Objective Using a large, de‐identified electronic health record database with over 3.2 million patients, we aimed to identify trends of systemic lupus erythematosus (SLE) medication use during pregnancy and birth outcomes from 1989 to 2020. Methods Using a previously validated algorithm for SLE deliveries, we identified 255 pregnancies in patients with SLE and 604 pregnancies in controls with no known autoimmune diseases. We examined demographics, medications, SLE comorbidities, and maternal and fetal outcomes in SLE and control deliveries. Results Compared with control deliveries, SLE deliveries were more likely to be complicated by preterm delivery (odds ratio [OR]: 6.71; 95% confidence interval [CI]: 4.31‐10.55; P < 0.001) and preeclampsia (OR: 3.22; 95% CI: 1.83‐5.66; P < 0.001) after adjusting for age at delivery, race, and parity. In a longitudinal analysis, medication use during SLE pregnancies remained relatively stable, with some increased use of hydroxychloroquine over time but no increase in aspirin use. For SLE deliveries, preterm delivery and preeclampsia rates remained stable. Conclusion We observed rates of preeclampsia and preterm delivery in SLE that were five times higher than the general population and higher compared with other prospective SLE cohorts. Furthermore, we did not observe improved outcomes over time with preeclampsia and preterm delivery. Despite increasing evidence for universal use of hydroxychloroquine and aspirin, we did not observe substantially higher use of these medications over time, particularly for aspirin. Our results demonstrate the continued need to prioritize educational and implementation efforts to improve adverse pregnancy outcomes in SLE.

Modern technologies designed for tissue structure visualization like brightfield microscopy, fluorescent microscopy, mass cytometry imaging (MCI) and mass spectrometry imaging (MSI) provide large amounts of quantitative and spatial information about cells and tissue structures like vessels, bronchioles etc. Many published reports have demonstrated that the structural features of cells and extracellular matrix (ECM) and their interactions strongly predict disease development and progression. Computational image analysis methods in combination with spatial analysis and machine learning can reveal novel structural patterns in normal and diseased tissue. Here, we have developed a Python package designed for integrated analysis of cells and ECM in a spatially dependent manner. The package performs segmentation, labeling and feature analysis of ECM fibers, combines this information with pre-generated single-cell based datasets and realizes cell-cell and cell-fiber spatial analysis. To demonstrate performance and compatibility of our computational tool, we integrated it with a pipeline designed for cell segmentation, classification, and feature analysis in the KNIME analytical platform. For validation, we used a set of mouse mammary gland tumors and human lung adenocarcinoma tissue samples stained for multiple cellular markers and collagen as the main ECM protein. The developed package provides sufficient performance and precision to be used as a novel method to investigate cell-ECM relationships in the tissue, as well as detect structural patterns correlated with specific disease outcomes.

Summary Patients with systemic lupus erythematosus (SLE) have an increased risk of developing osteoporosis and fractures due to systemic inflammation and glucocorticoids (GCs). Professional organizations recommend bone mineral density (BMD) testing in SLE patients on GCs, especially within 6 months of initiation. Using a validated algorithm, we identified SLE patients in an electronic health record cohort with long-term GC exposure (≥90 days). Our primary outcome was ever BMD testing. We assessed the impact of patient and provider factors on testing. We identified 693 SLE cases with long-term GC exposure, 41% of whom had BMD testing performed. Only 18% of patients had BMD testing within 6 months of GC initiation. In a logistic regression model for BMD testing, male sex (OR = 0.49, 95% CI 0.27 – 0.87, p = 0.01) was associated with being less likely to have BMD testing after adjusting for race and ethnicity. In contrast, older age (OR = 1.04, p < 0.001) and nephritis (OR = 1.83, p = 0.003) were associated with being more likely to have BMD testing after adjusting for race and ethnicity. Bone health in SLE patients remains an area in need of improvement with attention to patients who are younger and male.

ObjectiveSystemic lupus erythematosus (SLE) poses diagnostic challenges. We undertook this study to evaluate the utility of a phenotype risk score (PheRS) and a genetic risk score (GRS) to identify SLE individuals in a real‐world setting.MethodsUsing a de‐identified electronic health record (EHR) database with an associated DNA biobank, we identified 789 SLE cases and 2,261 controls with available MEGAEX genotyping. A PheRS for SLE was developed using billing codes that captured American College of Rheumatology SLE criteria. We developed a GRS with 58 SLE risk single‐nucleotide polymorphisms (SNPs).ResultsSLE cases had a significantly higher PheRS (mean ± SD 7.7 ± 8.0 versus 0.8 ± 2.0 in controls; P < 0.001) and GRS (mean ± SD 12.2 ± 2.3 versus 11.0 ± 2.0 in controls; P < 0.001). Black individuals with SLE had a higher PheRS compared to White individuals (mean ± SD 10.0 ± 10.1 versus 7.1 ± 7.2, respectively; P = 0.002) but a lower GRS (mean ± SD 9.0 ± 1.4 versus 12.3 ± 1.7, respectively; P < 0.001). Models predicting SLE that used only the PheRS had an area under the curve (AUC) of 0.87. Adding the GRS to the PheRS resulted in a minimal difference with an AUC of 0.89. On chart review, controls with the highest PheRS and GRS had undiagnosed SLE.ConclusionWe developed a SLE PheRS to identify established and undiagnosed SLE individuals. A SLE GRS using known risk SNPs did not add value beyond the PheRS and was of limited utility in Black individuals with SLE. More work is needed to understand the genetic risks of SLE in diverse populations.

The purpose of this study is to determine the pathways by which short-term cigarette smoke exposure induces expression of the cystine-glutamate antiporter xCT (SLC7A11) and its downstream implications in carcinogenesis. BEAS-2B lung epithelial cells and their tumorigenic counterpart, B39-TL cells, were exposed to cigarette smoke condensate (CSC) for 3-15 days. Cells were also exposed to a range of inhibitors. Erastin and buthionine sulfoximine (BSO) are inhibitors of various steps in the glutathione synthesis pathway, found to be hyperactive in xCT-overexpressing cells. Cells were also exposed to the drug mito-2-hydroxybenzoic acid (mito-2-HOBA), which scavenges isolevuglandins, reactive γ-ketoaldehydes implicated in oxidative stress and carcinogenesis. Expression of xCT and related proteins was measured using Western blotting. Glutathione levels were detected using the luciferase-based GSH-Glo assay (Promega). Oxidative stress was detected using dihydroethidium (DHE) fluorescence. It was found that CSC exposure significantly increased the expression of xCT and SLC1A5, a transporter that potentially works in synergy with xCT, and that tumorigenic B39-TL cells had significantly increased xCT and SLC1A5 expression compared to BEAS-2B cells. In addition, BEAS-2B cells exposed to CSC and a glutathione synthesis inhibitor such as erastin or BSO showed faster depletion of glutathione than cells treated with only inhibitor. Finally, it was found that BEAS-2B cells treated for 3 days with CSC did not show increased levels of superoxide compared to control cells. However, cells treated with CSC and mito-2-HOBA together showed significantly increased superoxide. These data suggest that CSC induces an antioxidant response which is ablated by mito-2-HOBA. This antioxidant response seems to at least partially rely on glutathione synthesis fueled by xCT, as evidenced by inhibitor studies. The response also seems to be activated by isolevuglandins, because removing these molecules significantly raises oxidative stress. The mechanistic link between CSC exposure, isolevuglandin generation, and xCT/glutathione induction will be clarified in further experiments. Citation Format: Alex Camai. Determining the role of altered redox metabolism in lung tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2663.