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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University of California, San Francisco1, Veterans Health Administration2, United States Department of Veterans Affairs3, University of California, San Diego4, University of California, Davis5, Washington University in St. Louis6, Brigham and Women's Hospital7, Mayo Clinic8, Helen Wills Neuroscience Institute9, Janssen Pharmaceutica10, Indiana University11, University of Pennsylvania12, Foundation for the National Institutes of Health13, Bristol-Myers Squibb14, University of California, Los Angeles15
TL;DR: The major accomplishments of ADNI have been the development of standardized methods for clinical tests, magnetic resonance imaging, positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting, and the improvement of clinical trial efficiency.
Abstract: The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.
906 citations
Cites background from "Predicting MCI outcome with clinica..."
...While the above papers developed a range of automatic multi-modal methods of the prediction of disease progression, Heister et al [295] asked whether MCI to AD conversion can be predicted using clinically available biomarker systems (commercially available software for fully automated volumetric MRI and commercial CSF analysis)....
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TL;DR: This study provides Class II evidence that for patients with AD resveratrol is safe, well-tolerated, and alters some AD biomarker trajectories.
Abstract: Objective: A randomized, placebo-controlled, double-blind, multicenter 52-week phase 2 trial of resveratrol in individuals with mild to moderate Alzheimer disease (AD) examined its safety and tolerability and effects on biomarker (plasma Ab40 and Ab42, CSF Ab40, Ab42, tau, and phospho-tau 181) and volumetric MRI outcomes (primary outcomes) and clinical outcomes (secondary outcomes). Methods: Participants (n 5 119) were randomized to placebo or resveratrol 500 mg orally once daily (with dose escalation by 500-mg increments every 13 weeks, ending with 1,000 mg twice daily). Brain MRI and CSF collection were performed at baseline and after completion of treatment. Detailed pharmacokinetics were performed on a subset (n 5 15) at baseline and weeks 13, 26, 39, and 52. Results: Resveratrol and its major metabolites were measurable in plasma and CSF. The most common adverse events were nausea, diarrhea, and weight loss. CSF Ab40 and plasma Ab40 levels declined more in the placebo group than the resveratrol-treated group, resulting in a significant difference at week 52. Brain volume loss was increased by resveratrol treatment compared to placebo. Conclusions: Resveratrol was safe and well-tolerated. Resveratrol and its major metabolites penetrated the blood–brain barrier to have CNS effects. Further studies are required to interpret the biomarker changes associated with resveratrol treatment. Classification of evidence: This study provides Class II evidence that for patients with AD resveratrol is safe, well-tolerated, and alters some AD biomarker trajectories. The study is rated Class II because more than 2 primary outcomes were designated. Neurology® 2015;85:1–9 GLOSSARY 3G-RES 5 3-O-glucuronidated-resveratrol; 4G-RES 5 4-O-glucuronidated-resveratrol; AD 5 Alzheimer disease; ADAScog 5 Alzheimer’s Disease Assessment Scale–cognitive; ADCS 5 Alzheimer’s Disease Cooperative Study; ADCS-ADL 5 Alzheimer’s Disease Cooperative Study Activities of Daily Living Scale; AE 5 adverse event; BMI 5 body mass index; CDRSOB 5 Clinical Dementia Rating-sum of boxes; Cmax 5 maximal plasma concentration; DMSO 5 dimethyl sulfoxide; ITT 5 intention-to-treat; MMRM 5 mixed-model repeated-measures; MMSE 5 Mini-Mental State Examination; NPI 5 Neuropsychiatric Inventory; S-RES 5 3-sulfated-resveratrol; SAE 5 serious adverse event.
468 citations
TL;DR: The extent of innate immune gene upregulation in AD was modest relative to the robust response apparent in the aged brain, consistent with the emerging idea of a critical involvement of inflammation in the earliest stages, perhaps even in the preclinical stage, of AD.
Abstract: Background
This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD).
399 citations
Cites result from "Predicting MCI outcome with clinica..."
...Aβ is likely to be both an initiating trigger and chronic driver of innate immune activation [111], consistent with growing data suggesting that MCI cases with high Aβ are at increased probability for converting to AD [112]....
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TL;DR: A lineage of work beginning with Alzheimer’s own writings and drawings is reviewed, then jump to the modern era beginning in the 1970s and early 1980s and a sampling of neuropsychological and other contextual work from each ensuing decade is provided.
