bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asymmetric caudate hypometabolism in the absence of frontal involvement on FDG‐PET in patients with semantic dementia and behavioral symptoms
Authors: Choudhury Parichita , Savica Rodolfo , Radford Jonathan Graff , Duffy Joseph R , Machulda Mary M. , Schwarz Christopher G. , Spychalla Anthony J. , Senjem Matthew L. , Gunter Jeffrey L. , Lowe Val J , Whitwell Jennifer L , Josephs Keith A 
Published: December 2020

AbstractBackgroundAlthough semantic dementia (SMD) presents with language decline, patients often develop behavioral changes. Behavioral symptoms in SMD are attributed to both cortical (orbitofrontal cortex atrophy) and subcortical (nucleus accumbens) degeneration in imaging and neuropathological studies. The caudate nucleus has been implicated in early behavioral changes in some phenotypes of frontotemporal dementia. The objective of this study was to determine whether asymmetric ipsilateral caudate nucleus hypometabolism on [18F]‐fluorodeoxyglucose positron emission tomography (FDG‐PET) is associated with early behavioral changes in the absence of frontal hypometabolism in SMD.MethodFifteen patients with a diagnosis of SMD evaluated by the Neurodegenerative Research Group (NRG) at the Mayo Clinic, Rochester from 2006‐2016, who had FDG‐PET, were included in this study. Clinical data was extracted from the medical records including age at presentation, sex, behavioral symptoms and duration of symptoms. Automated average Z‐scores generated from CortexID (GE Healthcare, WI, USA) using 3D stereotactic surface projections were obtained for the following regions bilaterally: temporal lobes, frontal lobes and caudate nucleus. Patients were categorized as left or right hemisphere lateralized based on the higher temporal lobe Z‐scores. Caudate nucleus and frontal lobe Z‐scores were then compared between the two sides for each patient. Hypometabolism was considered present if Z‐scores were greater than 2.ResultOf our cohort, 9/15 (60%) were females with a median age of 68 at presentation and had 3.5 years symptom duration. 13/15 had at least 1 behavioral symptom at presentation. Eleven patients were considered to have left‐lateralized whereas 4 were right‐lateralized in their temporal lobe hypometabolism. Median Z‐scores were significantly different for ipsilateral and contralateral caudate nuclei at 2.5 and 1.6, respectively (p=0.02, Wilcoxon nonparametric test). Frontal lobe median Z‐scores were 1.2 (ipsilateral) and 0.59 (contralateral) with no statistical difference between two sides (p=0.13).ConclusionIn SMD patients who exhibit behavioral symptoms with no frontal hypometabolism on FDG‐PET, asymmetric caudate nuclei hypometabolism should be explored as a possible imaging marker. This implicates abnormal frontal‐striatal circuitry in the development of behavioral symptoms even in the absence of frontal hypometabolism in early behavioral changes in SMD.
Cerebral amyloid deposition correlates with objectively measured sleep dysfunction
Authors: Tissot Cécile , Blais Hélène , Thompson Cynthia , Benedet Andréa Lessa , Pascoal Tharick A. , Therriault Joseph , Chamoun Mira , Lussier Firoza Z. , Savard Melissa , Rahmouni Nesrine , Stevenson Jenna , Gauthier Serge , Gosselin Nadia , Rosa‐Neto Pedro 
Published: December 2020

AbstractBackgroundSleep and circadian problems are known to be common along the Alzheimer’s disease (AD) spectrum. Previous research correlated an increase in CSF Aβ with poor sleep quality through self‐reported questionnaires in cognitively unimpaired (CU) individuals. Research on AD patients however showed an increase in tau‐PET. Today, there is increasing evidence that sleep disturbances are an early marker for AD pathology and marker of future risk of cognitive impairment. Our main objective was to study the relationship between sleep efficiency as assessed with polysomnography and amyloid, tau and neuroinflammation.Method28 individuals (21 CU and 7 mild cognitive impairment (MCI)) underwent a [18F]AZD4694 amyloid‐PET scan, [18F]MK6240 tau‐PET scan, [11C]PBR28 neuroinflammation‐PET scan, an MRI a full neuropsychological evaluation as well as a polysomnography. [18F]AZD4694, [18F]MK6240 and [11C]PBR28 standardized uptake value ratios (SUVRs) used the cerebellum grey matter as the reference region and were calculated between 40‐70 min, 90‐110 min and 0‐90 min post‐injection respectively. A voxel based regression model evaluated the relationship between the different pathophysiologies of AD, amyloid, tau and neuroinflammation, and sleep efficiency. The model’s covariates were age and diagnosis.ResultWe found a negative correlation between sleep efficiency as measured with a polysomnography and amyloid. The most impacted regions were the temporal poles, the inferior parietal cortex and subcortical regions such as the thalamus. However, we did not find a correlation with [18F]MK6240 and [11C]PBR28. When we corrected for apnea‐hypopnea index, sex and years of education, results were similar.ConclusionThese preliminary results show that poor sleep quality correlates with amyloid deposition in the brain of CU and MCI individuals. The regions impacted have been related to sleep regulation, such as the thalamus. They are also known to be vulnerable to AD pathophysiology, for example, temporal and inferior parietal cortices. Our study adds to previous research by identifying anatomical correlates, and also using objective assessment of sleep quality. It also corroborates with the idea that sleep deprivation promote Aβ deposition.
Data‐driven characterization of tau accumulation across the Alzheimer’s disease spectrum
Authors: Groh Jenna Rae , Svaldi Diana , Stage Eddie , Sanjay Apoorva Bharthur , Logan Paige E. , Risacher Shannon L. , Saykin Andrew J. , Apostolova Liana G. 
Published: December 2020

