ReviewRMD open2026
How multi-omic technologies can help define paediatric undifferentiated systemic autoinflammatory diseases: the experience of the European PerSAIDs consortium.
Review in RMD open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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0 citing papers in PubMed.
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Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systemic AutoInflammatory Diseases (SAIDs) are rare conditions characterised by impaired control of inflammatory and innate immune responses. Precision medicine is already well established for monogenic SAIDs, while personalised approaches remain elusive for those conditions with not identified genetic cause, collectively named undifferentiated SAIDs (uSAIDs).The multi-omic approach integrates findings from various 'omics'" technologies (eg, genomics, transcriptomics, proteomics, epigenomics, immunomics), thus representing a potential way of identifying disease-specific biomarkers or complex molecular patterns, offering significant improvements in diagnosis and personalised therapies. At present, significant challenges remain in patient's sample collection, methodological standardisation and the development of robust bioinformatics tools before the findings can be translated into clinical practice. We provide examples of successful applications of multi-omic analyses to immune-mediated disorders, address the challenges and opportunities associated with multi-omics in paediatric uSAIDs and introduce the ERA PerMed project 'PerSAIDs', which combines multi-omic research with artificial intelligence-based decision support solutions to further advance the diagnosis and management of SAIDs.
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