Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome, and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.

ObjectivesRheumatoid arthritis (RA) is an autoimmune disease accompanied by lymphocyte infiltration into joint synovium. While T cells are considered to be important for its pathogenesis, the features that are the most relevant to disease and how they change after treatment remain unclear. The aim of this study was to clarify the characteristics of T cells in RA, comprehensively.MethodsWe enrolled a total of 311 patients with RA and 73 healthy participants, and carefully classified them by disease state, constructed multiple cohorts and analysed clinical samples from them in a stepwise manner. We performed immunophenotyping with multiple evaluation axes, and two independent transcriptome analyses complementary to each other.ResultsWe identified that ‘effector memory-Tfh’ subset was specifically expanded in the peripheral blood (PB) of patients with RA in correlation with disease activity, and reverted after treatment. Besides, we revealed distinct features of T cells in synovial fluid (SF) that the expression of Tfh/Tph-related genes and pro-inflammatory cytokines and chemokines, including CXCL13, were significantly enriched, whereas these phenotype were Th1-like. Finally, we identified specific pathways, such as mTORC1, IL-2-stat5, E2F, cell cycle and interferon-related genes, that were significantly enriched in SF, in particular, as well as PB of untreated patients with RA, and notably, these features reverted after treatment.ConclusionOur multi-dimensional investigation identified disease relevant T-cell subsets and gene signatures deeply involved in pathogenesis of RA. These findings could aid in our understanding of essential roles of T cells in RA and will facilitate to development better diagnostic and therapeutic interventions.

ObjectivesMultiomics study was conducted to elucidate the crucial molecular mechanisms of primary Sjögren’s syndrome (SS) pathology.MethodsWe generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation.ResultsOur integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 ­T cells­ were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS.ConclusionsOur multiomics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Mitochondria increase in number by the fission of existing mitochondria. Mitochondrial fission is needed to provide mitochondria to daughter cells during cell division. In Arabidopsis thaliana, four kinds of genes have been reported to be involved in mitochondrial fission. Two of them, DRP3 (dynamin-related protein3) and FIS1 (FISSION1), are well conserved in eukaryotes. The other two are plant-specific ELM1 (elongated mitochondria1) and PMD (peroxisomal and mitochondrial division). To better understand the commonality and diversity of mitochondrial fission factors in land plants, we examined mitochondrial fission-related genes in a liverwort, Marchantia polymorpha. As a bryophyte, M. polymorpha has features distinct from those of the other land plant lineages. We found that M. polymorpha has single copies of homologues for DRP3, FIS1 and ELM1, but does not appear to have a homologue of PMD. Citrine-fusion proteins with MpDRP3, MpFIS1 and MpELM1 were localized to mitochondria in M. polymorpha. MpDRP3- and MpELM1-defective mutants grew slowly and had networked mitochondria, indicating that mitochondrial fission was blocked in the mutants, as expected. However, knockout of MpFIS1 did not affect growth or mitochondrial morphology. These results suggest that MpDRP3 and MpELM1 but neither MpFIS1 nor PMD are needed for mitochondrial fission in M. polymorpha.

Background: The aim of this study was to identify the molecular mechanism of dysregulation of B cell subpopulations of primary Sjögren's syndrome (pSS) at the transcriptome level. Methods: We enrolled patients with pSS (n = 6) and healthy controls (HCs) (n = 6) in the discovery cohort using microarray and pSS (n = 14) and HCs (n = 12) in the validation cohort using quantitative PCR (qPCR). Peripheral B cells acquired from these subjects were separated by cell sorting into four subsets: CD38 − IgD + (Bm1), CD38 + IgD + (naive B cells), CD38 high IgD + (pre-germinal centre B cells) and CD38 ± IgD − (memory B cells). We performed differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA). Results: Expression of the long non-coding RNA LINC00487 was significantly upregulated in all B cell subsets, as was that of HLA and interferon (IFN) signature genes. Moreover, the normalized intensity value of LINC00487 significantly correlated with the disease activity score of all pSS B cell subsets. Studies of human B cell lines revealed that the expression of LINC00487 was strongly induced by IFNα. WGCNA revealed six gene clusters associated with the B cell subpopulation of pSS. Further, SOX4 was identified as an inter-module hub gene. Conclusion: Our transcriptome analysis revealed key genes involved in the dysregulation of B cell subpopulations associated with pSS. Trial registration: Not required.