period of time (HR: 2.26, 95% CI: 1.45‐ 3.51). Atrophy in the language network was also a predictor, although slightly weaker (HR: 2.05, 95% CI: 1.41‐ 2.98). Atrophy in the visual association network did not predict time of conversion to dementia (left hemisphere: HR: 1.19, 95% CI: 0.86‐ 1.64; right hemisphere: HR: 1.21, 95% CI: 0.86‐ 1.68).ConclusionIn PPA patients, baseline cortical atrophy outside language networks is an important predictor of more rapid progression to dementia. This measure should be included in precision medicine models of prognosis in PPA.
Normative morphometrics from MRI are associated with episodic memory test performance in amnestic MCI
Authors: Kraal A. Zarina , Benitez Andreana 
Published: February 2022

AbstractBackgroundProprietary software that generate normative scores for brain regions using MRI (e.g. NeuroQuant, Neuroreader) have identified greater atrophy in MCI patients than controls, particularly in the hippocampus, and have associated these measurements with episodic memory performance (Tanpitukpongse et al., 2017; Umfleet et al., 2020). While useful in clinical settings, these may be cost‐prohibitive for research purposes. Our goal was to conduct a validation study using free, non‐proprietary morphometric software (Potvin et al., 2016; 2017) with data from a cross‐sectional study of amnestic MCI (aMCI) and normal controls (NC).Method102 older adults ages 60 to 86 (nNC=75; naMCI=27) underwent 3T brain MRI and neuropsychological testing (Weintraub et al., 2018). T1‐weighted images were segmented using FreeSurfer v5.3, and from these outputs normed z‐scores were generated, adjusting for age, sex, total intracranial volume, and MRI field strength (Potvin et al., 2016a; 2016b; 2017). We hypothesized that volumes of AD‐relevant regions (hippocampus, amygdala, entorhinal cortex, parahippocampus) would be smaller in aMCI than NC with no differences in non‐AD “control regions” (cuneus, lingual gyrus, pericalcarine; Fig. 1.A), and that AD‐relevant volumes would correlate with episodic memory composites (i.e. average of normed scores (percentiles) on immediate, delay, and recognition trials from list‐learning (Rey‐Auditory Verbal Learning Test) and story‐learning (Wechsler‐Logical Memory) tests).ResultBonferroni‐corrected t‐tests showed significantly lower volumes of all AD‐relevant regions in the aMCI versus NC, with large effect sizes (Hedge’s g=0.9 to 1.2), and no group differences in control regions (ps<0.05, Hedge’s g<0.3). Bivariate correlations showed moderate (rs=0.38 to 0.55) associations between memory composites and most AD‐relevant regions in the aMCI but not the NC group (Fig. 1.B.1), and no associations between memory composites and control regions except for a positive association between story‐learning and cuneus volume in aMCI (Fig. 1.B.2).ConclusionSimilar to results using proprietary software, this study validates the potential clinical utility of a non‐proprietary normative morphometric software when distinguishing aMCI from NC, with AD‐relevant volumes associated with episodic memory in aMCI. Future studies are needed to characterize associations between other AD‐relevant brain regions and cognitive domains.
