Neuroimaging biomarkers for clinical trials of disease-modifying therapies in Alzheimer’s disease

Department of Neurology and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA.
NeuroRx 05/2005; 2(2):348-60. DOI: 10.1602/neurorx.2.2.348
Source: PubMed


The pathophysiologic process leading to neurodegeneration in Alzheimer's disease (AD) is thought to begin long before clinical symptoms develop. Existing therapeutics for AD improve symptoms, but increasing efforts are being directed toward the development of therapies to impede the pathologic progression of the disease. Although these medications must ultimately demonstrate efficacy in slowing clinical decline, there is a critical need for biomarkers that will indicate whether a candidate disease-modifying therapeutic agent is actually altering the underlying degenerative process. A number of in vivo neuroimaging techniques, which can reliably and noninvasively assess aspects of neuroanatomy, chemistry, physiology, and pathology, hold promise as biomarkers. These neuroimaging measures appear to relate closely to neuropathological and clinical data, such as rate of cognitive decline and risk of future decline. As this work has matured, it has become clear that neuroimaging measures may serve a variety of potential roles in clinical trials of candidate neurotherapeutic agents for AD, depending in part on the question of interest and phase of drug development. In this article, we review data related to the range of neuroimaging biomarkers of Alzheimer's disease and consider potential applications of these techniques to clinical trials, particularly with respect to the monitoring of disease progression in trials of disease-modifying therapies.

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Available from: Bradford Dickerson, Dec 13, 2013
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    • "All these measures can detect accelerated brain changes in the preclinical disease stages, before symptoms appear. High-resolution structural MRI is now commonly included in AD drug trials to monitor potential side effects (e.g., microhemorrhage and vasogenic edema) and to track brain atrophyda macroscopic reflection of neuronal death, myelin reduction, and cellular atrophy (Chertkow and Black, 2007; Dickerson and Sperling, 2005; Fleisher et al., 2009; Jack et al., 2003; Salloway et al., 2014). Numerous MRIderived biomarkers have been developed and tested (Baron et al., 2001; Carmichael et al., 2006; Chetelat et al., 2002; Chou et al., 2009; Fox et al., 2001; Freeborough and Fox, 1997; Holland et al., 2009; Hua et al., 2013; Jack et al., 1999; Morra et al., 2009; Reuter et al., 2012; Schuff et al., 2009; Thompson et al., 2004). "
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    ABSTRACT: The goal of this work was to assess statistical power to detect treatment effects in Alzheimer's disease (AD) clinical trials using magnetic resonance imaging (MRI)-derived brain biomarkers. We used unbiased tensor-based morphometry (TBM) to analyze n = 5,738 scans, from Alzheimer's Disease Neuroimaging Initiative 2 participants scanned with both accelerated and nonaccelerated T1-weighted MRI at 3T. The study cohort included 198 healthy controls, 111 participants with significant memory complaint, 182 with early mild cognitive impairment (EMCI) and 177 late mild cognitive impairment (LMCI), and 155 AD patients, scanned at screening and 3, 6, 12, and 24 months. The statistical power to track brain change in TBM-based imaging biomarkers depends on the interscan interval, disease stage, and methods used to extract numerical summaries. To achieve reasonable sample size estimates for potential clinical trials, the minimal scan interval was 6 months for LMCI and AD and 12 months for EMCI. TBM-based imaging biomarkers were not sensitive to MRI scan acceleration, which gave results comparable with nonaccelerated sequences. ApoE status and baseline amyloid-beta positron emission tomography data improved statistical power. Among healthy, EMCI, and LMCI participants, sample size requirements were significantly lower in the amyloid+/ApoE4+ group than for the amyloid-/ApoE4- group. ApoE4 strongly predicted atrophy rates across brain regions most affected by AD, but the remaining 9 of the top 10 AD risk genes offered no added predictive value in this cohort.
    Neurobiology of aging 11/2015; DOI:10.1016/j.neurobiolaging.2015.09.018 · 5.01 Impact Factor
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    • "Currently for clinical diagnosis of AD, neuroimaging examinations, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), are widely used. Among numerous imaging examination methods, morphological MRI scans are generally used to detect gray matter (GM) abnormalities for the early diagnosis of AD, including atrophy of the whole brain, hippocampal formation, and entorhinal cortex, as well as expansion of the temporal horn in the lateral ventricles [3]. However, there are increasing MRI investigations suggesting that AD patients also present with white matter (WM) abnormalities including WM volume (WMV) deficits and disruption of the integrity of WM pathways [4] [5] [6]. "
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    ABSTRACT: An increasing number of MRI investigations suggest that patients with Alzheimer's disease (AD) show not only gray matter decreases but also white matter (WM) abnormalities, including WM volume (WMV) deficits and integrity disruption of WM pathways. In this study, we applied multimodal voxel-wise meta-analytical methods to study WMV and fractional anisotropy in AD. Fourteen studies including 723 participants (340 with AD and 383 controls) were involved. The meta-analysis was performed using effect size signed differential mapping. Significant WMV reductions were observed in bilateral inferior temporal gyrus, splenium of corpus callosum, right parahippocampal gyrus, and hippocampus. Decreased fractional anisotropy was identified mainly in left posterior limb of internal capsule, left anterior corona radiata, left thalamus, and left caudate nucleus. Significant decreases of both WMV and fractional anisotropy were found in left caudate nucleus, left superior corona radiata, and right inferior temporal gyrus. Most findings showed to be highly replicable in the jackknife sensitivity analyses. In conclusion, AD patients show widespread WM abnormalities mainly in bilateral structures related to advanced mental and nervous activities.
    Journal of Alzheimer's disease: JAD 07/2015; 47(2):495-507. DOI:10.3233/JAD-150139 · 4.15 Impact Factor
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    • "In the following sections, specific strengths and weaknesses of the current technologies are reviewed. Because of their minimally invasive nature and sensitivity to the earliest changes within the brain substrate, many of the following neuroimaging methods have been promoted as being able to identify " leveraged cohorts " of individuals with an elevated risk of developing clinical AD in the short term [68]. This notion is yet to be realized, but many are hopeful that some of the novel techniques recently developed will provide breakthroughs in AD and other diseases. "
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    ABSTRACT: The increasing number of afflicted individuals with late-onset Alzheimer's disease (AD) poses significant emotional and financial burden on the world's population. Therapeutics designed to treat symptoms or alter the disease course have failed to make an impact, despite substantial investments by governments, pharmaceutical industry, and private donors. These failures in treatment efficacy have led many to believe that symptomatic disease, including both mild cognitive impairment (MCI) and AD, may be refractory to therapeutic intervention. The recent focus on biomarkers for defining the preclinical state of MCI/AD is in the hope of defining a therapeutic window in which the neural substrate remains responsive to treatment. The ability of biomarkers to adequately define the at-risk state may ultimately allow novel or repurposed therapeutic agents to finally achieve the disease-modifying status for AD. In this review, we examine current preclinical AD biomarkers and suggest how to generalize their use going forward.
    Alzheimer's and Dementia 06/2014; 10(3):S196–S212. DOI:10.1016/j.jalz.2014.04.015 · 12.41 Impact Factor
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