Genetic data: The new challenge of personalized medicine, insights for rheumatoid arthritis patients

Rapid advances in genotyping technology, analytical methods, and the establishment of large cohorts for population genetic studies have resulted in a large new body of information about the genetic basis of human rheumatoid arthritis (RA). Improved understanding of the root pathogenesis of the disease holds the promise of improved diagnostic and prognostic tools based upon this information. In this review, we summarize the nature of new genetic findings in human RA, including susceptibility loci and gene-gene and gene-environment interactions, as well as genetic loci associated with sub-groups of patients and those associated with response to therapy. Possible uses of these data are discussed, such as prediction of disease risk as well as personalized therapy and prediction of therapeutic response and risk of adverse events. While these applications are largely not refined to the point of clinical utility in RA, it seems likely that multi-parameter datasets including genetic, clinical, and biomarker data will be employed in the future care of RA patients

A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history

Objective To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects. Material and Methods We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features. Results We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of >= 0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles. Discussion Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data. Conclusion We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.Molecular Epidemiolog

Toward earlier diagnosis using combined eHealth tools in rheumatology: the joint pain assessment scoring tool (JPAST) project

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.Pathophysiology and treatment of rheumatic disease

Consensus Report : 2nd European Workshop on Tobacco Use Prevention and Cessation for Oral Health Professionals

Tobacco use has been identified as a major risk factor for oral disorders such as cancer and periodontal disease. Tobacco use cessation (TUC) is associated with the potential for reversal of precancer, enhanced outcomes following periodontal treatment, and better periodontal status compared to patients who continue to smoke. Consequently, helping tobacco users to quit has become a part of both the responsibility of oral health professionals and the general practice of dentistry. TUC should consist of behavioural support, and if accompanied by pharmacotherapy, is more likely to be successful. It is widely accepted that appropriate compensation of TUC counselling would give oral health professionals greater incentives to provide these measures. Therefore, TUC-related compensation should be made accessible to all dental professionals and be in appropriate relation to other therapeutic interventions. International and national associations for oral health professionals are urged to act as advocates to promote population, community and individual initiatives in support of tobacco use prevention and cessation (TUPAC) counselling, including integration in undergraduate and graduate dental curricula. In order to facilitate the adoption of TUPAC strategies by oral health professionals, we propose a level of care model which includes 1) basic care: brief interventions for all patients in the dental practice to identify tobacco users, assess readiness to quit, and request permission to re-address at a subsequent visit, 2) intermediate care: interventions consisting of (brief) motivational interviewing sessions to build on readiness to quit, enlist resources to support change, and to include cessation medications, and 3) advanced care: intensive interventions to develop a detailed quit plan including the use of suitable pharmacotherapy. To ensure that the delivery of effective TUC becomes part of standard care, continuing education courses and updates should be implemented and offered to all oral health professionals on a regular basis