bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of 18F‐Flortaucipir visual assessment, SUVR quantification and CSF pTau for defining T‐status in the AT(N) framework
Authors: Provost Karine , Iaccarino Leonardo , Soleimani‐Meigooni David N. , Lesman‐Segev Orit H. , Joie Renaud , Mattsson Niklas , Hansson Oskar , Eichenlaub Udo , Edwards Lauren , Strom Amelia , Pham Julie Q. , Mellinger Taylor J. , Janabi Mustafa , Baker Suzanne L. , Jagust William J. , Rabinovici Gil D. ,   ADNI
Published: December 2020

AbstractBackgroundTau‐PET is included in the AT(N) research framework to define T‐status. However, no consensus exists as to how to classify patients as T+ or T‐ with this modality. We aim to compare T‐status derived from 18F‐Flortaucipir (FTP) PET visual assessment, 18F‐FTP SUVR quantification, and CSF pTau.Methods278 subjects who underwent 18F‐FTP PET and CSF analysis within 1 year were included from UCSF and ADNI. The cohort consisted of a continuum from cognitively normal controls (CN) to Alzheimer’s disease dementia (AD), and non‐Alzheimer’s disorders (clinical diagnoses, Table 1). T‐status was derived from: (1) 18F‐FTP consensus between two readers performing blinded visual assessment based on a priori criteria (Figure 1, inter‐rater k=0.68, 95%CI 0.59‐0.76; Provost et al, HAI Conference, 2020); (2) 18F‐FTP SUVR quantification of from a temporal meta‐ROI using a previously validated threshold (SUVR >1.27, Ossenkoppele et al. 2018); (3) Elecsys® Phospho‐Tau (181P) CSF (Roche Diagnostics) applying a ROC‐based threshold derived from an external ADNI cohort comparing amyloid‐positive AD vs. healthy controls (pTau >24.5 pg/mL).ResultsT+ was assigned in a higher proportion of AD, MCI and amyloid‐positive CN with 18F‐FTP visual assessment compared to 18F‐FTP SUVR and CSF pTau (Table 2). However, visual ratings also yielded the highest proportion of T+ in amyloid‐negative CN and MCI. Contrasting amyloid‐positive AD/MCI with other groups, sensitivity was highest for 18F‐FTP visual assessment, while specificity was highest for 18F‐FTP SUVR (Table 3). In a subset of patients with autopsy (n=11), T‐status derived from 18F‐FTP visual assessment had an accuracy of 100%, compared to 82% for SUVR quantification and 64% for CSF pTau. Overall agreement between the 3 classification criteria ranged from 68% to 76% in the whole cohort (Figure 2) and was highest in patients with AD (94%). Patients with concordant T‐status across all three modalities were significantly younger, had higher CSF pTau, higher 18F‐FTP SUVR (Figure 3), and were more likely to be amyloid positive.ConclusionsConcordance of T‐status derived from 18F‐FTP visual assessment, SUVR quantification and CSF pTau varies across disease stage, being highest in AD. 18F‐FTP visual assessment offers highest sensitivity, while SUVR threshold maximizes specificity.
Determining the role of lactate metabolism on age‐dependent memory decline and neurodegeneration in Drosophila melanogaster
Authors: Frame Ariel K. , Simon Anne F. , Cumming Robert C. 
Published: December 2020

