Background: The search for microbial biomarkers of periodontitis has been hampered by our ability to separate disease-specific associations from those that are common to all forms of periodontitis. Here, we present the first functional characterization of the microbiomes of three common clinical phenotypes of this disease: Localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP) and chronic periodontitis (CP). Methods: We collected subgingival plaque samples from sites with disease of 59 subjects with Stage 3 periodontitis and 25 periodontally healthy individuals and used shotgun metagenomics to characterize the aggregate of bacterial genes. Results: Beta-dispersion metrics demonstrated that no two individuals with disease, especially those with chronic disease, are alike (the Anna Karenina Principle), indicating that microbial modulation therapies will have to incorporate patient-specific parameters for efficacy. We discovered broad patterns of microbial dysbiosis that spanned the three disease phenotypes, as well as disease-specific indicators unique to each phenotype. Genes common to all forms of periodontitis encoded pathways that facilitate life in an oxygen-poor, protein and heme-rich, pro-oxidant environment, and enhance capacity for attachment and biofilm formation, while genes encoding the acetate switch, c-type cytochrome and molybdenum cofactor biosynthesis, iron-sulfur clusters, and formate dehydrogenase were unique to LAP. These can serve as potential biomarkers for molecular identification of clinical phenotypes and clarify the role of the microbiome in disease pathogenesis. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one-third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease. Conclusion: Within the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease entity, or an artifact induced by cross-sectional study designs.