Involvement of extracellular vesicle microRNA clusters in developing healthy and Rett syndrome brain organoids.

Rett syndrome (RTT) is a neurodevelopmental disorder caused by de novo mutations in the MECP2 gene. Although miRNAs in extracellular vesicles (EVs) have been suggested to play an essential role in several neurological conditions, no prior study has utilized brain organoids to profile EV-derived miRNAs during normal and RTT-affected neuronal development. Here we report the spatiotemporal expression pattern of EV-derived miRNAs in region-specific forebrain organoids generated from female hiPSCs with a MeCP2:R255X mutation and the corresponding isogenic control. EV miRNA and protein expression profiles were characterized at day 0, day 13, day 40, and day 75. Several members of the hsa-miR-302/367 cluster were identified as having a time-dependent expression profile with RTT-specific alterations at the latest developmental stage. Moreover, the miRNA species of the chromosome 14 miRNA cluster (C14MC) exhibited strong upregulation in RTT forebrain organoids irrespective of their spatiotemporal location. Together, our results suggest essential roles of the C14MC and hsa-miR-302/367 clusters in EVs during normal and RTT-associated neurodevelopment, displaying promising prospects as biomarkers for monitoring RTT progression.

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. HIGHLIGHTS: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

A novel insight into neurological disorders through HDAC6 protein-protein interactions.

Due to its involvement in physiological and pathological processes, histone deacetylase 6 (HDAC6) is considered a promising pharmaceutical target for several neurological manifestations. However, the exact regulatory role of HDAC6 in the central nervous system (CNS) is still not fully understood. Hence, using a semi-automated literature screening technique, we systematically collected HDAC6-protein interactions that are experimentally validated and reported in the CNS. The resulting HDAC6 network encompassed 115 HDAC6-protein interactions divided over five subnetworks: (de)acetylation, phosphorylation, protein complexes, regulatory, and aggresome-autophagy subnetworks. In addition, 132 indirect interactions identified through HDAC6 inhibition were collected and categorized. Finally, to display the application of our HDAC6 network, we mapped transcriptomics data of Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis on the network and highlighted that in the case of Alzheimer's disease, alterations predominantly affect the HDAC6 phosphorylation subnetwork, whereas differential expression within the deacetylation subnetwork is observed across all three neurological disorders. In conclusion, the HDAC6 network created in the present study is a novel and valuable resource for the understanding of the HDAC6 regulatory mechanisms, thereby providing a framework for the integration and interpretation of omics data from neurological disorders and pharmacodynamic assessments.