
A study on consistency between routine clinical diagnosis of AD and PET-amyloid imaging
LI Weiwei, XU Yali, SHEN Yingying, CHEN Dongwan, BU Xianle, ZENG Fan, LIU Yuhui, JIN Wangsheng, CHEN Yang, ZHU Jie, YAO Xiuqing, GAO Changyue, XU Zhiqiang, ZHOU Huadong, LI Qiming, JIAO Fangyang, WEN Jianliang, JIN Rongbing, WANG Yanjiang
A study on consistency between routine clinical diagnosis of AD and PET-amyloid imaging
Objective: Evaluate the consistency between clinical diagnosis and the diagnosis based on 11C-Pittsburgh Compound B-positron emission tomography (PiB-PET) for Alzheimer's disease (AD), and discuss the factors that may influence brain Aβ deposition. Methods: 48 AD and 14 mild cognitive impairment (MCI) patients were enrolled in our study. The information of age, sex, education level, Neuropsychological assessment and vascular risk factors (VRF) (including hypertension, diabetes, hyperlipemia, coronary heart disease and stroke history) were collected and PiB-PET scanning and APOE gene sequencing were carried out on all subjects. We compared the consistency of AD clinical diagnosis and PiB-PET based diagnosis, analysed the neuropsychological test scores differences between PET positive and negative subjects, and discuss the correlation between VRF, education lever, APOE genotype and brain Aβ deposition. Results: The consistency between AD clinical diagnosis and PiB-PET based diagnosis were 77.1%, while PET positive subjects only cover 21.4% in MCI patients. The MMSE scores of PET positive subjects were lower than PET negative subjects (t=-3.232, P=0.004), and CDR(t=2.727, P=0.012)and ADL(t=2.261, P=0.034)scores were higher. Among all these risk factors, APOE genotype was the only significant one (OR=4.913, P=0.049) that can affect the brain Aβ deposition. Conclusion: Misdiagnose exists and can hardly be avoided in clinical diagnosis, it is necessary to bring into more assistance tools like biological biomarkers, neuroimaging and hereditary factor for a more precise clinical diagnosis. As the most important gene of AD, APOE perform well at AD diagnosis, evaluation, prevention and treatment.
Alzheimer's disease / Clinical diagnosis / PiB-PET / Risk factor {{custom_keyword}} /
表1 研究对象PET诊断结果比较 |
PiB-PET诊断 | |||||
---|---|---|---|---|---|
阳性 | 阴性 | 总数 | 阳性一致率(%) | ||
临床诊断 | AD组 | 37 | 11 | 48 | 77.1 |
MCI组 | 3 | 11 | 14 | 21.4 |
注:AD,阿尔茨海默病;MCI,轻度认知功能障碍。 |
表2 研究对象一般资料及神经心理学量表评分 |
组别 | 例数(例) | 年龄( | 性别(男/女) | MMSE( | CDR( | ADL( | |
---|---|---|---|---|---|---|---|
总样本 | PET(+) | 40 | 70.4±9.30 | 19/21 | 13.74±7.12 | 1.89±0.92 | 43.52±14.27 |
PET(-) | 22 | 63.18±8.15 | 8/14 | 23.21±4.59 | 0.89± 0.53 | 27.14±11.05 | |
P值 | 0.003 | 0.397 | <0.001 | <0.001 | 0.001 | ||
AD组 | PET(+) | 37 | 70.14±9.11 | 17/20 | 12.89±6.27 | 1.97±0.88 | 44.72±13.67 |
PET(-) | 11 | 65.00±9.43 | 6/5 | 21.43±4.86 | 1.00±0.50 | 30.57±15.06 | |
P值 | 0.111 | 0.616 | 0.004 | 0.012 | 0.034 | ||
MCI组 | PET(+) | 3 | 74.00±13.11 | 2/1 | 27.33±1.53 | 0.67±0.29 | 24.00±1.73 |
PET(-) | 11 | 61.36±6.56 | 2/9 | 25.00±3.83 | 0.79±0.57 | 23.71±3.20 | |
P值 | 0.033 | 0.176 | 0.35 | 0.745 | 0.89 |
注:AD,阿尔茨海默病;MCI,轻度认知功能障碍;MMSE,简易智力状态检查量表;CDR,临床痴呆评定量表;ADL,日常生活能力评定量表。 |
表3 单因Logistic回归分析 |
高血压 | 糖尿病 | 高血脂 | 冠心病 | 卒中史 | APOE | 教育年限 | ||
---|---|---|---|---|---|---|---|---|
总样本 | OR值 | 0.602 | 1.389 | 1.802 | 0.929 | 0.658 | 3.540 | 1.064 |
P值 | 0.467 | 0.745 | 0.410 | 0.912 | 0.685 | 0.044 | 0.530 | |
AD组 | OR值 | 0.225 | 0.412 | 0.720 | 0.597 | 0.407 | 4.913 | 1.044 |
P值 | 0.113 | 0.414 | 0.698 | 0.514 | 0.409 | 0.049 | 0.733 |
[1] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[2] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[3] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[4] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[5] |
There is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer's disease, but there is limited information on this from neuropathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid-β (Aβ) brain burden measured by Pittsburgh Compound B-positron emission tomography (PiB-PET) studies in the Alzheimer's Disease Neuroimaging Initiative.Ninety-nine subjects from the Alzheimer's Disease Neuroimaging Initiative cohort who had a PiB-PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP], and cholesterol and fasting glucose test results) were included. Eighty-one subjects also had plasma cortisol, C-reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB-PET score.The