AIがクローン病の早期診断と治療への新たな道を開く (AI opens routes to Crohn’s disease diagnosis and treatment)

ad

2026-08-12 バーミンガム大学

英国のUniversity of Birminghamの研究チームは、人工知能(AI)を活用してクローン病の早期診断と治療につながる新たな手法を開発した。クローン病は炎症性腸疾患の一種で、診断までに長期間を要することが多く、その間に症状の悪化や腸管損傷が進行する恐れがある。研究では、大規模な医療データをAIで解析し、診断前の段階から患者に共通するパターンやリスク因子を特定した。その結果、従来より早い時点でクローン病の可能性を検出できることが示された。さらに、患者ごとの病態や進行リスクを把握することで、より適切な治療選択や介入時期の判断にも役立つ可能性が示された。今回の成果は、診断の遅れによる合併症リスクの低減や患者の生活の質向上に貢献するとともに、AIを活用した個別化医療の発展を後押しすることが期待される。

<関連情報>

クローン病における炎症性および線維性疾患状態全体にわたる、生成AIで強化されたトランスクリプトームおよびマイクロバイオーム解析 Generative AI-augmented transcriptomic and microbiome analysis across inflammatory and fibrotic disease states in Crohn’s disease

Daryll Philip,Daniela Santos,Sudip Mondal,Haneen Alomar,Georgios Gkoutos,Animesh Acharjee
Frontiers in Artificial Intelligence  Published:04 August 2026
DOI:https://doi.org/10.3389/frai.2026.1881820

Flowchart diagram illustrating the workflow for studying intestinal disease progression, from dataset and sample acquisition through transcriptomic and microbiome analyses, LLM-based synthetic data augmentation, model training with baseline and fibrotic Crohn’s disease, to predictive modeling, correlation heatmaps, and network analysis.

Abstract

Introduction:
Intestinal fibrosis is a major complication of Crohn’s disease (CD), a subtype of inflammatory bowel disease (IBD) driven by chronic inflammation and resulting in irreversible structural damage requiring surgery. However, the molecular differences between inflammatory and fibrotic CD remain poorly defined.

Methods:
Here, we developed an integrated multi-omics framework combining transcriptomics, microbiome analysis, and generative AI to characterise transcriptomic differences across non-IBD (n = 176), baseline CD (n = 187), and fibrosis CD (n = 85) tissues. Bulk and single-cell RNA-seq and 16S rRNA datasets were integrated, and machine learning identified disease-stage associated features.

Results:
A shared set of 43 genes between baseline and fibrotic CD was organised into three modules: Module 1 (S100A8, TREM1, CXCL1) linked to innate immune activation which was upregulated in fibrosis CD; Module 2 (FABP6, MGAM, ALDOB) reflecting epithelial metabolic dysfunction which was upregulated in baseline CD; and Module 3 (CHI3L1, SAA2-SAA4, IL1RN) associated with epithelial stress and loss of barrier integrity. GSVA highlighted LCN2 and MMP3 across disease states. Microbiome analysis showed depletion of SCFA-producing genera (Faecalibacterium, Anaerostipes, Coprococcus, Ruminococcus) and enrichment of Bilophila and Bacteroides. Notably, LLM-guided augmentation improved model stability and facilitated the identification of key fibrosis-associated genes, including IL-23R, TNF-α, and TGF-β.

Discussion:
These findings suggest that intestinal fibrosis in CD does not represent a separate molecular state, but a reconfigured inflammatory condition characterised by persistent immune activation, epithelial dysfunction, and altered host-microbiome interactions.

医療・健康
ad
ad
Follow
ad
タイトルとURLをコピーしました