bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognition in healthy older women is a predictor of 14‐year falls risk
Authors: Faux Noel G , Bird Stefanie , Michalewicz Aleks , Pasco Julie A , Sales Myrla P Reis , Russo‐Batterham Daniel , Vogrin Sara , Williams Lana j , Duque Gustavo , Szoeke Cassandra 
Published: December 2021

AbstractBackgroundFalls are a significant cause of injuries, loss of confidence, increased morbidity, and institutionalisation in all older people, with women at 50% greater risk than men. The relationship between dementia and falls is well established and 2/3 of all dementia occurs in women. In this study we explored risk factors associated with a 14 year falls risk in a community‐based cohort of women, which included validated measures across a wide range of clinical domains including neuropsychological, mood, quality of life and biomarkers (including hormonal).MethodThe Australian Women’s Healthy Aging Project is an longitudinal observation study, assessments every year (1991 –1999), followed by assessments in 2002, 2004, 2012 and 2014. The assessments included cognitive (as of 2002), blood, and cardiovascular disease risk assessment, and questions related to falls. After data cleaning, the remaining cohort consisted of 180 participants (Table 1). Missing data were imputed using mice random forest. To identify key risk factors associated with a 14 year falls risk, random survival (time to event) forest (RSF) machine learning was used.ResultThe RSF model, using all 290+ possible predictive variables, performed well with an Out Of Bag (OOB, withheld data) prediction error (C‐index) of 32.8%. The most predictive variables in the model were identified using the variable importance measure (VIM).The initial model was refined by taking the top 30 predictive variables and retraining the RSF. This refined model resulted in an improved OOB C‐index of 5.8% (27%). The top 20 predictive variables, Figure 1, include those associated with cardiovascular disease risk, cognitive performance, and hormone levels (e.g., family history of heart attack, digit symbol coding, and estradiol levels).ConclusionNinety percent of the top 20 predictive risk variables for the 14 year fall risk in women, were from three key domains, cognition (40%), cardiovascular (25%) and hormone‐related measurements (25%). Our data suggest that for long term prevention of falls these domains may be important reducing risk of falls in the senior female population.
QyScore® MRI markers' diagnostic accuracy in the clinical spectrum of Alzheimer's disease
Authors: Cavedo Enrica , Tran Philippe , Thoprakarn Urielle , Martini Jean‐Baptiste , Samper‐Gonzàlez Jorge , Movschin Antoine , Longo dos Santos Clarisse 
Published: December 2021

AbstractBackgroundDiagnostic criteria for Alzheimer’s disease (AD) acknowledge a key role of imaging markers such as hippocampus and amygdala volumes, for early diagnosis. Here we aim at assessing the diagnostic accuracy of QyScore® medial temporal lobe atrophy markers in distinguishing AD dementia and Mild Cognitive Impairment (MCI) individuals from healthy controls (HC) in US and EU cohorts.Method3DT1 images were selected from different cohorts (ADNI, MEMORA, NACC, OASIS3) and analyzed using the QyScore® automatic segmentation pipeline. Brain volumes of the hippocampus and the amygdala were normalized to the total intracranial volume. Analyses of variance were performed to compare volumetric measurements among clinical groups. Areas under the curve were calculated to identify the diagnostic accuracy of QyScore® markers in discriminating AD and MCI from HC.ResultThe sample was composed of 425 AD, 909 MCI and 993 HC with a higher prevalence of men and Apoe Ɛ4 carriers in each group. Analysis of variance showed a significant difference in hippocampal and amygdala volumes among groups. Preliminary results on the area under the curve (AUC) showed a good diagnostic accuracy in discriminating AD vs HC and MCI versus HC both for the hippocampal volumes (ADvsHC: AUC=0.86, 95%CI: 0.832‐0.877; MCIvsHC: AUC =0.75, 95%Ci: 0.726‐0.770), and the amygdala volumes (ADvsHC: AUC =0.77, 95%CI: 0.737‐0.791; MCIvsHC: AUC =0.70,95%CI 95%: 0.675‐0.720).ConclusionOur results highlight the good diagnostic performance of QyScore® markers, and support the relevance of implementing these markers in the diagnostic workflow of AD patients.
Metabolic syndrome impact on cognitive composites domain scores and on white matter hyperintensities in subjective cognitive decline: The FACEHBI Cohort
Authors: Ortega Gemma , Espinosa Ana , Alegret Montserrat , Monté‐Rubio Gemma , Sotolongo‐Grau Oscar , Sanabria Angela , Tartari Juan Pablo , Rodriguez‐Gomez Octavio , Marquié Marta , Vivas Assumpta , Gómez‐Chiari M , Alarcón‐Martín Emilio , Pérez‐Cordón Alba , Roberto Natalia , Hernandez Isabel , Rosende‐Roca Maitee , Vargas Liliana , Mauleon Ana , Abdelnour Carla , Antonio Ester Esteban‐De , López‐Cuevas Rogelio , Alonso‐Lana S , Moreno‐Grau Sonia , de Rojas Itziar , Orellana Adelina , Montrreal Laura , Tarraga Lluis , Ruiz Agustin , Boada Mercè , Valero Sergi 
Published: December 2021

