دورية أكاديمية
Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model
| العنوان: | Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model |
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| المؤلفون: | Hui Xie, Yin-mei Deng, Jiao-yan Li, Kai-hong Xie, Tan Tao, Jian-fang Zhang |
| المصدر: | Heliyon, Vol 10, Iss 10, Pp e31307- (2024) |
| بيانات النشر: | Elsevier, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Science (General) LCC:Social sciences (General) |
| مصطلحات موضوعية: | N7-methylguanosine, Machine learning, Primary Sjögren's syndrome, Gene expression omnibus database, Science (General), Q1-390, Social sciences (General), H1-99 |
| الوصف: | Objectives: N7-methylguanosine (m7G) plays a crucial role in mRNA metabolism and other biological processes. However, its regulators' function in Primary Sjögren's Syndrome (PSS) remains enigmatic. Methods: We screened five key m7G-related genes across multiple datasets, leveraging statistical and machine learning computations. Based on these genes, we developed a prediction model employing the extreme gradient boosting decision tree (XGBoost) method to assess PSS risk. Immune infiltration in PSS samples was analyzed using the ssGSEA method, revealing the immune landscape of PSS patients. Results: The XGBoost model exhibited high accuracy, AUC, sensitivity, and specificity in both training, test sets and extra-test set. The decision curve confirmed its clinical utility. Our findings suggest that m7G methylation might contribute to PSS pathogenesis through immune modulation. Conclusions: m7G regulators play an important role in the development of PSS. Our study of m7G-realted genes may inform future immunotherapy strategies for PSS. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2405-8440 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2405844024073389; https://doaj.org/toc/2405-8440 |
| DOI: | 10.1016/j.heliyon.2024.e31307 |
| URL الوصول: | https://doaj.org/article/0679c87465984e9bba6c3112135c95a2 |
| رقم الأكسشن: | edsdoj.0679c87465984e9bba6c3112135c95a2 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 24058440 |
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| DOI: | 10.1016/j.heliyon.2024.e31307 |