bluuebunny/crossref_metadata_2025_split huggingface dataset:
Worse baseline lung function is associated with worse cognition among older black and white adults
Authors: Bobrow Kirsten , Rouch Laure , Hoang Tina D , Yaffe Kristine 
Published: December 2020

AbstractBackgroundPrior studies indicate that lung function may be an important risk factor for cognitive impairment and decline, but the body of evidence has largely been restricted to cross‐sectional and single‐time point measurement studies in white populations.MethodsWe studied 1128 black and 1641 white participants, mean age 74 years (SD 3), without prevalent dementia at enrollment in the Health Aging and Body Composition (Health ABC) Study. Participants completed spirometry assessments including Forced Expiratory Volume in 1 second (FEV1) at baseline, years 5, 8, and 10. Digit Symbol Substitution Test (DSST) and Modified Mini‐Mental exam (3MS) were used to assess processing speed and global cognitive function at years 5, 8, 10, and 11. We evaluated the association of baseline and rate of change in lung function in relation to baseline and change in cognitive performance (stratified by race) with mixed linear regression models and adjusting for demographics, comorbid health conditions and health behaviors.ResultsCompared to white participants, black participants had less education, lower socioeconomic status, and were more likely to be current smokers. Baseline mean FEV1 was 2300 ml (SD 551) and 1949 ml (SD 640) in white and black participants. During follow‐up lung function decreased by 207 ml (95%CI 199, 215) and 139 ml (95%CI 130, 148) respectively. In multivariable adjusted analyses, higher baseline lung function was associated with better cognitive test scores. One standard deviation (SD) lower baseline FEV1 was associated with worse DSST scores (by 1.50 (95%CI 0.42,2.73) and 0.60 (95%CI ‐1.0, 2.16) points in whites and blacks respectively, p for interaction = 0.04.) In both black and white participants, there were small but not significant effects of decline in lung function on subsequent cognitive performance and decline.ConclusionWhile the magnitude of the association was stronger in whites, we found worse baseline lung function was associated with worse cognitive function up to 10 years later in both black and white participants. Declines in lung and cognitive function vary by population‐level factors. For interventions, it is important to determine if these associations are biological or socially patterned.
Approaches to overcome recruitment challenges in a rural setting in India: Strategies adopted in Srinivasapur Aging, Neuro Senescence and Cognition (SANSCOG) study
Authors: Chaudhary Kiran , Rao Girish N , Sivakumar Palanimuthu T , Sundarakumar Jonas , Rao Naren P , Ravindranath Vijayalakshmi , Investigators SANSCOG 
Published: December 2020

AbstractBackgroundRecruitment and retention of participants is a rate limiting step in any clinical research study, more so in a rural setting. The SANSCOG study is a large‐scale, longitudinal, rural, cohort study, to gather long term data to identify risk and protective factors for normal and pathological aging, dementia and other related disorders.MethodThe study will recruit 10,000 participants, out of which 1500 have completed baseline visit. Our recruitment strategy centred around utilising expertise within existing health care set‐up in Srinivaspur, India. We targeted 6 primary health centres and their associated villages. We collaborated with public health officials and gathered census data to identify potential participants (age ≥ 45 years). We formed a field team, conversant with the language and knowledgeable about local culture. By working closely with link workers, who are part of government health system, to promote health and well‐being initiatives in villages (ASHA), we were able to build better connections with the community. In consultation with village leaders, we conducted awareness programs, informing participants about our study. We maintained periodic contact with participants through telephone or in‐person house visits and actively engaged the community through activities like general health awareness camps, street plays and sports events. Though we don’t offer any treatment, the clinical team provides brief feedback on participants blood test reports, ECG and MRI and makes appropriate referrals to the primary health system, if necessary.ResultWe approached 3891 participants from 19 villages, out of which 48% consented. We observed that despite being marginalized, this community’s willingness to contribute to the study, with the notion of potentially helping their future generations, was remarkable. From our experience, the most crucial approach was forming alliance with existing health system to build community connections. We assessed participants interest to continue in the study via telephone calls (n=700) or house visits (n=255); having found the later strategy to be more effective, our approach was modified for subsequent follow‐ups. A pilot follow‐up was completed for 142 participants.ConclusionThe SANSCOG project provides unique insights on recruitment approaches that can be tailored and adopted for increasing study enrolment in rural cohorts in developing countries.
Dementia prediction in the general population: External validation of 12 prognostic models in the AGES‐Reykjavik Study
Authors: Vonk Jet M.J. , Geerlings Mirjam I. , Gudnason Vilmundur , Launer Lenore J. , Greving Jacoba P. 
Published: December 2020

