Immune Dynamics of Lithium Treatment and Response in Individuals with Bipolar Disorder
1 University Hospital Bonn
Background: Lithium remains one of the most effective treatment options in individuals with bipolar disorder (BPD). However, the clinical response to lithium is highly variable, with some patients experiencing significant benefits while others showing little to no improvement. Despite advances in understanding the genetic determinants of lithium response through genome-wide association studies (GWAS), the cellular mechanisms mediating genetic risk remain unclear. Recent research has highlighted the potential of immune-mediated processes and immune cells as key players and potential biological markers in the pathophysiology of these disorders, where both genetic and environmental factors likely play important roles. Leveraging immune cells as potential biological markers offers a promising avenue to refine diagnostic methods and understand pathophysiological processes. To address this, this study focused on a comprehensive investigation of immune cell behavior in lithium-treated peripheral blood mononuclear cells (PBMCs) of individuals with BPD.
Method: This study capitalizes on a whole transcriptome dataset from PBMCs of individuals with BPD. PBMCs were collected from 149 BPD subjects in whom the BPD diagnosis was made in line with DSM-IV criteria and response to treatment with lithium as a lifetime measure was judged using the Alda-Scale. 21 individuals with the most extreme response profiles (n=10 non-responders and n=11 responders) were selected and PBMCs from all 21 individuals were cultivated with and without lithium. Bulk RNA-Seq was performed on the Illumina platform. Transcriptomic data were normalized, log-transformed, and differentially expressed genes (DEGs) were calculated using the DESeq2 package in R. DEGs between lithium responders and non-responders were identified and gene set enrichment analysis (GSEA) was performed. SingleR algorithm was employed to deconvolute the transcriptomic profiles and to identify immune cell populations.
Results: DEGs of lithium responders and non-responders intersected with a list of immune-specific genes (3714 unique genes, Calvano et al., 2005) revealed 15 common genes. Notably, we observed a significant downregulation of 13 immune-specific genes (ATP5I, CR1, DISC1, DTX4, FLT3LG, HIST2H2BE, NDUFA3, NPHP3, ORM2, RAB3D, RSC1A1, THRA, TIAF1, and ZNF85) in lithium responders with BPD. Moreover, GSEA revealed enrichment in inflammatory pathways, such as inflammatory response, cytokine receptor binding, interleukin-1 beta production, regulation of interleukin-1 beta production, regulation of interleukin-1 production, and regulation of inflammatory response. Furthermore, deconvolution analysis of DEGs identified 36 cell types, predominantly representing immune cell populations. Interestingly, we noted a significant downregulation of identified immune cell populations in lithium responders.
Discussion: This study explored the transcriptional dynamics within PBMCs in patients with BPD in the context of lithium response. We have identified distinct gene expression patterns linked to immune-specific cellular responses through comprehensive transcriptomics analysis and deconvolution techniques. We noted a significant downregulation of immune-related genes, pathways, and cell types in lithium responders, suggesting a potential immune modulatory mechanism upon lithium treatment. We will expand this study by performing single-cell immune profiling for the PBMCs of the same individuals with BPD and integrate the human forebrain single-cell and mouse brain spatial transcriptomics data.