[關鍵詞]
[摘要]
目的 考察靶向下一代測序分析耐藥結核病使用抗結核藥物后的耐藥基因突變特征。方法 收集2022年2月—2023年8月南寧市第四人民醫(yī)院結核科收治的87例結核病患者的菌株。以表型藥物敏感性試驗結果為參照標準,采用靶向下一代測序檢出利福平、異煙肼、鏈霉素和乙胺丁醇的耐藥突變基因分布、診斷效能,與Xpert MTB/RIF比較對利福平耐藥的診斷效能。結果 利福平耐藥基因突變類型以Ser531Leu(rpoB)為主,異煙肼耐藥基因突變類型以Ser315Thr(katG)為主,鏈霉素耐藥基因突變類型以Lys43Arg(rpsL)為主,乙胺丁醇耐藥基因突變類型以Met306Val(embB)為主。以表型藥物敏感性試驗結果為參照標準,靶向下一代測序對利福平、異煙肼、鏈霉素和乙胺丁醇的準確率均大于80%,Xpert MTB/RIF檢測利福平耐藥的各指標均低于靶向下一代測序。結論 靶向下一代測序診斷利福平、異煙肼、鏈霉素和乙胺丁醇耐藥性表現(xiàn)出較高的敏感度、特異度和準確率。
[Key word]
[Abstract]
Objective To explore the mutation characteristics of drug-resistant genes in drug-resistant tuberculosis patients treated with antituberculosis drugs by targeting next generation sequencing analysis. Methods The strains from 87 tuberculosis patients admitted to the Tuberculosis Department of Nanning Fourth People's Hospital from February 2022 to August 2023 were collected. Based on the results of phenotype drug sensitivity tests, targeting next generation sequencing analysis was used to detect the distribution and diagnostic efficacy of resistance mutation genes for rifampicin, isoniazid, streptomycin, and ethambutol. The diagnostic efficacy for rifampicin resistance was compared with Xpert MTB/RIF. Results The mutation types of rifampicin resistance genes were mainly Ser531Leu (rpoB), isoniazid resistance genes were mainly Ser315Thr (katG), streptomycin resistance genes were mainly Lys43Arg (rpsL), and ethambutol resistance genes were mainly Met306Val (embB). Based on the results of phenotype drug sensitivity tests, the accuracy of targeting next generation sequencing analysis results for rifampicin, isoniazid, streptomycin, and ethambutol were greater than 80%. The Xpert MTB/RIF detection of rifampicin resistance indicators was lower than that of targeting next generation sequencing analysis. Conclusion Targeting next generation sequencing analysis has shown high sensitivity, specificity, and accuracy in diagnosing resistance to rifampicin, isoniazid, streptomycin, and ethambutol.
[中圖分類號]
R969
[基金項目]
廣西自然科學基金資助項目(2023GXNSFAA026022);廣西生健康委員會自籌經費科研課題(Z-A20231211)