Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Front Cell Infect Microbiol. 2018 Sep 20;8:307. doi: 10.3389/fcimb.2018.00307. eCollection 2018.
Sexually transmitted infection (STI) of the upper reproductive tract can result in inflammation and infertility. A biomarker of STI-induced upper tract inflammation would be significant as many women are asymptomatic and delayed treatment increases risk of sequelae. Blood mRNA from 111 women from three cohorts was profiled using microarray. Unsupervised analysis revealed a transcriptional profile that distinguished 9 cases of STI-induced endometritis from 18 with cervical STI or uninfected controls. Using a hybrid feature selection algorithm we identified 21 genes that yielded maximal classification accuracy within our training dataset. Predictive accuracy was evaluated using an independent testing dataset of 5 cases and 10 controls. Sensitivity was evaluated in a separate test set of 12 women with asymptomatic STI-induced endometritis in whom cervical burden was determined by PCR; and specificity in an additional test set of 15 uninfected women with pelvic pain due to unknown cause. Disease module preservation was assessed in 42 women with a clinical diagnosis of pelvic inflammatory disease (PID). We also tested the ability of the biomarker to discriminate STI-induced endometritis from other diseases. The biomarker was 86.7% (13/15) accurate in correctly distinguishing cases from controls in the testing dataset. Sensitivity was 83.3% (5/6) in women with high cervical burden and asymptomatic endometritis, but 0% (0/6) in women with low burden. Specificity in patients with non-STI-induced pelvic pain was 86.7% (13/15). Disease modules were preserved in all 8 biomarker predicted cases. The 21-gene biomarker was highly discriminatory for systemic infections, lupus, and appendicitis, but wrongly predicted tuberculosis as STI-induced endometritis in 52.4%. A 21-gene biomarker can identify asymptomatic women with STI-induced endometritis that places them at risk for chronic disease development and discriminate STI-induced endometritis from non-STI pelvic pain and other diseases.
性传播感染（STI）上生殖道可导致炎症和不孕。STI 引起的上生殖道炎症的生物标志物将是重要的，因为许多妇女无症状，延迟治疗会增加后遗症的风险。使用微阵列对来自三个队列的 111 名女性的血液 mRNA 进行了分析。无监督分析显示出一种转录谱，可以区分 9 例 STI 引起的子宫内膜炎与 18 例宫颈 STI 或未感染对照。使用混合特征选择算法，我们确定了 21 个基因，这些基因在我们的训练数据集中产生了最大的分类准确性。使用 5 例和 10 例对照的独立测试数据集评估预测准确性。在另一组 12 例无症状 STI 引起的子宫内膜炎妇女中，通过 PCR 确定宫颈负担的独立测试组中评估了敏感性；在另外一组 15 例因不明原因导致盆腔疼痛的未感染妇女中评估了特异性。在 42 例临床诊断为盆腔炎性疾病（PID）的妇女中评估了疾病模块的保存。我们还测试了该生物标志物区分 STI 引起的子宫内膜炎与其他疾病的能力。在测试数据集，该生物标志物正确区分病例和对照组的准确率为 86.7%（13/15）。在宫颈负担高且无症状子宫内膜炎的妇女中，敏感性为 83.3%（5/6），但在负担低的妇女中为 0%（0/6）。在非 STI 引起的盆腔疼痛患者中，特异性为 86.7%（13/15）。在所有 8 个预测病例中均保存了疾病模块。21 基因生物标志物对系统性感染、狼疮和阑尾炎具有高度的鉴别能力，但错误地将结核病预测为 STI 引起的子宫内膜炎，准确率为 52.4%。21 基因生物标志物可识别无症状的 STI 引起的子宫内膜炎妇女，使她们面临慢性疾病发展的风险，并可将 STI 引起的子宫内膜炎与非 STI 性盆腔疼痛和其他疾病区分开来。
