Predicting MCI outcome with clinically available MRI and CSF biomarkers
TL;DR: In this paper, the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI).
Abstract: Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8– 4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. Neurology ® 2011;77:1619–1628
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TL;DR: Psychometric tests perform as well as imaging biomarkers to predict presence of molecular markers of AD pathology in MCI patients and should be considered in the determination of the likelihood that MCI is due to AD.
Abstract: Background: Psychometric tests predict conversion of mild cognitive impairment (MCI) to probable Alzheimer’s disease (AD). Because the definition of clinical AD relies on those same psychometric tests, the ability of these tests to identify underlying AD pathology remains unclear. 14 15 16 Objective: To determine the degree to which psychometric testing predicts molecular evidence of AD amyloid pathology, as indicated by cerebrospinal fluid (CSF) amyloid- (A)1-42, in patients with MCI, as compared to neuroimaging biomarkers. 17 18 Methods: We identified 408 MCI subjects with CSF A levels, psychometric test data, FDG-PET scans, and acceptable volumetric MR scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used psychometric tests and imaging biomarkers in univariate and multivariate models to predict A status.
23 citations
Cites background from "Predicting MCI outcome with clinica..."
...to clinical AD in patients either with “positive” CSF 576 or PET amyloid studies or neurodegenerative markers 577 [1, 35, 36]....
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TL;DR: CSF VGF enhances the ability of conventional biomarkers to predict MCI to AD conversion and combinations of CSF Aβ1-42 and phosphorylated tau, hippocampal volume, and VGF peptide levels outperformed conventional biomarker alone.
Abstract: Background Previous work has suggested that the brain and cerebrospinal fluid (CSF) levels of a neural protein involved in synaptic transmission, VGF (a noninitialism), may be altered in mild cognitive impairment (MCI) and Alzheimer Disease (AD). The objective of the current work is to examine the potential of CSF levels of a peptide derived from VGF to predict conversion from MCI to AD. Materials and methods Using multivariate analytical approaches, the performance of the conventional biomarkers (CSF Aβ1-42 and phosphorylated tau +/- hippocampal volume) was compared with the same biomarkers combined with CSF VGF peptide levels in a large publicly available data set from human subjects. Results It was observed that VGF peptides are lowered in CSF of patients with AD compared with controls and that combinations of CSF Aβ1-42 and phosphorylated tau, hippocampal volume, and VGF peptide levels outperformed conventional biomarkers alone (hazard ratio=2.2 vs. 3.9), for predicting MCI to AD conversion. Conclusions CSF VGF enhances the ability of conventional biomarkers to predict MCI to AD conversion. Future work will be needed to determine the specificity of VGF for AD versus other neurodegenerative diseases.
23 citations
TL;DR: Convergence of neuropsychological and neuroanatomical data, particularly HOC (as opposed to standard cross-sectional volume), supports early identification of MCI as defined by some neuroPsychological criteria.
Abstract: Objective In an effort to address earliest detection of mild cognitive impairment (MCI), we examined hippocampal volumes and atrophy in middle-aged men to explore neuroanatomical support for different neuropsychological definitions of MCI. Methods 460 men aged 51–60 years underwent neuropsychological testing and MRI. MCI was defined according to five criteria sets. MRI-derived hippocampal volume and hippocampal occupancy (HOC) were obtained via FreeSurfer. Statistical analyses were performed using linear mixed models. Results Differences in HOC between normal cognitive functioning, amnestic, and non-amnestic MCI were observed using MCI criteria that required one impaired (>1.5 SD) cognitive measure in a given cognitive domain or a cognitive composite score method with a cut-point 2 SD below the mean. Differences in standard hippocampal volume were only found between normal and amnestic presentations and only when using the composite score method. Conclusion Results provide empirical support for detection of pre-MCI in younger cohorts. Convergence of neuropsychological and neuroanatomical data, particularly HOC (as opposed to standard cross-sectional volume), supports early identification of MCI as defined by some neuropsychological criteria.