The relationship between APOE genotype and subcortical volume: A UK Biobank study (N=36,920)
Authors: Muir Alexandra M , Ching Christopher , Santhalingam Vigneshwaran , Abaryan Zvart , Zhu Alyssa H , Thomopoulos Sophia I , Jahanshad Neda , Thompson Paul M 
Published: February 2022

AbstractBackgroundTwo copies of the apolipoprotein (APOE) ε4 allele is associated with approximately 10 to 20 times greater risk for late‐onset Alzheimer’s disease (AD)1,2,3, depending on genetic ancestry. Although reduced hippocampus and amygdala volumes are seen in ε4 carriers with mild cognitive impairment (MCI) and AD4,5, the relationship between genetic risk and brain structure in healthy older adults is unresolved. Here we mapped normative subcortical volume trajectories in a large sample of healthy adults and tested for the effects of APOE genotype.MethodT1‐weighted images from 36,920 UK Biobank7,8 participants () were processed using FreeSurfer 7.1. Averaged thalamus, pallidum, hippocampus, amygdala, caudate, nucleus accumbens, and lateral ventricle volumes were calculated. APOE genotypes included ε2ε2, ε2ε3, ε3ε3, ε3ε4, and ε4ε4. ε2ε4 carriers and individuals with neurological/psychological disorders were not included. Nomograms of subcortical volumes were plotted. The statistical relationship between subcortical volume and APOE genotype was assessed using linear mixed models, adjusting for age, sex, intracranial volume, population structure, and scan site. Additionally, an age‐by‐APOE interaction was assessed, with all p‐values corrected using the standard false discovery rate9.ResultNomograms separated by APOE genotype () show a general trend of smaller volumes, but larger ventricles, with increasing age. Statistically, hippocampal and amygdala volumes were smaller in ε4ε4 compared to carriers of the ε3 allele (; d: ‐0.12 to ‐0.05). Carriers of at least one ε4 allele had smaller nucleus accumbens and thalamic volumes compared to carriers of the ε3 allele (d: ‐0.08 to ‐0.03). Lower thalamic volumes were associated with ε2ε2 compared to ε2ε3 and ε3ε3 (d: ‐0.14 to ‐0.03). No ROI showed a significant age‐by‐APOE genotype interaction.ConclusionThese results suggest a pattern of subtle and structure‐specific effects of AD genetic risk on subcortical volume across adulthood. Future studies aim to bolster the ε2ε2 sample size to confirm lower thalamic volume in these carriers. Additionally, we will investigate other genetic and environmental risk factors that affect brain structure, modulate healthy brain aging, and predict conversion to MCI or AD.
Sensory stimulation for nursing home residents: Systematic review and meta‐analysis of its effects on sleep quality and rest‐activity rhythm in dementia
Authors: Prins Angela J , Scherder Erik JA , van Straten Annemieke , Zwaagstra Yvonne , Milders Maarten V 
Published: February 2022

AbstractBackgroundDespite the evidence that disrupted sleep‐wake cycles are associated with an exacerbation of behavioural disturbances and an acceleration of the disease progression in dementia, the effect of sensory stimulation for improving sleep quality and rest‐activity rhythm is unclear. The aim of the current meta‐analysis is to give an overview of the effectiveness of sensory stimulation interventions on reduction and prevention of sleep disturbances in nursing homes residents with dementia.MethodA systematic literature search and meta‐analysis were performed on December 3, 2019. Twenty‐seven studies examining the effects of a sensory stimulation intervention on rest‐activity rhythm and/or nocturnal restlessness in nursing home residents with dementia were included. Outcomes were measured with Actiwatches and/or standardized observation scales. Extensive subgroup meta‐analyses were performed to adjust for varying characteristics of included studies.ResultUni‐sensory stimulation including tactile and visual stimulation (i.e. light therapy, massage, acupuncture, animal‐assisted interventions) seemed effective for improving sleep quality and strengthen the rest‐activity rhythm (Hedges g=.47, p ≤ .01, Figure 1). More specifically, visual and tactile stimulation with a minimum of 30 minutes/day for two weeks have effectively reduced the duration of nocturnal awakenings (g=‐.29, p≤.05), sleep onset latency (g=‐.25, p≤.05), and nocturnal behaviour disturbances (g=‐.57, p≤.01), and have improved nocturnal sleep duration (g = .38, p ≤ .01), and sleep efficiency (g=.48, p≤.01). The heterogeneity within the majority of outcomes varied between medium and large. The majority of studies were of poor quality (59%, Figure 2). Dementia type and severity, gender, treatment duration and intensity (light levels in lux values) were not related to the effectiveness of sensory stimulation in all outcomes.ConclusionAlthough the methodological quality of the studies was limited, we found indications that sleep quality and nocturnal restlessness in nursing home residents with dementia may benefit from sensory stimulation. Recommended is to use a sensory stimulating environment in nursing homes which may prevent or improve sleep disturbances, and therefore can contribute to higher quality of life of their patients. Future research should conduct RCTs, while using comparable interventions, measuring instruments and procure, so the quality of dementia can be further improved.
