The human leukocyte antigen (HLA) system is the most polymorphic in the human genome that has been associated with protection and predisposition to a broad array of infectious, autoimmune, and malignant diseases. More recently over the last two decades, HLA class I alleles have been strongly associated with T‐cell‐mediated drug hypersensitivity reactions. In the case of abacavir hypersensitivity and HLA‐B*57:01, the 100% negative predictive value and low number needed to test to prevent a single case has led to a durable and effective global preprescription screening strategy. However, HLA associations are still undefined for most drugs clinically associated with different delayed drug hypersensitivity phenotypes, and an HLA association relevant to one population is not generalizable across ethnicities. Furthermore, while a specific risk HLA allele is necessary for drug‐induced T‐cell activation, it is not sufficient. The low and incomplete positive predictive value has hindered efforts at clinical implementation for many drugs but has provided the impetus to understand the mechanisms of HLA class I restricted T‐cell‐mediated drug hypersensitivity reactions. Current research has focused on defining the contribution of additional elements of the adaptive immune response and other genetic and ecologic risk factors that contribute to drug hypersensitivity risk. In this review we focus on new insights into immunological, pharmacological, and genetic mechanisms underpinning HLA‐associated drug reactions and the implications for future translation into clinical care.

Type B adverse drug reactions (ADRs) are iatrogenic immune-mediated syndromes with mechanistic etiologies that remain incompletely understood. Some of the most severe ADRs, including delayed drug hypersensitivity reactions, are T-cell mediated, restricted by specific human leukocyte antigen risk alleles and sometimes by public or oligoclonal T-cell receptors (TCRs), central to the immunopathogenesis of tissue-damaging response. However, the specific cellular signatures of effector, regulatory, and accessory immune populations that mediate disease, define reaction phenotype, and determine severity have not been defined. Recent development of single-cell platforms bringing together advances in genomics and immunology provides the tools to simultaneously examine the full transcriptome, TCRs, and surface protein markers of highly heterogeneous immune cell populations at the site of the pathological response at a single-cell level. However, the requirement for advanced bioinformatics expertise and computational hardware and software has often limited the ability of investigators with the understanding of diseases and biological models to exploit these new approaches. Here we describe the features and use of a state-of-the-art, fully integrated application for analysis and visualization of multiomic single-cell data called Visual Genomics Analysis Studio (VGAS). This unique user-friendly, Windows-based graphical user interface is specifically designed to enable investigators to interrogate their own data. While VGAS also includes tools for sequence alignment and identification of associations with host or organism genetic polymorphisms, in this review we focus on its application for analysis of single-cell TCR–RNA–Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE)-seq, enabling holistic cellular characterization by unbiased transcriptome and select surface proteome. Critically, VGAS does not require user-directed coding or access to high-performance computers, instead incorporating performance-optimized hidden code to provide application-based fast and intuitive tools for data analyses and production of high-resolution publication-ready graphics on standard specification laptops. Specifically, it allows analyses of comprehensive single-cell TCR sequencing (scTCR-seq) data, detailing (i) functional pairings of α–β heterodimer TCRs, (ii) one-click histograms to display entropy and gene rearrangements, and (iii) Circos and Sankey plots to visualize clonality and dominance. For unbiased single-cell RNA sequencing (scRNA-seq) analyses, users extract cell transcriptome signatures according to global structure via principal component analysis, t-distributed stochastic neighborhood embedding, or uniform manifold approximation and projection plots, with overlay of scTCR-seq enabling identification and selection of the immunodominant TCR-expressing populations. Further integration with similar sequence-based detection of surface protein markers using oligo-labeled antibodies (CITE-seq) provides comparative understanding of surface protein expression, with differential gene or protein analyses visualized using volcano plot or heatmap functions. These data can be compared to reference cell atlases or suitable controls to reveal discrete disease-specific subsets, from epithelial to tissue-resident memory T-cells, and activation status, from senescence through exhaustion, with more finite transcript expression displayed as violin and box plots. Importantly, guided tutorial videos are available, as are regular application updates based on the latest advances in bioinformatics and user feedback.