first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ɛ4 alleles, BMI (P =.023), and DBP (P =.012). BMI showed an inverse relation with PiB-PET score, and DBP had a positive relation with PiB-PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB-PET score (P =.004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB-PET values.In this cross-sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB-PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer's disease risk factors.Copyright © 2012 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[6] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[7] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[8] |
Alzheimer's disease (AD) is the most common cause of cognitive dysfunction in older adults. The pathological hallmarks of AD such as beta amyloid (Aβ) aggregation and neurometabolic change, as indicated by altered myo-inositol (mI) and N-acetylaspartate (NAA) levels, typically precede the onset of cognitive dysfunction by years. Furthermore, cerebrovascular disease occurs early in AD, but the interplay between vascular and neurometabolic brain change is largely unknown. Thirty cognitively normal older adults (age = 70 ± 5.6 years, Mini-Mental State Examination = 29.2 ± 1) received 11-C-Pittsburgh Compound B positron emission tomography for estimating Aβ-plaque density, 7 Tesla fluid-attenuated inversion recovery magnetic resonance imaging for quantifying white matter hyperintensity volume as a marker of small vessel cerebrovascular disease and high-resolution magnetic resonance spectroscopic imaging at 7 Tesla, based on free induction decay acquisition localized by outer volume suppression to investigate tissue-specific neurometabolism in the posterior cingulate and precuneus. Aβ (β = 0.45, p = 0.018) and white matter hyperintensities (β = 0.40, p = 0.046) were independently and interactively (β = -0.49, p = 0.026) associated with a higher ratio of mI over NAA (mI/NAA) in the posterior cingulate and precuneus gray matter but not in the white matter. Our data suggest that cerebrovascular disease and Aβ burden are synergistically associated with AD-related gray matter neurometabolism in older adults.Copyright © 2017 Elsevier Inc. All rights reserved.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[9] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[10] |
The brain mechanisms underlying the effect of intellectual enrichment may evolve along the normal aging Alzheimer's disease (AD) cognitive spectrum and may include both protective and compensatory mechanisms. We assessed the association between early intellectual enrichment (education, years) and average cortical florbetapir standardized uptake value ratio as well as performed voxel-wise analyses in a total of 140 participants, including cognitively normal older adults, mild cognitive impairment (MCI), and AD patients. Higher education was associated with lower cortical florbetapir positron emission tomography (florbetapir-PET) uptake, notably in the frontal lobe in normal older adults, but with higher uptake in frontal, temporal, and parietal regions in MCI after controlling for global cognitive status. No association was found in AD. In MCI, we observed an increased fluorodeoxyglucose positron emission tomography (FDG-PET) uptake with education within the regions of higher florbetapir-PET uptake, suggesting a compensatory increase. Early intellectual enrichment may be associated with protection and compensation for amyloid beta (Aβ) deposition later in life, before the onset of dementia. Previous investigations have been controversial as regard to the effects of intellectual enrichment variables on Aβ deposition; the present findings call for approaches aiming to evaluate mechanisms of resilience across disease stages.Copyright © 2017 Elsevier Inc. All rights reserved.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[11] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[12] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[13] |
