Severe cutaneous adverse reactions (SCARs) are morbid immunologic reactions to drugs that confer a mortality of 10-50%. Over the last decade, significant promise for prediction and prevention has come from the discovery that many SCARs are associated with variation within HLA class I alleles. For HLA-B*15:02, this has led to routine pre-prescription screening for carbamazepine in many Southeast Asian countries and a significant reduction in cases of carbamazepine SJS/TEN. Despite this progress, there is little known about genetic and epidemiological risk factors for SCARs related to commonly used drugs such as antibiotics. There is also limited information about HLA risk for SCARs across the diverse populations present in the United States. Furthermore, imprecision of clinical phenotyping and lack of standardized coding has led to challenges in finding SCAR cases in the electronic health record (EHR). Our proposed study aims to address critical challenges and gaps in our knowledge of antibiotic SCARs.
In Aim 1, we will leverage advanced informatics and longitudinal EHR data for over 11 million patients from Partners HealthCare System since the 1980s to identify SCAR cases. We will create, optimize and standardize reproducible methods for finding SCAR cases and validating a cohort of SCAR patients. This iterative process will be used to refine and disseminate an electronic phenotype to be validated cross-institutionally.
In Aim 2, we will analyze SCAR prevalence and conduct a case-control study to identify drug-specific and patient-specific risk factors for antibiotic-associated SCARs. We will compare clinical sequelae, quality of life and adherence of SCAR patients compared to controls through validated survey instruments.
In Aim 3, we will identify candidate HLA and genetic associations from patients with validated antibiotic- associated SCARs. We will examine difference in genetic risk in minority and health disparity populations and predict that we will be powered to establish HLA associations for vancomycin DRESS (i.e., drug reaction with eosinophilia and systemic symptoms) and sulfonamide antimicrobial and beta-lactam SCAR. HLA alone, or in combination with clinical risk factors, can lead to improved SCAR prevention and early diagnosis. We will establish a data sharing platform, in the form of an online electronic phenotype and patient registry, that can be used to enlarge SCAR cohorts for future large-scale genomics studies. The roadmap we develop will translate into the development of electronic phenotypes for serious adverse drug reactions that facilitate genetic discovery. Knowledge gained will be crucial to the translation of genetic data into clinical decision making. This is in close alignment with NIH?s research mission to accelerate genetic discovery for iatrogenic and preventable drug-induced diseases that will translate into prevention, earlier diagnosis and an enhanced mechanistic understanding that may lead to targeted therapeutic approaches.
Severe cutaneous adverse reactions (SCARs) result in substantial morbidity, long term disability, health care burden and a mortality of 10-50%. To advance the science of clinical and genetic risk factor identification for antibiotic SCAR, we will leverage large electronic health record (EHR) data and advanced informatics technology. Through case validation we will create an informatics roadmap for other institutions with similar EHR data to identify SCAR cases and we will establish a data sharing platform, including an online electronic phenotype and patient registry, that can be used to enlarge SCAR cohorts for future large-scale genomics studies.