AbstractBackgroundWhile tau imaging is showing promise as a prognostic biomarker in Alzheimer’s disease (AD), additional work is needed to fully characterize its clinical usefulness. Using a data‐driven approach, we classified individuals based on tau deposition in Braak regions and assessed how demographic, cognitive, and imaging biomarkers behaved in relation to tau deposition in the brain.MethodWe included 317 ADNI participants (126 cognitively normal, 152 mild cognitive impairment, 39 dementia) with available AV1451 PET, FDG PET, AV45 PET, and MPRAGE MRI. Imaging summary variables for PET and MRI were downloaded form ADNI (http://adni.loni.usc.edu). Average AV1451 SUVR maps (Figure 2) were created in SPM 12. We used k‐means clustering to derive a two‐group solution for each Braak stage (Figure 1A) and the 75th percentile + interquartile range of the negative group from each clustering solution to define tau‐positivity. Subjects were grouped by tau positivity in Braak regions 1&2, 3&4 and 5&6. Group 000 is negative in all six regions; group 100 is negative in all regions except Braak 1&2; group 110 is only negative in Braak regions 5&6; and lastly, group 111 is positive in all regions (see Table 2). We used ANOVA with Bonferroni correction for multiple comparisons to compare demographic and cognitive, imaging biomarker measures across the groups.ResultTau‐positive Braak 1&2 individuals (group 100) were significantly older compared to individuals with more diffuse tau positivity. Mean cortical AV45 SUVR, prevalence of amyloid positivity, and cortical hypometabolism increased with increase in tau burden (group 000<100<110<111, Table 1 and Figure 1B). Absence of significant tau binding in group 000 did not indicate lack of amyloid deposition or hypometabolism (Figure 1B). In contrast, global tau deposition (group 111) showed higher global amyloid deposition and hypometabolism (Figure 1B).ConclusionGreater tau deposition makes individuals more likely to exhibit cognitive deficits. Absence of tau didn’t correlate with absence of cognitive impairment.
The association between migraine genetic risk and dementia: A Mendelian randomization study
Authors: Ackley Sarah F. , Rist Pamela M. , Brenowitz Willa D. , Graff Rebecca E. , Glymour M. Maria 
Published: December 2020

AbstractBackgroundAlthough some studies have suggested a possible link between migraine and dementia, there have been concerns that these associations may be due to diagnostic bias or unmeasured confounding. We tested whether migraine causes an increased risk of dementia using Mendelian randomization, which leverages genetic variability in migraine risk to estimate effects independent of confounding.MethodIn a sample of 259,839 individuals of European Ancestry aged 55 years or older from the UK Biobank, we calculated a migraine genetic risk score (MGRS) for each individual based on 38 known genome‐wide significant risk single nucleotide polymorphisms. Using algorithmically defined dementia diagnosis and migraine diagnosis from hospital and primary care sources, 2,069 and 11,357 individuals were diagnosed with dementia and migraine, respectively. Fluid intelligence score (score on a 13‐item test to assess logic and reasoning ability) and total brain volume normalized for skull size (TBV) were used as outcomes in addition to dementia diagnosis and were available for 174,609 and 10,229 individuals, respectively. Linear, logistic, and linear mixed‐effects models were used to assess the associations between the MGRS and TBV, dementia diagnosis, and fluid intelligence, respectively. Using instrumental variable regression with the MGRS as the instrument, we estimated the causal effect of migraine on dementia diagnosis, fluid intelligence, and TBV. All analyses were adjusted for the first 10 genetic ancestry principal components, orthogonal polynomials of degrees 1‐4 for age at time of outcome assessment, and genetic sex.ResultThe MGRS was strongly associated with migraine (p < 0.0001), but not dementia diagnosis (p = 0.22), fluid intelligence (p = 0.15), or TBV (p = 0.12). The estimated causal effect of migraine was a 3% (95% CI: [‐2%, 8%]) increase in absolute risk of dementia, a 1.1 (95% CI: [‐1.0, 3.1]) point increase in total fluid intelligence score, and a 123 (95% CI: [‐50, 296]) cubic centimeter decrease in TBV.ConclusionThe MGRS was not significantly associated with dementia diagnosis, fluid intelligence, or TBV. Using a Mendelian randomization approach, we did not find evidence that migraine causes dementia.
fMRI complexity is associated with tau‐PET and cognitive decline in Alzheimer’s disease
Authors: Jann Kay , Kim Hosung , Albrecht Daniel , Wang Danny J.J. ,   Alzheimer’s Disease Neuroimaging Initiative
Published: December 2020

