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Journal ArticleDOI

Predicting MCI outcome with clinically available MRI and CSF biomarkers

25 Oct 2011-Neurology (American Academy of Neurology)-Vol. 77, Iss: 17, pp 1619-1628
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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Journal ArticleDOI
TL;DR: In this article , the authors show how the method of reflective equilibrium (RE) can be used to systematically weigh the relevant arguments on both sides of the debate to decide whether to offer Alzheimer biomarker testing.
Abstract: An increasing number of people seek medical attention for mild cognitive symptoms at older age, worried that they might develop Alzheimer's disease. Some clinical practice guidelines suggest offering biomarker testing in such cases, using a brain scan or a lumbar puncture, to improve diagnostic certainty about Alzheimer's disease and enable an earlier diagnosis. Critics, on the other hand, point out that there is no effective Alzheimer treatment available and argue that biomarker tests lack clinical validity. The debate on the ethical desirability of biomarker testing is currently polarized; advocates and opponents tend to focus on their own line of arguments. In this paper, we show how the method of reflective equilibrium (RE) can be used to systematically weigh the relevant arguments on both sides of the debate to decide whether to offer Alzheimer biomarker testing. In the tradition of RE, we reflect upon these arguments in light of their coherence with other argumentative elements, including relevant facts (e.g. on the clinical validity of the test), ethical principles, and theories on societal ideals or relevant concepts, such as autonomy. Our stance in the debate therefore rests upon previously set out in-depth arguments and reflects a wide societal perspective.

3 citations

Journal ArticleDOI
TL;DR: This updated version of a previous review concludes that NeuroQuant® and NeuroGage® meet the Daubert standard based on their reliability, validity, and objectivity.
Abstract: Over 40 years of research have shown that traumatic brain injury affects brain volume. However, technical and practical limitations made it difficult to detect brain volume abnormalities in patients suffering from chronic effects of mild or moderate traumatic brain injury. This situation improved in 2006 with the FDA clearance of NeuroQuant®, a commercially available, computer-automated software program for measuring MRI brain volume in human subjects. More recent strides were made with the introduction of NeuroGage®, commercially available software that is based on NeuroQuant® and extends its utility in several ways. Studies using these and similar methods have found that most patients with chronic mild or moderate traumatic brain injury have brain volume abnormalities, and several of these studies found—surprisingly—more abnormal enlargement than atrophy. More generally, 102 peer-reviewed studies have supported the reliability and validity of NeuroQuant® and NeuroGage®. Furthermore, this updated version of a previous review addresses whether NeuroQuant® and NeuroGage® meet the Daubert standard for admissibility in court. It concludes that NeuroQuant® and NeuroGage® meet the Daubert standard based on their reliability, validity, and objectivity. Due to the improvements in technology over the years, these brain volumetric techniques are practical and readily available for clinical or forensic use, and thus they are important tools for detecting signs of brain injury.

