Together, the findings nominate candidate genes and pathways for further investigation; they do not establish causal mechanisms, diagnostic performance or therapeutic effects. The researchers performed RNA sequencing on total messenger RNA, comparing 16 bipolar disorder cases with 15 unaffected relatives. They used differential gene-expression analysis to identify genes with different expression between the two groups and Weighted Gene Co-expression Network Analysis, or WGCNA, to identify groups of genes expressed together.

Five bipolar disorder-associated expression modules emerged from WGCNA. The most significant module was associated with ion transmembrane transport, corpus callosum hypoplasia and a protein network related to solute carriers. These associations indicate shared molecular patterns in the analyzed samples, but they do not demonstrate that the implicated processes cause bipolar disorder.

Five of the 60 differentially expressed genes were prioritized through the Polygenic Priority Score, or PoPS. One, ENSG00000279277, is a long non-coding RNA that maps within a bipolar disorder genome-wide association study locus. The researchers also conducted gene-based association analysis with MAGMA using genome-wide association study summary statistics.

The convergence of expression differences, co-expression modules and genetic prioritization provides multiple lines of evidence for the selected candidates, although the study remains observational and does not show that changing any candidate gene's expression would alter disease outcomes. Three methods were used to validate or extend the discovery results. The researchers examined their findings against brain-derived RNA-sequencing data from an independent cohort of 71 people with bipolar disorder and 252 control individuals.

They also used MAGMA for gene-based association analysis and PoPS for gene prioritization. In addition, gene-set analysis examined biological enrichments and whether the differential-expression and co-expression results converged on the same pathways. The study authors interpret this combined evidence as suggesting that long non-coding RNAs may participate in bipolar disorder pathophysiology and that disturbed ion homeostasis, involving dysregulated gated channels, may be an impaired process in the condition.

The discovery cohort was small in absolute terms, comprising 31 lymphoblastoid cell lines from eight multiplex families, and its molecular findings came from an experimental cell-line model. The independent brain-derived RNA-sequencing cohort broadened the evidence available for replication, but the reported analysis does not determine whether expression changes in the cell lines correspond to changes in specific human brain cells. The results therefore identify a limited set of expression differences and associated pathways rather than a single cause of bipolar disorder.

Their principal contribution is to prioritize long non-coding RNAs, including LINC01237 and ENSG00000279277, and to highlight ion transport and gated-channel activity as pathways that merit further study.

Subject of Research: Family-based RNA sequencing of candidate genes and ion-transport pathways in bipolar disorder.

Article Title: Family-based RNA sequencing in bipolar disorder points to novel candidate genes and dysregulated pathways

Article References: García-Ortiz, I., Martínez-Jiménez, M., Kavanagh, T., Marshall, L. L., Lucas, J. J., Romero-Miguel, D., Schofield, P. R., Mitchell, P. B., Cooper, A. A., Fullerton, J. M., & Toma, C. (2026). Family-based RNA sequencing in bipolar disorder points to novel candidate genes and dysregulated pathways. Translational Psychiatry. https://doi.org/10.1038/s41398-026-04473-w

Image Credits: AI Generated

DOI: 10.1038/s41398-026-04473-w

Keywords: bipolar disorder, RNA sequencing, long non-coding RNA, LINC01237, ion transport, gated channels, gene expression, co-expression networks, genetic prioritization, multiplex families, Family-based, sequencing