Several novel classes of small regulatory RNAs show widespread changes in schizophrenia and bipolar disorder and extensive linkages to critical brain processes.

Publication/Presentation Date

2-4-2026

Abstract

Transcriptomic studies of post-mortem brain samples in schizophrenia (SCZ) and bipolar disorder (BD) have primarily focused on messenger RNAs (mRNAs) but have given limited attention to small non-coding RNAs (sncRNAs). In this study, we present our analyses of sncRNA profiles from the prefrontal cortex of SCZ and BD cases and controls (53 SCZ cases, 40 BD cases, 77 controls), which we sourced from the Icahn School of Medicine at Mount Sinai and the NIMH Human Brain Collection Core brain banks. Corresponding mRNA-seq data were obtained from the CommonMind Consortium. Using a state-of-the-art pipeline, we mapped reads and determined differentially abundant and co-expressed sncRNAs and mRNAs, adjusting for known and hidden confounders. Across samples, 98% of all sncRNAs comprised miRNA isoforms (60.6%), tRNA-derived fragments (17.8%), rRNA-derived fragments (11.4%), and Y RNA-derived fragments (8.3%). In SCZ, 15% of the identified sncRNAs exhibited significant fold changes (FCs), with many also altered in BD, albeit to a lesser extent. For miRNAs, the FCs correlated strongly with the presence of non-templated nucleotides to their 3'-ends, independently of miRNA identity or locus of origin. Disease- and age-associated sncRNAs and mRNAs revealed accelerated aging in both SCZ and BD. Co-expression analyses also revealed, for the first time, disease-independent associations of many isomiRs, tRFs, rRFs, and yRFs with critical brain processes. These findings suggest complex and previously uncharacterized roles for novel classes of regulatory sncRNAs in synaptic signaling, neurogenesis, memory, behavior, and cognition.

Volume

16

Issue

1

First Page

72

Last Page

72

ISSN

2158-3188

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

41639050

Department(s)

Administration and Leadership

Document Type

Article

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