bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive profile and motor phenotype in Mexican patients with familial early onset Alzheimer disease with the p. Ala431Glu variant of the PSEN1 gene
Authors: Téllez‐Martínez José Alberto , Verson Carmen Alaez , Sosa‐Ortíz Ana Luisa 
Published: December 2020

AbstractBackgroundGiven the deleterious consequences for patients and families with autosomal dominant AD, it is necessary to identify individuals at risk in preclinical phases, with the objective of include them in clinical intervention trialsMethodWe included 11 DNA samples from patients diagnosed with FAD and 9 DNA samples with of patients with EAD, which were analyzed by clinical exome sequencing in Nextera Next Seq equipment. Results are reported on a case‐by‐case basis for genomics, cognitive, neuropsychiatric, motor, and functional evaluations.ResultWe identify 9 carriers of the pathogenic variant p. Ala431Glu of the PSEN1 gene and in 4 of these patients, more than one uncertain significance variant was identified in the ANO5, TYROBP, ALS2, WASHC5, ABCA7, TOMM40, CLU, ATP7B, USH2A genes. In 5 patients we identify another pathogenic variants in PSEN1 gene. Estimated age at onset (AAO) in carriers of A431E variant was 40.6 ± 3.1 years, while in the Non A431E group was 46 ± 11.6. Patients with E431E variant had the worst performance at the beginning and in his last evaluation in all the cognitive tests. The most striking differences were in MMSE (16.3 ± 6.1 and 9.4 ± 6.2 vs 18.1 ± 2.1 and 11.9 ± 4.7) and PHFV tests (4 ± 5.2 and 1.33 ± 2.2 vs 6.1 ± 0.2 and 2.6 ± 2). The most frequent neuropsychiatric symptoms in A431E group was depression, anxiety and irritability, while in the EAD was apathy. Near to 40% of patients A431E has motor symptoms at baseline, and this percentage increased to 80% in the latest evaluation. This group had a high frequency of stiffness, tremor and spastic gait and in EAD the most consistent symptom was postural tremor. The motor‐symptom profile is presented in Figure 1.ConclusionA high frequency of the Jalisco variant is reported in Mexican patients with FAD. This variant is related to early onset of symptoms, rapid progression, as well as a high frequency of motor symptoms. This makes it necessary to consider their identification of this variant as a first step in the diagnostic algorithm of this type of population. The identification of patients carrying this variant requires correct genetic counseling and makes them candidates to enroll in international clinical trials of pharmacological intervention.
Detecting language impairment using ELIEC
Authors: Parsapoor Mahboobeh 
Published: December 2020

AbstractBackgroundMachine learning (ML) can detect language impairment. However, it is challenging, if we do not have sufficient language data. To deal with this issue, we suggest using ELiEC or "Emotional Learning‐inspired Ensemble Classifier". It is a new ML algorithms that can learn from a few examples. This paper briefly describes ELiEC (structurally and functionally) and presents preliminary results obtained from employing it on the textual datasets extracted from speech produced by 14 (i.e., five patients and nine healthy control) subjects. We collected the speech samples via a web portal named Talk2Me.MethodWe have developed a language assessment tool combining natural language processing (NLP) techniques and the ELiEC (as an ML tool). NLP techniques extract the total number of word tokens and the total number of unique word types, the total number of sentences, and the total number of syllables. Using the above parameters, we calculate lexical features such as the lexical diversity score, Brunet’s Index (BI), Honore’s Statistic (HS) , Flesch‐Kincaid, and the Flesch Reading‐Ease (FRES) Test readability scores. ELiEC maps linguistic features to patients and healthy controls. In more detail, the ELiEC, which is an ensemble classifier, is developed based on LeDoux’s emotional theory. The theory describes the neural structures underlying the processing of threatening stimuli (see Figure 1) We develop ELiEC by combining classifiers (see Figure 2) according to the interconnections between regions of the brain that are responsible for processing threatening stimuli.ResultTable 1 compares results obtained from using various ML tools such as Support Vector Machines (SVMs), k nearest neighbor, and ELiEC to distinguish patients and healthy subjects. As observed, ELiEC’s accuracy is 0.87 (+/‐ 0.33). Thus, compared to other ML tools, it can associate language impairment to people with dementia with the highest accuracy and when there is not a sufficient amount of language data from patients.ConclusionOur results verified that by utilizing ELiEC, we could develop an accurate MLbased language assessment tool when there is a limitation in recruiting patients. We will improve the ELiEC framework and use it to distinguish people with different types of dementia.