22 citations
Cites background from "Predicting MCI outcome with clinica..."
...as a way to cross-sectionally estimate hippocampal atrophy.(44) Standard hippocampal volume measurements are adjusted for intracranial volume or overall head size whereas hippocampal occupancy is a measure of the process of expansion of the ventricles resultant from cortical atrophy, since hippocampal volume is adjusted for the sum of the hippocampal and temporal horn area....
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TL;DR: The MTAi is a simple 2D-method for measuring the relative extent of atrophy in the MTL in relation to the global brain atrophy that can be useful for a more accurate diagnosis of AD in routine clinical practice.
Abstract: Background and purpose: Despite a strong correlation between severity of Alzheimer disease (AD) pathology and medial temporal lobe atrophy (MTA), its measurement has not been widely used in daily clinical practice as a criterion in the diagnosis of prodromal and probable AD. This is mainly because the methods available to date are sophisticated and difficult to implement for routine use in most hospitals. In this pilot study we aim to describe a novel, simple and objective method for measuring the rate of MTA in relation to the global atrophy using clinically available neuroimaging and describe the rationale behind this method.Description: This method consists of calculating a ratio of 3 regions traced manually on one single coronal MRI slide at the level of the interpeduncular fossa: i) the medial temporal lobe region (A); ii) the parenchyma within the medial temporal region, that includes the hippocampus and the parahippocampal gyrus -the fimbriae taenia and choroid plexus are excluded- (B); and iii) the body of the ipsilateral lateral ventricle (C). Therefore we can compute the ratio “Medial Temporal Atrophy index” at both sides as follows: MTAi = (A-B) x10/C.Conclusions: The MTAi is a simple 2D-method for measuring the relative extent of atrophy in the MTL in relation to the global brain atrophy. This method can be useful for a more accurate diagnosis of AD in routine clinical practice. Further studies are needed to assess the usefulness of MTAi in the diagnosis of early AD, in tracking the progression of AD and in the differential diagnosis of AD with other dementias.
22 citations
TL;DR: In this article, the authors examined the relationship between baseline serum levels of 349 known lipids from 16 classes of lipids to differentiate disease state as well as to predict the conversion from mild cognitive impairment (MCI) to AD.
Abstract: Background There is intense interest in the development of blood-based biomarkers, not only that can differentiate Alzheimer's disease (AD) from controls, but that can also predict conversion from mild cognitive impairment (MCI) to AD. Serum biomarkers carry the potential advantage over imaging or spinal fluid markers both in terms of cost and invasiveness. Objective Our objective was to measure the potential for serum lipid markers to differentiate AD from age-matched healthy controls as well as to predict conversion from MCI to AD. Methods Using a publicly-available dataset, we examined the relationship between baseline serum levels of 349 known lipids from 16 classes of lipids to differentiate disease state as well as to predict the conversion from MCI to AD. Results We observed that several classes of lipids (cholesteroyl ester, phosphatidylethanolamine, lysophosphatidylethanolamine, and acylcarnitine) differentiated AD from normal controls. Among these, only two classes, phosphatidylethanolamine (PE) and lysophosphatidylethanolamine (lyso-PE), predicted time to conversion from MCI to AD. Low levels of PE and high levels of lyso-PE result in two-fold faster median time to progression from MCI to AD, with hazard ratios 0.62 and 1.34, respectively. Conclusion These data suggest that serum PE and lyso-PE may be useful biomarkers for predicting MCI to AD conversion. In addition, since PE is converted to lyso-PE by phospholipase A2, an important inflammatory mediator that is dysregulated in AD, these data suggest that the disrupted serum lipid profile here may be related to an abnormal inflammatory response early in the AD pathologic cascade.
22 citations
References
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Johns Hopkins University1, Johns Hopkins University School of Medicine2, Mayo Clinic3, McGill University4, Harvard University5, University of California, Irvine6, University of Pittsburgh7, Columbia University Medical Center8, Eli Lilly and Company9, Washington University in St. Louis10, UCL Institute of Neurology11, VU University Medical Center12, Alzheimer's Association13, Northwestern University14, National Institutes of Health15
TL;DR: The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available.