AbstractBackgroundMultivariable prognostic models in the general population predict individual risk of developing Alzheimer’s disease (AD) or all‐cause dementia, which can aid selection of high‐risk individuals for clinical trials and prevention. Development of new models flourished across the past decades. However, external validation for the majority of models is lacking. We aimed to evaluate external performance of previously published prediction models for AD or all‐cause dementia.MethodBased on multiple systematic literature reviews, we identified 12 eligible models for external validation in the AGES‐Reykjavik Study, a prospective population‐based cohort study (n=5343 without dementia at baseline; 76.6±5.7 years). Models were developed to predict either AD or all‐cause dementia up to 5, 6, or 10 years of follow‐up, and were based on logistic, Cox, or competing risk regression. Predictive performance was assessed with C‐statistics (discrimination) and calibration plots (observed vs. predicted probabilities).ResultDuring 45,021 and 40,917 person‐years of follow‐up, 1099 participants developed dementia and 492 participants developed AD, respectively. The mean observed risk of dementia was 5.1% [CI:4.5‐5.7] for 5 years, 10.1% [CI:9.2‐11.0] for 6 years, and 22.8% [CI:21.5‐24.1] for 10 years; the risk for AD was 2.0% [CI:1.6‐2.4], 5.6% [CI:4.9‐6.3], and 12.1% [11.0‐13.2], respectively. Table 1 presents the validated models and their C‐statistics. Models ranged from 2‐11 predictors; all models with a cognitive test obtained C‐statistics ≥0.75, all models without ≤0.73. Information to perform calibration was provided for 5 models, and all but one showed overestimation of predicted risk (Figure 1).ConclusionThe majority of models showed acceptable discrimination (C‐statistic >0.70), but poor calibration with systematic overestimation. These models may be acceptable for exclusion of dementia or AD (if the predicted risk is low, the observed risk is even lower), but lack the ability to accurately identify individuals at higher risk. The one model that calibrated well was developed with logistic regression, a technique that ignores observation times and censoring, which can introduce bias into the prediction process. Updating existing models or development and external validation of new models aimed at identifying high‐risk individuals using Cox regression or competing risk regression is therefore warranted.
Predicting conversion from mild cognitive impairment to Alzheimer's disease using cortical diffusivity analysis
Authors: Torso Mario , Hardingham Ian , Jenkinson Mark , Chance Steven A ,   National Alzheimer’s Coordinating Center (NACC)
Published: December 2020

