ObjectiveRecent advances in understanding Spinal Muscular Atrophy (SMA) etiopathogenesis prompted development of potent intervention strategies and raised need for sensitive outcome measures capable of assessing disease progression and response to treatment. Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression.Methods18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations.Results QMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year.InterpretationWe probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. The proposed biomarker framework can guide implementation of more sensitive endpoints in future clinical trials and prove their utility in search for novel disease‐modifying therapies.

Background Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. Methods We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2–32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants’ MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%–30% split). Results In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52–0.62, specificity 0.59–0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. Limitations The statistical power to detect weak effects—of the magnitude of those found in the training dataset—in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset’s effects. Conclusions This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

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Electroconvulsive therapy (ECT) is an effective neuromodulatory therapy for major depressive disorder (MDD). Treatment is associated with regional changes in brain structure and function, indicating activation of neuroplastic processes. To investigate the underlying neurobiological mechanism of macroscopic reorganization following ECT, we longitudinally (before and after ECT in two centers) collected magnetic resonance images for 96 MDD patients. Similar patterns of cortical thickness (CT) changes following ECT were observed in two centers. These CT changes were spatially colocalized with a weighted combination of genes enriched for neuroplasticity-related ontology terms and pathways (e.g., synaptic pruning) as well as with a higher density of D2/3 dopamine receptors. A multiple linear regression model indicated that the regionspecific gene expression and receptor density patterns explained 40% of the variance in CT changes after ECT. In conclusion, these findings suggested that dopamine signaling and neuroplasticity-related genes are associated with the ECT-induced morphological reorganization. Keywords Cortical thickness • Electroconvulsive therapy • Gene expression • Major depressive disorder • NeurotransmitterGong-Jun Ji and Jiao Li equally contributed to this work.