It is increasingly recognized that an important step towards improving overall health is to accurately measure biomarkers of health from the molecular activities prevalent in the oral cavity. We present a general methodology for computationally quantifying the activity of microbial functional pathways using metatranscriptomic data. We describe their implementation as a collection of eight oral pathway scores using a large salivary sample dataset (n=9,350), and we evaluate score associations with oropharyngeal disease phenotypes within an unseen independent cohort (n=14,129). Through this validation, we show that the relevant oral pathway scores are significantly worse in individuals with periodontal disease, acid reflux, and nicotine addiction, compared with controls. Given these associations, we make the case to use these oral pathway scores to provide molecular health insights from simple, non-invasive saliva samples, and as molecular endpoints for actionable interventions to address the associated conditions.

人们越来越认识到，改善整体健康的重要一步是根据口腔中普遍存在的分子活动准确测量健康的生物标志物。我们提出了一种使用宏转录组数据计算量化微生物功能途径活性的通用方法。我们将其实施描述为使用大型唾液样本数据集（n = 9,350）的八个口腔通路评分的集合，并且我们评估了未见过的独立队列（n = 14,129）中的评分与口咽疾病表型的关联。通过这一验证，我们发现，与对照组相比，患有牙周病、胃酸反流和尼古丁成瘾的个体的相关口腔通路评分明显较差。鉴于这些关联，我们提出使用这些口腔途径评分来从简单的非侵入性唾液样本中提供分子健康见解，并作为解决相关病症的可行干预措施的分子终点。