AbstractBackgroundAlzheimer's Disease (AD) is characterized pathologically by important neural architecture changes. Diffusion Tensor Imaging (DTI) has provided promising results for the investigation of microstructural changes of white matter, but its use in cortical grey matter is still limited. In the present study, we investigated the performance of our novel cortical diffusivity measurements [McKavanagh et al. 2019] for classifying patients with AD, healthy elderly subjects (HS), patients with mild cognitive impairment (MCI) who progress to probable‐AD (MCI‐converter, MCI‐C), and those with MCI who do not progress to probable‐AD (MCI‐stable, MCI‐S). The aim here was to test the classification power of our novel cortical diffusion measurements and to test their correspondence with the standard hallmarks of AD pathology measured in CSF (total‐tau, phosphorylated‐tau and amyloid beta).MethodDTI and T1 structural scans and CSF data of 454 subjects (respectively 310 HS, 48 MCI‐S, 45 MCI‐C and 51 AD) from the National‐Alzheimer’s‐Coordinating‐Center (NACC) were used. Three novel whole brain cortical diffusivity measures (AngleR, PerpPD, and ParlPD) [McKavanagh et al. 2019], and three standard measures (mean diffusivity [MD], cortical grey matter volume, and bilateral hippocampal volume) were calculated for each subject. Receiver Operating Characteristics (ROC) curve analysis and the Area Under the Curve (AUC) were used to assess the group discrimination capability of our method.ResultThe results showed that the new DTI derived measures can detect altered quality of cortical grey matter in AD patients, distinguishing between these and HS with an AUC of 97.5, and between MCI‐C and MCI‐S with an AUC of 87.8%. All the cortical diffusivity measures were significantly correlated with CSF values (total‐tau, phosphorylated‐tau and amyloid beta).ConclusionOur findings support using cortical diffusivity measurements as a surrogate of cortical microstructure quality for identification of the early stages of AD. These changes were consistent with CSF signature in which B amyloid was sensitive in the early stages and tau was elevated in the late stages (MCI‐C and AD). Further development may aid early diagnosis, patient cohort selection, and quantification of the microstructural changes in response to therapies in clinical trials.
Neuronal activity topography (NAT) analysis of EEG can predict neurocognitive deterioration earlier than FDG‐PET
Authors: Ishii Kenji , Tanaka Mieko , Watanabe Yuri , Sano Akiko , Kobayashi Yohei , Ishibashi Kenji , Wagatsuma Kei , Asada Takashi , Kosugi Yukio 
Published: December 2020

AbstractBackgroundWe recently reported that FDG‐PET can predict neurocognitive deterioration three years earlier than cognition in our aging cohort. This study examined whether EEG detects the deterioration as early as FDG‐PET.MethodTwo groups of subjects’ data‐set with normal PET/cognition were selected from our cognitively normal (CN) elderly cohort who participated in the same‐day EEG and FDG‐PET annually. The NLC group (n = 41, age = 75.2±4.7y, MMSE = 29.3±1.1) consists of those whose PET findings remain normal for more than three successive years. NL2 group (n = 22, age = 75.1±4.9y, MMSE = 29.0±1.5) consists of those whose PET findings deteriorate within three years. Each PET image was classified into five ranks (A/A‐/B/B‐/C) by visual and statistical analysis and A/A‐ were regarded as normal. The results of neuropsychological tests (MMSE, HDS‐R, MoCA) and Neuronal Activity Topography (NAT) analysis indices derived from five minutes EEG record at rest with eyes closed were compared between the two groups.ResultThe average value of the two groups is significantly different in (1) the index sNAT value based on the power spectrum of the EEG, (2) the index vNAT value based on the power ratio of the sNAT values of adjacent frequency subbands, and (3) the mean power frequency of the occipital region (sNATNLC = ‐0.077±0.071, sNATNL2 = ‐0.022±0.103, p = 0.03* ; vNATNLC = ‐0.080±0.076, vNATNL2 = ‐0.038±0.059, p = 0.03* ; MPFNLC = 9.29±0.48Hz, MPFNL2 = 8.97±0.55Hz, p = 0.02*). In the NL2 group, a significant negative correlation was found between vNAT value and MMSE, and MoCA (CORvNAT‐MMSE = ‐0.43, p = 0.05* ; CORvNAT‐MoCA = ‐0.59, p < 0.01**. Above findings suggest that the signs of cognitive deterioration in near future is detectable using NAT analysis.ConclusionIn cognitively normal subjects whose PET findings start to deteriorate in the next following years, signs of deterioration are already detectable with NAT analysis of EEG. This suggests that the alteration of neuro‐electrical activity may precede the decline of cerebral glucose metabolism. Further study with larger groups is necessary.
Studies on the pragmatic performance and validity of a plasma amyloid β measurement system by immunoprecipitation‐mass spectrometry
Authors: Kaneko Naoki , Yoda Ritsuko , Korenaga Akihito , Ohashi Yuko , Honda Mamoru , Hioki Yusaku , Sekiya Sadanori , Iwamoto Shinichi , Tsujino Kazushige , Tanaka Koichi 
Published: December 2020

