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.

/pdf/genomic-risk-factors-driving-immune-mediated-delayed-drug-362litgozp.pdf

Genomic Risk Factors Driving Immune-Mediated Delayed Drug Hypersensitivity Reactions.

sMSROC: Assessment of Diagnostic and Prognostic Markers

The endoplasmic reticulum aminopeptidase ERAP1 regulates innate and adaptive immune responses, trimming peptides and loading onto HLA class I molecules. Coding single nucleotide polymorphisms within ERAP1 are associated with autoimmune diseases, viral infections, and cancer development. Our purpose was to analyze the influence of ERAP1 variants on fibrogenesis in hepatitis C virus (HCV)–infected patients. A range of ERAP1 polymorphisms were genotyped in 722 unrelated Caucasian patients diagnosed with chronic HCV from two Spanish cohorts. Patients were classified according to their fibrosis stage. Paraffin-embedded tissue microarrays were constructed to assess ERAP1 expression (HCV = 38; alcoholic = 20) by immunohistochemistry. A statistical algorithm was applied to derive a fibrogenesis prediction model. The ERAP1 variants rs30187/T (K528, pc < 0.001) and rs27044/G (Q730, pc < 0.001) were related with severe fibrosis. These results were validated in the two independent cohorts. Furthermore, patients with the rs30187/T allele had stronger ERAP1 protein expression than those with the rs30187/C (p < 0.05). The statistical model showed that patients with rs30187 C/T and T/T genotypes took 15.58 years (median) to develop advanced fibrosis, but this value was 32.08 years in patients carrying C/C genotype (p < 0.005). ERAP1 variants may influence the clinical course of fibrogenesis in HCV-infected patients. These polymorphisms could be exploited as constitutive new markers of fibrosis evolution. The results highlight the possibility of using modulators of ERAP1 to generate a protective immune response against chronic HCV infection. What is known






 What is new here






 Potential translational impact

Genetic contribution of endoplasmic reticulum aminopeptidase 1 polymorphisms to liver fibrosis progression in patients with HCV infection.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Manuel Rodríguez

Author Tools

Chat about Author

Papers

Genetic contribution of endoplasmic reticulum aminopeptidase 1 polymorphisms to liver fibrosis progression in patients with HCV infection.