AbstractBackgroundAmyloid‐PET is considered an early marker for the preclinical stage of AD, while the neurofibrillary tangle pathology detected with tau‐PET imaging correlates more closely with neuronal injury and cognitive decline. However, PET scans are expensive and involve radiation exposure. Recently, entropy measures have been explored as indices of the complexity of rs‐fMRI time‐series. Reduced entropy values were associated with aging, APOE ɛ4 genotype and cognitive decline in AD. Here we use complexity of BOLD signals as an index of the information processing capacity of regional neuron populations, and test the hypothesis that it is sensitive to tau‐related neuronal injury and cognitive decline in the AD processes.MethodData used in this study were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Our cohort consisted of a sample of 50 subjects form ADNI‐3 (age = 72.4±8.2, 19M/31F, 25CN, 19MCI, 6AD) with a T1 structural, a tau‐PET (tracer: 18F‐AV1451) and two fMRI scans. FMRI data underwent standard preprocessing before computing Multi‐Scale Entropy (MSE). Parametric SUVR images were calculated with a cerebellar reference region. Correlations between SUVR tau‐PET and MSE were calculated for 195 ROIs (Craddock atlas parcellation) including age, gender and regional gray matter volume as covariates. To evaluate if MSE and PET can be used to classify AD from CN we trained and tested a random‐forest classifier (via 10‐fold cross‐validation).ResultWe found significant negative correlations between low frequency MSE and tau‐PET measures in hippocampus, parahippocampal gyrus and posterior cingulate cortex (Figure 2). The classification model revealed that MSE and PET have similar prediction accuracy and sensitivity (Table Figure 3A). The most informative areas for the prediction revealed a large degree of overlap between MSE and tau‐PET (Figure 3B).ConclusionCorrelation and classification results for MSE in relation with tau‐PET revealed areas in PCC, temporal and parietal lobes. These areas are implicated in tau pathology and cognitive decline. Hence, these overlapping findings support our hypothesis that the complexity of rs‐fMRI is associated with regional tau protein accumulation measured by PET and could provide a marker for information processing capacity of regional neuron populations and prediction of cognitive decline in the AD processes.
Tau‐first subtype of Alzheimer’s disease progression consistently identified through PET and CSF
Authors: Aksman Leon M. , Oxtoby Neil P. , Scelsi Marzia Antonella , Wijeratne Peter A. , Young Alexandra L. , Alves Isadora Lopes , Alexander Daniel C. , Barkhof Frederik , Altmann Andre 
Published: December 2020