Combining evidence across multiple endpoints with a global statistical test: Comparison of z‐scores versus ranks
Authors: Dickson Samuel P. , Knowlton Newman , Hendrix Suzanne B. 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is a multi‐symptom disease which has cognitive, behavioral, functional and global outcomes. These outcomes are all important measures of disease severity and are driven by the underlying disease process. These symptoms provide multiple, potentially conflicting, answers to the question, “Did the treatment work?”MethodOutcomes can be combined through standardization of outcomes using ranks or z‐scores. Additionally, the standardization can be performed before calculating change from baseline or after. These four combinations are explored by simulations with no effect, corroborative effects across outcomes, and disparate effects across outcomes (a mix of positive and null effects) to demonstrate the type I error (no effect) and power under various secenarios along with other performance metrics.ResultAll four methods of calculating a GST adequately control type I error. In the absence of ceiling and floor effects, the GST that calculates change from baseline first then combines evidence using z‐scores has the highest power. In the presence of disparate effects, the GST can still be more powerful than any single outcome, though the effect is appropriately attenuated. The GSTs that use ranking outperform z‐score methods in the presence of strong floor or ceiling effects.ConclusionA clinical trial with a GST analyzed first can show success as a proof of concept even if the individual outcomes fail to achieve significance, signalling that a development can proceed to later phases. Change from baseline should be calculated first. If there are no ceiling or floor effects, standardization should be performed using z‐scores, otherwise percentiles should be used. GSTs offer a good way to combine outcomes to demonstrate efficacy using fewer subjects.
A comparison of the Montreal Cognitive Assessment and standard cognitive measures in the National Alzheimer’s Coordinating Center and Knight Alzheimer’s Disease Research Center cohorts
Authors: LaRose Megan , Aschenbrenner Andrew J. , Benzinger Tammie L.S. , Gordon Brian A. , Cruchaga Carlos , Morris John C. , Hassenstab Jason 
Published: December 2020

AbstractBackgroundThe Montreal Cognitive Assessment (MoCA) could be described as a “sampling” of more comprehensive cognitive measures. We investigated the utility of the MoCA in predicting disease progression in the National Alzheimer’s Coordinating Center (NACC) sample in comparison to standard comprehensive cognitive measures collected in the NACC Uniform Dataset 3 (UDS 3). In addition, using the imaging biomarker‐rich cohorts at the Knight Alzheimer Disease Research Center (ADRC), we compared the sensitivity of the MoCA and UDS 3 measures to APOE 4 status, amyloid PET, tau PET, and structural MRI.MethodAnalysis One: In cognitively normal older adults from the NACC cohort (n=6,273, 2.3 +/‐ 0.9 years follow‐up), survival and receiver operating characteristic (ROC) analyses compared the MoCA and UDS 3 measures on their ability to classify disease progression, defined as change in Clinical Dementia Rating (CDR) status from 0 to >0. Analysis Two: In Knight ADRC participants (n = 445), regression models compared the sensitivity of the MoCA and standard cognitive measures to AD biomarkers in all participants and separately in CDR 0s.ResultDisease progression analyses in the NACC sample resulted in an area under the curve (AUC) estimate for the MoCA of 0.69 for the total score and 0.55‐0.73 for domain scores. For the UDS 3 measures, AUCs ranged from 0.57‐0.73. A cognitive composite similar to a “PACC” yielded an AUC of 0.71. Sensitivity to AD biomarkers including amyloid PET, tau PET, cortical thickness, and APOE 4 status was similar for both the MoCA and UDS 3 measures (all p’s < 0.001). Analyses of CDR 0 participants produced small but significant relationships only with tau PET and cortical thickness (p’s 0.01 – 0.02) for both MoCA and UDS 3 tests.ConclusionNeither the MoCA nor UDS 3 cognitive measures demonstrated adequate classification of disease progression. Correlations with biomarkers suggests that the MoCA is capable of tracking pathological indicators of AD in individuals with symptomatic disease. However, in cognitively normal participants, both the MoCA and UDS 3 measures were weakly correlated with indicators of neurodegeneration. More sensitive measures or improved assessment methodology is required to reliably detect AD pathology prior to clinical diagnosis.
