Researchers at Vanderbilt University Medical Center and the University of Arizona College of Pharmacy have found that EHRs can aid the understanding, treatment – and ultimately – prevention of disease, said senior author Joshua Denny, MD, professor of biomedical informatics and medicine at Vanderbilt.
The researchers created what they label as the first comprehensive catalog of diseases associated with variations in human leukocyte antigen, or HLA – genes that regulate the body's immune system.
The catalog could help identify individuals who are at-risk for certain autoimmune diseases or who may generate antibodies that attack their own tissues in response to an infection.
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The findings, published in the journal Science Translational Medicine, notes the power of electronic health records to advance understanding, treatment and prevention of disease.
"In one fell swoop we essentially replicated decades of research on autoimmune associations with the HLA," said Jason Karnes, co-author of the paper with Lisa Bastarache, lead data scientist in the Vanderbilt Center for Precision Medicine. Karnes is an assistant professor in the University of Arizona College of Pharmacy in Tucson. "To my knowledge no other investigations have made this level of data available" to the wider research community, Karnes said.
HLAs are proteins expressed on the surfaces of cells. Like nametags, they enable the immune system to distinguish "self" tissues of the body from "non-self," such as invading pathogens.
Individual variations in HLA genes also have been linked to adverse drug reactions, rejection of transplanted organs and autoimmune diseases including type 1 diabetes and rheumatoid arthritis, in which the immune system mistakes normal tissue for a foreign invader and attacks it.
This research scanned patients' entire "phenome" of all health characteristics as noted in the EHR.
To date, more than 230,000 samples from different individuals have been stored in BioVU, Vanderbilt's DNA database. Genetic samples are linked to the corresponding EHRs in which identifying information has been deleted to protect patient privacy.
From the genetic code, the researchers inferred which HLAs would be expected to be expressed in nearly 29,000 individuals whose DNA samples were stored in BioVU and another 8,400 samples provided by Scott Hebbring and colleagues from the Marshfield Clinic.
The EHRs from these individuals were screened for the presence of nearly 1,400 different phenotypes that could be linked to the HLA genes.
Type 1 diabetes was the strongest previously described HLA association confirmed by the study, but the researchers also found evidence for several new potential associations with multiple sclerosis and cervical cancer.
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