scholarly journals Predictors of rapid cognitive decline in Alzheimer's disease: results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing

2011 ◽  
Vol 24 (2) ◽  
pp. 197-204 ◽  
Author(s):  
Alessandro Sona ◽  
Ping Zhang ◽  
David Ames ◽  
Ashley I. Bush ◽  
Nicola T. Lautenschlager ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rating Scale ◽  
Cognitive Status ◽  
Imaging Biomarkers ◽  
Clinical Dementia Rating ◽  
Factors Associated ◽  
Biological Variables ◽  
Rapid Cognitive Decline

ABSTRACTBackground: The AIBL study, which commenced in November 2006, is a two-center prospective study of a cohort of 1112 volunteers aged 60+. The cohort includes 211 patients meeting NINCDS-ADRDA criteria for Alzheimer's disease (AD) (180 probable and 31 possible). We aimed to identify factors associated with rapid cognitive decline over 18 months in this cohort of AD patients.Methods: We defined rapid cognitive decline as a drop of 6 points or more on the Mini-Mental State Examination (MMSE) between baseline and 18-month follow-up. Analyses were also conducted with a threshold of 4, 5, 7 and 8 points, as well as with and without subjects who had died or were too severely affected to be interviewed at 18 months and after, both including and excluding subjects whose AD diagnosis was “possible” AD. We sought correlations between rapid cognitive decline and demographic, clinical and biological variables.Results: Of the 211 AD patients recruited at baseline, we had available data for 156 (73.9%) patients at 18 months. Fifty-one patients were considered rapid cognitive decliners (32.7%). A higher Clinical Dementia Rating scale (CDR) and higher CDR “sum of boxes” score at baseline were the major predictors of rapid cognitive decline in this population. Furthermore, using logistic regression model analysis, patients treated with a cholinesterase inhibitor (CheI) had a higher risk of being rapid cognitive decliners, as did males and those of younger age.Conclusions: Almost one third of patients satisfying established research criteria for AD experienced rapid cognitive decline. Worse baseline functional and cognitive status and treatment with a CheI were the major factors associated with rapid cognitive decline over 18 months in this population.

scholarly journals Association between plasma exosome neurogranin and brain structure in patients with Alzheimer’s disease: a protocol study

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e036990 ◽  
Author(s):  
MengFei He ◽  
Li Sun ◽  
Wenhui Cao ◽  
Changhao Yin ◽  
Wenqiang Sun ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rating Scale ◽  
Early Stage ◽  
Verbal Learning ◽  
Blood Collection ◽  
Clinical Dementia Rating ◽  
Protocol Study ◽  
Medical University

IntroductionNeurogranin is known to be significantly elevated in patients with Alzheimer’s disease (AD) and may be an effective clinical predictor of cognitive decline and neurodegeneration. Amnestic mild cognitive impairment (aMCI) is an intermediate disease state between normal cognitive ageing and dementia, the latter of which can easily revert to AD. There remains significant uncertainty regarding the conversion of aMCI to AD, and therefore, elucidating such progression is paramount to the field of cognitive neuroscience. In this protocol study, we therefore aim to investigate the changes in plasma neurogranin in the early stage of AD and the mechanism thereof regarding the cognitive progression towards AD.Methods and analysisIn this study, patients with aMCI and AD patients (n=70 each) will be recruited at the memory clinic of the Department of Neurology of Hongqi Hospital affiliated with the Mudanjiang Medical University of China. Healthy older controls (n=70) will also be recruited from the community. All subjects will undergo neuroimaging and neuropsychological evaluations in addition to blood collection at the first year and the third year. We hope to identify a new biomarker of cognitive decline associated with AD and characterise its behaviour throughout the progression of aMCI to AD. This work will reveal novel targets for the therapeutic prevention, diagnosis and treatment of AD. The primary outcome measures will be (1) neuropsychological evaluation, including Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating scale, Shape Trail Test-A&B, Auditory Verbal Learning Test-HuaShan version; (2) microstructural alterations and hippocampal features from MRI scans; and (3) neurogranin levels in the neuronal-derived exosomes from peripheral blood samples.Ethics and disseminationThe ethics committee of the Hongqi Hospital affiliated with the Mudanjiang Medical University of China has approved this study protocol. The results will be published in peer-reviewed journals and presented at national or international scientific conferences.Trial registration numberChiCTR2000029055.

scholarly journals Trajectories of cognitive decline in Alzheimer's disease

2009 ◽  
Vol 22 (2) ◽  
pp. 281-290 ◽  
Author(s):  
Patricia A. Wilkosz ◽  
Howard J. Seltman ◽  
Bernie Devlin ◽  
Elise A. Weamer ◽  
Oscar L. Lopez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Complex Disease ◽  
Latent Class ◽  
Rating Scale ◽  
Late Onset ◽  
Psychotic Symptoms ◽  
Concomitant Variables ◽  
Rapid Cognitive Decline