SINGER (Singapore)
Authors: Chen Christopher 
Published: December 2020

AbstractBackgroundThe SINGapore GERiatric intervention study to reduce physical frailty and cognitive decline (SINGER) is a pilot study, aiming to evaluate culturally appropriate adaptations of the FINGER interventions, and the feasibility of implementing this protocol in 70 seniors, aged >65 years, with mild‐to‐moderate frailty and/or cognitive impairment over a 6‐month period (Table). The main outcome of this pilot study is the feasibility of and adherence to the multidomain intervention as concerns have been raised particularly for the dietary and cognitive interventions which could require novel and culturally appropriate approaches. We aim to develop scalable digital platforms and build partnerships so as to conduct a larger definitive study in 1200 elderly community dwelling Singaporeans who are at risk for cognitive impairment and dementia. This larger study comparing self‐guided lifestyle management versus a structured multidomain lifestyle intervention will also incorporate neuroimaging and blood biomarkers so as to investigate mechanisms of action.
The association between herpes simplex virus type 1 infection and Alzheimer’s disease
Authors: Wu Donghong , Wang Chuqiao , Pang Peilin , Kong Han , Hao Zixiao , Guo Xuguang 
Published: December 2020

AbstractBackgroundThere are growing evidences demonstrating the relationship between herpes simplex virus type 1 (HSV‐1) infection and Alzheimer’s disease (AD).MethodWe searched Pubmed, Embase and Cochrane databases for relevant articles. Newcastle‐Ottawa Scale (NOS) was used to evaluate the qualities of these studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random‐effects models. We also performed subgroup analyses stratified by apolipoprotein ε4 (APOE ε4), NOS score and the method of confirming AD.ResultA total of 21 studies between 1990 and 2020 were identified. The pooled OR suggested that HSV‐1 infection is a risk factor of AD: pooled OR 1.40 (95% CI: 1.13‐1.75; I2 = 3%, P = 0.42). In the subgroup analyses, the pooled ORs of HSV‐1 infection associated with AD were 0.75 (95% CI: 0.24‐2.37) among the APOE ε4 positive individuals; 0.85 (95% CI: 0.61‐1.17) among the APOE ε4 negative individuals; 1.51 (95% CI: 1.10‐2.06) in the high NOS score studies; 1.23 (95% CI: 0.85‐1.76) in the moderate NOS score studies; 1.47 (95% CI: 1.16‐1.87) in the clinical diagnosis group, 1.20 (95% CI: 0.77‐1.87) in the autopsy group, respectively.ConclusionOur systematic review and meta‐analysis suggest that HSV‐1 infection is a risk factor of Alzheimer’s Disease.
