Recently, a novel disorder coined VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome was identified in patients with adult-onset inflammatory syndromes, often accompanied by myelodysplastic syndrome1. All patients had myeloid lineage-restricted somatic mutations in UBA1 affecting the Met41 residue of the protein and resulting in decreased cellular ubiquitylation activity and hyperinflammation. We here describe the clinical disease course of two VEXAS syndrome patients with somatic UBA1 mutations of which one with a mild phenotype characterized by recurrent rash and symmetric polyarthritis, and another who was initially diagnosed with idiopathic multicentric Castleman disease and developed macrophage activation syndrome as a complication of the VEXAS syndrome. The latter patients was treated with anti-IL6 therapy (siltuximab) leading to a resolution of systemic symptoms and reduction of transfusion requirements.

The molecular basis of interindividual clinical variability upon infection with Staphylococcus aureus is unclear. We describe patients with haploinsufficiency for the linear deubiquitinase OTULIN, encoded by a gene on chromosome 5p. Patients suffer from episodes of life-threatening necrosis, typically triggered by S. aureus infection. The disorder is phenocopied in patients with the 5p− (Cri-du-Chat) chromosomal deletion syndrome. OTULIN haploinsufficiency causes an accumulation of linear ubiquitin in dermal fibroblasts, but tumor necrosis factor receptor–mediated nuclear factor κB signaling remains intact. Blood leukocyte subsets are unaffected. The OTULIN-dependent accumulation of caveolin-1 in dermal fibroblasts, but not leukocytes, facilitates the cytotoxic damage inflicted by the staphylococcal virulence factor α-toxin. Naturally elicited antibodies against α-toxin contribute to incomplete clinical penetrance. Human OTULIN haploinsufficiency underlies life-threatening staphylococcal disease by disrupting cell-intrinsic immunity to α-toxin in nonleukocytic cells.

Drug hypersensitivity reactions (DHR) have been present since the advent of drugs. In particular T‐cell mediated delayed‐type hypersensitivity reactions represent a heterogeneous clinical entity with a diverse pathogenesis and result in a considerable burden of morbidity and mortality not only driven by the reactions themselves but also by the use of alternatives which are sometimes less effective or even more dangerous. Diagnostic procedures rely on clinical history, skin testing and potential provocation testing, whereas validated in vitro diagnostic procedures are still lacking for most of them. Recent work in the field of pharmacogenomics combined with basic scientific research has provided insights in the pathogenesis of abacavir and carbamazepine hypersensitivities linked with certain human leucocyte antigen risk alleles. Nevertheless, important scientific questions on how other DHR arise and how host‐drug interactions occur, remain unanswered. Recent work indicates an intricate relation between host, drug and pathogens in severe cutaneous and systemic reactions and provides more insights in the role of regulatory T‐cells and viral reactivation in these reactions. In this review we focus on type IV delayed‐type DHR, and address recent advances in the pathogenesis, pharmacogenomics, and diagnosis of these reactions with an emphasis on the understandings arising from basic research.

Inborn errors of immunity (IEI) are a heterogenous group of disorders driven by genetic defects that functionally impact the development and/or function of the innate and/or adaptive immune system. The majority of these disorders are thought to have polygenic background. However, the use of next-generation sequencing in patients with IEI has led to an increasing identification of monogenic causes, unravelling the exact pathophysiology of the disease and allowing the development of more targeted treatments. Monogenic IEI are not only seen in a pediatric population but also in adulthood, either due to the lack of awareness preventing childhood diagnosis or due to a delayed onset where (epi)genetic or environmental factors can play a role. In this review, we discuss the mechanisms accounting for adult-onset presentations and provide an overview of monogenic causes associated with adult-onset IEI.

Background: Clinical decision support systems are implemented in many hospitals to prevent medication errors and associated harm. They are however associated with a high burden of false positive alerts and alert fatigue. The aim of this study was to evaluate a drug–drug interaction (DDI) clinical decision support system in terms of its performance, uptake and user satisfaction and to identify barriers and opportunities for improvement. Methods: A quantitative evaluation and end-user survey were performed in a large teaching hospital. First, very severe DDI alerts generated between 2019 and 2021 were evaluated retrospectively. Data collection comprised alert burden, override rates, the number of alert overrides reviewed by pharmacists and the resulting pharmacist recommendations as well as their acceptance rate. Second, an e-survey was carried out among prescribers to assess satisfaction, usefulness and relevance of DDI alerts as well as reasons for overriding. Results: A total of 38,409 very severe DDI alerts were generated, of which 88.2% were overridden by the prescriber. In 3.2% of reviewed overrides, a recommendation by the pharmacist was provided, of which 79.2% was accepted. False positive alerts were caused by a too broad screening interval and lack of incorporation of patient-specific characteristics, such as QTc values. Co-prescribing of a non-vitamin K oral anticoagulant and a low molecular weight heparin accounted for 49.8% of alerts, of which 92.2% were overridden. In 88 (1.1%) of these overridden alerts, concurrent therapy was still present. Despite the high override rate, the e-survey revealed that the DDI clinical decision support system was found useful by prescribers. Conclusions: Identified barriers were the lack of DDI-specific screening intervals and inclusion of patient-specific characteristics, both leading to a high number of false positive alerts and risk for alert fatigue. Despite these barriers, the added value of the DDI clinical decision support system was recognized by prescribers. Hence, integration of DDI-specific screening intervals and patient-specific characteristics is warranted to improve the performance of the DDI software.