CAJ | 학술논문

目的探讨慢性乙型肝炎肝纤维化患者血清差异蛋白质表达的临床意义,为肝纤维化的无创诊断提供依据.方法经肝活体组织检查证实为慢性乙型肝炎患者110例,建模组83例,验证组27例.肝纤维化按Ishak分期F≥3期为明显肝纤维化,建模组明显肝纤维化(F≥3)55例,无-轻度肝纤维化(F0～F2)28例,验证组明显肝纤维化15例,无-轻度肝纤维化12例.用基质辅助激光解析电离高分辨飞行时间串联质谱检测标本的血清蛋白质,得到每个样品的质谱图,应用FlexAnalsis3.0分析软件得到差异蛋白质图谱,并与临床病理诊断进行比较,建立遗传算法的诊断模型,并对模型的诊断效能进行验证.结果明显肝纤维化组(F≥3)与无-轻度肝纤维化组(F0～F2)患者蛋白质图谱比较,得到差异有统计学意义(P＜0.01)的差异蛋白质15个,其中最显著的蛋白质为2081.73 m/z和1944.41 m/z,以这两个差异最显著的蛋白峰建立坐标系的样品分布,建立6个特征蛋白峰组成的遗传算法模型,采用该模型对12例无-轻度肝纤维化组患者、15例明显肝纤维化组患者进行验证,结果识别率为100%,预测能力为94.14%,准确率为100%.结论检测血清差异蛋白质表达可早期判断患者肝纤维化的程度.
목적 탐토만성을형간염간섬유화환자혈청차이단백질표체적림상의의,위간섬유화적무창진단제공의거.방법 경간활체조직검사증실위만성을형간염환자110례,건모조83례,험증조27례.간섬유화안Ishak분기F≥3기위명현간섬유화,건모조명현간섬유화(F≥3)55례,무-경도간섬유화(F0～F2)28례,험증조명현간섬유화15례,무-경도간섬유화12례.용기질보조격광해석전리고분변비행시간천련질보검측표본적혈청단백질,득도매개양품적질보도,응용FlexAnalsis3.0분석연건득도차이단백질도보,병여림상병리진단진행비교,건립유전산법적진단모형,병대모형적진단효능진행험증.결과 명현간섬유화조(F≥3)여무-경도간섬유화조(F0～F2)환자단백질도보비교,득도차이유통계학의의(P＜0.01)적차이단백질15개,기중최현저적단백질위2081.73 m/z화1944.41 m/z,이저량개차이최현저적단백봉건립좌표계적양품분포,건립6개특정단백봉조성적유전산법모형,채용해모형대12례무-경도간섬유화조환자、15례명현간섬유화조환자진행험증,결과식별솔위100%,예측능력위94.14%,준학솔위100%.결론 검측혈청차이단백질표체가조기판단환자간섬유화적정도.
Objective To investigate the clinical significance of the expression of serum differential protein in patients with chronic hepatitis B (CHB) related liver fibrosis. Methods One hundred and ten CHB patients confirmed by liver biopsies were enrolled, 83 for modeling and 27 for verification. According to Ishak staging, 55 patients in the modeling group were with significant liver fibrosis (F ≥ 3) and 28 patients with normal/mild liver fibrosis (F0-F2). While that in the verification group were 15 (F ≥ 3) and 12 (F0-F2), respectively. MALDI-TOF-MS/MS was used to detect serum proteins and the spectrum for each sample was analyzed in FlexAnalysis3.0 to produce the spectrum of differential proteins. The results were compared with clinicopathologic diagnosis and the diagnosis model based on genetic algorithm was established and evaluated. Results There were 15 proteins differentially expressed in significant liver fibrosis group and normal/mild fibrosis group (P ＜ 0.01), in which the differences on proteins 2081.73 m/z and 1944.41 m/z were the most significant. Based on these two proteins, the coordinate system was set up and the diagnosis model based on genetic algorithm was established by six characteristic peaks. After detecting 12 cases of normal/mild liver fibrosis and 15 cases of significant liver fibrosis, the results showed that the diagnostic model could identify significant fibrosis (F ≥ 3) and normal/mild liver fibrosis (F0-F2) at 100% recognition, 94.14% prediction and 100% accuracy. Conclusion Serum differential proteins examination can be used for early prediction of CHB related fibrosis. The study provides the basis for non-invasive diagnosis of hepatic fibrosis according to identifying the potential differences of the serum samples from patients with HBV related fibrosis.