Dataset Information

Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design.

ABSTRACT: Importance:The heterogeneity of rate of clinical progression among patients with Alzheimer disease leads to difficulty in providing clinical counseling and diminishes the power of clinical trials using disease-modifying agents. Objective:To gain a better understanding of the factors that affect the natural history of progression in Alzheimer disease for the purpose of improving both clinical care and clinical trial design. Design, Setting, and Participants:A longitudinal cohort study of aging from 2005 to 2014 in the National Alzheimer Coordinating Center. Clinical evaluation of the participants was conducted in 31 National Institute on Aging's Alzheimer Disease Centers. Nine hundred eighty-four participants in the National Alzheimer Coordinating Center cohort study who died and underwent autopsy and met inclusion and exclusion criteria. Main Outcomes and Measures:We sought to model the possibility that knowledge of neurofibrillary tangle burden in the presence of moderate or frequent plaques would add to the ability to predict clinical rate of progression during the ensuing 2 to 3 years. We examined the National Alzheimer Coordinating Center autopsy data to evaluate the effect of different neurofibrillary tangle stages on the rates of progression on several standard clinical instruments: the Clinical Dementia Rating Scale sum of boxes, a verbal memory test (logical memory), and a controlled oral word association task (vegetable naming), implementing a reverse-time longitudinal modeling approach in conjunction with latent class estimation to adjust for unmeasured sources of heterogeneity. Results:Several correlations between clinical variables and neurocognitive performance suggest a basis for heterogeneity: Higher education level was associated with lower Clinical Dementia Rating Scale sum of boxes (??=?-0.19; P?

SUBMITTER: Qian J

PROVIDER: S-EPMC5547572 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design.

Qian Jing J Hyman Bradley T BT Betensky Rebecca A RA

JAMA neurology 20170501 5

<h4>Importance</h4>The heterogeneity of rate of clinical progression among patients with Alzheimer disease leads to difficulty in providing clinical counseling and diminishes the power of clinical trials using disease-modifying agents.<h4>Objective</h4>To gain a better understanding of the factors that affect the natural history of progression in Alzheimer disease for the purpose of improving both clinical care and clinical trial design.<h4>Design, setting, and participants</h4>A longitudinal co ...[more]

PMID: 28288263

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Project description:The apolipoprotein E (APOE [GenBank, 348; OMIM, 107741]) ?4 allele is a common and well-established genetic risk factor for Alzheimer disease (AD). Sleep consolidation is also associated with AD risk, and previous work suggests that APOE genotype and sleep may interact to influence cognitive function.To determine whether better sleep consolidation attenuates the relationship of the APOE genotype to the risk of incident AD and the burden of AD pathology.A prospective longitudinal cohort study with up to 6 years of follow-up was conducted. Participants included 698 community-dwelling older adults without dementia (mean age, 81.7 years; 77% women) in the Rush Memory and Aging Project.We used up to 10 days of actigraphic recording to quantify the degree of sleep consolidation and ascertained APOE genotype.Participants underwent annual evaluation for AD during a follow-up period of up to 6 years. Autopsies were performed on 201 participants who died, and ?-amyloid (A?) and neurofibrillary tangles were identified by immunohistochemistry and quantified.During the follow-up period, 98 individuals developed AD. In a series of Cox proportional hazards regression models, better sleep consolidation attenuated the effect of the ?4 allele on the risk of incident AD (hazard ratio, 0.67; 95% CI, 0.46-0.97; P = .04 per allele per 1-SD increase in sleep consolidation). In a series of linear mixed-effect models, better sleep consolidation also attenuated the effect of the ?4 allele on the annual rate of cognitive decline. In individuals who died, better sleep consolidation attenuated the effect of the ?4 allele on neurofibrillary tangle density (interaction estimate, -0.42; SE = 0.17; P = .02), which accounted for the effect of sleep consolidation on the association between APOE genotype and cognition proximate to death.Better sleep consolidation attenuates the effect of APOE genotype on incident AD and development of neurofibrillary tangle pathology. Assessment of sleep consolidation may identify APOE+ individuals at high risk for incident AD, and interventions to enhance sleep consolidation should be studied as potentially useful means to reduce the risk of AD and development of neurofibrillary tangles in APOE ?4+ individuals.

