2026 ECNP Congress

PS04-4108

Peripheral gene expression and white matter microstructure in bipolar disorder: evidence for lithium-related effects

Serena Furno — D. Betelli, B. Bravi, C. Di Carlo, S. Spadini, M.C. Lorenzi, C. Colombo, S. Poletti, F. Benedetti · IRCCS Ospedale San Raffaele, Psychiatry and Clinical Psychobiology Unit- Division of Neuroscience, Milan, Italy

2026 ECNP Congress

Introduction

Bipolar disorder (BD) is consistently associated with alterations in white matter (WM) microstructure, suggesting impaired structural connectivity [1]. Lithium remains the gold-standard treatment for BD and is associated with neuroprotective and neurotrophic effects, although its mechanisms of action are still poorly understood [2]. Emerging evidence indicates that lithium treatment is linked to widespread gene expression changes, particularly involving cell signaling and immune pathways [3]. Peripheral blood mononuclear cell (PBMC) transcriptomics provides an accessible approach to capture lithium-related systemic transcriptional effects, which may reflect brain-relevant biological processes [4, 5]. However, the association between peripheral gene expression and brain structure remains largely unexplored in BD. Therefore, we aimed to investigate whether lithium treatment modulates the relationship between PBMC gene expression and WM microstructure in BD.

Methods

The sample included 116 patients with BD (DSM-5), classified as lithium-treated (n=66; ≥6 months of treatment) or not treated with lithium (n=50). PBMC RNA sequencing was performed, and differential gene expression associated with lithium exposure was assessed using edgeR quasi-likelihood models (FDR<0.05), adjusting for sex. A subset of 66 patients (31 lithium-treated, 35 non-treated) underwent diffusion MRI on 3T scanners. WM microstructure was assessed using tract-based spatial statistics (TBSS) in FSL (v6.0), deriving fractional anisotropy (FA), axial (AD), radial (RD), and mean diffusivity (MD). Voxelwise separate-slope analyses tested whether gene expression had different effects on WM measures depending on lithium treatment. Analyses were adjusted for age, sex, and MRI scan. Statistical inference was performed using permutation-based testing with threshold-free cluster enhancement (TFCE) correction (p<0.05) as implemented in FSL’s Randomise tool.

Results

Lithium-treated patients showed differential PBMC expression of five genes: SEPTIN11, DGKK, and TPPP3 were upregulated, whereas LEF1-AS1 and PLXDC1 were downregulated. Significant lithium-by-gene expression interactions on WM microstructure were observed; post hoc analyses indicated that these associations were present exclusively in patients receiving lithium treatment. Specifically, interactions were detected for SEPTIN11 (AD p=0.010; RD p=0.035; MD p=0.027), LEF1-AS1 (FA p=0.007; RD p=0.017), PLXDC1 (FA p=0.010; RD p=0.009; MD p=0.006), while no interaction was observed for TPPP3. DGKK also showed significant voxelwise interactions, but this did not survive the post hoc single-slope analyses. In lithium-treated patients, higher LEF1-AS1 and PLXDC1 expression was associated with widespread increases in FA and lower RD and MD, consistent with greater WM integrity. SEPTIN11 showed lithium-dependent associations with diffusivity measures, with higher expression associated with increased AD, RD, and MD.

Conclusions

To our knowledge, this is the first study to investigate the relationship between lithium, PBMC gene expression, and WM microstructure in BD. Our findings show that lithium treatment modulates the relationship between PBMC gene expression and WM microstructure in BD, with associations between gene expression and WM integrity emerging only in lithium-treated patients. These associations were characterized by gene-specific patterns across diffusion metrics, indicating differential relationships with WM integrity. Overall, convergence between lithium-related gene expression and WM microstructure suggests that these transcriptional changes may contribute to neurobiological processes underlying lithium’s effects.

References

  1. Favre, P., Pauling, M., Stout, J. et al. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals. Neuropsychopharmacol. 44, 2285–2293 (2019). https://doi.org/10.1038/s41386-019-0485-6
  2. Malhi, G. S., Gessler, D., & Outhred, T. (2017). The use of lithium for the treatment of bipolar disorder: Recommendations from clinical practice guidelines. Journal of Affective Disorders, 217, 266–280. https://doi.org/10.1016/j.jad.2017.03.052
  3. Krebs, C. E., Ori, A. P. S., Vreeker, A., Wu, T., Cantor, R. M., Boks, M. P. M., Kahn, R. S., Olde Loohuis, L. M., & Ophoff, R. A. (2020). Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect. Psychological Medicine, 50(15), 2575–2586. https://doi.org/10.1017/S0033291719002745
  4. Goossens, J., Morrens, M., & Coppens, V. (2021). The Potential Use of Peripheral Blood Mononuclear Cells as Biomarkers for Treatment Response and Outcome Prediction in Psychiatry: A Systematic Review. Molecular Diagnosis & Therapy, 25(3), 283–299. https://doi.org/10.1007/s40291-021-00516-8
  5. Ibrahim, E. C., Guillemot, V., Comte, M., Tenenhaus, A., Zendjidjian, X. Y., Cancel, A., Belzeaux, R., Sauvanaud, F., Blin, O., Frouin, V., & Fakra, E. (2017). Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients. Npj Schizophrenia, 3(1), 25. https://doi.org/10.1038/s41537-017-0027-3