AbstractBackgroundAlthough lactate has traditionally been considered a waste product, recent discoveries show lactate plays many beneficial roles in the brain. Astrocyte generated lactate can function as a fuel for neurons to enable long‐term memory. However, elevated lactate has been detected within the brain and cerebrospinal fluid of Alzheimer’s disease patients; a finding associated with hastened memory impairment. Whether perturbed lactate levels contribute to age‐related memory impairment is unknown. This study uses the fruit fly Drosophila melanogaster to elucidate the role of lactate metabolism in cognition during aging.MethodThe enzyme lactate dehydrogenase (dLdh), which facilitates the interconversion between lactate and pyruvate, was genetically manipulated in glia and neurons of Drosophila melanogaster. Transgenic flies were tested for changes in lifespan, memory, climbing ability, neurodegeneration as well as dLdh and lactate levels in the brain. Tests in transgenic flies were performed at ages ranging from young (7 days) to old (28 days). Memory was assessed using the courtship conditioning paradigm, of which only male flies can be tested.ResultsLactate and dLdh protein levels were correspondingly elevated or lowered in transgenic flies with increased or decreased dLdh expression respectively. Transgenic flies with either increased or decreased dLdh expression exhibited reduction in lifespan and neurodegeneration at old age. These detrimental effects were present whether dLdh expression was altered in either neurons or glia, yet only neuronal dLdh upregulation caused deficits in climbing ability. Young transgenic flies with altered dLdh expression in either neurons or glia all exhibited memory similar to control. Interestingly, only flies with increased glial‐derived dLdh expression had an impact; memory was impaired at middle age then recovered at old age.ConclusionProlonged perturbation of lactate metabolism results in neurodegeneration and increased rate of health decline in flies. The impact of altered lactate levels on memory appears to be cell type specific and dynamic. Excess glial‐derived lactate only appears detrimental to memory during middle age. However, excess or diminished production of lactate, within neurons or glia, hastens aging and neurodegeneration. Future studies of age‐related diseases, such as Alzheimer’s, should focus on lactate metabolism and metabolic interplay between neurons and glia.
Visual attention as a model for interpretable neuroimage classification in dementia
Authors: Cole James , Wood David , Booth Thomas 
Published: December 2020

AbstractBackgroundDeep learning has the potential to aid clinical decision‐making in dementia, by automatically classifying brain images. However, several key limitations currently prohibit clinical adoption: 1) network design must be optimised for 3D neuroimaging; 2) analysis must be computationally feasible; 3) model decisions must be interpretable. Interpretability is particularly crucial, as clinicians need to understand how and why each automated decision is made.MethodWe address these issues using a 3D recurrent visual attention model tailored for neuroimaging: NEURO‐DRAM. The model comprises an agent which, trained by reinforcement learning, learns to navigate through volumetric images, selectively attending to the most informative regions for a given task. We trained and tested NEURO‐DRAM using T1‐weighted MRIs from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. This entailed n=162 Alzheimer’s Disease (AD) patients and n=160 healthy controls (HCs), split into training (90%) and testing (10%) data. Classification generalisability was evaluated using independent AD patients (n=130) and HCs (n=100) data from the Open Access Series of Imaging Studies (OASIS) dataset. Finally, we assessed the potential to transfer the classification task (i.e., no extra training needed) to discriminate between the baseline MRIs of people with stable or progressive mild cognitive impairment (MCI).ResultNEURO‐DRAM achieved 98.5% balanced accuracy when classifying AD patients from HCs from ADNI and 99.8% in OASIS, significantly out‐performing a baseline convolutional neural network. When classifying stable versus progressive MCI, accuracy was 77.8%. For each test participant, an individualised trajectory was obtained, depicting the brain regions that were used to make the specific classification (Fig. 1). The regions ‘visualised’ by the model’s trajectories included the hippocampus, parahippocampal gyrus and lateral ventricles. Computation time for training NEURO‐DRAM was substantially faster than the baseline network (10 minutes versus 45 minutes).ConclusionUsing a data‐driven approach, near‐perfect classification of AD patients from HCs can be achieved. To reach this high level of performance, our model learns to ‘visually’ attend to the areas of the brain radiologically associated with AD. Importantly, the neuroanatomical trajectory for each individual run through the analysis can be visualised, providing an intuitive way to interpret how NEURO‐DRAM has reached a classification decision.
Screening for dementia in Down syndrome using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE)
Authors: Mattar Guilherme Prado , Haddad Glenda Guerra , Uchida Ricardo Riyoiti , Fonseca Luciana Mascarenhas , Forlenza Orestes Vicente 
Published: December 2020