Project description:Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their cognitive symptoms. But the cognitive capability of a patient at any time throughout this deterioration reflects not only the disease state, but also the effect of the cognitive decline on the patient's pre-disease cognitive capability. Patients with high pre-disease cognitive capabilities tend to score better on cognitive tests that are sensitive early in disease relative to patients with low pre-disease cognitive capabilities at a similar disease stage. Thus, a single assessment with a cognitive test is often not adequate for determining the stage of an AD patient. Repeated evaluation of patients' cognition over time may improve the ability to stage AD patients, and such longitudinal assessments in combinations with biomarker assessments can help elucidate the time dynamics of biomarkers. In turn, this can potentially lead to identification of markers that are predictive of disease stage and future cognitive decline, possibly before any cognitive deficit is measurable. Methods and Findings: This article presents a class of statistical disease progression models and applies them to longitudinal cognitive scores. These non-linear mixed-effects disease progression models explicitly model disease stage, baseline cognition, and the patients' individual changes in cognitive ability as latent variables. Maximum-likelihood estimation in these models induces a data-driven criterion for separating disease progression and baseline cognition. Applied to data from the Alzheimer's Disease Neuroimaging Initiative, the model estimated a timeline of cognitive decline that spans ~15 years from the earliest subjective cognitive deficits to severe AD dementia. Subsequent analyses demonstrated how direct modeling of latent factors that modify the observed data patterns provides a scaffold for understanding disease progression, biomarkers, and treatment effects along the continuous time progression of disease. Conclusions: The presented framework enables direct interpretations of factors that modify cognitive decline. The results give new insights to the value of biomarkers for staging patients and suggest alternative explanations for previous findings related to accelerated cognitive decline among highly educated patients and patients on symptomatic treatments.

Project description:Alzheimer's disease (AD) can be classified based on the relative density of neurofibrillary tangles (NFTs) in the hippocampus and association cortices into three subtypes: typical AD, hippocampal-sparing AD (HpSp AD), and limbic-predominant AD (LP AD). AD subtypes not only have pathologic, but also demographic, clinical, and genetic differences. Neurofibrillary tangle-predominant dementia (NFTD), a disorder with NFTs relatively restricted to limbic structures, shares this feature with LP AD raising the possibility that NFTD is a variant of AD. The objective criteria for pathologic diagnosis of NFTD are not available. A goal of this study was to design a mathematical algorithm that could diagnose NFTD from NFT and senile plaque (SP) counts in hippocampus and association cortices, analogous to that used to subtype AD. Moreover, we aimed to compare pathologic, demographic, clinical, and genetic features of NFTD (n = 18) with LP AD (n = 19), as well as the other AD subtypes, typical AD (n = 52) and HpSp AD (n = 17). Using digital microscopy, we confirmed that burden of phospho-tau (CP13) and of an NFT conformational epitope (Ab39) correlated with NFT densities and showed expected patterns across AD subtypes. HpSp AD had the highest and LP AD had the lowest burden of cortical CP13 and Ab39 immunoreactivity. On the other hand, cortical β-amyloid burden did not significantly differ between AD subtypes. Semi-quantitative assessment of SPs in the basal ganglia did show HpSp AD to have significantly more frequent presence of SPs compared to typical AD, which was more frequent than LP AD. Compared to LP AD, NFTD had an older age at disease onset and shorter disease duration, as well as lower Braak NFT stage. NFTs and SPs on thioflavin-S fluorescent microscopy, as well as CP13, Ab39, and Aβ immunoreactivities were very low in the frontal cortex of NFTD, differentiating NFTD from AD subtypes, including LP AD. MAPT H1H1 genotype frequency was high (~70 %) in NFTD and LP AD, and similar to typical AD, while APOE ε4 carrier state was low in NFTD. While it shares clinical similarities with regard to female sex predominance, onset in advanced age, and a slow cognitive decline, NFTD has significant pathologic differences from LP AD, suggesting that it may not merely be a variant of AD.

Dataset Information

Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design.

Publications

Neurofibrillary Tangle Stage and the Rate of Progression of Alzheimer Symptoms: Modeling Using an Autopsy Cohort and Application to Clinical Trial Design.

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