AbstractBackgroundSeveral studies contend that some Alzheimer’s disease (AD) subjects develop early‐stage tau pathology before amyloid pathology1,2, supporting a hypothesis that there are multiple distinct subtypes of amyloid and tau pathology progression within AD. We investigated this hypothesis, applying data‐driven disease subtyping models to both amyloid and tau PET as well as CSF measures.MethodWe performed two separate analyses using cross‐sectional data from ADNI. The first was a tau‐PET‐based analysis, which used eight regional amyloid PET (AV‐45) SUVRs and ten tau PET (AV‐1451) SUVRs from 402 subjects with both scans at the same visit. The second was a tau‐CSF‐based analysis, substituting CSF‐based prediction of tau PET SUVR (see Figure 2) in place of actual tau PET to give a larger dataset of 996 subjects. We used the Subtype and Stage Inference (SuStaIn3) algorithm to infer disease progression subtypes and individuals’ disease stages, and characterized demographic, cognitive and CSF differences across subtypes.ResultWe found two PET‐based subtypes in the tau‐PET‐based analysis: an amyloid‐first (84% of subjects) subtype and a tau‐first (16% of subjects) subtype in which Braak stage I‐III related tau SUVRs (hippocampus, amygdala, entorhinal cortex) become abnormal first (Figure 1A,B). The tau‐CSF‐based analysis confirms these subtypes: amyloid‐first (83% of subjects) and tau‐first (17% of subjects; Figure 2A,B). There were no significant differences in demographics or subject stages between subtypes in the tau‐PET‐based analysis (Figure 1C,D). In the tau‐CSF‐based analysis there was a small difference in age (amyloid‐first subjects 2.4 years older, Cohen’s f2 = 0.02, p < 0.05). Amyloid‐first individuals also had slightly worse executive function (Cohen’s f2 = 0.02, p < 0.05; Figure 3C) and, as expected, more abnormal CSF amyloid (Cohen’s f2 = 0.10, p < 0.001; Figure 3D) while tau‐first individuals had more abnormal CSF tau (Cohen’s f2 = 0.06, p < 0.001; Figure 3D).ConclusionWe identified amyloid‐first and tau‐first AD subtypes consistently across PET and CSF biomarkers. Our data‐driven approach supports the existence of a subtype of AD with tau accumulation prior to amyloid pathology. References: 1. Duyckaerts, et al., 2015, Acta Neuropath; 2. Weigand, et al., 2019, Brain Comm; 3. Young, et al., 2018, Nature Comm.
Sleep inefficiency is associated with altered hippocampal functional connectivity during encoding in postmenopausal women
Authors: Maki Pauline M , Wu Minjie , Aizenstein Howard J , Derby Carol A. , Thurston Rebecca C 
Published: December 2020

AbstractBackgroundIn a recent systematic review, the Alzheimer’s Association concluded that it is yet unclear whether sleep disturbance may be a modifiable risk factor for cognitive decline and dementia. This conclusion underscored the gap in understanding of which specific aspects of sleep (e.g., amount or quality) are associated with that risk and whether the sleep problems are a cause or precursor of dementia. To address that gap, we examined objective (actigraphy) measures of sleep in relation to hippocampal functional connectivity during a memory task. We focused on community‐dwelling postmenopausal women, a population with frequent poor sleep and a heightened lifetime risk of Alzheimer’s disease. We hypothesized that lower sleep efficiency but not sleep quantity would be associated with alterations in connectivity between the hippocampus and prefrontal cortex.MethodA total of 109 women (mean age=59.11 years; mean MOCA= 26.36; 78.0% white) from the MsBrain study completed 72‐hour sleep actigraphy assessments (Phillips Actiwatch‐A2) and blood‐oxygen‐level‐dependent (BOLD) fMRI assessments of verbal encoding and recognition. A generalized psychophysiological interaction (gPPI) analysis estimated task‐based hippocampal functional connectivity using SPM12 and Conn. The design matrix included principal time series of the seed region (left or right hippocampus), task conditions (novel words, familiar words), interaction variables (seed times series × task condition), and motion parameters. Sleep efficiency (% of time in bed spent sleeping) and total sleep time (hours slept) were regressed on patterns of brain connectivity in a region of interest confined to the hippocampus and prefrontal cortex, controlling for age, education and body mass index.ResultSleep inefficiency but not sleep quantity was associated with lower hippocampal‐prefrontal connectivity during encoding (corrected p < .05). During encoding, sleep inefficiency was associated with lower connectivity between the /right hippocampus and left/right middle frontal gyrus and dorsal anterior cingulate cortex (ACC). No effects were evident for recognition.ConclusionThe well‐established association between poor sleep and memory dysfunction in aging may be driven by poor sleep efficiency, which in turn may influence memory performance through decreased hippocampal‐prefrontal connectivity during encoding. Findings indicate a need for sleep interventions that help older adults to sleep better rather than longer.
HARMONY: Response to pimavanserin in the 12‐week, open‐label treatment phase
Authors: Foff Erin P. , Devanand Davangere P. , Ballard Clive , McEvoy Bradley , Stankovic Srdjan 
Published: December 2020

