Francis I Proctor Foundation, University of California, San Francisco.
Department of Ophthalmology, University of California, San Francisco.
JAMA Ophthalmol. 2024 Sep 1;142(9):865-871. doi: 10.1001/jamaophthalmol.2024.2891.
Infectious conjunctivitis can lead to corneal involvement and result in ocular morbidity. The identification of biomarkers associated with corneal involvement has the potential to improve patient care.
To identify biomarkers in patients with acute infectious conjunctivitis.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study took place from December 2016 to March 2024. Analyses were performed in 3 phases. First, logistic regression and machine learning algorithms were used to predict the probability of demonstrating corneal involvement in patients with presumed infectious conjunctivitis. Second, quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to confirm the most important biomarker gene identified by the algorithm. Third, the biomarker gene was validated in prospectively collected conjunctival samples of adult patients from 3 outpatient centers in Thailand and 1 in India. Patients with signs and symptoms of infectious conjunctivitis and onset within less than 14 days were eligible. Exclusion criteria were the inability to consent, presumed toxicity, or allergic conjunctivitis.
Acute infectious conjunctivitis.
The identification and validation of ocular surface gene expression associated with corneal findings on slitlamp examination.
Thirteen genes exhibited a 1.5-log2 fold change in expression in patients with corneal involvement compared to patients without corneal involvement. Using the 13 genes to train and cross validate, logistic regression produced the highest mean area under the receiver operating characteristic curve (AUROC; 0.85; 95% CI, 0.84-0.86) for corneal involvement. The removal of apolipoprotein E (APOE) from the gene ensemble led to a decline in predictive performance of the logistic regression classifier (from mean AUROC 0.85 [95% CI, 0.84-0.86] to 0.74 [95% CI, 0.73-0.75]; adjusted P = .001 [Tukey test]). Orthogonal testing of APOE expression level with RT-qPCR showed that APOE expression was higher in patients with corneal involvement compared to patients without (median [IQR], 0.23 [0.04-0.47] vs 0.04 [0.02-0.06]; P = .004 [Mann-Whitney U test]). Using a Youden index of 0.23 Δ threshold cycle, APOE had a sensitivity of 56% (95% CI, 33-77) and a specificity of 88% (95% CI, 79-93) in 106 samples with conjunctivitis at Aravind, India (P < .001 [Fisher exact test]). When applied to a different patient population in Thailand, the same criteria could discriminate between disease states (58 samples; sensitivity, 47%; 95% CI, 30-64 and specificity, 93%; 95% CI, 77-99; P = .001 [Fisher exact test]).
The results from this study suggest that the host conjunctival immune response can be meaningfully interrogated to identify biomarkers for ocular surface diseases.
重要性:传染性结膜炎可导致角膜受累,进而导致眼部发病率。鉴定与角膜受累相关的生物标志物有可能改善患者的护理。
目的:鉴定急性传染性结膜炎患者的生物标志物。
设计、地点和参与者:这是一项横断面研究,于 2016 年 12 月至 2024 年 3 月进行。分析分为 3 个阶段。首先,使用逻辑回归和机器学习算法预测疑似传染性结膜炎患者出现角膜受累的概率。其次,使用定量逆转录聚合酶链反应(RT-qPCR)确认算法确定的最重要的生物标志物基因。最后,在来自泰国 3 家门诊中心和印度 1 家门诊中心的成年患者前瞻性收集的结膜样本中验证该生物标志物基因。符合以下条件的患者纳入研究:具有传染性结膜炎的症状和体征,且发病时间少于 14 天。排除标准为无法同意、疑似毒性或过敏性结膜炎。
暴露:急性传染性结膜炎。
主要结局和措施:鉴定并验证与裂隙灯检查下的角膜发现相关的眼表基因表达。
结果:与无角膜受累的患者相比,13 个基因在有角膜受累的患者中的表达水平变化了 1.5 个对数倍。使用这 13 个基因进行训练和交叉验证,逻辑回归产生了最高的角膜受累受试者工作特征曲线下面积(AUROC;0.85;95%CI,0.84-0.86)。从基因组合中去除载脂蛋白 E(APOE)会导致逻辑回归分类器的预测性能下降(从平均 AUROC 0.85[95%CI,0.84-0.86]降至 0.74[95%CI,0.73-0.75];调整 P = .001[Tukey 检验])。使用 RT-qPCR 对 APOE 表达水平进行正交检验显示,与无角膜受累的患者相比,APOE 在有角膜受累的患者中的表达水平更高(中位数[IQR],0.23[0.04-0.47] vs 0.04[0.02-0.06];P = .004[Mann-Whitney U 检验])。使用 0.23 Δ循环阈值的约登指数,APOE 在印度阿格拉文达的 106 份结膜炎样本中具有 56%(95%CI,33-77)的灵敏度和 88%(95%CI,79-93)的特异性(P < .001[Fisher 精确检验])。当应用于泰国的另一组患者人群时,相同标准可以区分疾病状态(58 份样本;灵敏度,47%;95%CI,30-64 和特异性,93%;95%CI,77-99;P = .001[Fisher 精确检验])。
结论和相关性:这项研究的结果表明,可以对宿主结膜免疫反应进行有意义的检测,以鉴定眼表疾病的生物标志物。