Objective To characterize patients with systemic lupus erythematosus (SLE) affected by coronavirus disease 2019 (COVID‐19) and to analyze associations of comorbidities and medications on infection outcomes. Methods Patients with SLE and reverse transcriptase–polymerase chain reaction–confirmed COVID‐19 were identified through an established New York University lupus cohort, query of 2 hospital systems, and referrals from rheumatologists. Data were prospectively collected via a web‐based questionnaire and review of medical records. Data on baseline characteristics were obtained for all patients with COVID‐19 to analyze risk factors for hospitalization. Data were also collected on asymptomatic patients and those with COVID‐19–like symptoms who tested negative or were not tested. Statistical analyses were limited to confirmed COVID‐19–positive patients. Results A total of 226 SLE patients were included: 41 with confirmed COVID‐19, 19 who tested negative for COVID‐19, 42 with COVID‐19–like symptoms who did not get tested, and 124 who remained asymptomatic without testing. Of the SLE patients with confirmed COVID‐19, hospitalization was required in 24 (59%) and intensive care unit–level of care in 4, and 4 died. Hospitalized patients tended to be older, nonwhite, Hispanic, have higher body mas index (BMI), history of nephritis, and at least 1 comorbidity. An exploratory (due to limited sample size) logistic regression analysis identified race, presence of at least 1 comorbidity, and BMI as independent predictors of hospitalization. Conclusion In general, the variables predictive of hospitalization in our SLE patients were similar to those identified in the general population. Further studies are needed to understand additional risk factors for poor COVID‐19 outcomes in patients with SLE.

The stability of various pesticides in water at 4 °C was compared with their stability on C-18 SPE disks under three storage regimes. The disk storage regimes involved using the disk to extract the chemical from water, removing the disk and placing it in a plastic bag, and then storing it at either -20 or +4 °C for 1 day and then -20 °C for the remainder of the storage period. The storage periods included 0, 3, 30, 90, and 180 days. The percent recovery of each chemical was determined and used to compare storage treatments. Results indicate that the pesticides have equivalent or greater stability on solid-phase extraction disks compared to their storage in water at 4 °C. The data suggest that freezing the disk after pesticide loading is the most favorable storage option. Results show that field extraction/storage methodology is feasible, which could improve the reliability of future environmental water sampling procedures.

Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. Methods: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. Results: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. Conclusion:The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

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