AbstractBackgroundThe measurement of plasma amyloid β recently attracts much attention as a biomarker of Alzheimer’s disease. We developed a highly sensitive method for simultaneous detection of a plurality of amyloid β peptides in human plasma by using immunoprecipitation combined with matrix‐assisted laser desorption ionization time‐of‐flight mass spectrometry (IP‐MALDI‐MS). In this study, we examined the effects of interfering substances in human plasma to reinforce the performance and practicability of this approach.MethodAnticoagulants, Alzheimer's disease drugs, peptides having the epitope with high homology to 6E10 anti‐amyloid β antibody, and a drug having a similar mass to the amyloid β peptide were added to human plasma. The doped plasmas were then analyzed by IP‐MALDI‐MS. Plasma with PBS added was used as a control.ResultTwo biomarker values (Aβ1‐40/Aβ1‐42 and APP669‐711/Aβ1‐42) in the interfering substances doped plasma were compared to those of control plasma. The results showed that the addition of any of those drugs had only a slight effect on the measured values, and the difference between the plasma biomarkers to which the compound was added was ± 10% or less relative to the control.ConclusionThe analysis of plasma amyloid β biomarkers by IP‐MALDI‐MS is a unique method for the simultaneous detection of multiple amyloid β peptides requiring only one kind of antibody. Addition of twelve kinds of contaminants to the human plasma have limited effects on the analytical performance of the system.
Impact of APOE‐ε4 on cerebral amyloid deposition in participants with abnormal soluble amyloid levels
Authors: Cacciaglia Raffaele , Molinuevo Jose Luis , Salvadó Gemma , Suárez‐Calvet Marc , Shekari Mahnaz , Operto Greg , Fauria Karine , Minguillón Carolina , Farrar Gill , Buckley Chris J , Blennow Kaj , Zetterberg Henrik , Eichenlaub Udo , Kollmorgen Gwendlyn , Gispert Juan Domingo ,   ALFA study
Published: December 2020

AbstractBackgroundAmyloid pathology can be detected using cerebrospinal fluid (CSF) biomarkers and positron emission tomography (PET) imaging, even though they measure two distinct beta‐amyloid (Aβ) pools. While CSF Aβ concentrations reflect the clearance of soluble amyloid species from the brain, PET imaging informs on the presence of insoluble fibrillary plaques in the brain tissue. Many studies have shown the concordance between the two measures in individuals along the Alzheimer’s continuum. Here, we assessed whether APOE‐ε4, the major genetic risk factor for Alzheimer’s disease (AD), affects the pattern of cerebral Aβ load as a function of CSF Aβ levels.MethodThe first consecutive 276 cognitively unimpaired (CDR = 0) individuals of the ALFA+ study, aged between 48 and 74, with valid structural MRI and [18F]flutemetamol (FTM) PET, APOE genotyping and CSF samples were included. Aβ40 and Aβ42 concentrations were determined with the Roche NeuroToolKit (Roche Diagnostics) and parametric standardized uptake value ratio images (SUVr) were calculated with the whole cerebellum as reference region. A voxel‐wise regression was performed to predict FTM uptake, with the following independent variables: age, sex, APOE‐ε4, and CSF Aβ42/40 ratio. Statistical threshold was set to p < 0.001 with a cluster extent correction of 100 voxels.ResultAs expected, CSF Aβ42/40 ratio was negatively associated with cerebral FTM uptake (Figure 1a‐1b). Age and APOE‐ε4 gene dose mapped onto distinct spatial patterns of FTM‐binding across the whole sample (Figure 2b‐2c). Importantly, we found a significant interaction between CSF Aβ42/40 and APOE‐ε4 indicating that carriers had a negative association between fluid and imaging Aβ measures in the bilateral hippocampus, as well as the bilateral middle temporal and temporo‐parietal junction (Figure 3).ConclusionCompared to non‐carriers, APOE‐ε4 carriers showed higher cerebral Ab load for any given level of CSF Aβ42/40 in areas that are not typically vulnerable to Aβ deposition yet undergoing neurodegeneration early in the Alzheimer’s continuum, such as the hippocampus. This suggests that APOE‐ε4 may influence the biological mechanisms regulating the equilibrium between soluble and deposited amyloid, which may transcend the hindering effect caused by Aβ fibrillary plaques and render medial temporal lobe structures particularly vulnerable when Aβ metabolism becomes deficient.
Blood pressure at the age of 70 as a predictor of incident dementia: A 15‐year longitudinal study
Authors: Wetterberg Hanna , Najar Jenna , Rydén Lina , Kern Silke , Zettergren Anna , Skoog Ingmar 
Published: December 2020