AbstractBackgroundTo explore the impact of Metabolic Syndrome (MetS) and its components on Cognitive Composites (CCs) domain scores and on White Matter Hyperintensities (WMHs) in individuals experiencing Subjective Cognitive Decline (SCD).MethodTwo hundred participants from the FACEHBI cohort underwent structural Magnetic Resonance Imaging (MRI), 18F‐Florbetaben Positron Emission Tomography (FBB‐PET), and a comprehensive neuropsychological assessment. MetS was defined using the Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention criteria (elevated fasting glucose, elevated blood pressure, reduced HDL‐C, elevated triglycerides and elevated waist circumference). WMHs were addressed through the Fazekas scale, the Age‐related white matter changes (ARWMC) scale, and the FreeSurfer pipeline. Ten CCs domain scores were created using principal components analysis (PCA): (1) executive function fluency, (2) executive function processing speed, (3) executive function attention, (4) verbal memory, (5) visual memory, (6) face–name associative memory, (7) face–occupation associative memory, (8) language, (9) visuoperception, and (10) praxis. Age, sex, education, and Apolipoprotein E (APOE) were used as adjusting variables. Several analyses were performed to explore a sex effect.ResultForty‐seven individuals matched the MetS criteria. This syndrome behaves differently based on sex. Only women with MetS showed better performance in language (p = .002; OR = 2.12) than those without MetS. The only differentiating component between both groups (presence/absence MetS) was that women in the MetS subgroup presented greater abdominal obesity (Mann‐Whitney p = .001). From Mets group, antihypertensive drug treatment was significantly associated with better praxis scores (p = .012; OR = 1.84) and HDL‐C drug treatment with better language scores but worse episodic memory performance (p = .028; OR = 1.60; and p = .007; OR = .57, respectively). Drug treatment for elevated glucose was associated with low WMH load in the ARWMC scale (β= ‐.144; p = .045).ConclusionThis study demonstrated a protective effect of MetS in cognitive performance among SCD women with greater abdominal obesity and a lack of association between MetS and WMH load, although further investigation is needed to explore the long term impact of its entity.
A panel of novel astrocytic and synaptic biomarkers in serum and CSF for the differential diagnosis of frontotemporal dementia
Authors: Bolsewig Katharina , Hok‐A‐Hin Yanaika S. , Sepe Federica Nicoletta , Boonkamp Lynn , Jacobs Dirk , Bellomo Giovanni , Paoletti Federico Paolini , Vanmechelen Eugeen , Teunissen Charlotte E. , Parnetti Lucilla , Willemse Eline A.J. 
Published: December 2021

