Using Big Data to Evaluate the Association between Periodontal Disease and Rheumatoid Arthritis.

An association between periodontal disease and rheumatoid arthritis is believed to exist. Most investigations into a possible relationship have been case-control studies with relatively low sample sizes. The advent of very large clinical repositories has created new opportunities for data-driven research. We conducted a retrospective cohort study to measure the association between periodontal disease and rheumatoid arthritis in a population of 25 million patients. We demonstrated that subjects with periodontal disease were roughly 1.4 times more likely to have rheumatoid arthritis. These results compare favorably with those of previous studies on smaller cohorts. Additional work is needed to identify the mechanisms behind this association and to determine if aggressive treatment of periodontal disease can alter the course of rheumatoid arthritis.

Metabolic profiling in personalized medicine: bridging the gap between knowledge and clinical practice in Type 2 diabetes.

Type 2 diabetes mellitus (DM2) is the most commonly diagnosed metabolic disease and its prevalence is expected to increase. Epidemiological studies clearly show excess mortality associated with DM2, as well as an increased risk of DM2-related complications. Advances in personalized medicine would greatly improve patient care in the field of diabetes and other metabolic diseases. Prediction of the disease in asymptomatic patients as well as its harsh complications in patients already diagnosed is becoming a necessity, with the considerable increase in the cost of the treatment. In the current article, we review the known clinical, molecular metabolic and genetic biomarkers that should be integrated in a future bioinformatic platform to be used at the point-of-care, and discuss the challenges we face in applying this vision of personalized medicine for diabetes into reality.