3 citations

Posted ContentDOI
11 Aug 2019-bioRxiv
TL;DR: A model is developed that predicts the onset of dementia over an eight-year time window in individuals with genetics data and a T1-weighted MRI who were dementia-free at baseline and was validated in an independent multisite cohort.
Abstract: SUMMARY Background Alzheimer’s disease is a major health problem, affecting ~4⋅5% of people aged 60 and older in 2016 with over 43 million affected globally1. The traditional approach for detection evaluates an individual in the presence of symptoms. However, it has been established that amyloid deposits begin to accumulate years before symptoms begin to appear2,3. With improved technology, there is increased focus on risk reduction, timely diagnosis, and early intervention. Early identification of at-risk individuals may enable patients and their families to better prepare for and reduce the impact of this condition. Methods We obtained data for patients from two longitudinal retrospective cohorts (Alzheimer’s Disease Neuroimaging Initiative: ADNI and National Alzheimer’s Coordinating Center: NACC), including T1-weighted MRI and genetics data. The polygenic risk score (PRS) used in this study was built based on a published Genome Wide Association Study (GWAS) that identified variants associated with Alzheimer’s disease. Quantitative MRI features were obtained using a 3D U-Net neural network for brain segmentation. Cox proportional hazards (CPH) regression models were used with subjects censored at death or the last evaluation. Time-to-event was defined as the time it takes for an individual who is dementia-free at the baseline MRI to progress to dementia as defined by the criteria described by ADNI. Time-dependent ROC areas under curve (AUCs) were estimated in the presence of censored data. The time-dependent AUCs were compared among models using the Wilcoxon rank sum test for dependent samples. Data was binned into three groups according to survival probability to eight years after baseline and Kaplan-Meier survival analysis was used to estimate the probability of surviving at least to time t. Calibration for both training and validation cohorts was evaluated using the predicted survival probability, splitting samples into five risk groups of equal size based on the predicted survival probability. Findings We developed a model that predicts the onset of dementia over an eight-year time window in individuals with genetics data and a T1-weighted MRI who were dementia-free at baseline. We then validated the model in an independent multisite cohort. We observed that models using PRS in addition to MRI-derived features performed significantly better as measured by time-varying AUC up to eight years in both the training (p = 0⋅0071) and validation (p = 0⋅050) cohorts. We observed improved performance of the two modalities versus MRI alone when compared with more invasive amyloid measures. The combined MRI and PRS model showed equivalent performance to cerebral spinal fluid (CSF) amyloid measurement up to eight years prior to disease onset (p = 0⋅181) and while the MRI only model performed worse (p = 0⋅040). Finally, we compared to amyloid positron emission tomography (PET) three to four years prior to disease onset with favorable results. Interpretation Our finding suggests that the two modalities are complementary measures, in that MRI reflects near-term decline and the addition of genetics extends the prediction scope of quantitative MRI by adding additional long-term predictive power. The proposed multimodal model shows potential as an alternate solution for early risk assessment given the concordance with CSF amyloid and amyloid PET. Future work will include further comparison with amyloid PET (greater than four years) and with CSF (greater than eight years) as additional long-term data becomes available. Also, the model will be evaluated for its clinical utility in the “active surveillance” of individuals who may be concerned about their risk of developing dementia but are not yet eligible for assessment by amyloid PET or CSF. RESEARCH IN CONTEXT Evidence before this study The most significant known genetic factor in Alzheimer’s disease (AD) is the e4 allele for the Apolipoprotein E (APOE) gene. Carriers of the allele have a three-fold increased risk of developing AD, whereas individuals who are homozygous have a 15-fold increased risk. Genome-wide association studies (GWASs) have identified many additional genetic variants that are associated with AD. Recent studies have shown that the risk for AD is better predicted by combining effects from several genetic variants into “polygenic risk scores” (PRS). Studies have also demonstrated that the age of onset for AD is better predicted using PRS rather than APOE status alone. Regional brain atrophy, as measured using volumetric MRI, is also an important biomarker for evaluating an individual’s risk of developing dementia. Previous predictions have shown that medial temporal lobe atrophy, as measured by a Hippocampal Occupancy Score (HOC) is highly associated with progression from MCI to AD. Added value of this study In the proposed model, the addition of genetics to MRI data lengthens the time over which the model can predict onset of dementia. The two measures appear to be complementary, with MRI showing near-term decline and genetics providing additional predictive power in the long-term. When compared to more invasive measures of amyloid, which have been shown to have long-term predictive power, we observed equivalent performance to CSF amyloid up to 8 years prior to disease onset and equivalent performance to amyloid PET three to four years prior to disease onset. Implications of all the available evidence Although MRI remains relatively expensive, it is less expensive, less invasive, more accessible, and more commonly available than amyloid PET. Furthermore, MRI is already part of standard clinical practice and this model may be applied to standard clinical MRIs with no additional acquisition required. A recent survey of patients and their caregivers has highlighted a desire for access to better diagnostics, such as amyloid PET, to aid them in long-term legal, financial and healthcare planning. Our model, given the concordance with CSF and amyloid PET could be an alternate solution to fulfill this need. Furthermore, our model could facilitate the “active surveillance” of individuals who are high-risk and thereby enhance the possibility of early intervention.

3 citations

Proceedings ArticleDOI
22 Oct 2022
TL;DR: The results indicate that a conversational “check-in” medication management assistant increased system acceptance while also potentially decreasing the likelihood of accidental over-medication, a common concern for older adults dealing with MCI.
Abstract: Improving medication management for older adults with Mild Cognitive Impairment (MCI) requires designing systems that support functional independence and provide compensatory strategies as their abilities change. Traditional medication management interventions emphasize forming new habits alongside the traditional path of learning to use new technologies. In this study, we navigate designing for older adults with gradual cognitive decline by creating a conversational “check-in” system for routine medication management. We present the design of MATCHA - Medication Action To Check-In for Health Application, informed by exploratory focus groups and design sessions conducted with older adults with MCI and their caregivers, alongside our evaluation based on a two-phased deployment period of 20 weeks. Our results indicate that a conversational “check-in” medication management assistant increased system acceptance while also potentially decreasing the likelihood of accidental over-medication, a common concern for older adults dealing with MCI.

2 citations

Posted ContentDOI
07 Jan 2019-bioRxiv
TL;DR: Cerebrospinal fluid levels of a peptide derived from a neural protein involved in synaptic transmission, VGF, are examined to enhance accuracy of prediction of conversion from mild cognitive impairment to Alzheimer’s Disease and suggest that VGF may serve as a more general marker of neurodegeneration.
Abstract: Sensitive and accurate biomarkers for the prediction of conversion from mild cognitive impairment (MCI) to Alzheimer’s Disease (AD) are needed to both support clinical care and enhance clinical trial design. Here, we examined the potential of cerebrospinal fluid (CSF) levels of a peptide derived from a neural protein involved in synaptic transmission, VGF (a non-initialism), to enhance accuracy of prediction of conversion from MCI to AD. The performance of conventional biomarkers (CSF Aβ1-42 and phosphorylated tau +/− hippocampal volume) was compared to the same biomarkers with CSF VGF peptide levels. It was observed that VGF peptides are lowered in patients with AD compared to 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). VGF peptide levels were correlated most strongly with total tau levels, but not hippocampal volume, suggesting that they serve as a marker for neuronal degradation, but not necessarily in the hippocampus. The latter point suggests that VGF may serve as a more general marker of neurodegeneration. Future work will be needed to determine the specificity of VGF for AD vs. other neurodegenerative diseases.

2 citations


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References
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

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