Evidence map›Paper›PMID 42558604›Full record

ArticleFrontiers in pediatrics2026

Implications of isonicotinylation-associated patterns in NK cells in the pathogenesis of Kawasaki disease: evidence from artificial intelligence-driven multi-omics and clinical validation.

Yanli Yang, Pengjuan Hu

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Yanli YangDepartment of Cardiovascular and Rheumatology Immunology, Children's Hospital of Shanxi Province, Taiyuan City, China.
Pengjuan HuDepartment of Cardiovascular and Rheumatology Immunology, Children's Hospital of Shanxi Province, Taiyuan City, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Kawasaki disease (KD) is a systemic vasculitis of childhood driven by aberrant immune activation. Natural killer (NK) cell dysregulation plays a critical role, but its upstream molecular mechanisms remain unclear. Isonicotinylation (Kinic), a novel lysine acylation acting as a metabolic sensor, represents an unexplored regulatory layer in KD. Methods: We employed an artificial intelligence (AI)-driven multi-omics framework. Limma differential expression analysis on GSE68004 (KD patient bulk profile) identified Kinic-related differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) and CIBERSORT on GSE18606 (KD patient bulk profile) delineated an NK cell-correlated module. Their intersection defined Kinic- and NK (KN)-related signature, which was used to construct a diagnostic model via an explainable machine learning pipeline on KD patient bulk profiles (GSE73463, GSE73462, and GSE63881). The central hub gene was validated using KD patient single-cell RNA-sequencing (scRNA-seq) data (GSE24757). An AI-based drug screen (DrugReflector) and molecular docking nominated therapeutic candidates. Finally, PPID expression was validated in an independent clinical cohort using q-RT-PCR. Results: We identified a six-gene KN-associated signature that demonstrated excellent diagnostic performance. PPID can be considered upregulated hub gene. Single-cell analysis confirmed predominant PPID expression in NK cells and linked its function to epigenetic modification and inflammatory signaling. Drug screening nominated BRD-K90382497 as a potential PPID-targeting compound. Conclusion: This study unveils a novel KN-associated molecular axis in KD pathogenesis, with PPID as an NK cell-centric hub. This axis provides a promising diagnostic biomarker and identifies a potential therapeutic target, bridging a novel metabolic modification to NK cell dysfunction in KD.

Indexed as

artificial intelligenceisonicotinylationKawasaki diseasemulti-omicsNK cells

Identifiers

PMID42558604
PMCPMC13437692

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