Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.
バイオインフォマティクスと機械学習を統合した変形性関節症における分岐鎖アミノ酸関連遺伝子のバイオマーカー同定 (機械翻訳の邦題)
記録の確認項目
- 研究デザイン
- その他の原著論文
- 対象
- ヒト
- 出版年
- 2025
- 出典
- doi.org
- 抄録の表示
- 表示あり
- 出版状態
- 有効な記録
- 状態確認日
- 2026/08/17
- 収集日
- 2026/08/03
- 鮮度
- 確認期限内
- 確認段階
- 自動処理
- 記録状態
- 公開
日本語要約(機械生成)
変形性関節症(OA)における分岐鎖アミノ酸(BCAA)関連遺伝子(BCAA-RGs)のバイオマーカーと作用機序を明らかにするため、GEOデータベースから得た差次的発現遺伝子とBCAA-RGsの交差により候補遺伝子を特定し、GO・KEGG解析で機構を探索した。さらに3つの機械学習アルゴリズムを用いてOAと強く関連する遺伝子を同定し、診断能をROC曲線で評価した。その結果、8つの候補遺伝子からSLC3A2、SLC7A5、SLC43A2、SLC43A1、SLC7A7の5つが選ばれ、特にSLC3A2とSLC7A5は検証セットとqRT-PCRで確認された。これらはリボソームやインスリンシグナル伝達経路などに関与し、XISTやOIP5-AS1によるマイクロRNAを介した調節が示唆された。また、アセトアミノフェンなど150の薬剤がこれらのバイオマーカーを標的とすることが判明した。本研究はOAの診断と治療に新たな知見を提供する。
この要約は公開抄録のみを根拠にAIが機械的に生成したものです。正確な内容は原文を確認してください。
抄録
Background: Branched-chain amino acids (BCAA) metabolism is significantly associated with osteoarthritis (OA), but the specific mechanism of BCAA related genes (BCAA-RGs) in OA is still unclear. Therefore, this research intended to identify potential biomarkers and mechanisms of action of BCAA-RGs in OA tissues.Methods: Differential genes were obtained from the Gene Expression Omnibus (GEO) database and intersections were taken with BCAA-RGs to identify candidate genes. The underlying mechanisms were revealed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, by combining three machine learning algorithms to identify genes with highly correlated OA features. In addition, created diagnostic maps and subject Receiver operating characteristic curves (ROCs) to assess the ability of the signature genes to diagnose OA and to predict their possible roles in molecular regulatory network axes and molecular signaling pathways.Results: Eight candidate genes were acquired by intersecting 4,178 DEGs and 14 BCAA-RGs. Subsequently, five candidate biomarkers were obtained, namely SLC3A2, SLC7A5, SLC43A2, SLC43A1, and SLC7A7. Importantly, SLC3A2 and SLC7A5 were validated by validation set and qRT-PCR. Furthermore, the nomogram constructed by SLC3A2 and SLC7A5 exhibited excellent accuracy in predicting the incidence of OA. The enrichment results demonstrated that SLC3A2 and SLC7A5 were significantly enriched in ribosome, insulin signaling pathway, olfactory transduction, etc. Meanwhile, we also found XIST regulated SLC7A5 through hsa-miR-30e-5p, and regulated SLC3A2 through hsa-miR-7-5p.OIP5-AS1 regulated SLC7A5 and SLC3A2 through hsa-miR-7-5p. By the way, 150 drugs were identified, including Acetaminophen and Acrylamide, which exhibited simultaneous targeting of these two biomarkers.Conclusion: Based on bioinformatics, SLC3A2 and SLC7A5 were identified as biomarkers related to BCAA in OA, which may provide a new reference for the treatment and diagnosis of OA patients.
MeSH
DOI 10.1186/s12891-025-08779-6
PMID 40420260
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