Many observational studies have shown that physical activity reduces the risk of cognitive decline; however, evidence from randomized trials is lacking.To determine whether physical activity reduces the rate of cognitive decline among older adults at risk.Randomized controlled trial of a 24-week physical activity intervention conducted between 2004 and 2007 in metropolitan Perth, Western Australia. Assessors of cognitive function were blinded to group membership.We recruited volunteers who reported memory problems but did not meet criteria for dementia. Three hundred eleven individuals aged 50 years or older were screened for eligibility, 89 were not eligible, and 52 refused to participate. A total of 170 participants were randomized and 138 participants completed the 18-month assessment.Participants were randomly allocated to an education and usual care group or to a 24-week home-based program of physical activity.Change in Alzheimer Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores (possible range, 0-70) over 18 months.In an intent-to-treat analysis, participants in the intervention group improved 0.26 points (95% confidence interval, -0.89 to 0.54) and those in the usual care group deteriorated 1.04 points (95% confidence interval, 0.32 to 1.82) on the ADAS-Cog at the end of the intervention. The absolute difference of the outcome measure between the intervention and control groups was -1.3 points (95% confidence interval,-2.38 to -0.22) at the end of the intervention. At 18 months, participants in the intervention group improved 0.73 points (95% confidence interval, -1.27 to 0.03) on the ADAS-Cog, and those in the usual care group improved 0.04 points (95% confidence interval, -0.46 to 0.88). Word list delayed recall and Clinical Dementia Rating sum of boxes improved modestly as well, whereas word list total immediate recall, digit symbol coding, verbal fluency, Beck depression score, and Medical Outcomes 36-Item Short-Form physical and mental component summaries did not change significantly.In this study of adults with subjective memory impairment, a 6-month program of physical activity provided a modest improvement in cognition over an 18-month follow-up period.anzctr.org.au Identifier: ACTRN12605000136606.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[14] |
The primary aim of this study was to determine whether the presence of one or more APOE epsilon4 alleles modifies the association between diabetes (defined by glucose > or =7 mmol/l or treatment) and cognitive function.Diabetic status and APOE genotype interactions were assessed cross-sectionally for 826 community-dwelling, stroke-free, non-demented individuals (526 non-diabetic non-APOE epsilon4 carriers, 174 non-diabetic APOE epsilon4 carriers, 87 diabetic APOE epsilon4 non-carriers, 39 diabetic APOE epsilon4 carriers) ranging in age from 50 to 98 years. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), the similarities subtest from the Wechsler Adult Intelligence Scale, and four composite scores derived from 17 additional neuropsychological tests. Multiple linear regression analyses were employed to relate diabetes and APOE genotype to cognitive performance and to examine the interaction between these two risk factors as they relate to cognitive performance. Multiple cardiovascular disease risk factors were statistically controlled.With adjustment for age, education, sex, race/ethnicity and APOE genotype, performance level was lower for the diabetic than for the non-diabetic group for the MMSE, the similarities subtest and each of the cognitive composites with the exception of the verbal memory composite. Interactions (p < 0.05) between diabetes and APOE genotype were found for all but the visual-spatial memory/organisation composite. The negative association between diabetes and cognitive performance was of a higher magnitude for individuals who carry one or more APOE epsilon4 alleles. Results were similar with additional adjustment for cardiovascular disease and associated risk factors.The presence of one or more APOE epsilon4 alleles modifies the association between diabetes and cognitive function.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[15] |