ABSTRACTBackground: Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects.Methods: 201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE ϵ4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included.Results: AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE ϵ4 was not associated with any trajectory.Conclusion: Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.

scholarly journals Factors Affecting Rapid Cognitive Decline in Patients with Alzheimer’s Disease: A Longitudinal Follow-Up Study

2021 ◽  
Vol 18 (16) ◽  
pp. 8576
Author(s):  
Chih-Chuan Pan ◽  
Che-Sheng Chu ◽  
Chien-Liang Chen ◽  
Yao-Chung Chuang ◽  
Nai-Ching Chen
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Protective Factor ◽  
Proportional Hazards ◽  
Acetylcholinesterase Inhibitors ◽  
Cox Proportional Hazards ◽  
Research Database ◽  
Clinical Dementia Rating ◽  
Rapid Cognitive Decline

We investigated the preventive and risk factors of rapid cognitive decline in patients with Alzheimer’s disease (AD). Using the Chang Gung Research Database (CGRD), we enrolled patients with AD aged over 65 years between 1 January 2001 and 30 May 2019, and followed up for at least two years. Rapid cognitive decline was defined by a Mini-Mental State Examination (MMSE) score decline of ≥4 in 2 years. A longer prescription of acetylcholinesterase inhibitors (AChEIs) was defined as 22 months based on the median treatment duration of the cohorts. The Cox proportional hazards regression model adjusted for age, sex, medication, and physical comorbidities was used to examine the candidate risk and protective factors. We analyzed data from 3846 patients with AD (1503 men, 2343 women) with a mean age and percentage of females of 77.8 ± 6.2 years and 60.9%, respectively. The mean duration of patients with AD receiving AChEIs was 658.7 ± 21.9 days. In general, 310 patients with AD showed a rapid cognitive decline, accounting for 8.1%. Treatment of a consecutive AChEI prescription for >22 months in patients with AD was a protective factor against rapid cognitive decline (adjusted hazard ratio (aHR) = 0.41, 95% confidence interval (CI) = 0.33–0.52, p < 0.001). Patients with AD aged >85 years (aHR = 0.53, 95% CI = 0.36–0.79, p < 0.01) and aged 75–85 years (aHR = 0.73, 95% CI = 0.57–0.93, p < 0.05) had a significantly lower risk of rapid cognitive decline than those aged 65–75 years. Additionally, patients with mild and moderate AD (clinical dementia rating (CDR = 1, aHR = 1.61, 95% CI = 1.26–2.07, p < 0.001; CDR = 2, aHR = 2.64, 95% CI = 1.90–3.65, p < 0.001) were more likely to have rapid cognitive decline than those with early AD (CDR = 0.5). Sex, medication with different types of AChEIs, and physical comorbidities were not associated with rapid cognitive decline. These findings indicate that it is important to maintain longer consecutive AChEI prescriptions in patients with AD to prevent cognitive decline.

scholarly journals Association of peripheral blood DNA methylation level with Alzheimer’s disease progression

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Qingqin S. Li ◽  
Aparna Vasanthakumar ◽  
Justin W. Davis ◽  
Kenneth B. Idler ◽  
Kwangsik Nho ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Cognitive Decline ◽  
Peripheral Blood ◽  
Rating Scale ◽  
Association Studies ◽  
Clinical Dementia Rating ◽  
Cpg Sites ◽  
Cognition And Learning

