Schizophrenia (SZ) is a serious mental disorder that is typically treated with antipsychotic medication. Treatment-resistant schizophrenia (TRS) is the condition where symptoms remain after pharmacological intervention, resulting in long-lasting functional and social impairments. As the identification and treatment of a TRS patient requires previous failed treatments, early mechanisms of detection are needed in order to quicken the access to effective therapy, as well as improve treatment adherence. In this study, we aim to find a microRNA (miRNA) signature for TRS, as well as to shed some light on the molecular pathways potentially involved in this severe condition. To do this, we compared the blood miRNAs of schizophrenia patients that respond to medication and TRS patients, thus obtaining a 16-miRNA TRS profile. Then, we assessed the ability of this signature to separate responders and TRS patients using hierarchical clustering, observing that most of them are grouped correctly (~70% accuracy). We also conducted a network, pathway analysis, and bibliography search to spot molecular pathways potentially altered in TRS. We found that the response to stress seems to be a key factor in TRS and that proteins p53, SIRT1, MDM2, and TRIM28 could be the potential mediators of such responses. Finally, we suggest a molecular pathway potentially regulated by the miRNAs of the TRS profile.

Aging leads to cognitive decline and increased risk of neurodegenerative diseases. While molecular changes in central nervous system (CNS) cells contribute to this decline, the mechanisms are not fully understood. Long non-coding RNAs (lncRNAs) are key regulators of cellular functions. Background/Objectives: The roles of lncRNAs in aging, especially in glial cells, are not well characterized. Methods: We investigated lncRNA expression in non-neuronal cells from aged mice and identified 3222401L13Rik, a previously unstudied lncRNA, as upregulated in astrocytes during aging. Results: Knockdown of 3222401L13Rik in primary astrocytes revealed its critical role in regulating genes for neuronal support and synapse organization, a function conserved in human iPSC-derived astrocytes. A 3222401L13Rik interacts with the transcription factor Neuronal PAS Domain Protein 3 (Npas3), and overexpression of Npas3 rescues deficits in astrocytes lacking 3222401L13Rik. Conclusions: These data suggest that 3222401L13Rik upregulation may help delay age-related cognitive decline.

Background: Heart failure (HF) is associated with an increased risk of cognitive impairment and hippocampal dysfunction, yet the underlying molecular mechanisms remain poorly understood. This study aims to investigate the role of microRNA (miRNA) networks in hippocampus-dependent memory recovery in a mouse model of HF. Methods: CaMKIIδC transgenic (TG) mice, a model for HF, were used to assess hippocampal function at 3 and 6 months of age. Memory performance was evaluated using hippocampus-dependent behavioral tasks. Small RNA sequencing was performed to analyze hippocampal miRNA expression profiles across both time points. Bioinformatic analyses identified miRNAs that potentially regulate genes previously implicated in HF-induced cognitive impairment. Results: We have previously shown that at 3 months of age, CaMKIIδC TG mice exhibited significant memory deficits associated with dysregulated hippocampal gene expression. In this study, we showed that these impairments, memory impairment and hippocampal gene expression, were no longer detectable at 6 months, despite persistent cardiac dysfunction. However, small RNA sequencing revealed a dynamic shift in hippocampal miRNA expression, identifying 27 miRNAs as “compensatory miRs” that targeted 73% of the transcripts dysregulated at 3 months but reinstated by 6 months. Notably, miR-181a-5p emerged as a central regulatory hub, with its downregulation coinciding with restored memory function. Conclusions: These findings suggest that miRNA networks contribute to the restoration of hippocampal function in HF despite continued cardiac pathology and provide an important compensatory mechanism towards memory impairment. A better understanding of these compensatory miRNA mechanisms may provide novel therapeutic targets for managing HF-related cognitive dysfunction.

The spatial relationship between gene expression profiles and neural response patterns known to be altered in neuropsychiatric disorders, e.g. depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in neuronal development, synapse regulation, and gene transcription. An overlap of these genes with risk genes from major depressive disorder genome-wide associations studies revealed the involvement of the master regulators TCF4 and MEF2C. These results were further validated by means of meta-analytic fMRI data. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.