Purpose To determine the test-retest reproducibility of neurochemical concentrations obtained with a highly optimized, short-echo, single voxel proton MRS pulse sequence at 3T and 7T using state-of-the-art hardware. Methods A semi-LASER sequence (TE = 26–28ms) was used to acquire spectra from the posterior cingulate and cerebellum at 3T and 7T from 6 healthy volunteers who were scanned weekly 4 times on both scanners. Spectra were quantified with LCModel. Results More neurochemicals were quantified with mean Cramér-Rao lower bounds (CRLB) ≤ 20% at 7T than at 3T despite comparable frequency-domain SNR. While CRLB were lower at 7T (p < 0.05), between-session coefficients of variance (CVs) were comparable at the two fields with 64 transients. Five metabolites were quantified with between-session CVs ≤ 5% at both fields. Analysis of subspectra showed that a minimum achievable CV was reached with a lower number of transients at 7T for multiple metabolites and that between-session CVs were lower at 7T than at 3T with fewer than 64 transients. Conclusion State-of-the-art MRS methodology allows excellent reproducibility for many metabolites with 5 minute data averaging on clinical 3T hardware. Sensitivity and resolution advantages at 7T are important for weakly represented metabolites, short acquisitions and small volumes-of-interest.

Neurochemical abnormalities are detectable in individuals before manifest disease, which may allow premanifest enrollment in future SCA trials. Correlations with ataxia and quality-of-life scores show that neurochemical levels can serve as clinically meaningful endpoints in trials. Ranking of SCA types by degree of neurochemical abnormalities indicates that the neurochemistry may reflect synaptic function or density. Ann Neurol 2018;83:816-829.

BackgroundOral taxa are often found in the chronic obstructive pulmonary disease (COPD) lung microbiota, but it is not clear if this is due to a physiologic process such as aspiration or experimental contamination at the time of specimen collection.MethodsMicrobiota samples were obtained from nine subjects with mild or moderate COPD by swabbing lung tissue and upper airway sites during lung lobectomy. Lung specimens were not contaminated with upper airway taxa since they were obtained surgically. The microbiota were analyzed with 16S rRNA gene qPCR and 16S rRNA gene hypervariable region 3 (V3) sequencing. Data analyses were performed using QIIME, SourceTracker, and R.ResultsStreptococcus was the most common genus in the oral, bronchial, and lung tissue samples, and multiple other taxa were present in both the upper and lower airways. Each subject’s own bronchial and lung tissue microbiota were more similar to each other than were the bronchial and lung tissue microbiota of two different subjects (permutation test, p = 0.0139), indicating more within-subject similarity than between-subject similarity at these two lung sites. Principal coordinate analysis of all subject samples revealed clustering by anatomic sampling site (PERMANOVA, p = 0.001), but not by subject. SourceTracker analysis found that the sources of the lung tissue microbiota were 21.1% (mean) oral microbiota, 8.7% nasal microbiota, and 70.1% unknown. An analysis using the neutral theory of community ecology revealed that the lung tissue microbiota closely reflects the bronchial, oral, and nasal microbiota (immigration parameter estimates 0.69, 0.62, and 0.74, respectively), with some evidence of ecologic drift occurring in the lung tissue.ConclusionThis is the first study to evaluate the mild-moderate COPD lung tissue microbiota without potential for upper airway contamination of the lung samples. In our small study of subjects with COPD, we found oral and nasal bacteria in the lung tissue microbiota, confirming that aspiration is a source of the COPD lung microbiota.

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Background Spinocerebellar ataxia type 1 (SCA1) causes progressive degeneration of the cerebellum and brainstem. Volumetric magnetic resonance imaging (MRI) was shown to be more sensitive to disease progression than the most sensitive clinical measure, the Scale for the Assessment and Rating of Ataxia (SARA), in longitudinal studies, and magnetic resonance spectroscopy (MRS) was shown to detect neurochemical abnormalities with high sensitivity cross‐sectionally in SCA1. Objectives The objectives of this study were to compare the sensitivities to change of volumetric MRI, MRS, and SARA in a 3‐year longitudinal study in SCA1. Methods A total of 16 early‐to‐moderate stage patients with SCA1 (SARA 0‐14) and 21 matched healthy participants were scanned up to 3 times with 1.5‐year intervals. Ataxia severity was assessed with SARA. T1‐weighted images and magnetic resonance spectra from the cerebellar vermis, cerebellar white matter, and pons were acquired at 3T. Results The pontine total N‐acetylaspartate‐to‐myo‐inositol ratio was the most sensitive MRS measure to change (−3.9 ± 4.6%/yr in SCA1 vs. −0.3 ± 3.5%/yr in controls; P < 0.02), and the pontine volume was the most sensitive MRI measure to change (−2.6 ± 1.2%/yr in SCA1 vs. −0.1 ± 1.2 in controls; P < 0.02). Effect size (mean percent change/standard deviation of percent change) of pontine volume was highest (−2.13) followed by pontine N‐acetylaspartate‐to‐myo‐inositol ratio (−0.84) and SARA (+0.60). The pontine N‐acetylaspartate‐to‐myo‐inositol ratio was abnormal for 1 premanifest patient at all visits and predicted study withdrawal as a result of disease progression in 3 patients. Conclusion Both MRI and MRS were more sensitive to disease progression than SARA in SCA1. Pontine volume was most sensitive to change, whereas MRS may have more sensitivity at the premanifest stage and predictive value for disease progression.

