Statnikov Alexander, Alekseyenko Alexander V, Li Zhiguo, Henaff Mikael, Perez-Perez Guillermo I, Blaser Martin J, Aliferis Constantin F
1] Center for Health Informatics and Bioinformatics (CHIBI), New York University Langone Medical Center, New York, New York [2] Department of Medicine, New York University School of Medicine, New York, New York.
Sci Rep. 2013;3:2620. doi: 10.1038/srep02620.
Psoriasis is a common chronic inflammatory disease of the skin. We sought to use bacterial community abundance data to assess the feasibility of developing multivariate molecular signatures for differentiation of cutaneous psoriatic lesions, clinically unaffected contralateral skin from psoriatic patients, and similar cutaneous loci in matched healthy control subjects. Using 16S rRNA high-throughput DNA sequencing, we assayed the cutaneous microbiome for 51 such matched specimen triplets including subjects of both genders, different age groups, ethnicities and multiple body sites. None of the subjects had recently received relevant treatments or antibiotics. We found that molecular signatures for the diagnosis of psoriasis result in significant accuracy ranging from 0.75 to 0.89 AUC, depending on the classification task. We also found a significant effect of DNA sequencing and downstream analysis protocols on the accuracy of molecular signatures. Our results demonstrate that it is feasible to develop accurate molecular signatures for the diagnosis of psoriasis from microbiomic data.
银屑病是一种常见的慢性皮肤炎症性疾病。我们试图利用细菌群落丰度数据来评估开发多变量分子特征以区分皮肤银屑病病变、银屑病患者临床上未受影响的对侧皮肤以及匹配的健康对照受试者中类似皮肤位点的可行性。我们使用16S rRNA高通量DNA测序技术,对51个这样的匹配样本三联体的皮肤微生物群进行了检测,这些样本包括不同性别、年龄组、种族以及多个身体部位的受试者。所有受试者近期均未接受过相关治疗或使用过抗生素。我们发现,根据分类任务的不同,用于诊断银屑病的分子特征的准确率显著,曲线下面积(AUC)范围为0.75至0.89。我们还发现DNA测序和下游分析方案对分子特征的准确性有显著影响。我们的结果表明,从微生物组数据开发用于诊断银屑病的准确分子特征是可行的。