Systemic lupus erythematosus (SLE) is characterized by immune system dysfunction and is clinically heterogeneous, exhibiting renal, dermatological, neuropsychiatric, and cardiovascular symptoms. Clinical and physiological assessment is usually inadequate for diagnosing and assessing pathophysiological processes in SLE. Clinical and immunological biomarkers could play a critical role in improving diagnosis, assessment, and ultimately, control of SLE. This article reviews clinical and immunological biomarkers that could diagnose and monitor disease activity in SLE, with and without organ-specific injury. In addition, novel SLE biomarkers that have been discovered through “omics” research are also reviewed.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to destructive arthritis. Although the HLA class II locus is the strongest genetic risk factor for rheumatoid arthritis, the relationship between HLA class II alleles and lymphocyte activation remains unclear. We performed immunophenotyping of peripheral blood mononuclear cells on 91 HLA-DRB1-genotyped RA patients and 110 healthy donors. The frequency of memory CXCR4⁺CD4⁺T cells and not Th1 and Th17 cells, was significantly associated with disease severity by multiple linear regression analysis. RA patients with one or more susceptible HLA-DR haplotypes (shared epitope: SE) displayed a significantly higher frequency of memory CXCR4⁺CD4⁺T cells. Moreover, the frequency of memory CXCR4⁺CD4⁺T cells significantly correlated with the expression level of HLA-DR on B cells, which was elevated in RA patients with SE.In vitroanalysis and transcriptomic pathway analysis suggested that the interaction between HLA-DR and T cell receptors is an important regulator of memory CXCR4⁺CD4⁺T cells. Clinically, a higher frequency of memory CXCR4⁺CD4⁺T cells predicted a better response to CTLA4-Ig. Memory CXCR4⁺CD4⁺T cells may serve as a powerful biomarker for unraveling the linkage between HLA-DRB1 genotype and disease activity in RA.

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4 ⁺ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3 ^mid CD4 ⁺ effector memory T cell subset that expands with age, which we designated “age-associated T helper (T _H A) cells.” T _H A cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of T _H A cells, gene expression in T _H A cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that T _H A cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of T _H A cells may facilitate improved understanding of the relationship between aging and autoimmune diseases.

Splicing quantitative trait loci (sQTLs) are one of the major causal mechanisms in genome-wide association study (GWAS) loci, but their role in disease pathogenesis is poorly understood. One reason is the complexity of alternative splicing events producing many unknown isoforms. Here, we propose two approaches, namely integration and selection, for this complexity by focusing on protein-structure of isoforms. First, we integrate isoforms with the same coding sequence (CDS) and identify 369-601 integrated-isoform ratio QTLs (i²-rQTLs), which altered protein-structure, in six immune subsets. Second, we select CDS incomplete isoforms annotated in GENCODE and identify 175-337 isoform-ratio QTL (i-rQTL). By comprehensive long-read capture RNA-sequencing among these incomplete isoforms, we reveal 29 full-length isoforms with unannotated CDSs associated with GWAS traits. Furthermore, we show that disease-causal sQTL genes can be identified by evaluating their trans-eQTL effects. Our approaches highlight the understudied role of protein-altering sQTLs and are broadly applicable to other tissues and diseases.