To examine the relationship between cholesterol and other lipids, APOE genotype, and risk of Alzheimer disease (AD) in a population-based study of elderly Yoruba living in Ibadan, Nigeria.Blood samples and clinical data were collected from Yoruba study participants aged 70 years and older (N = 1,075) as part of the Indianapolis-Ibadan Dementia Project, a longitudinal epidemiologic study of AD. Cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride levels were measured in fasting blood samples. DNA was extracted and APOE was genotyped. Diagnoses of AD were made by consensus using National Institute of Neurologic Disorders/Stroke-Alzheimer's Disease and Related Disorders Association criteria.Logistic regression models showed interaction after adjusting for age and gender between APOE-epsilon4 genotype and biomarkers in the risk of AD cholesterol*genotype (p = 0.022), LDL*genotype (p= 0.018), and triglyceride*genotype (p = 0.036). Increasing levels of cholesterol and LDL were associated with increased risk of AD in individuals without the APOE-epsilon4 allele, but not in those with APOE-epsilon4. There was no significant association between levels of triglycerides and AD risk in those without APOE-epsilon4.There was a significant interaction between cholesterol, APOE-epsilon4, and the risk of Alzheimer disease (AD) in the Yoruba, a population that has lower cholesterol levels and lower incidence rates of AD compared to African Americans. APOE status needs to be considered when assessing the relationship between lipid levels and AD risk in population studies.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[16] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[17] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[18] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[19] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[20] |
Dementia with Lewy bodies (DLB) is the second commonest cause of neurodegenerative dementia in older people. It is part of the range of clinical presentations that share a neuritic pathology based on abnormal aggregation of the synaptic protein alpha-synuclein. DLB has many of the clinical and pathological characteristics of the dementia that occurs during the course of Parkinson's disease. Here we review the current state of scientific knowledge on DLB. Accurate identification of patients is important because they have specific symptoms, impairments, and functional disabilities that differ from those of other common types of dementia. Severe neuroleptic sensitivity reactions are associated with significantly increased morbidity and mortality. Treatment with cholinesterase inhibitors is well tolerated by most patients and substantially improves cognitive and neuropsychiatric symptoms. Clear guidance on the management of DLB is urgently needed. Virtually unrecognised 20 years ago, DLB could within this decade be one of the most treatable neurodegenerative disorders of late life.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[21] |
Background: This study compared individuals whose clinical diagnosis of Alzheimer's disease (AD) matched or did not match neuropathologic results at autopsy on clinical and functional outcomes (cognitive impairment, functional status and neuropsychiatric symptoms). The study also assessed the extent of potentially inappropriate medication use (using potentially unnecessary medications or potentially inappropriate prescribing) among misdiagnosed patients.;Methods: Longitudinal data from the National Alzheimer's Coordinating Center Uniform Data Set (NACC-UDS, 2005-2010) and corresponding NACC neuropathological data were utilized to compare 88 misdiagnosed and 438 accurately diagnosed patients.;Results: Following adjustment of sociodemographic characteristics, the misdiagnosed were found to have less severe cognitive and functional impairment. However, after statistical adjustment for sociodemographics, dementia severity level, time since onset of cognitive decline and probable AD diagnosis at baseline, the groups significantly differed on only one outcome: the misdiagnosed were less likely to be depressed/dysphoric. Among the misdiagnosed, 18.18% were treated with potentially inappropriate medication. An additional analysis noted this rate could be as high as 67.10%.;Conclusions: Findings highlight the importance of making an accurate AD diagnosis to help reduce unnecessary treatment and increase appropriate therapy. Additional research is needed to demonstrate the link between potentially inappropriate treatment and adverse health outcomes in misdiagnosed AD patients.
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[22] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[23] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[24] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[25] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[26] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
[27] |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
{{custom_ref.label}} |
{{custom_citation.content}}
{{custom_citation.annotation}}
|
/
〈 |
|
〉 |