AbstractBackgroundFrontotemporal dementia (FTD) is the second most common form of presenile dementia. The differential diagnosis of FTD is still a challenging task due to its symptomatic overlap with other neurological diseases and the lack of diagnostic biomarkers. Here, we aimed to investigate the diagnostic potential of novel biomarkers in cerebrospinal fluid (CSF) and blood.MethodWe included 137 patients from the Centre for Memory Disturbances in Perugia with a diagnosis of FTD (n=37), Alzheimer’s disease (AD, n=47), Parkinson’s Disease (PD, n=14), Dementia with Lewy bodies (DLB, n=8), and cognitively unimpaired patients with other neurological diseases as controls (OND, n=31). All had AD biomarker measurements available. Enzyme‐linked immunosorbent assay (ELISA) or single molecule array (Simoa) were used to quantify the biomarker levels of NPTX2, NPTXR, NfL and GFAP in CSF, as well as NfL and GFAP in serum. Statistical analyses were performed using age and sex corrected analysis of covariance (ANCOVA), generalized linear mixed models (GLMM), ROC analyses, and Spearman correlation coefficients (ρ).ResultDifferences in protein levels across diagnostic groups were found for NPTX2, NPTXR, NfL (serum and CSF), and GFAP (serum and CSF, figure 1). GLMM predicted NPTX2 and total tau (t‐tau) to best distinguish FTD from OND (p<0.002), while serum GFAP and t‐tau best distinguished FTD from AD (p<0.05). A combined panel of NPTX2, serum GFAP and t‐tau differentiated FTD from the other groups with good accuracy (table 1). Serum GFAP and NPTX2 correlated negatively in FTD (ρ =‐0.40, p<0.05) and AD (ρ=‐0.31, p<0.05), but positively in DLB (ρ =0.87, p<0.01), while no significant correlation was found in OND and PD (figure 2).ConclusionWe show the potential use of a novel biomarker panel including CSF t‐tau, CSF NPTX2 and serum GFAP, for differential diagnosis of FTD from other dementias. The included biomarkers reflect different neurological pathways, i.e. neurodegeneration, synaptic and astrocytic function, respectively. This suggests a unique interplay of these pathways in FTD and demonstrates the added value of the novel biomarkers to the established classical AD biomarkers. To assess the diagnostic potential of this novel panel, validation in a larger cohort should be performed.
Altered music processing phenotypes in patients with frontotemporal dementia
Authors: van 't Hooft Jochum J. , Fieldhouse Jay L.P. , Singleton Ellen H. , Jaschke Artur C. , Warren Jason D. , Tijms Betty M. , Pijnenburg Yolande A.L. 
Published: December 2021

AbstractBackgroundFrontotemporal dementia (FTD) can present with changes in music appreciation. The aim of the present study was to determine the prevalence and nature of music appreciation phenotypes among FTD syndromes in a memory clinic population.MethodForty‐seven FTD patients (44.7% female, mean age 65.0±8.4, 31 behavioral variant FTD (bvFTD), 10 semantic dementia (SD), 6 progressive nonfluent aphasia (PNFA)) who consecutively visited our memory clinic were included in this study. Forty‐six caregivers (54.3% female, mean age 61.8±9.2) were included as a control group. Based on reported musical changes in the literature, we developed an informant‐based questionnaire by extending a previously used questionnaire (Fletcher et al., 2015). Music‐emotion recognition was assessed with a live music test in which both participants and caregivers were played 9 guitar chords, and rated if these were major, minor or dissonant (i.e. happy, sad or disharmonic). Visual emotion recognition was examined with the Ekman 60 faces test in a subgroup of patients (n= 23). Non‐parametric tests were used for group comparisons.ResultMusic appreciation phenotypes were observed in 79% of the FTD patients. Musicophilia was most often present (in 12/47 patients, 26%), followed by music anhedonia (23%), change of music taste (21%), increased singing (21%), sound‐aversion (19%), music‐aversion (13%), music agnosia (9%) and increased dancing (5%). Musicophilia was present in a third of bvFTD patients, but only in 10% of the semantic dementia and none of PNFA patients. The other reported music changes were more evenly distributed. The presence of music changes was not associated with lower performance on the music emotion recognition task (p = 0.62) or visual emotion recognition task (p = 0.87). However, compared to controls, bvFTD performed worse on the music emotion recognition task (p< .003), SD performed worse at trend level (p = .06) and no differences were found with PNFA (p = .8) patients (figure 1).ConclusionMusic appreciation phenotypes are highly prevalent in the FTD population, consist of a variety of symptoms, differ between syndromes and do not do not correlate with emotion recognizing capacities. Furthermore, compared to controls, bvFTD performed worse on a music emotion recognition test.
A comparison between tau and amyloid‐b cerebrospinal fluid biomarkers in chronic traumatic encephalopathy and Alzheimer disease
Authors: Turk Katherine W. , Geada Alexandra W. , Alvarez Victor E. , Xia Weiming , Cherry Jonathan D. , Huber Bertrand R. , Mez Jesse , Alosco Michael L. , Meng Gaoyuan , Nicks Raymond W. , Tripodis Yorghos , Budson Andrew , Dwyer Brigid , Kowall Neil W. , Cantu Robert , Goldstein Lee E. , Katz Douglas I. , Stern Robert A. , McKee Ann C. , Stein Thor D. 
Published: December 2021

