Treatment modulation of transcriptional profiles in lupus nephritic patients

Abstract

Title: Treatment Modulation of Transcriptional Profile in Lupus Nephritic Patients Introduction: Systemic lupus erythematosus (SLE) is a complex autoimmune disease affecting multiple organ systems. The pathogenesis of SLE is heterogeneous with diverse clinical manifestations, which often leads to poor prognosis and poses a major challenge in the treatment of SLE. Most SLE patients will develop lupus nephritis (LN), which is a major cause of end-stage organ failure in lupus patients. Currently, overall SLE activity is assessed by routine testing of serum levels of complement C3 and C4, creatinine and anti-dsDNA autoantibodies; while urinary protein level, urinary sediment analysis as well as creatinine clearance are used for renal involvement assessment. These markers and tests aid diagnosis but lack the sensitivity and specificity for predicting LN flare and progression. Histological examination of renal biopsies is more reliable and remains as the standard test in LN diagnosis and classification. However, it is impractical to perform frequent invasive procedures. Therefore, a reliable and less invasive method for predicting and monitoring LN flare is needed. With the emerging high-throughput sequencing technology, the study of blood transcriptomics can identify transcriptional signature of active LN patients, which may be translated into clinically useful molecular biomarkers. The aim of this pilot study is to determine the differential transcriptional profiles of LN patients pre-treatment vs. post-treatment. Methods: Whole blood was collected from 9 SLE patients experiencing renal flare with biopsy-confirmed nephritis (lupus nephritis/LN) within 7 days before or after the scheduled biopsy. Blood samples were obtained again after treatment. Total RNA was extracted and sequenced using the Illumina HiSeq1500. Reads were mapped to the reference genome using STAR software and differential expression was determined using EBSeq software. A heatmap was generated using hierarchical clustering analysis with ClustVis. Gene set enrichment analysis was performed using GO Analysis. Protein interaction was analysed using STRING. Results: A differential transcriptome expression pattern was observed in LN patients after treatment compared to that of pre-treatment. A cluster of transcripts (ISG15, USP18, IFIT1, IFI44, IFI44L) mainly involved in interferon (IFN) signalling was down regulated after treatment, while transcripts (UBE2O, NEDD4L, UBE2H, FBXO9, FBXO7, HERC6) involved in antigen processing were up-regulated. Conclusion: The transcripts involved in IFN signalling and antigen presentation could be potential biomarkers for monitoring lupus nephritis. Acknowledgement: This research is supported by the Health and Medical Research Fund (HMRF)