Abstract: The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia.
13,710 citations
Brigham and Women's Hospital1, University of California, San Diego2, University of California, Davis3, Rush University Medical Center4, University of Washington5, Washington University in St. Louis6, University of Tokyo7, Mayo Clinic8, Oregon Health & Science University9, University of Texas at Dallas10, University of Melbourne11, Eli Lilly and Company12, Columbia University13, University of California, San Francisco14, Alzheimer's Association15, National Institutes of Health16
TL;DR: A conceptual framework and operational research criteria are proposed, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies and it is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD.
Abstract: The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long "preclinical" phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from "normal" cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.
5,671 citations
TL;DR: This work proposes a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegnerative biomarker become abnormal later, and correlate with clinical symptom severity.
Abstract: Summary Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of β-amyloid (Aβ) peptide, ultimately leading to formation of Aβ plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain β-amyloidosis are reductions in CSF Aβ 42 and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Aβ biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.
3,953 citations
Mayo Clinic1, University College London2, University of California, Los Angeles3, Arizona State University4, University of California, Davis5, University of California, San Diego6, Boston University7, University of California, San Francisco8, Siemens9, General Electric10, Philips11, Johns Hopkins University12, Stanford University13, University of Virginia14
TL;DR: The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom‐based monitoring of all scanners could be used as a model for other multisite trials.
Abstract: Dementia, one of the most feared associates of increasing longevity, represents a pressing public health problem and major research priority. Alzheimer's disease (AD) is the most common form of dementia, affecting many millions around the world. There is currently no cure for AD, but large numbers of novel compounds are currently under development that have the potential to modify the course of the disease and slow its progression. There is a pressing need for imaging biomarkers to improve understanding of the disease and to assess the efficacy of these proposed treatments. Structural magnetic resonance imaging (MRI) has already been shown to be sensitive to presymptomatic disease (1-10) and has the potential to provide such a biomarker. For use in large-scale multicenter studies, however, standardized methods that produce stable results across scanners and over time are needed.
The Alzheimer's Disease Neuroimaging Initiative (ADNI) study is a longitudinal multisite observational study of elderly individuals with normal cognition, mild cognitive impairment (MCI), or AD (11,12). It is jointly funded by the National Institutes of Health (NIH) and industry via the Foundation for the NIH. The study will assess how well information (alone or in combination) obtained from MRI, (18F)-fludeoyglucose positron emission tomography (FDG PET), urine, serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical and neuropsychometric assessments, can measure disease progression in the three groups of elderly subjects mentioned above. At the 55 participating sites in North America, imaging, clinical, and biologic samples will be collected at multiple time points in 200 elderly cognitively normal, 400 MCI, and 200 AD subjects. All subjects will be scanned with 1.5 T MRI at each time point, and half of these will also be scanned with FDG PET. Subjects not assigned to the PET arm of the study will be eligible for 3 T MRI scanning. The goal is to acquire both 1.5 T and 3 T MRI studies at multiple time points in 25% of the subjects who do not undergo PET scanning [R2C1]. CSF collection at both baseline and 12 months is targeted for 50% of the subjects. Sampling varies by clinical group. Healthy elderly controls will be sampled at 0, 6, 12, 24, and 36 months. Subjects with MCI will be sampled at 0, 6, 12, 18, 24, and 36 months. AD subjects will be sampled at 0, 6, 12, and 24 months.
Major goals of the ADNI study are: to link all of these data at each time point and make this repository available to the general scientific community; to develop technical standards for imaging in longitudinal studies; to determine the optimum methods for acquiring and analyzing images; to validate imaging and biomarker data by correlating these with concurrent psychometric and clinical assessments; and to improve methods for clinical trials in MCI and AD. The ADNI study overall is divided into cores, with each core managing ADNI-related activities within its sphere of expertise: clinical, informatics, biostatistics, biomarkers, and imaging. The purpose of this report is to describe the MRI methods and decision-making process underlying the selection of the MRI protocol employed in the ADNI study.