AbstractBackgroundDown syndrome (DS) is genetically associated with Alzheimer´s disease (AD), and the neuropathological features of AD can be found in DS brains since early adulthood. Screening tests are required for the clinical assessment of dementia; however, the presence of intellectual disability at various degrees precludes the use of most of the available cognitive screening tests in this population, and few instruments have so far been validated for this purpose. The aim of the present study was to examine the psychometric properties of the IQCODE for the screening for cognitive/functional decline and dementia in DS.Method92 aging adults with DS (mean age 43.45 SD 8.51; 61.0% males) were enrolled for a cross‐sectional assessment by two independent psychiatrists. Inclusion criteria were: diagnosis of DS according to the International Classification of Diseases, tenth edition (ICD‐10); minimum age of 30 years; and having an informant with daily contact with the subject for the past 10 years at least. Participants were assessed by the Cambridge Examination for Mental Disorders of Older People with Down syndrome and others with Intellectual Disability (CAMDEX‐DS) using a validated Brazilian version, and by the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). The concurrent validity of the IQCODE was analyzed in relation to the gold standard CAMDEX‐DS diagnosis.ResultParticipants were allocated into three diagnostic groups according to the CAMDEX‐DS: 1‐ dementia (N= 13); 2‐ prodromal dementia (N=17); and 3‐ stable cognition (N=62). ROC curve analyses were carried out to determine the diagnostic accuracy of the IQCODE in comparison to CAMDEX‐DS by diagnostic pairs indicated that the IQCODE optimal cut‐off scores for each diagnostic pair were as follows: (a) AD versus stable cognition: 3.14 (AUC=0.993; sensitivity: 100% specificity: 96.8%; (b) AD + prodromal versus stable cognition: 3.11 (AUC=0.975; sensitivity: 93.3%; specificity: 91.9%).ConclusionThe IQCODE appears to be a suitable tool for the brief screening of cognitive/functional decline in aging DS adults.
Racial comparisons of MRI and PiB PET in acute stroke
Authors: Koenig Lauren N , McCue Lena , Grant Elizabeth A , Massoumzadeh Parinaz , Roe Catherine M , Xiong Chengjie , Moulder Krista L. , Wang Liang , Zazulia Allyson , Kelly Peggy , Dincer Aylin , Zaza Aiad , Morris John C. , Shimony Joshua S , Benzinger Tammie L.S. 
Published: December 2020

AbstractBackgroundStroke and Alzheimer disease share risk factors and often co‐occur, and both have been reported to have a higher prevalence in African‐Americans. However, the interaction of race, stroke, and Alzheimer disease has not been established.MethodWe compared MRI and PiB PET biomarkers of non‐demented participants with and without acute ischemic stroke (total n=243, age 65‐101), with a focus on comparing African‐Americans (n=42 with stroke, n=84 without) to Non‐Hispanic Whites (n=39 with stroke, n=78 without). Our assessment included radiologic reads of the number of large infarcts, small infarcts, microbleeds, and leukoaraiosis; a PET measure of amyloid binding; quantitative measures of hippocampal volume and white matter hyperintensities; and longitudinal Mini Mental State Exam (MMSE) scores. Statistical analysis used logistic regression models to predict each biomarker using race and stroke status, while controlling for age, family history, APOE4, education, sex, and high blood pressure.ResultPiB PET did not differ significantly by stroke status or by race, with 23.6% of participants being classified as amyloid positive (Figure 1). As expected in stroke, the acute stroke participants were more likely to have large infarcts, small infarcts, microbleeds, and non‐zero Fazekas scores. MMSE showed racial differences at baseline (mean 26.8 for African‐Americans, 27.9 for Non‐Hispanic Whites, p=0.03), but not longitudinally. Overall, African‐Americans were more likely to have microbleeds (32.8% vs 22.6%, p=0.04). Within the stroke group African‐Americans were more likely to have small infarcts (75.6% vs 56.8%, p=0.049). Combined, African‐Americans were also more likely to have more than 5 microbleeds ‐ the cutoff for many Alzheimer clinical trials (15.2% vs 9.6%, p=0.04).ConclusionPreclinical Alzheimer disease does not appear to be a risk factor for stroke and did not differ by race in our sample. Standard clinical MRI measures differed by stroke status, but showed few racial differences. The observed lower MMSE scores in African‐Americans has been reported previously and may arise for a variety of reasons. In individuals with stroke, African‐Americans may have more severe pathology as evidenced by greater numbers of small infarcts and microbleeds. African‐Americans may be more likely to be excluded from Alzheimer disease clinical trials due to having 5 or more microbleeds.
Investigating early changes in cognitive ability in the cognitively healthy and early‐stage cognitively impaired older adult populations
Authors: Idowu Mojitola , Parton Andrew , Szameitat Andre 
Published: December 2020

