非酒精性脂肪肝病（NAFLD）是最常见的慢性肝病之一。 NAFLD会导致肝纤维化和肝细胞癌，并且还具有与代谢疾病、心血管疾病、慢性肾脏疾病和恶性肿瘤相关的全身影响。因此，早期诊断 NAFLD 以防止这些不良影响非常重要。从 Gene Expression Omnibus 数据库下载 GSE89632 数据集，然后使用 lasso 和支持向量机递归特征消除（SVM- RFE）。计算诊断 NAFLD 的最佳基因的 ROC 值。使用 DECONVOLUTION 算法 CIBERSORT 确定最佳基因和免疫细胞之间的关系。最后，通过检测 320 名 NAFLD 患者的血液样本和 12 只小鼠的肝脏样本中诊断基因的表达来验证诊断基因的特异性和敏感性。通过机器学习，我们确定 FOSB、GPAT3、RGCC 和 RNF43 是关键的诊断基因。 NAFLD 的基因，并通过受试者工作特征曲线分析进一步证明了它们。我们发现这四种基因的联合诊断可以很好地从正常样本中识别出NAFLD样本（AUC = 0.997）。 FOSB、GPAT3、RGCC 和 RNF43 与免疫细胞浸润密切相关。我们还通过实验检测了这些基因在NAFLD患者和NAFLD小鼠中的表达，结果表明这些基因具有高度的特异性和敏感性。临床和动物研究的数据证明了FOSB、GPAT3、RGCC的高敏感性、特异性和安全性RNF43 用于诊断 NAFLD。诊断关键基因与免疫细胞浸润之间的关系可能有助于了解 NAFLD 的发展。该研究于2021年经天津市第二人民医院伦理委员会审查并批准（ChiCTR1900024415）。© 2024。作者。

Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. NAFLD leads to liver fibrosis and hepatocellular carcinoma, and it also has systemic effects associated with metabolic diseases, cardiovascular diseases, chronic kidney disease, and malignant tumors. Therefore, it is important to diagnose NAFLD early to prevent these adverse effects.The GSE89632 dataset was downloaded from the Gene Expression Omnibus database, and then the optimal genes were screened from the data cohort using lasso and Support Vector Machine Recursive Feature Elimination (SVM-RFE). The ROC values of the optimal genes for the diagnosis of NAFLD were calculated. The relationship between optimal genes and immune cells was determined using the DECONVOLUTION algorithm CIBERSORT. Finally, the specificity and sensitivity of the diagnostic genes were verified by detecting the expression of the diagnostic genes in blood samples from 320 NAFLD patients and liver samples from 12 mice.Through machine learning we identified FOSB, GPAT3, RGCC and RNF43 were the key diagnostic genes for NAFLD, and they were further demonstrated by a receiver operating characteristic curve analysis. We found that the combined diagnosis of the four genes identified NAFLD samples well from normal samples (AUC = 0.997). FOSB, GPAT3, RGCC and RNF43 were strongly associated with immune cell infiltration. We also experimentally examined the expression of these genes in NAFLD patients and NAFLD mice, and the results showed that these genes are highly specific and sensitive.Data from both clinical and animal studies demonstrate the high sensitivity, specificity and safety of FOSB, GPAT3, RGCC and RNF43 for the diagnosis of NAFLD. The relationship between diagnostic key genes and immune cell infiltration may help to understand the development of NAFLD. The study was reviewed and approved by Ethics Committee of Tianjin Second People's Hospital in 2021 (ChiCTR1900024415).© 2024. The Author(s).