3,611 citations
TL;DR: Develop a cerebrospinal fluid biomarker signature for mild Alzheimer's disease (AD) in Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects.
Abstract: If the clinical diagnosis of probable AD is imprecise with accuracy rates of approximately 90% or lower using established consensus criteria for probable AD, but definite AD requires autopsy confirmation, it is not surprising that diagnostic accuracy is lower at early and presymptomatic stages of AD.1–4 It is believed that the development of full-blown AD takes place over an approximately 20-year prodromal period, but this is difficult to determine in the absence of biomarkers that reliably signal the onset of nascent disease before the emergence of measurable cognitive impairments. Because intervention with disease-modifying therapies for AD is likely to be most efficacious before significant neurodegeneration has occurred, there is an urgent need for biomarker-based tests that enable a more accurate and early diagnosis of AD.5–7 Moreover, such tests could also improve monitoring AD progression, evaluation of new AD therapies, and enrichment of AD cohorts with specific subsets of AD subjects in clinical trials.
The defining lesions of AD are neurofibrillary tangles and senile plaques formed, respectively, by neuronal accumulations of abnormal hyperphosphorylated tau filaments and extracellular deposits of amyloid β (Aβ) fibrils, mostly the 1 to 42 peptide (Aβ1-42), the least soluble of the known Aβ peptides produced from Aβ precursor protein by the action of various peptidases.1–3 Hence, for these and other reasons summarized in consensus reports on AD biomarkers, cerebrospinal fluid (CSF), total tau (t-tau), and Aβ were identified as being among the most promising and informative AD biomarkers.5,6 Increased levels of tau in CSF are thought to occur after its release from damaged and dying neurons that harbor dystrophic tau neurites and tangles, whereas reduced CSF levels of Aβ1-42 are believed to result from large-scale accumulation of this least soluble of Aβ peptides into insoluble plaques in the AD brain. The combination of increased CSF concentrations of t-tau and phosphotau (p-tau) species and decreased concentrations of Aβ1-42 are considered to be a pathological CSF biomarker signature that is diagnostic for AD.5,6,8,9 Notably, recent studies have provided compelling preliminary data to suggest that this combination of CSF tau and Aβ biomarker changes may predict the conversion to AD in mild cognitive impairment (MCI) subjects.10 Thus, an increase in levels of CSF tau associated with a decline in levels of CSF Aβ1-42 may herald the onset of AD before it becomes clinically manifest.
However, before the utility of CSF Aβ1-42 and tau concentrations for diagnosis of AD can be established, it is critical to standardize the methodology for their measurement.5–8,10 For example, among the published studies of CSF tau and Aβ, there is considerable variability in the observed levels of these analytes, as well as their diagnostic sensitivity and specificity. This is attributable to variability in analytical methodology standardization and other factors that differ between studies of the same CSF analytes in similar but not identical cohorts.5–7
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) was launched in 2004 to address these and other limitations in AD biomarkers (see reviews in Shaw and colleagues7 and Mueller and coauthors,11 and the ADNI Web site [http://www.adni-info.org/index] where the ADNI grant and all ADNI data are posted for public access). To this end, the Biomarker Core of ADNI conducts studies on ADNI-derived CSF samples to measure CSF Aβ1-42, t-tau, and p-tau (tau phosphorylated at threonine181 [p-tau181p]) in standardized assays. Evaluation of CSF obtained at baseline evaluation of 416 of the 819 ADNI subjects is now complete, and we report here our findings on the performance of these tests using a standardized multiplex immunoassay system that measures the biomarkers simultaneously in the same sample aliquot in ADNI subjects and in an independent cohort of autopsy-confirmed AD cases.
1,912 citations