Abstract: Although dementia has been described in ancient texts over many centuries (e.g., "Be kind to your father, even if his mind fail him." - Old Testament: Sirach 3:12), our knowledge of its underlying causes is little more than a century old. Alzheimer published his now famous case study only 110 years ago, and our modern understanding of the disease that bears his name, and its neuropsychological consequences, really only began to accelerate in the 1980s. Since then we have witnessed an explosion of basic and translational research into the causes, characterizations, and possible treatments for Alzheimer's disease (AD) and other dementias. We review this lineage of work beginning with Alzheimer's own writings and drawings, then jump to the modern era beginning in the 1970s and early 1980s and provide a sampling of neuropsychological and other contextual work from each ensuing decade. During the 1980s our field began its foundational studies of profiling the neuropsychological deficits associated with AD and its differentiation from other dementias (e.g., cortical vs. subcortical dementias). The 1990s continued these efforts and began to identify the specific cognitive mechanisms affected by various neuropathologic substrates. The 2000s ushered in a focus on the study of prodromal stages of neurodegenerative disease before the full-blown dementia syndrome (i.e., mild cognitive impairment). The current decade has seen the rise of imaging and other biomarkers to characterize preclinical disease before the development of significant cognitive decline. Finally, we suggest future directions and predictions for dementia-related research and potential therapeutic interventions. (JINS, 2017, 23, 818-831).
354 citations
United States Department of Veterans Affairs1, University of California, San Diego2, University of California, Davis3, Washington University in St. Louis4, Biogen Idec5, Brigham and Women's Hospital6, Mayo Clinic7, Helen Wills Neuroscience Institute8, Eisai9, Indiana University10, University of Pennsylvania11, Eli Lilly and Company12, University of Southern California13
TL;DR: The major accomplishments of ADNI have been the development of standardized methods for clinical tests, magnetic resonance imaging, positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting, and the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes.
Abstract: The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [ 18 F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU , and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.
249 citations
Cites background from "Predicting MCI outcome with clinica..."
...While the above papers developed a range of automatic multi-modal methods of the prediction of disease progression, Heister et al [295] asked whether MCI to AD conversion can be predicted using clinically available biomarker systems (commercially available software for fully automated volumetric MRI and commercial CSF analysis)....
[...]
References
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TL;DR: Exploratory analysis of the vMRI subgroup suggests that tramiprosate slows hippocampal atrophy, and reveals some evidence of a beneficial effect on cognition, and the clinical validity of thevMRI biomarker is discussed.
Abstract: The efficacy, safety and disease-modification of tramiprosate (homotaurine)were investigated in a recently completed large-scale Phase III clinical study in patients with mild to moderate Alzheimer’s disease (AD), the Alphase study. Disease-modification was assessed using longitudinal volumetric MRI (vMRI) measurements of the hippocampus in a subgroup of patients. The present study describes the vMRI, cognitive and clinical results obtained in this subgroup. Multi-center, double-blind, randomized, placebocontrolled study in a subset of the 1052 patients of the Alphase study. 51 vMRI investigative sites in the United States and Canada. A total of 508 patients underwent vMRI scanning. Of these, 312 provided scan pairs for assessing hippocampus volume changes and were included in the analyses. Patients were randomized to receive Placebo BID (n = 109), tramiprosate 100 mg BID (n = 103), or tramiprosate 150 mg BID (n = 100) for 78 weeks. Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog) and Clinical Dementia Rating-Sum-of-boxes CDR-SB assessments were conducted at Baseline and at Weeks 13, 26, 39, 52, 65 and 78. Exploratory analyses were performed using similar First and Final mixed-effects repeated-measures models that were used for the analysis of the entire patient dataset. Psychometric score results showed numerical trends in favour of tramiprosate that did not reach statistical significance. While there were no statistically significant group differences in hippocampus volume using the First modeling approach, a significant dose-response reduction in hippocampus volume change was found in the Final models. Moreover, there was a marginally significant overall treatment main effect and a significant slope difference in favour of tramiprosate according to the Final model analysis of the ADAS-cog scores. ADAS-cog scores analyzed according to this model also revealed differences in favor of the tramiprosate 150 mg group at weeks 26 and 52, with marginally significant differences at Weeks 13 and 39. Slope analyses of ADAS-cog score changes showed significant differences in favor of the 150 mg BID group, and when both active groups were combined, in comparison to the placebo group. No between-group differences with respect to changes to each visit in the CDR-SB were observed with either modeling approach. Although there was a similar dose-response relationship observed in the hippocampus volume and ADAS-cog Final model analyses, the overall changes in psychometric scores and hippocampus volume were not significantly correlated. Exploratory analysis of the vMRI subgroup suggests that tramiprosate slows hippocampal atrophy, and reveals some evidence of a beneficial effect on cognition. The clinical validity of the vMRI biomarker is discussed.
125 citations
TL;DR: New, fully-automated measures of brain structure volumes coupled with large, multi-center studies using standardized MRI protocols now allow the development of age-adjusted normative ranges for vMRI, critical for providing physicians a framework for assessing the pattern and degree of regional atrophy in a patient's brain and applying vMRI in clinical practice.