Quality comparison of remote vs. in‐person digital speech assessment for dementia
Authors: Robin Jessica , Novikova Jekaterina , Sirotkin Sasha , Yancheva Maria , Kaufman Liam D , Simpson William 
Published: December 2020

AbstractBackgroundThe COVID‐19 pandemic has brought the need for reliable, remote assessments for clinical trials into sharp focus. Remote, home‐based assessment reduces patient and caregiver burden, enabling more frequent monitoring. There are concerns, however, regarding the quality of in‐clinic vs. remote assessments. In the present study, we compared the quality of verbal responses to a tablet‐based speech assessment in patients with dementia across two settings: in‐person at a clinical research site, and remotely, at home.MethodThe in‐person sample consisted of individuals with Alzheimer’s disease, participating in a clinical trial. The remote sample consisted of individuals with variants of Frontotemporal dementia, participating in a longitudinal observational study. In‐person assessments were conducted at a clinical research site and administered by a trained rater. Remote assessments were conducted in the participant’s home, by a caregiver who had received assessment training and a tablet by mail. 575 in‐person speech samples and 574 remote speech samples were compared. All samples were manually transcribed and tagged for recording anomalies or task compliance issues by trained transcriptionists.ResultOverall incidence of recording anomalies was low and did not differ significantly (p = 0.63) between in‐person (10.1%; 58/574) and remote (11.1%, 64/575) recordings. Less than 1% of samples in either study were marked as “incomplete task”, “low audio quality” or “noisy background”. Incidences of clinician/caregiver interference were more frequent for remote recordings (1.2% in‐person, 4.5% remote, p = 0.001) and incidences of quiet participants were more frequent for in‐person recordings (4.5% in‐person, 1.0% remote, p < 0.001), though both were relatively rare overall. The mean duration of in‐person samples was significantly longer than remote samples, but mean speech rate did not differ.ConclusionThis study suggests that remote speech assessments yield recordings of comparable quality to in‐person assessments. We found higher, though still low, rates of caregiver interference for remote assessment, which should be monitored and mitigated in future remote assessment. Remote assessments yielded shorter recordings, but this may be due to the different dementia diagnoses across groups. Future work should compare the same participants across both assessment settings.
The solely A+ CSF Aβ42/40 ratio using Elecsys® assays performs similar to A/T and A/N ratios in predicting amyloid PET positivity
Authors: Grimmer Timo , Amft Michaela , Ortner Marion , Eichenlaub Udo , Goldhardt Oliver , Müller‐Sarnowski Felix , Diehl‐Schmid Janine , Förstl Hans , Yakushev Igor 
Published: December 2020

AbstractBackgroundpTau181/Aβ42 (A+/T+ as per A/T/(N) classification) and tTau/Aβ42 (A+/(N)+) ratios using fully automated Elecsys® cerebrospinal‐fluid (CSF) immunoassays have been shown to perform well in distinguishing amyloid‐positivity (A+) by positron emission tomography (PET) among patients with subjective and mild to severe cognitive impairment. Higher performance has also been demonstrated for the CSF Aβ42/40 ratio compared to CSF amyloid 42 (Aβ42) alone. We aimed to further evaluate the performance of the Elecsys® Aβ42/40 ratio in a clinical cohort.MethodsFrozen (‐80°C) CSF samples from 103 patients treated in the Centre for Cognitive Disorders, Technical University of Munich were selected based on availability of visual amyloid‐PET status (n=54 PET+; 49 PET‐) determined during standard treatment around the time of CSF collection. In total, 71 patients were undergoing treatment for mild cognitive impairment (MCI) (n=44) or mild to moderate dementia (n=27) due to Alzheimer’s disease (AD) and 32 