Abstract Background Identifying biomarkers associated with Alzheimer’s disease (AD) progression may enable patient enrichment and improve clinical trial designs. Epigenome-wide association studies have revealed correlations between DNA methylation at cytosine-phosphate-guanine (CpG) sites and AD pathology and diagnosis. Here, we report relationships between peripheral blood DNA methylation profiles measured using Infinium® MethylationEPIC BeadChip and AD progression in participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Results The rate of cognitive decline from initial DNA sampling visit to subsequent visits was estimated by the slopes of the modified Preclinical Alzheimer Cognitive Composite (mPACC; mPACCdigit and mPACCtrailsB) and Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) plots using robust linear regression in cognitively normal (CN) participants and patients with mild cognitive impairment (MCI), respectively. In addition, diagnosis conversion status was assessed using a dichotomized endpoint. Two CpG sites were significantly associated with the slope of mPACC in CN participants (P < 5.79 × 10−8 [Bonferroni correction threshold]); cg00386386 was associated with the slope of mPACCdigit, and cg09422696 annotated to RP11-661A12.5 was associated with the slope of CDR-SB. No significant CpG sites associated with diagnosis conversion status were identified. Genes involved in cognition and learning were enriched. A total of 19, 13, and 5 differentially methylated regions (DMRs) associated with the slopes of mPACCtrailsB, mPACCdigit, and CDR-SB, respectively, were identified by both comb-p and DMRcate algorithms; these included DMRs annotated to HOXA4. Furthermore, 5 and 19 DMRs were associated with conversion status in CN and MCI participants, respectively. The most significant DMR was annotated to the AD-associated gene PM20D1 (chr1: 205,818,956 to 205,820,014 [13 probes], Sidak-corrected P = 7.74 × 10−24), which was associated with both the slope of CDR-SB and the MCI conversion status. Conclusion Candidate CpG sites and regions in peripheral blood were identified as associated with the rate of cognitive decline in participants in the ADNI cohort. While we did not identify a single CpG site with sufficient clinical utility to be used by itself due to the observed effect size, a biosignature composed of DNA methylation changes may have utility as a prognostic biomarker for AD progression.

scholarly journals Predicting Clinical Dementia Rating Using Blood RNA Levels

Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 706
Author(s):  
Justin B. Miller ◽  
John S. K. Kauwe
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Cognitive Status ◽  
Clinical Dementia Rating ◽  
Intracellular Channel ◽  
Rna Levels

The Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimer’s disease patients and is included in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. We divided 741 ADNI participants with blood microarray data into three groups based on their most recent CDR assessment: cognitive normal (CDR = 0), mild cognitive impairment (CDR = 0.5), and probable Alzheimer’s disease (CDR ≥ 1.0). We then used machine learning to predict cognitive status using only blood RNA levels. Only one probe for chloride intracellular channel 1 (CLIC1) was significant after correction. However, by combining individually nonsignificant probes with p-values less than 0.1, we averaged 87.87% (s = 1.02) predictive accuracy for classifying the three groups, compared to a 55.46% baseline for this study due to unequal group sizes. The best model had an overall precision of 0.902, recall of 0.895, and a receiver operating characteristic (ROC) curve area of 0.904. Although we identified one significant probe in CLIC1, CLIC1 levels alone were not sufficient to predict dementia status and cannot be used alone in a clinical setting. Additional analyses combining individually suggestive, but nonsignificant, blood RNA levels were significantly predictive and may improve diagnostic accuracy for Alzheimer’s disease. Therefore, we propose that patient features that do not individually predict cognitive status might still contribute to overall cognitive decline through interactions that can be elucidated through machine learning.

SUBJECTIVE COGNITIVE DECLINE, LONGITUDINAL COGNITIVE PERFORMANCE, AND IMAGING BIOMARKERS IN PRECLINICAL ALZHEIMER’S DISEASE

2017 ◽  
Vol 13 (7) ◽  
pp. P176
Author(s):  
Rebecca Amariglio ◽  
Rachel F. Buckley ◽  
Beth C. Mormino ◽  
Cathy Wang ◽  
Sarah L. Aghjayan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Cognitive Performance ◽  
Imaging Biomarkers ◽  
Subjective Cognitive Decline ◽  
Preclinical Alzheimer’S Disease

Influence of Educational Attainment on Cognition-Based Intervention Programs for Persons with Mild Alzheimer’s Disease

2016 ◽  
Vol 22 (5) ◽  
pp. 577-582 ◽  
Author(s):  
Israel Contador ◽  
Bernardino Fernández-Calvo ◽  
Francisco Ramos ◽  
Javier Olazarán
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Effect Size ◽  
Study Groups ◽  
Total Sample ◽  
Cognitive Intervention ◽  
Potential Effect ◽  
Cognitive Status ◽  
Disease Assessment

AbstractObjectives: This research retrospectively analyzed the effect of education on cognitive interventions carried out in patients with mild Alzheimer’s disease (AD). Methods: The total sample consisted of 75 patients with mild AD receiving treatment with cholinesterase inhibitors. The participants were divided into two groups: cognitive intervention (IG; n=45) and waiting list (WLG; n=30). Patients in the IG received either the Big Brain Academy (n=15) or the Integrated Psychostimulation Program (n=30) during 12 weeks. The influence of education on intervention effect was analyzed comparing mean change scores of the two study groups in the cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog), stratified by educational level. The potential effect of age, sex, cognitive status, and type of intervention was examined using post hoc stratification analyses. Results: Higher education was associated with faster cognitive decline in the WLG (effect size=0.51; p<.01). However, cognitive evolution was not influenced by education in the IG (effect size=0.12; p=.42). Conclusions: Our results suggest that cognitive intervention might delay accelerated cognitive decline in higher educated individuals with mild AD. (JINS, 2016, 23, 1–6)

scholarly journals Association of naturally occurring antibodies to β-amyloid with cognitive decline and cerebral amyloidosis in Alzheimer’s disease