Association of deep‐learning–derived brain computed tomography measures with cognition and blood‐based biomarkers of neurodegenerative diseases
Authors: Srikrishna Meera , Ashton Nicholas J. , Pereira Joana B. , Heckemann Rolf A. , Westen Danielle , Volpe Giovanni , Simrén Joel , Zettergren Anna , Kern Silke , Wahlund Lars‐Olof , Gyanwali Bibek , Hilal Saima , Chong Joyce R. , Zetterberg Henrik , Blennow Kaj , Westman Eric , Chen Christopher , Skoog Ingmar , Schöll Michael 
Published: February 2022

AbstractBackgroundExisting imaging biomarkers for neurodegenerative diseases such as magnetic resonance imaging (MRI) and positron emission tomography are costly or have limited accessibility. Computed tomography (CT) and novel blood tests have greater potential as screening modalities for suspected neurodegenerative diseases and to potentially exclude other treatable causes of neurodegeneration.ObjectiveTo evaluate the association of volumetric brain measures, derived using a novel CT‐based deep‐learning algorithm with cognition and blood levels of neurodegeneration markers.MethodWe previously developed deep‐learning‐based models using 734 datasets (722 cognitively normals (CN)) from Gothenburg H70 Birth Cohort to segment head CTs by learning from MRI‐derived labels. We used these models to segment, without further training, 204 novel CT datasets (73 Alzheimer's disease (AD), 49 mild cognitive impairment (MCI), 20 vascular dementia (VAD), 40 vascular cognitive impairment (VCI), 22 CN) recruited from the Singaporean Memory Clinic cohort (mean age= 74.0±8.2 years, 50.5% female), without MRI intervention. We tested associations between six CT‐derived volumetric measures (grey matter (GM), white matter (WM), GM/CSF, GM/ventricular CSF (VCSF), brain volume (BV)/CSF, BV/VCSF) with diagnosis, plasma biomarkers, and cognition. The plasma biomarkers were measured using a Simoa platform (Quanterix, Bilerica, MA,USA).ResultThe novel CT segmentations correlated significantly with their corresponding MRI‐segmentations. Lower CT‐derived tissue volumes correlated with higher plasma neurofilament (NFL) concentrations in the H70 cohort. In the MCC NUH cohort, lower CT‐derived volumes correlated with lower MMSE scores and higher plasma NFL. CT‐derived volumes yielded high diagnostic accuracy for AD vs CN (AUC ROC 0.87). Mean CT‐based volumetric measures were lower in AD and VAD compared with CN. Kruskal‐Wallis tests showed a statistically significant difference in CT‐based volumetric measures predominantly for GM/CSF and BV/CSF across all diagnostic groups, notably between AD vs CN and CN vs early stages of dementia.ConclusionDeep‐learning‐derived CT‐based volumetric measures correlate with relevant other imaging, cognitive and biochemical markers of neurodegenerative diseases. This supports the potential application of CT‐derived volumetric measures in aiding diagnostics and early detection of dementia. Further explorations of the association between CT‐based measures with visual assessments and other clinical and imaging biomarkers will be undertaken.