AbstractBackgroundDementia‐related psychosis (DRP) is common in patients with Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), Parkinson’s disease dementia (PDD), vascular dementia (VaD), and frontotemporal dementia (FTD). However, no therapies have been approved. Current guidelines and real‐world practice involve a trial of off‐label antipsychotics when other interventions fail, with assessment of response in an individual patient and taper within 4 months in patients who have responded. Pimavanserin is an inverse agonist/antagonist at the 5‐HT2A receptor and is approved in the U.S. for treating hallucinations and delusions associated with Parkinson’s disease psychosis. The objective of this analysis was to examine the response (≥30% reduction on the SAPS‐H+D Total Score AND a CGI‐I score of 1=very much improved or 2=much improved) to pimavanserin during open‐label treatment of patients with DRP.MethodHARMONY was a placebo‐controlled, randomized, Phase 3, relapse prevention study in patients with dementia (NIA‐AA criteria) and moderate to severe psychosis associated with PDD, DLB, AD, FTD or VaD. Eligible patients who failed brief psychosocial therapy during screening entered into a 12‐week open‐label (OL) period where they received pimavanserin 34 mg once daily. Patients were assessed for response at Weeks 8 and 12. Only patients who demonstrated sustained response (response at both Weeks 8 and 12) were eligible to randomize into the double‐blind portion of the trial. OL response rates and changes in psychotic symptoms were assessed in various subgroups within the study populationResult392 patients were enrolled into the open‐label period; 41 patients were ongoing at the time of early study termination. Overall, 61.8% of patients demonstrated sustained response (59.8% AD, 71.2% PDD, 71.4% VaD, 45.5% DLB, and 50.0% FTD). Mean change in the SAPS scores across the OL period was similar regardless of dementia subtype or baseline characteristics. The response rate was similar regardless of age, dementia severity, or previous drug therapy, with more than 50% patients meeting response criteria at Week 4 across most factors.ConclusionIn this Phase 3 study, during the OL treatment phase, pimavanserin produced a robust reduction in psychosis symptoms, irrespective of most likely clinical diagnosis of dementia subtype or baseline MMSE/dementia severity.
Brain connectivity and metacognition in persons with subjective cognitive decline (COSCODE): Retrospective analyses on the Geneva Memory Clinic cohort
Authors: Ribaldi Federica , Altomare Daniele , Garibotto Valentina , Mendes Aline , Assal Frederic , Eshmawey Mohamed , Chicherio Christian , Frisoni Giovanni B 
Published: December 2020

AbstractBackgroundAdvances in the Alzheimer’s disease (AD) field have enhanced awareness on brain health and prevention. This brings an increasing number of adults to ask for help in memory clinics for mild forgetfulness, leading to the increased use of health care resources. Nowadays, about 25% of memory clinics patients complain of cognitive decline in absence of objective deficits (subjective cognitive decline,SCD), and they are expected to increase in the coming years. Some patients with SCD later develop cognitive impairment and dementia, often due to AD, but the majority have psychiatric conditions, physical diseases, polypharmacy, or normal brain ageing. Differentiating these potential causes is often a difficult exercise even for expert physicians. The COSCODE project, funded by Swiss National Science Foundation and led by the Geneva Memory Clinic, aims to identify possible subgroups of SCD and their associated risk of decline. This abstract is focused on the retrospective analyses of SCD patients, to develop and future validate the recruitment criteria and SCD categorization.MethodsWe included 42 SCD from the Geneva Memory Clinic cohort with the following criteria:(i)Amyloid‐PET;(ii)MRI;(iii)clinical and neuropsychological evaluation;(iv)at least 1 follow‐up planned. To evaluate the representativeness of our sample we assessed the correlation between age, episodic memory and medial temporal lobe atrophy scale; Amyloid SUVr and Episodic memory. Then, a neuropsychologist and a neurologist evaluated the clinical reports in order to identify possible aetiologies of the cognitive complaint.ResultsIn the whole sample (age, mean±SD:71±7years; 54% female; education:16.3±4.1; MMSE:28.8±0.8; 24% A+) age is inversely correlated with episodic memory (Free‐and‐cue‐selective‐reminding‐test, p=0.003) and positively with medial temporal lobe atrophy scale (p=0.017). Amyloid SUVr correlates negatively with episodic memory performance (p<0.05). On the other hands, the clinicians found 3 different aetiologies of the SCD: Comorbidity (stroke, brain injury, cardio‐vascular risk factors, physical disability,...), Psychopathology (depression, anxiety, personality trait); Unknown (apparently, no reason associated to the complaint). The prevalence of the 3 groups is respectively:29%,33%,38%.ConclusionsOur SCD sample can be considered representative of a memory clinic population, indeed it’s a very heterogeneous group. The 3 groups categorization will be validated using a data driven approach and studying longitudinal trajectory of each subgroup to better understand their associated risk of decline.