2021 ◽  
Vol 7 (1) ◽  
pp. eabb0457
Author(s):  
Yu-Hui Liu ◽  
Jun Wang ◽  
Qiao-Xin Li ◽  
Christopher J. Fowler ◽  
Fan Zeng ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Plasma Levels ◽  
Imaging Biomarkers ◽  
Amino Terminus ◽  
Cross Sectional ◽  
Naturally Occurring ◽  
Β Amyloid ◽  
Naturally Occurring Antibodies

The pathological relevance of naturally occurring antibodies to β-amyloid (NAbs-Aβ) in Alzheimer’s disease (AD) remains unclear. We aimed to investigate their levels and associations with Aβ burden and cognitive decline in AD in a cross-sectional cohort from China and a longitudinal cohort from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. NAbs-Aβ levels in plasma and cerebrospinal fluid (CSF) were tested according to their epitopes. Levels of NAbs targeting the amino terminus of Aβ increased, and those targeting the mid-domain of Aβ decreased in both CSF and plasma in AD patients. Higher plasma levels of NAbs targeting the amino terminus of Aβ and lower plasma levels of NAbs targeting the mid-domain of Aβ were associated with higher brain amyloidosis at baseline and faster cognitive decline during follow-up. Our findings suggest a dynamic response of the adaptive immune system in the progression of AD and are relevant to current passive immunotherapeutic strategies.

Risk Factors for Rapid Cognitive Decline in Alzheimer’s Disease

2017 ◽  
Vol 7 (5) ◽  
pp. 770-776
Author(s):  
Myung Chul Kim ◽  
Eun Hye Jeong ◽  
Hyun Keun Lee ◽  
Young Kyu Park
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rapid Cognitive Decline

scholarly journals Amyloid and tau imaging biomarkers explain cognitive decline from late middle-age

Brain ◽  
2019 ◽  
Vol 143 (1) ◽  
pp. 320-335 ◽  
Author(s):  
Tobey J Betthauser ◽  
Rebecca L Koscik ◽  
Erin M Jonaitis ◽  
Samantha L Allison ◽  
Karly A Cody ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Middle Age ◽  
Neurofibrillary Tangle ◽  
Imaging Biomarkers ◽  
Cognitive Tests ◽  
Preclinical Alzheimer’S Disease ◽  
Significant Group ◽  
Health Factors

Abstract This study investigated differences in retrospective cognitive trajectories between amyloid and tau PET biomarker stratified groups in initially cognitively unimpaired participants sampled from the Wisconsin Registry for Alzheimer’s Prevention. One hundred and sixty-seven initially unimpaired individuals (baseline age 59 ± 6 years; 115 females) were stratified by elevated amyloid-β and tau status based on 11C-Pittsburgh compound B (PiB) and 18F-MK-6240 PET imaging. Mixed effects models were used to determine if longitudinal cognitive trajectories based on a composite of cognitive tests including memory and executive function differed between biomarker groups. Secondary analyses investigated group differences for a variety of cross-sectional health and cognitive tests, and associations between 18F-MK-6240, 11C-PiB, and age. A significant group × age interaction was observed with post hoc comparisons indicating that the group with both elevated amyloid and tau pathophysiology were declining approximately three times faster in retrospective cognition compared to those with just one or no elevated biomarkers. This result was robust against various thresholds and medial temporal lobe regions defining elevated tau. Participants were relatively healthy and mostly did not differ between biomarker groups in health factors at the beginning or end of study, or most cognitive measures at study entry. Analyses investigating association between age, MK-6240 and PiB indicated weak associations between age and 18F-MK-6240 in tangle-associated regions, which were negligible after adjusting for 11C-PiB. Strong associations, particularly in entorhinal cortex, hippocampus and amygdala, were observed between 18F-MK-6240 and global 11C-PiB in regions associated with Braak neurofibrillary tangle stages I–VI. These results suggest that the combination of pathological amyloid and tau is detrimental to cognitive decline in preclinical Alzheimer’s disease during late middle-age. Within the Alzheimer’s disease continuum, middle-age health factors likely do not greatly influence preclinical cognitive decline. Future studies in a larger preclinical sample are needed to determine if and to what extent individual contributions of amyloid and tau affect cognitive decline. 18F-MK-6240 shows promise as a sensitive biomarker for detecting neurofibrillary tangles in preclinical Alzheimer’s disease.

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