Adverse drug reactions (ADRs) remain associated with significant mortality. Delayed hypersensitivity reactions (DHRs) that occur greater than 6 h following drug administration are T-cell mediated with many severe DHRs now associated with human leukocyte antigen (HLA) risk alleles, opening pathways for clinical prediction and prevention. However, incomplete negative predictive value (NPV), low positive predictive value (PPV), and a large number needed to test (NNT) to prevent one case have practically prevented large-scale and cost-effective screening implementation. Additional factors outside of HLA contributing to risk of severe T-cell-mediated DHRs include variation in drug metabolism, T-cell receptor (TCR) specificity, and, most recently, HLA-presented immunopeptidome-processing efficiencies via endoplasmic reticulum aminopeptidase (ERAP). Active research continues toward identification of other highly polymorphic factors likely to impose risk. These include those previously associated with T-cell-mediated HLA-associated infectious or auto-immune disease such as Killer cell immunoglobulin-like receptors (KIR), epistatically linked with HLA class I to regulate NK- and T-cell-mediated cytotoxic degranulation, and co-inhibitory signaling pathways for which therapeutic blockade in cancer immunotherapy is now associated with an increased incidence of DHRs. As such, the field now recognizes that susceptibility is not simply a static product of genetics but that individuals may experience dynamic risk, skewed toward immune activation through therapeutic interventions and epigenetic modifications driven by ecological exposures. This review provides an updated overview of current and proposed genetic factors thought to predispose risk for severe T-cell-mediated DHRs.

The angiotensin type 2 (AT2) receptor and the bradykinin type 2 (B2) receptor are G protein-coupled receptors (GPCRs) that have major roles in the cardiovascular system. The two receptors are known to functionally interact at various levels, and there is some evidence that the observed crosstalk may occur as a result of heteromerization. We investigated evidence for heteromerization of the AT2 receptor and the B2 receptor in HEK293FT cells using various bioluminescence resonance energy transfer (BRET)-proximity based assays, including the Receptor Heteromer Investigation Technology (Receptor-HIT) and the NanoBRET ligand-binding assay. The Receptor-HIT assay showed that Gαq, GRK2 and β-arrestin2 recruitment proximal to AT2 receptors only occurred upon B2 receptor coexpression and activation, all of which is indicative of AT2-B2 receptor heteromerization. Additionally, we also observed specific coupling of the B2 receptor with the Gαz protein, and this was found only in cells coexpressing both receptors and stimulated with bradykinin. The recruitment of Gαz, Gαq, GRK2 and β-arrestin2 was inhibited by B2 receptor but not AT2 receptor antagonism, indicating the importance of B2 receptor activation within AT2-B2 heteromers. The close proximity between the AT2 receptor and B2 receptor at the cell surface was also demonstrated with the NanoBRET ligand-binding assay. Together, our data demonstrate functional interaction between the AT2 receptor and B2 receptor in HEK293FT cells, resulting in novel pharmacology for both receptors with regard to Gαq/GRK2/β-arrestin2 recruitment (AT2 receptor) and Gαz protein coupling (B2 receptor). Our study has revealed a new mechanism for the enigmatic and poorly characterized AT2 receptor to be functionally active within cells, further illustrating the role of heteromerization in the diversity of GPCR pharmacology and signaling.

Purpose of reviewAn update of the pharmacogenetic risk factors associated with T-cell-mediated delayed hypersensitivity reactions. Recent findingsRecent HLA associations relevant to our understanding of immunopathogenesis and clinical practice include HLA-B Ã 13:01 with co-trimoxazole-induced SCAR, and HLA-A Ã 32:01 with vancomycin-DRESS, for which an extended HLA class II haplotype is implicated in glycopeptide antibiotic cross-reactivity. Hypoactive variants of ERAP1, an enzyme-trimming peptide prior to HLA loading, are now associated with protection from abacavir-hypersensitivity in HLA-B Ã 57:01þ patients, and single-cell sequencing has defined the skinrestricted expansion of a single, public and drug-reactive dominant TCR across patients with HLA-B Ã 15:02restricted carbamazepine-induced SJS/TEN. More recent strategies for the use of HLA and other risk factors may include risk-stratification, early diagnosis, and diagnosis in addition to screening. SummaryHLA is necessary but insufficient as a risk factor for the development of most T-cell-mediated reactions. Newly emerged genetic and ecological risk factors, combined with HLA-restricted response, align with underlying immunopathogenesis and drive towards enhanced strategies to improve positive-predictive and negative-predictive values. With large population-matched cohorts, genetic studies typically focus on populations that have been readily accessible to research studies, but it is now imperative to address similar risk in globally relevant and understudied populations.