Disease Progression In Therapeutic Trials Research Articles

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies

IntroductionAlthough the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored. MethodsWe studied 298 patients (AD = 250, DLB = 48; 38 autopsy-confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis. ResultsAcross the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall. DiscussionThese findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease.

D.P.15 Quantitative T2 relaxation times in lower leg of Duchenne and Becker muscular dystrophy patients

Edema can be present in muscles of Duchenne muscular dystrophy (DMD) patients, and is thought to indicate inflammation. It can be quantified using MRI and could be useful as a marker of the disease progression in therapeutic trials. In this study, we compared edema in muscles of DMD patients, Becker muscular dystrophy (BMD) patients, and healthy controls. Edema was assessed in eight lower leg muscles of 19 DMD patients (10±3y, range 5–14y) and nine BMD patients (38±11y, range 26–63y) by measuring the T2 relaxation time using fat suppressed MRI at 3T (multi-echo sequence with seven echo times: 13–91ms). T2 values were obtained using manually drawn ROIs. T2 relaxation times in both DMD (mean 45ms) and BMD (mean 45ms) were higher than in healthy controls. As high fat fractions could still influence T2 relaxation times despite the application of fat suppression, we only included muscles with less than 20% fat (assessed by Dixon MRI) in the final analysis This did not alter the range and showed means of 42ms in DMD and 43ms in BMD. Surprisingly, muscles in DMD and BMD had similar T2 values. The only exception was tibialis anterior (TA) muscle. In patients younger than 10years the T2 relaxation time of this muscle was increased in both DMD (n=8) and BMD patients (50 vs 58ms). In DMD patients above the age of 10 the T2 of the TA was significantly lower than in BMD patients, contrary to what one might expect. These results suggest that edema, as defined by increased T2 relaxation times, is more pronounced in relatively mildly affected muscle tissue, and specifically the TA muscle in BMD patients and DMD patients under 10. Therefore, the use of quantitative T2 for disease evaluation or effects of therapy needs further study before it can be used routinely in trials in DMD patients.

Diffusion tensor imaging and cognition in cerebral small vessel disease: The RUN DMC study

Background Cerebral small vessel disease (SVD) is very common in elderly and related to cognition, although this relation is weak. This might be because the underlying pathology of white matter lesions (WML) is diverse and cannot be properly appreciated with conventional FLAIR MRI. In addition, conventional MRI is not sensitive to early loss of microstructural integrity of the normal appearing white matter (NAWM), which might be an important factor. Diffusion tensor imaging (DTI) provides alternative information on microstructural white matter integrity and we have used this to investigate the relation between white matter integrity, in both WML and NAWM, and cognition among elderly with cerebral SVD. Methods The RUN DMC study is a prospective cohort study among 503 independently living, non-demented elderly with cerebral SVD aged between 50 and 85 years. All subjects underwent MRI and DTI scanning. WML were segmented manually. We measured mean diffusivity (MD) and fractional anisotropy (FA), as assessed by DTI in both WML and NAWM. Results Inverse relations were found between MD in the WML and NAWM and global cognitive function (β = −.11, p < 0.05; β = −.18, p < 0.001), psychomotor speed (β = −.15, p < 0.01; β = −.18, p < 0.001), concept shifting (β = −.11, p < 0.05; β = −.10, p < 0.05) and attention (β = −.12, p < 0.05; β = −.15, p < 0.001). The relation between DTI parameters in both WML and NAWM and cognitive performance was most pronounced in subjects with severe WML. Conclusion DTI parameters in both WML and NAWM correlate with cognitive performance, independent of SVD. DTI may be a promising tool in exploring the mechanisms of cognitive decline and could function as a surrogate marker for disease progression in therapeutic trials. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Possible clinical outcome measures for clinical trials in patients with multiple sclerosis.

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease with both clinical and pathological heterogeneity. The complexity of the MS population has offered challenges to the measurement of MS disease progression in therapeutic trials. The current standard clinical outcome measures are relapse rate, Expanded Disability Severity Scale (EDSS), and the MS Functional Composite (MSFC). These measures each have strengths and some weakness. Two additional measures, the six-minute walk and accelerometry, show promise in augmenting current measures. MS therapeutics is a quickly advancing field which requires sensitive clinical outcome measures that can detect small changes in disability that reliably reflect long-term changes in sustained disease progression in a complex population. A single clinical outcome measure of sustained disease progression may remain elusive. Rather, an integration of current and new outcome measures may be most appropriate and utilization of different measures depending on the MS population and stage of the disease may be preferred.

Thin skin

Three structural MRI techniques have been developed in recent years to study patients with mild cognitive impairment (MCI) and Alzheimer disease (AD): MRI volumetry,1 voxel-based morphometry (VBM),2 and surface-based morphometry (SBM).3 Since patients with amnestic MCI progress to AD at a rate of approximately 12% per year,4 the aim of many of these studies has been to identify quantitative structural measures (e.g., ventricular volume, whole-brain volume, hippocampal/entorhinal cortical volume, cortical thickness) that accurately predict the progression of amnestic MCI to AD and can therefore serve as surrogate markers of disease progression in therapeutic trials.] In this issue of Neurology ®, Bakkour et al.5 describe the use of structural MRI and FreeSurfer-generated estimates of cortical thickness6 to determine 1) if a quantifiable in vivo cortical signature of AD-related thinning is present in patients with questionable dementia (QAD, defined as Clinical Dementia Rating [CDR] = 0.5), 2) if …

A computational method for the estimation of atrophic changes in Alzheimer's disease and mild cognitive impairment

Early diagnosis and objective monitoring of disease progression are essential for the development of therapeutic strategies in Alzheimer's disease (AD). Current techniques are mainly based on semi-objective measures such as neuropsychological tests and a physician's magnetic resonance imaging (MRI) inspection. We have developed a computational method for automatic and unbiased assessment of the brain's state of atrophy from MRI. Sixty-eight high-resolution MRI scans were acquired from 25 AD patients (age: 69.8 ± 7.5), 16 mild cognitive impairment (MCI) patients (67.6 ± 9.1) and 27 control subjects (64.9 ± 8.8). On the basis of the computations we were able to recognize MCI subjects with a sensitivity of 81% and a specificity of 80% in a group of MCIs and controls using a linear classifier. To date, comparable results have only been received by manual labelling or human inspection. Our calculations are light weighted and can be applied on usual workstations in everyday clinical practice. Each step can be understood and applied by the physicians, independent of their computer knowledge. The applied image analysis process produces visual maps of atrophic changes as intermediate steps of the calculations. These can be helpful for the physician during inspection of the brain. The proposed analysis has the potential to improve AD diagnosis and treatment, especially in early its stages, and could also be used to monitor disease progression in therapeutic trials.