Influence of amyloid deposition on the interaction between tau and glucose metabolism
Authors: Nowell Joseph , Raza Sanara , Livingston Nicholas R. , Crook Harry , Young Megan , Edison Paul 
Published: February 2022

AbstractBackgroundPathological hallmarks of Alzheimer’s disease include the formation of extracellular Aβ plaques and intracellular neurofibrillary tau tangles, which with recent PET imaging advances can be assessed in vivo. Accumulation of tau has been closely linked to metabolic abnormalities in PET imaging studies, with inverse associations between tau deposition and glucose metabolism. This study aimed to assess whether the association between [18F]FDG and [18F]AV1451 in cognitively impaired patients is dependent on the presence of significant amyloid pathology.Method240 patients with mild cognitive impairment or Alzheimer’s disease (Mean age = 74.5 years, SD = 8.03) were evaluated from the Alzheimer’s Disease Neuroimaging Initiative (adni.loni.usc.edu). All participants completed a T1‐weighted MPRAGE MRI, amyloid ([18F]AV45 or [18F]florbetaben), [18F]AV1451 and [18F]FDG scans. Standard uptake ratio values were calculated in SPM12 to identify the glucose metabolic rate and tau deposition within cortical regions. Amyloid status (Aβ‐positive/Aβ‐negative) was determined from processed data using a whole brain cerebellar ratio with a cut‐off value of 1.11 ([18F]AV45) and 1.08 ([18F)florbetaben). Pearson’s correlation coefficients were calculated to assess the relationship between imaging modalities.ResultThere were significant negative associations between AV1451 and FDG tracer uptake in the medial temporal lobe (r = ‐0.389, p <0 .001), occipital lobe (r = ‐0.276, p = 0.001), parietal lobe (r = ‐0.209, p = 0.014), and posterior cingulate (r = ‐0.245, p = 0.004) in Aβ‐positive patients. Similarly, a strong negative relationship was observed between the imaging modalities in Aβ‐negative patients in the medial temporal lobe (r = ‐0.345, p < 0.001), however a significant positive association was also observed in the anterior cingulate cortex (r = 0.350, p < 0.001).ConclusionThis study demonstrated that [18]FDG and [18F]AV1451 tracers have strong regional signal associations in patients with cognitive impairment. The results indicate that tau has a detrimental effect on glucose metabolism in the medial temporal lobe, independent of significant amyloid plaque formation. In patients determined as amyloid‐negative, we may be observing some compensatory regional increase in glucose metabolism in the early stages of tau accumulation.
Fixel‐based analysis of the effect of amyloid beta on white matter tracts in neurologically normal 70 year olds
Authors: Wagen Aaron Z. , Zarkali Angeliki , Coath William , Buchanan Sarah M. , Keuss Sarah E. , Keshavan Ashvini , Lu Kirsty , James Sarah‐Naomi , Pavisic Ivanna M. , Street Rebecca E. , Parker Thomas D. , Lane Christopher A. , Murray‐Smith Heidi , Cash David M. , Malone Ian B. , Wong Andrew , Richards Marcus , Fox Nick C. , Altmann Andre , Cole James H. , Weil Rimona S. , Schott Jonathan M. 