AbstractBackgroundCerebrospinal fluid (CSF) tau and beta‐amyloid levels in chronic traumatic encephalopathy (CTE), a disease which can be clinically indistinguishable from Alzheimer’s disease (AD), are largely unknown. We examined postmortem CSF analytes among participants with autopsy confirmed CTE and AD.MethodA total of 192 participants from the Boston University AD Center and VA‐BU‐CLF Center had post‐mortem CSF collected at autopsy. Participants were divided into pathological groups based on consensus AD and CTE criteria, resulting in 61 participants with CTE (18 low, 43 high stage), 79 participants with AD (23 low, 56 intermediate to high pathological change), 11 participants with concurrent CTE and AD, and 41 participants lacking both CTE and AD neuropathology. The Meso Scale Discovery immunoassay system was utilized to measure amyloid‐beta (Ab1‐40, Ab1‐42), total tau (t‐tau), and phosphorylated tau (p‐tau181 and p‐tau231).ResultThe low CTE group had higher levels of p‐tau231 compared no CTE/no AD (p=0.041), and compared to the low AD group (p=0.018). The low CTE group had lower levels of Aβ1‐42 compared to no CTE/no AD (p=0.016). The high CTE group had higher levels of p‐tau231 compared to AD (p=0.025) and lower levels of Aβ1‐42 compared to the AD group (p=0.015). Importantly, p‐tau231 and Aβ1‐42 were predictors of diagnosis of CTE vs. no CTE/no AD and CTE vs. AD (Figure 1).ConclusionIncreased CSF p‐tau231 is a promising potentially sensitive biomarkers of CTE and decreased CSF Aβ1‐42 in CTE warrants further investigation as to underlying mechanism and potential as an additional CTE biomarker.
Predicting institutionalization and mortality across the spectrum of Alzheimer’s disease
Authors: Mank Arenda , Van Maurik Ingrid S. , Bakker Els D. , Teunissen Charlotte E. , Barkhof Frederik , Scheltens Philip , Berkhof Johannes , van der Flier Wiesje M 
Published: December 2021

AbstractBackgroundPatients and care partners express a desire for accurate prognostic information. Previous studies predicting institutionalization and mortality focused on the dementia stage. Yet, Alzheimer’s disease (AD) is characterized by a long pre‐dementia stage. We aimed to predict institutionalization and mortality in patients across the cognitive spectrum of AD.MethodWe included n=1418 non‐demented patients with Subjective Cognitive Decline (SCD) or Mild Cognitive Impairment (MCI) (age 63±7, 38%F, Mini Mental State Examination (MMSE) 27±2) and n=1179 patients with AD dementia (age 65±7, 53%F, MMSE 20±5) from the Amsterdam Dementia Cohort. The dates of institutionalization (admission to a nursing home; follow‐up 3.4±2.7 years) and mortality (follow‐up 4.5±2.7 years) were derived from Statistics Netherlands. We constructed models, stratified by dementia status, to predict institutionalization and mortality using Cox regression. We evaluated the following determinants: MMSE, Neuropsychiatric Inventory (NPI), Charlson Comorbidity Index (CCI) and APOE e4 status, MRI (medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), white matter hyperintensities (WMH)) and CSF biomarker levels (Aβ42 and p‐tau). Determinants were selected using backward selection (p<0.10). All models included age and sex. In addition, we evaluated the discriminative performance of models without MRI and CSF biomarkers. Discriminative performance of the models was assessed with Harrell’s C statistics.ResultIn non‐demented patients, n=123 (9%) patients died and n=74 (5%) patients were institutionalized. In AD dementia, n=413 (35%) patients died and n=453 (38%) patients were institutionalized. Table 1 shows the optimal prediction models for institutionalization and mortality. Discriminative performance was better in non‐demented patients than in those in the dementia stage: institutionalization (Harrell’s C 0.81 vs 0.68) and mortality (0.78 vs 0.66). Although model fit was better for the full model, discriminative performance was comparable for the model without MRI for institutionalization and without CSF for mortality in non‐demented patients (Table 1).ConclusionWe constructed prediction models to predict institutionalization and mortality in patients across the spectrum of AD. Highest discriminative performance was found in models for non‐demented patients with SCD or MCI. CSF biomarkers contributed most to predict institutionalization and MRI biomarkers to predict mortality.
Life activity patterns and mild cognitive impairment in older adults
Authors: Wu Chao‐Yi , Gothard Sarah , Mattek Nora , Wright Kirsten M , Kaye Jeffrey A , Dodge Hiroko H , Beattie Zachary 
Published: December 2021

