ObjectivesPatients with lupus nephritis (LN) are in urgent need for early diagnosis and therapeutic interventions targeting aberrant molecular pathways enriched in affected kidneys.MethodsWe used mRNA-sequencing in effector (spleen) and target (kidneys, brain) tissues from lupus and control mice at sequential time points, and in the blood from 367 individuals (261 systemic lupus erythematosus (SLE) patients and 106 healthy individuals). Comparative cross-tissue and cross-species analyses were performed. The human dataset was split into training and validation sets and machine learning was applied to build LN predictive models.ResultsIn murine SLE, we defined a kidney-specific molecular signature, as well as a molecular signature that underlies transition from preclinical to overt disease and encompasses pathways linked to metabolism, innate immune system and neutrophil degranulation. The murine kidney transcriptome partially mirrors the blood transcriptome of patients with LN with 11 key transcription factors regulating the cross-species active LN molecular signature. Integrated protein-to-protein interaction and drug prediction analyses identified the kinases TRRAP, AKT2, CDK16 and SCYL1 as putative targets of these factors and capable of reversing the LN signature. Using murine kidney-specific genes as disease predictors and machine-learning training of the human RNA-sequencing dataset, we developed and validated a peripheral blood-based algorithm that discriminates LN patients from normal individuals (based on 18 genes) and non-LN SLE patients (based on 20 genes) with excellent sensitivity and specificity (area under the curve range from 0.80 to 0.99).ConclusionsMachine-learning analysis of a large whole blood RNA-sequencing dataset of SLE patients using human orthologs of mouse kidney-specific genes can be used for early, non-invasive diagnosis and therapeutic targeting of LN. The kidney-specific gene predictors may facilitate prevention and early intervention trials.

ObjectivesTreatment of Systemic Lupus Erythematosus (SLE) is characterized by a largely empirical approach and relative paucity of novel compound development. We sought to stratify SLE patients based on their molecular phenotype and identify putative therapeutic compounds for each molecular fingerprint.MethodsBy the use of whole blood RNA-seq data from 120 SLE patients, and in a data-driven, clinically unbiased manner, we established modules of commonly regulated genes (molecular endotypes) and re-stratified patients through hierarchical clustering. Disease activity and severity were assessed using SLEDAI-2K and Lupus Severity Index, respectively. Through an in silico drug prediction pipeline, we investigated drugs currently in use, tested in lupus clinical trials, and listed in the iLINCS prediction databases, for their ability to reverse the gene expression signatures in each molecular endotype. Drug repurposing analysis was also performed to identify perturbagens that counteract group-specific SLE signatures.ResultsMolecular taxonomy identified five lupus endotypes, each characterized by a unique gene module enrichment pattern. Neutrophilic signature group consisted primarily of patients with active lupus nephritis, while the B-cell expression group included patients with constitutional features. Patients with moderate severity and serologic activity exhibited a signature enriched for metabolic processes. Mild disease was distributed in two groups, exhibiting enhanced basic cellular functions, myelopoiesis, and autophagy. Bortezomib was predicted to reverse disturbances in the “neutrophilic” cluster, azathioprine and ixazomib in the “B-cell” cluster, and fostamatinib in the “metabolic” patient subgroup.ConclusionThe clinical spectrum of SLE encompasses distinct molecular endotypes, each defined by unique pathophysiologic aberrancies potentially reversible by distinct compounds.

Introduction: We present a female who had prolonged acute hepatocellular liver injury after undergoing a cholangiogram using Omnipaque contrast. About 10 cases of cholestatic liver injury have been reported after ERCP, however our case is unique being predominantly hepatocellular injury. Case Description/Methods: Initially presenting with abdominal pain then diagnosed with cholecystitis, she underwent cholecystectomy with cholangiogram. She subsequently underwent ERCP due to a retained stone and discharged home the next day without notable complications. She presented to the hospital two days later with pruritus. After ruling out infectious cause and further mechanical hepatobiliary pathology, she was discharged home due to improved symptoms with symptomatic management. Transaminases gradually resolved with close outpatient follow-up at two weeks and two months. Discussion: The exact mechanism remains unclear, liver injury due to idiosyncratic reaction from contrast was postulated. This is possibly due to local hepatic injury from the contrast agent in the biliary system. The contrast material being infused under high pressure, can have a toxic effect on the liver with disruption of canalicular plasma membranes. Systemic distribution of the contrast medium from the bile duct and the spreading of the agent extracellularly to the nearby tissues might be responsible for direct toxic liver injury. Awareness of this reaction is helpful in preventing unnecessary repeat ERCP to confirm bile duct clearance as well as liver biopsies. Prednisone may be considered if persistently elevated liver enzymes.[2949] Figure 1. Title: Liver Function Tests during clinical course Caption: Patient's liver function test over the hospitalization, readmission, two-week outpatient follow-up, and two-month outpatient follow-up revealing fluctuating elevation in transaminases after cholangiogram performed on day of admission while total bilirubin remains within normal limits. Gradual resolution of elevated transaminases over two-week and two-month follow-up. ERCP occurred on hospital day 1. Legend: HD-Hospital day RD-Readmission day ALP-alkaline phosphatase AST-Aspartate transaminase ALT-Alanine Transaminase.

using analysis of covariance models with modified baseline-observation-carried-forward method to handle missing data, adjusting for treatment, baseline value, and stratification factors. Results: In LUCENT-1, the PGRS (mean 6 standard deviation) scores at baseline were 4.24 6 0.82 in the mirikizumab 300 mg group and 4.28 6 0.81 for placebo. The least-squares mean (LSM) change from baseline for PGRS was statistically greater in patients given mirikizumab 300 mg than placebo, starting at Week 2 (LSM [standard error] mirikizumab vs