ArticleJCI insight2024
IFN-signaling gene expression as a diagnostic biomarker for monogenic interferonopathies.
Article in JCI insight, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Targeting ADAR1 in Cancer: Biology, Therapeutic Strategies, Challenges, and Limitations.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Melanoma cell states shape spatial tumor-immune ecosystems to dictate the efficacy of anti-PD1 immunotherapy.Journal for immunotherapy of cancer · 2026Article
- Mechanistic insights and therapeutic potential of targeting the cGAS-STING pathway in neurodegenerative diseases.Journal of neuroinflammation · 2026Review
- Rigorous genetic diagnosis review in natural history studies.Orphanet journal of rare diseases · 2026Article
- Article
- Gene expression profiling of dendritic cell tolerance dysfunction in women with systemic lupus erythematosus.Frontiers in immunology · 2026Article
- Two rare mutations in homozygosity synergize to silence TREX1 in Aicardi-Goutières syndrome.Frontiers in immunology · 2025Article
- Targeting TSPEAR-AS2 suppresses tumor growth and interferon signaling in esophageal cancer.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
IFN-signaling gene (ISG) expression scores are potential markers of inflammation with significance from cancer to genetic syndromes. In Aicardi Goutières Syndrome (AGS), a disorder of abnormal DNA and RNA metabolism, this score has potential as a diagnostic biomarker, although the approach to ISG calculation has not been standardized or validated. To optimize ISG calculation and validate ISG as a diagnostic biomarker, mRNA levels of 36 type I IFN response genes were quantified from 997 samples (including 334 AGS), and samples were randomized into training and test data sets. An independent validation cohort (n = 122) was also collected. ISGs were calculated using all potential combinations up to 6 genes. A 4-gene approach (IFI44L, IFI27, USP18, IFI6) was the best-performing model (AUC of 0.8872 [training data set], 0.9245 [test data set]). The majority of top-performing gene combinations included IFI44L. Performance of IFI44L alone was 0.8762 (training data set) and 0.9580 (test data set) by AUC. The top approaches were able to discriminate individuals with genetic interferonopathy from control samples. This study validates the context of use for the ISG score as a diagnostic biomarker and underscores the importance of IFI44L in diagnosis of genetic interferonopathies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.