Published: February 2022

AbstractBackgroundFixel‐based analysis (FBA) of diffusion MRI allows analysis of brain white matter (WM) tracts with greater specificity than voxel‐based approaches, including measures of microstructural fibre density (FD), macrostructural fibre cross section (FC), and representations of crossing fibres. We use FBA to explore early WM changes associated with amyloid‐β (Aβ) prior to manifestations of Alzheimer’s disease. We additionally explored global WM changes associated with increased cardiovascular risk.MethodWe performed FBA on 233 participants in the Insight 46 birth cohort study, all of whom have been followed prospectively since birth in a single week in 1946, including cardiovascular risk assessment using the Framingham Risk Score (FRS). At age 69‐71 participants underwent cognitive assessment and combined 18F‐florbetapir PET‐MRI scans on a single scanner. Aβ positive status was defined using a Gaussian mixed model as a standardised uptake value ratio over 0.6103. Using Aβ positive (n=40) and negative (n=193) participants with no major brain disorders and excellent scan quality, we assessed FD and FC, as well as the combined FD and FC (FDC) metric across all white matter fixels. Subsequently we performed a tract‐of‐interest analysis of associations between Aβ and FDC in 13 selected white matter tracts, 7 defined a priori based on Alzheimer’s disease mechanisms, and 6 based on results of the global analysis.ResultAβ positivity was associated with changes in microstructural and macrostructural changes (FD, FC and FDC), throughout the right corticospinal tract inferior to the internal capsule, and microstructurally in the right inferior longitudinal fasciculus. Similar left sided corticospinal changes were seen in FC and FDC only. Increased FRS was associated with FD changes in the right superior longitudinal fasciculus. Tract‐of‐interest analyses showed no significant associations between FDC and Aβ after false discovery correction using the Benjamini‐Hochberg method.ConclusionWe show Aβ associated changes in fixel‐based metrics in the corticospinal tracts, predominantly affecting the right hemisphere. These preliminary results raise the possibility of these fibres being predisposed to damage, perhaps in a length dependent manner, though longitudinal analysis based on further phases of Insight 46 may prove more powerful to detect change at this very early stage.
Longitudinal associations between amyloid and tau‐PET: Impact for prevention trials
Authors: Hanseeuw Bernard , Jacobs Heidi I.L. , Becker Alex , Buckley Rachel F. , Properzi Michael J. , Farrell Michelle E. , Schultz Aaron P. , Sanchez Justin S. , Chhatwal Jasmeer P. , Price Julie C. , Sperling Reisa A. , Johnson Keith A. 
Published: February 2022

AbstractBackgroundIn Alzheimer’s disease, cognitive decline is associated with a rapid increase in tau pathology, making tau‐PET a potentially useful outcome in prevention trials. To identify individuals most at‐risk of tau accumulation, we investigated the longitudinal associations between amyloid and tau in clinically normal (CN) and impaired (MCI/AD) participants from the Harvard Aging Brain Study.MethodSerial Flortaucipir tau‐PET measures (2‐4 observations over a median 2.2years [0.8 to 6.0]) were obtained from 128CN and 11MCI/AD participants (Table 1). PiB (amyloid‐PET) data were expressed as Centiloid (CL) values. Flortaucipir data were expressed as PVC‐SUVr in inferior temporal neocortex scaled to subcortical white matter. We obtained tau slopes per subject from linear mixed‐effect models with random intercept and slopes. We tested in the entire sample, and in CN only, the association between Tau slope and baseline PiB and Tau‐PET. Linear, quadratic, and cubic relationships were tested. Age and sex were used as covariates. We computed power curves simulating therapeutic trials.ResultIn the entire sample (n=139), both baseline Tau (R2=0.34, Fig. 1 red‐line) and PiB (R2=0.30, Fig. 2 red‐line) were linearly associated with subsequent tau slope. In CN (n=128), these associations were lower than in MCI/AD, but significant (Tau: R2=0.16, PiB: R2=0.15, p≤0.00001). Importantly, a cubic fit best matched the PiB data (Fig. 2 blue‐line): A positive association between baseline PiB and Tau changes was only observed between PiB CL=‐2 and CL=66, with a maximal association at CL=32. In CN, the greatest tau changes were observed at CL=66. There was evidence of slowing in tau accumulation rate in the small number of CN with higher PiB CL. As a result, trials simulations demonstrated that increasing the Centiloid threshold to enroll CN participants did not increase power (Fig. 3 blue‐lines); in contrast, power was increased when excluding CN with CL>66 (Fig. 3 red‐line) or when enrolling CN with high baseline tau (Fig. 4 red‐lines). Enrolling MCI patients in therapeutic trials had a similar effect than enrolling high‐amyloid CN participants with baseline Tau SUVr>1.30 (Fig. 4 blue‐line).ConclusionA combination of amyloid and tau thresholds proved more effective to increase the power of Tau‐PET outcomes in prevention trials than using only amyloid.