For clinical trials with time-to-event as the primary endpoint, the clinical cutoff is often event-driven and the log-rank test is the most commonly used statistical method for evaluating treatment effect. However, this method relies on the proportional hazards assumption in that it has the maximal power in this circumstance. In certain disease areas or populations, some patients can be curable and never experience the events despite a long follow-up. The event accumulation may dry out after a certain period of follow-up and the treatment effect could be reflected as the combination of improvement of cure rate and the delay of events for those uncurable patients. Study power depends on both cure rate improvement and hazard reduction. In this paper, we illustrate these practical issues using simulation studies and explore sample size recommendations, alternative ways for clinical cutoffs, and efficient testing methods with the highest study power possible.

High-dimensional linear classifiers, such as distance weighted discrimination (DWD) and versions of the support vector machine (SVM), are commonly used in biomedical research to distinguish groups of subjects based on a large number of features. However, their use is limited to applications where a single vector of features is measured for each subject. In practice, data are often multi-way, or measured over multiple dimensions. For example, metabolite abundance may be measured over multiple regions or tissues, or gene expression may be measured over multiple time points, for the same subjects. We propose a framework for linear classification of high-dimensional multi-way data, in which coefficients can be factorized into weights that are specific to each dimension. More generally, the coefficients for each measurement in a multi-way dataset are assumed to have low-rank structure. This framework extends existing classification techniques from single vector to multi-way features, and we have implemented multi-way versions of SVM and DWD. We describe informative simulation results, and apply multi-way DWD to data for two very different clinical research studies. The first study uses magnetic resonance spectroscopy metabolite data over multiple brain regions to compare participants with and without spinocerebellar ataxia; the second uses publicly available gene expression time-course data to compare degrees of treatment response among patients with multiple sclerosis. Our multi-way method can improve performance and simplify interpretation over naive applications of full rank linear and non-linear classification to multi-way data. The R package is available at https://github.com/lockEF/MultiwayClassification.

Chronic spontaneous urticaria (CSU) is characterized by the spontaneous development of wheals, itching, and/or angioedema, for ≥6 weeks. In China, non‐sedating H1‐antihistamines (H1AH) are the recommended first‐line treatment, with escalation up to 4× the standard dose in symptomatic patients to achieve control. Treatment options for Chinese patients who remain symptomatic on H1AH treatment are limited. This 20‐week randomized, double blind, placebo‐controlled, parallel‐group study investigated the efficacy and safety of omalizumab as an add‐on therapy for the treatment of patients with CSU who remained symptomatic despite H1AH treatment in China. Adult patients (N = 418) diagnosed with refractory CSU for ≥6 months were randomized (2:2:1) to receive omalizumab 300 mg (OMA300), omalizumab 150 mg (OMA150) or placebo, subcutaneously, every 4 weeks. Primary outcome was change from baseline to week 12 in weekly itch severity score (ISS7). Safety was assessed by rates of adverse events (AEs). Demographic and disease characteristics at baseline were comparable across treatment groups. At week 12, statistically significant greater decreases from baseline were observed in ISS7 with OMA300 (least square mean difference [LSM]: −4.23; 95% confidence interval [CI]: −5.70, −2.77; p < 0.001) and OMA150 (LSM: −3.79; 95% CI: −5.24, −2.33; p < 0.001) versus placebo. Incidence of treatment‐emergent AEs over 20 weeks was slightly higher with OMA300 (71.3%) compared to OMA150 and placebo groups (64.7% and 63.9%, respectively). The incidences of serious AEs were balanced between groups. This study demonstrated the efficacy and safety of omalizumab in Chinese adult patients with CSU who remained symptomatic despite H1AH therapy.