Abstract: Neurodegenerative disorders, such as Alzheimer’s disease (AD), are associated with characteristic patterns of neuropathological spread in the brain. Disease progression is usually accompanied by regional atrophy that can be detected noninvasively using structural magnetic resonance imaging (MRI). A wealth of data has demonstrated the value of quantitative measurements of regional atrophy in AD, suggesting that volumetric MRI (vMRI) may be a useful clinical tool. vMRI provides biological evidence of neurodegenerative disease in patients with cognitive impairment. However, several hurdles impede implementation of vMRI in clinical practice. These include a lack of standardized MRI acquisition protocols, spatial distortions in MRI data, labor-intensive vMRI methods susceptible to interoperator variability, a lack of normative ranges for volume measures, and difficulty integrating vMRI in clinical workflow. Advances in vMRI have resulted from multi-institutional studies of brain imaging, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and help address these challenges. New, fully-automated measures of brain structure volumes coupled with large, multi-center studies using standardized MRI protocols now allow the development of age-adjusted normative ranges for vMRI. Such advances are critical for providing physicians a framework for assessing the pattern and degree of regional atrophy in a patient's brain and applying vMRI in clinical practice.
113 citations
TL;DR: Fully automated and rapid measurement of segmental MTL volumes may help clinicians predict clinical decline in MCI patients.
Abstract: Medial temporal lobe (MTL) atrophy is associated with increased risk for conversion to Alzheimer disease, but manual tracing techniques and even semiautomated techniques for volumetric assessment are not practical in the clinical setting. In addition, most studies that examined MTL atrophy in Alzheimer disease have focused only on the hippocampus. It is unknown the extent to which volumes of amygdala and temporal horn of the lateral ventricle predict subsequent clinical decline. This study examined whether measures of hippocampus, amygdala, and temporal horn volume predict clinical decline over the following 6-month period in patients with mild cognitive impairment (MCI). Fully automated volume measurements were performed in 269 MCI patients. Baseline volumes of the hippocampus, amygdala, and temporal horn were evaluated as predictors of change in Mini-mental State Examination and Clinical Dementia Rating Sum of Boxes over a 6-month interval. Fully automated measurements of baseline hippocampus and amygdala volumes correlated with baseline delayed recall scores. Patients with smaller baseline volumes of the hippocampus and amygdala or larger baseline volumes of the temporal horn had more rapid subsequent clinical decline on Mini-mental State Examination and Clinical Dementia Rating Sum of Boxes. Fully automated and rapid measurement of segmental MTL volumes may help clinicians predict clinical decline in MCI patients.
110 citations
TL;DR: A constant conversion factor cannot be used successfully to recalculate results obtained with xMAP assays to those from the ELISAs, however, differentiation of clinical groups is equivalent when either xMAP technology or conventional ELISA is used.
Abstract: Background: Cerebrospinal fluid (CSF) concentrations of amyloid β42 (Aβ42) peptides and tau proteins may serve as biomarkers for Alzheimer disease (AD). Recently, the xMAP technology has been introduced as an alternative to ELISA for measurement of these markers.
Methods: We used xMAP assays and ELISA to analyze CSF concentrations of Aβ42, total tau (t-tau), and tau phosphorylated at threonine 181 (p-tau181) in samples from 69 patients with Alzheimer disease, 26 patients with vascular dementia, and 55 controls without neurological disorders.
Results: High CV values (>28%) for the ratio of xMAP:ELISA were observed for each biomarker, indicating that a constant correction factor cannot be applied to recalculate xMAP results into ELISA results. When a combination of CSF markers was used, the sensitivity, specificity, and area under the ROC curves for xMAP assays and ELISAs were not significantly different in differentiating AD patients from vascular dementia patients and controls.
Conclusions: A constant conversion factor cannot be used successfully to recalculate results obtained with xMAP assays to those from the ELISAs. With the use of analysis of a combination of Aβ42, t-tau, and p-tau in CSF, however, differentiation of clinical groups is equivalent when either xMAP technology or conventional ELISA is used.
71 citations
TL;DR: For example, this paper showed that quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical Alzheimer's disease and is predictive of decline to dementia in individuals with mild cognitive impairment.
Abstract: Alzheimer’s disease (AD) is a common progressive neurodegenerative disorder that is not currently diagnosed until a patient reaches the stage of dementia. There is a pressing need to identify AD at an earlier stage, so that treatment, when available, can begin early. Quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical AD, and is predictive of decline to dementia in individuals with mild cognitive impairment. Objective evidence of ongoing brain atrophy will be critical for risk/benefit decisions once potentially aggressive, disease-modifying treatments become available. Recent advances have paved the way for the use of quantitative structural MRI in clinical practice, and initial clinical use has been promising. However, further experience with these measures in the relatively unselected patient populations seen in clinical practice is needed to complete translation of the recent enormous advances in scientific knowledge of AD into the clinical realm.
64 citations