patients for non‐AD related fronto‐temporal lobar degeneration (n=17), MCI (n=8), depression (n=5), alcohol dependence (n=1), or subjective cognitive impairment (SCD) (n=1). CSF was measured using Elecsys® assays. CSF status for Aβ42 , pTau181/Aβ42 , and tTau/Aβ42 CSF (positive/negative) was determined based on pre‐defined biomarker cutoffs previously established using a different pre‐analytical protocol in MCI/SCD patients with suspected AD (CSF positive if Aβ42<1000 pg/ml, pTau181/Aβ42>0.024, and tTau/Aβ42>0.028). Sensitivity and specificity were calculated for CSF‐cutoff‐based status and ROC analysis was performed to determine AUC each versus visual amyloid‐PET status.ResultsPre‐defined biomarker thresholds were considered off‐label due to deviation from recommended sample collection protocol and storage parameters. Point estimates for sensitivity and specificity for each biomarker were; CSF Aβ42 alone (sensitivity = 0.93, specificity = 0.57), pTau181/Aβ42 (0.96, 0.69), and tTau/Aβ42 (0.92, 0.69). For AUC point estimates (95% confidence interval) were; CSF Aβ42 alone [0.78 (0.68‐0.88)], pTau181/Aβ42 [0.88 (0.81‐0.95)], tTau/Aβ42 [0.87(0.80‐0.95)], and Aβ42/40 [0.90 (0.83‐0.95)].ConclusionFully automated Elecsys® cerebrospinal fluid (CSF) immunoassay predicted amyloid positivity with high accuracy. In this study, the solely A+ marker CSF Aβ42/40 ratio outperformed Aβ42 alone and performed similarly to Tau ratios. These results support those of previous studies showing high performance for the non‐Tau marker CSF Aβ42/40.
A multifunctional chemical agent as an attenuator of amyloid and p‐tau burden and neuroinflammation in Alzheimer’s disease
Authors: Mirica Liviu M 
Published: December 2020

AbstractBackgroundNew therapeutic agents are being developed that target not only the amyloid plaques in Alzheimer’s disease (AD), but also the extracellular p‐tau aggregates, Aβ‐metal induced oxidative stress, and neuroinflammation.MethodWe have developed two novel multifunctional compounds (MFC) that exhibit high binding affinity for Aβ aggregates ‐ including soluble Aβ oligomers, and a series of ex vivo and in vivo immunostaining and imaging studies were employed to probe the beneficial properties of these MFCs.ResultUpon treatment of 5 × FAD mice with one of the MFC, fluorescence imaging of the brain sections shows that the MFC can easily penetrate the blood‐brain‐barrier and selectively bind to the Aβ oligomers, as confirmed by the colocalization with an Aβ oligomer‐specific antibody. Furthermore, when comparing the MFC‐treated mice vs. the vehicle‐treated mice, the total amount of Aβ species and the associated p‐tau aggregates was significantly decreased by ∼50%, along with a significant reduction in the amount of activated microglia.ConclusionThe multifunctional compounds reported herein can attenuate the formation of amyloid plaques and associated p‐tau aggregates, while also reducing the microglia‐mediated neuroinflammatory response, which is uncommon among the previously reported amyloid‐targeting chemical agents.
Insulin resistance is related to cognitive decline but not biomarkers of Alzheimer’s pathology in adults without dementia
Authors: Ennis Gilda E , Koscik Rebecca L , Ma Yue , Betthauser Tobey J , Jonaitis Erin M , Van Hulle Carol A , Bouges Shenikqua , Chin Nathaniel A , Engelman Corinne D , Anderson Rozalyn , Batrla Richard , Kollmorgen Gwendlyn , Carlsson Cynthia M , Asthana Sanjay , Johnson Sterling C , Zetterberg Henrik , Blennow Kaj , Bendlin Barbara B 
Published: December 2020