AbstractBackgroundDecline in cognitive ability is well understood to occur due to advanced age and pathological impairment. However, not all affected aspects of cognitive ability deteriorate at the same rate (Petersen, RC, et al., 1997; Craik, FI, and Salthouse TA, 2000, 2008, 2011; Salthouse, TA, 2009, 2012).In this study, we research how executive function abilities (mental processes that regulate and control our cognition) differ between cognitively healthy older adults and individuals living with Mild Cognitive Impairment (MCI) and early‐stage Alzheimer's disease (AD). Assessment was focused on four areas of executive functions dual‐tasking, inhibition, shifting and updating commonly utilised in everyday life (Miyake, A, et al., 2000; Alvarez, JA, and Emory, E, 2006; Suchy, Y, 2009; Baddeley, A., 2012). The aim is to better understand the nature and rate of deterioration as a means to aid in early detection and intervention for both conditions.MethodWe aim to assess approximately 30 cognitively healthy older adults, and a combination of 30 individuals living with MCI and early‐stage AD on four different aspects of executive functions, i.e. dual‐tasking, inhibition, shifting and updating. Two separate tasks will be utilised to measure each EF, dual‐tasking (the Test of Everyday Attention dual‐task telephone search subtest and Psychological Refractory Period paradigm task), inhibition (the Hayling Sentence Completion test and Stroop task), shifting (the Trail Making Test and a task switching test), and updating (the backward digit recall span test and a N‐back task).ResultData collection is ongoing.ConclusionWe predict better cognitive ability will be evident in the healthy older adult group, followed by the MCI and then the early‐stage AD groups. However, we expect dual‐tasking and updating ability to be most severely affected in individuals living with early‐stage AD and then shifting with inhibition showing most preservation.
A specific pattern of memory errors in asymptomatic at‐risk for AD
Authors: Gagliardi Geoffroy Pierre , La Corte Valentina , Epelbaum Stéphane , Houot Marion , Dubois Bruno , Dalla Barba Gianfranco 
Published: December 2020

AbstractBackgroundWhile memory performance is well studied in preclinical Alzheimer's disease (AD), there are relatively few studies concerning memory errors. However, in the clinical and prodromal stages, intrusions are very frequent, and the specific error profile appears to be particularly diacritical compared to other diseases. In this study, we explore whether the specific pattern of errors produced in memory tests can be predicted by AD biomarkers load in asymptomatic individuals at risk for AD.Method318 cognitively normal older adults from the INSIGHT‐PreAD cohort were studied. We present here the data for a three‐year follow‐up. Errors were recorded in two types of memory tests, a verbal test (i.e., FCSRT) and a visual test (i.e., DMS48). Given the distribution of the data, we used Zero‐Inflated Generalized Linear Mixed‐effects Models (ZIGLMMs). Concerning verbal intrusions, two types of patterns were studied, either their context of occurrence (free vs. cued recall) or the type of error (semantically related or not). For visual false recognitions we studied the type of error (i.e. Paired, Abstract or Unique).ResultParticipants produced significantly more semantically related intrusions regardless of the level of brain amyloidosis. Regarding context, participants with higher amyloid produced significantly more intrusions in free recall situations. However, there is no effect of the SUVr on those occurring in cued recall. For false recognitions, the level of brain amyloidosis significantly increases the frequency of unrelated errors (semantically and graphically). All together, the SUVr value efficiently predict a specific error pattern.ConclusionThis study demonstrates that a specific pattern of memory errors can occur even at early stages of AD evolution. Regarding verbal tests, our results show that asymptomatic at‐risk participants tend to exhibit errors in free recall situations, which can be related to an early executive retrieval dysfunction. In visual modality, the results suggest an abolition of familiarity, associated with the internal temporal regions, which are precociously affected in AD. Our results show that a specific error profile is associated with increased brain amyloidosis in cognitively normal elderly participants.
Do depressive symptoms at time of diagnosis affect the course of dementia over one year?
Authors: Edwards Devin A. , Kirk Andrew , O'Connell Megan E. , Karunanayake Chandima P. , Panyavin Ivan , Morgan Debra G. 
Published: December 2020

