Cortical morphology predicts placebo response in multiple sclerosis.

Despite significant insights into the neural mechanisms of acute placebo responses, less is known about longer-term placebo responses, such as those seen in clinical trials, or their interactions with brain disease. We examined brain correlates of placebo responses in a randomized trial of a then controversial and now disproved endovascular treatment for multiple sclerosis. Patients received either balloon or sham extracranial venoplasty and were followed for 48 weeks. Venoplasty had no therapeutic effect, but a subset of both venoplasty- and sham-treated patients reported a transient improvement in health-related quality of life, suggesting a placebo response. Placebo responders did not differ from non-responders in total MRI T2 lesion load, count or location, nor were there differences in normalized brain volume, regional grey or white matter volume or cortical thickness (CT). However, responders had higher lesion activity. Graph theoretical analysis of CT covariance showed that non-responders had a more small-world-like CT architecture. In non-responders, lesion load was inversely associated with CT in somatosensory, motor and association areas, precuneus, and insula, primarily in the right hemisphere. In responders, lesion load was unrelated to CT. The neuropathological process in MS may produce in some a cortical configuration less capable of generating sustained placebo responses.

Monthly At-Home Computerized Cognitive Testing to Detect Diminished Practice Effects in Preclinical Alzheimer's Disease.

Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline. Materials and Methods: N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed >0.10 SD annual decline on the PACC-5. Results: Overall, individuals improved on all C3 measures over 12 months (ß = 0.23, 95% CI [0.21-0.25], p < 0.001), but improvement over the first 3 months was greatest (ß = 0.68, 95% CI [0.59-0.77], p < 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = -0.20, 95% CI [-0.38 - -0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = -0.38, 95% CI [-0.54 - -0.19], p < 0.001) and inferior-temporal lobe (r = -0.23, 95% CI [-0.41 - -0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84-0.98]), which was better than baseline C3 (p < 0.001) and baseline PACC-5 scores (p = 0.02). Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.

Serotonergic System Impacts Levodopa Response in Early Parkinson's and Future Risk of Dyskinesia.

BACKGROUND: The serotonergic system is known to contribute to levodopa-derived dopamine release in advanced Parkinson's disease. OBJECTIVE: We investigated the role of the serotonergic system in determining response to treatment in early disease and risk for complications concurrently with dopaminergic alterations. METHODS: Eighteen patients with early and stable Parkinson's disease underwent multitracer positron emission tomography using [11 C]dihydrotetrabenazine (vesicular monoamine transporter 2 marker), [11 C]methylphenidate (dopamine transporter marker), [11 C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile (DASB, serotonin transporter marker), and [11 C]raclopride (D2 marker) to investigate relationships between striatal dopaminergic and serotonergic alterations and levodopa-induced dopamine release, related to motor response to treatment and risk for dyskinesias, using a novel joint pattern analysis. RESULTS: The joint pattern analysis revealed correlated spatial patterns conceptually related to abnormal dopamine turnover in the putamen (higher dopamine release associated with dopaminergic and serotonergic denervation); response to treatment significantly inversely correlated with turnover-related dopamine release (P < 10-5 ). Patterns identified without inclusion of the DASB data showed no correlation with clinical data, indicating an important contribution from the serotonergic system to a clinically relevant abnormal dopamine release in early disease. Subjects who experienced dyskinesia 3 years after baseline scans showed higher turnover-related dopamine release compared with subjects who remained stable (P < 0.01). CONCLUSIONS: Joint analysis of dopaminergic and serotonergic data identified a turnover-related dopamine release component, strongly related to motor response to levodopa in early disease and contributing to higher risk for dyskinesia. These findings suggest that the contribution of the serotonergic system to dopamine release not only increases the risk for motor complications but also fails to provide sustained therapeutic advantage in early disease. © 2020 International Parkinson and Movement Disorder Society.

Data-driven, voxel-based analysis of brain PET images: Application of PCA and LASSO methods to visualize and quantify patterns of neurodegeneration.

Spatial patterns of radiotracer binding in positron emission tomography (PET) images may convey information related to the disease topology. However, this information is not captured by the standard PET image analysis that quantifies the mean radiotracer uptake within a region of interest (ROI). On the other hand, spatial analyses that use more advanced radiomic features may be difficult to interpret. Here we propose an alternative data-driven, voxel-based approach to spatial pattern analysis in brain PET, which can be easily interpreted. We apply principal component analysis (PCA) to identify voxel covariance patterns, and optimally combine several patterns using the least absolute shrinkage and selection operator (LASSO). The resulting models predict clinical disease metrics from raw voxel values, allowing for inclusion of clinical covariates. The analysis is performed on high-resolution PET images from healthy controls and subjects affected by Parkinson's disease (PD), acquired with a pre-synaptic and a post-synaptic dopaminergic PET tracer. We demonstrate that PCA identifies robust and tracer-specific binding patterns in sub-cortical brain structures; the patterns evolve as a function of disease progression. Principal component LASSO (PC-LASSO) models of clinical disease metrics achieve higher predictive accuracy compared to the mean tracer binding ratio (BR) alone: the cross-validated test mean squared error of adjusted disease duration (motor impairment score) was 16.3 ± 0.17 years2 (9.7 ± 0.15) with mean BR, versus 14.4 ± 0.18 years2 (8.9 ± 0.16) with PC-LASSO. We interpret the best-performing PC-LASSO models in the spatial sense and discuss them with reference to the PD pathology and somatotopic organization of the striatum. PC-LASSO is thus shown to be a useful method to analyze clinically-relevant tracer binding patterns, and to construct interpretable, imaging-based predictive models of clinical metrics.