AbstractBackgroundShifting and diminished circadian and activity rhythms characterize older adults with cognitive impairment, but studies rarely consider both temporal and spatial aspects of life activity patterns. We examined hourly in‐home and out‐of‐home activity patterns using latent group trajectory models to characterize older adults with and without mild cognitive impairment (MCI).MethodOne hundred and seven older adults (19 with MCI) living alone (age=81.1±7.8, 76.6% women) from the Oregon Center for Aging & Technology (ORCATECH) were included. MCI was determined by the Clinical Dementia Rating (CDR) score = 0.5. In‐home and out‐of‐home activities were collected via passive infrared motion sensors in each room and contact sensors on the doors to the home for one month. Daily life activity patterns were estimated based on: 1) the hourly average amount of time the participant spent in each major life space (bathroom; bedroom; kitchen; living room) and out‐of‐home, and 2) the hourly average number of trips the participant made to each room and out‐of‐home.ResultLatent trajectory models identified two distinct patterns for three features: time spent out‐of‐home (high/low outdoor), time spent in the kitchen (high/low kitchen occupancy), and trips to the bathroom (more/fewer bathroom trips) from 5 am to 1 pm. Older adults with MCI were more likely to follow a pattern of low outdoor time (β=‐2.65; p=0.03), high kitchen occupancy (β=1.68; p=0.01), and more bathroom trips (β=1.60; p=0.02) than those with intact cognition. There were no differences in the bedroom patterns or time spent in the bathroom in older adults with and without MCI from 5 am to 1 pm. Potential covariates were controlled in the models (age, gender, years of education, sleep duration, gait speed, and the number of rooms in the house).ConclusionDifferent social and mealtime activity patterns from early morning to early afternoon may signal cognitive changes and contraction of life‐space. These may be caused by environmental, as well as chronobiological changes accompanying MCI. Unobtrusive measurement of in‐home and out‐of‐home activity patterns may be useful for integrating with chronotherapies in developing strategies to mitigate potential daily mal‐entrainment for older adults at risk for MCI and dementia.
Traumatic brain injury and age at onset of cognitive decline in corticobasal degeneration, corticobasal syndrome, and progressive supranuclear palsy
Authors: Spiegel Jonathan , Sone Je Yeong , Butler Tracy , Pirraglia Elizabeth , de Leon Mony J. 
Published: December 2021

AbstractBackgroundTraumatic brain injury (TBI) has been repeatedly shown to be a risk factor for several neurodegenerative diseases. However, no studies have yet examined TBI as a risk factor for corticobasal degeneration (CBD) or corticobasal syndrome (CBS), and few have examined progressive supranuclear palsy (PSP) in relation to TBI.MethodThis is a retrospective observational study using the National Alzheimer’s Coordinating Centers (NACC) database. TBI status was assessed based on self‐reported history. Clinicians estimate was used for determining age at onset (AAO) of cognitive decline and autopsy examination was used for neuropathological diagnosis of CBD and PSP. The most recent assessment of participants was used as of June 2018, including participant visits which occurred between 2005 and 2018. The NACC dataset includes a total of 38,249 participants. 101 (14 TBI+) participants were included with clinical (antemortem) diagnoses of PSP and 137 (16 TBI+) with CBS. 2,743 autopsy samples were also included, including 120 (14 TBI+), 58 (7 TBI+), and 11 (1 TBI+) with neuropathological (autopsy) diagnoses of PSP, CBD, or both, respectively. 181 (21 TBI+) of the participants with autopsy diagnosed PSP or CBD had antemortem cognitive decline.ResultTBI is associated with a significant 4‐year earlier AAO of cognitive decline among participants with an antemortem diagnosis of CBS and a 6‐year earlier AAO in participants with autopsy diagnosed PSP. Additionally, TBI among participants with autopsy diagnosed CBD without concomitant Alzheimer’s disease (AD) neuropathology was associated with a 7‐year earlier AAO of cognitive decline (p=.066). History of TBI was not significantly associated with the prevalence of PSP and/or CBD pathology postmortem.ConclusionThis is the first report linking TBI with an earlier onset of cognitive decline in CBS and in neuropathologically defined PSP.