AbstractBackgroundInsulin resistance (IR) has been related to increased risk for Alzheimer’s clinical syndrome. While some cross‐sectional studies have linked IR to Alzheimer’s disease (AD) pathology, others have been negative. We examined the relationship of IR to longitudinal cerebrospinal fluid (CSF) biomarkers of AD pathology, cerebral amyloid chronicity, and cognitive decline.MethodParticipants (Table 1) were enrolled in the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a longitudinal observational study of non‐demented adults. We utilized data from biennial visits and CSF and positron emission tomography (PET) sub‐studies. For our first study, participants (n=148) had CSF biomarker data (Aβ42: Aβ40 ratio, p‐tau181, t‐tau, and neurogranin) from 1‐5 CSF samples collected every 2‐8 years and fasting insulin and glucose (collected during 1‐5 visits before first CSF) for calculating homeostatic model assessment of insulin resistance (HOMA‐IR). CSF was assayed using the Roche NeuroToolKit on the Elecsys® platform. Linear mixed effects models tested HOMA‐IR as a moderator of aging‐related change in CSF biomarkers. In study 2, participants (n=253) had [C11]PiB PET imaging and 3‐6 HOMA‐IR values for calculating a within‐person HOMA‐IR mean and SD (i.e., fluctuation). Amyloid chronicity was calculated by subtracting estimated age at PiB positivity (i.e., estimated age when PiB DVR ≥ 1.2) (Koscik & Betthauser, et al., 2020) from age at last HOMA‐IR. Hierarchical regression tested whether HOMA‐IR and an HOMA‐IR x APOE4 interaction predicted amyloid chronicity. In study 3 (n=1,298), linear mixed effects tested if baseline HOMA‐IR moderated age‐related decline in longitudinal measures of the preclinical Alzheimer’s cognitive composite (PACC). Age, APOE4, sex, education, and systolic blood pressure (SBP) were controlled in all study models.ResultHOMA‐IR was not a significant moderator of aging‐related change in any CSF biomarker (Figure 1 & 2). HOMA‐IR mean and SD and the HOMA‐IR x APOE4 interaction were not significant predictors of amyloid chronicity. Increased HOMA‐IR predicted greater age‐related decline in PACC (Figure 3).ConclusionHOMA‐IR was related to cognitive decline but not cerebral amyloid chronicity or age‐related change in CSF biomarkers of AD pathology and neurodegeneration. IR may not be directly related to preclinical AD pathology. Pathways linking IR to dementia require further investigation.
Cerebrospinal fluid biomarkers in older adults with mild cognitive impairment, with and without a major depressive disorder
Authors: Golas Angela C , Salwierz Patrick , Rajji Tarek K , Bowie Christopher R , Butters Meryl A , Fischer Corinne E , Flint Alastair , Herrmann Nathan , Mulsant Benoit H , Mah Linda , Pollock Bruce G , Taghdiri Foad , Tartaglia Maria Carmela 
Published: December 2020

AbstractBackgroundMild Cognitive Impairment (MCI) and Major Depressive Disorder (MDD) have been independently associated with increased risk of dementia. Cerebrospinal fluid (CSF) biomarkers associated with Alzheimer’s disease (AD) show changes prior to the onset of symptoms of dementia or neuroimaging biomarkers of AD. We examined the association between a CSF biomarker profile of AD and diagnosis in three groups: MCI alone; a diagnosis of MDD alone; or MCI plus a diagnosis of MDD.MethodThe CSF total tau, p‐tau, amyloid‐β42, and the p‐tau/ amyloid‐β42 ratio were measured in 31 participants enrolled in the PACt‐MD study diagnosed with MCI (N=13), MDD (N=7), or both (MCI+MDD) (N=11) according to NIA‐AA and DSM IV criteria. We compared AD biomarkers in the 3 groups and then compared cognitive performance in those with and without a CSF biomarker profile consistent with ADResultAmong the 31 participants, 9 had a CSF biomarker profile consistent with AD: 7/13 with MCI; 0/7 with MDD; and 2/11 with MCI+MDD. Participants with an AD biomarker profile had significantly greater impairment in verbal memory than those without one (p=0.009). Of those without a profile consistent with AD, no significant differences were observed in cognitive performance between the MCI and MDD+MCI groups.ConclusionIn our sample, few participants with MDD had a CSF biomarker profile consistent with AD, even if they had a neurocognitive profile consistent with MCI. The etiopathology of cognitive impairment in older patients with MDD requires further investigation.