AbstractBackgroundDepressive symptomatology has long been associated with dementia. The exact form of this association (e.g. whether depression is a risk factor and/or a prodrome) is uncertain. While much research has gone into confirming this link, there has been little investigation into the effects of depression on dementia progression after diagnosis. The aim of this study is to investigate the relationship between depressive symptomatology at dementia diagnosis and cognitive and behavioural decline over a one year period as represented by clinical evaluations.MethodsIn 375 rural and remote patients who had been diagnosed with mild cognitive impairment (MCI), Alzheimer’s disease (AD), or non‐AD dementia, the Center for Epidemiological Studies Depression Scale (CES‐D) was completed at first visit to assess depressive symptomatology. The same cohort was evaluated for cognitive and behavioural decline through the completion of five clinical tests performed at first visit and at a one year follow up. Cognitive decline was assessed using the Mini Mental Status Examination (MMSE), Clinical Dementia Rating Scale (CDR), and two subsets of the Neuropsychiatric Inventory (NPI‐S and NPI‐D). Functional decline was assessed using the Functional Activities Questionnaire (FAQ). Correlations were examined between CES‐D score and change in cognitive and functional scores over one year in the subgroups of Patients with all types of dementia or mild cognitive impairment (ATD, N=375 ), Alzheimer’s type dementia (N=187), and Mild Cognitive Impairment (=74).ResultsNo significant correlations were observed between cognitive or functional decline and baseline depressive symptomatology.ConclusionSeverity of depressive symptomatology at the time of diagnosis does not predict severity of cognitive or functional decline at one year in patients with dementia or mild cognitive impairment.
Genetic and environmental influences on semantic verbal fluency across midlife and later life
Authors: Gustavson Daniel E. , Panizzon Matthew S. , Kremen William S. , Reynolds Chandra A. , Nygaard Marianne , Wod Mette , Catts Vibeke S. , Lee Teresa , Gatz Margaret , Franz Carol E. ,   IGEMS Consortium
Published: December 2020

AbstractBackgroundDespite the relevance of semantic fluency measures to risk for dementia and psychiatric disorders, little is known about their genetic and environmental architecture in mid‐to‐late life. Existing studies in community samples of middle‐aged or older adults have yielded a wide range of heritability estimates for semantic fluency (20% to 77%). Some inconsistency may be due to measures available, but genetic variance on semantic fluency may also differ as a function of age, education, or other variables that varied across these studies.MethodParticipants represent 21,684 middle‐aged and older adult twins (M = 60.84 years, SD = 11.21; Range 40‐89) from six studies from three countries participating in the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium, representing three countries (Australia, Denmark, and the United States). All subjects completed the same measure of semantic fluency (naming animals in 60 seconds). Education was based on the International standard classification of education (ISCED).ResultResults revealed small‐to‐moderate phenotypic associations with age (b = ‐.182, p < .001), age‐squared (b = ‐.005, p < .001) and education (b = 1.18, p < .001), with education more strongly positively associated with fluency performance in females than males. Heritability decreased with age, ranging from a2 = .58 to a2 = .40 in 40 versus 89‐year‐olds respectively. Genetic variance increased as education increased and nonshared environmental variance decreased with higher education, but the modification of heritability by education was only observed in males.ConclusionSemantic fluency is interwoven with a network of other cognitive abilities and highly relevant to aging/dementia. However, there is much to learn about its genetic and environmental structure and the way these influences vary based on other biological and environmental factors. This is the largest study to examine the genetic and environmental architecture of semantic fluency, and the first to demonstrate that these influences vary based on age, sex, and education. These findings highlight the dynamic interplay of genetic and environmental influences on cognitive function, and highlight the need to examine the genetic underpinnings of cognition using very large samples that can capture these complex associations.