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 = 9350), 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.