AbstractBackgroundWe have previously reported that blood pressure (BP) at age 70 predicted incident dementia in a birth cohort born 1901‐02. It is known that BP in older adults has decreased in high‐income countries during the last decades. The aim of this paper was to explore whether BP at age 70 still predicted incident dementia in a cohort born three decades later.MethodA population‐based sample of 70‐year‐olds born 1930 was followed for 15 years as part of the Gothenburg H70 Birth Cohort studies. Dementia was diagnosed by geriatric psychiatrists according to the DSM‐III‐R criteria at all examinations. All individuals with prevalent dementia at baseline were excluded in this study. Among drop‐outs, the Swedish National inpatient register was used to detect dementia. Systolic (SBP) and diastolic blood pressure (DBP) were measured at baseline and all follow‐ups. To compare the mean blood pressure levels between the groups, Students t‐tests were used.ResultAt baseline, 588 participants were free from dementia and 107 individuals developed dementia during the study period. Of these, 18 developed dementia between age 71‐75, 27 between 76‐80, and 62 between 81‐85. Those who developed dementia between age 76‐80 had higher mean SBP (165 [sd +21.9] versus 155 [sd +22.1], p=0.016), and DBP (90 [sd +10.7] versus 86 [sd +10.7] p=0.045) at age 70, compared to those who remained dementia‐free. There were no differences in SBP or DBP at age 70 among those who developed dementia between age 71‐75 or between age 81‐85.ConclusionOur results suggest that high blood pressure at the age of 70 predicts dementia incidence between age 76‐80 years, despite that mean BP was considerably lower in the later born cohort.
DNA methylation differences associated with peripheral biomarkers in the EMIF‐AD cohort
Authors: Smith Rebecca G. , Bos Isabelle , Vos Stephanie J.B. , Verhey Frans R.J. , Scheltens Philip , Engelborghs Sebastiaan , Frisoni Giovanni B. , Blin Olivier , Richardson Jill , Bordet Régis , Tsolaki Magda , Popp Julius , Martinez‐Lage Pablo , Lleó Alberto , Johannsen Peter , Freund Yvonne , Frölich Lutz , Vandenberghe Rik , Lovestone Simon , Streffer Johannes , Andreasson Ulf , Blennow Kaj , Visser Pieter Jelle , Zetterberg Henrik , Bertram Lars , Lunnon Katie 
Published: December 2020

AbstractBackgroundAlzheimer’s disease is associated with increases in amyloid β and hyperphosphorylated tau which is thought to occur decades before the onset of clinical symptoms, leading to cell loss and inhibition. Finding biomarkers to detect these changes before neuronal loss and therefore permanent damage has occurred is integral. Current biomarkers using cerebrospinal fluid (CSF) measures and positron‐emission tomography (PET) imaging are invasive or expensive to perform. In this study we use the European Medical Information Framework Alzheimer’s disease (EMIF‐AD) cohort to looks for blood related epigenetic (DNA methylation) changes which relate to CSF and existing peripheral biomarkers.MethodWhole blood samples from EMIF‐AD were accessed for DNA methylation on Illumina EPIC arrays. We assessed DNA methylation levels in 886 individuals with > 10 central and local biomarker measures, including amyloid, tau, neurogranin and YKL‐40. We also performed regional analysis to look for regions of significant DNA methylation change and identified specific pathways that show methylomic changes in association with specific biomarkers.ResultWe identified epigenome‐wide significant probes associated with many of our biomarker measures including most notably central amyloid β‐42, amyloid β‐40/42 ratio, neurogranin and YKL‐40 CSF levels as well as with local phosphorylated tau and total tau measurements. We also are able to use collections of CpG sites to create classifiers that predict high levels of CSF biomarkers.ConclusionIn the future, identified sites and collections of sites could be used as a proxy for other biomarker measures due to the less invasive and less expensive nature of blood collection DNA methylation analysis. We are currently undertaking further analysis of this cohort using imaging and clinical measures.