Study: EMRs may accelerate genome-driven diagnoses, treatments
One potential benefit of the rapidly accumulating databases of healthcare information is the ability to make unprecedented links between genomic data and clinical medicine, according to a study published by Cell Press in the April issue of the American Journal of Human Genetics.
The study supports the idea that large-scale DNA data banks linked to EMR systems could provide a valuable platform for discovering, assessing and validating associations between genes and diseases, according to senior study author Dan M. Roden, MD, from Vanderbilt University School of Medicine in Nashville, Tenn.
"The deployment of EMRs offers the hope of improving routine care, not only by enhancing individual practitioner access to patient information but also by aggregating information for clinical research," said Roden. "EMRs contain large populations with diverse diseases and have the potential to act as platforms for rapid and inexpensive creation of large inclusive patient sets."
Roden and colleagues, who specialized in informatics and in genome science, sought to examine whether large biorepositories containing DNA samples linked to EMRs might be useful for discovering and incorporating new genotype-phenotype associations.
"Implementing such a vision requires that major obstacles be overcome, including technological, computational, ethical and financial issues and determining whether genomic information will meaningfully inform clinical decision making and healthcare outcomes," he said.
The team of researchers used BioVU, the Vanderbilt DNA databank, to detect known common genetic variants associated with five diseases: atrial fibrillation, Crohn's disease, multiple sclerosis, rheumatoid arthritis and type 2 diabetes. It took only four months to generate a set of nearly 10,000 records from which the cases and controls were identified. Although the process of accessing and defining the samples was technically complex, for each of the five phenotypes, at least one previously reported genetic association was replicated.
The results support the use of DNA resources coupled to EMR systems as a valuable tool for clinical research, according to the authors.
"Our data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research and for discovery in genome science," Roden said.
The study supports the idea that large-scale DNA data banks linked to EMR systems could provide a valuable platform for discovering, assessing and validating associations between genes and diseases, according to senior study author Dan M. Roden, MD, from Vanderbilt University School of Medicine in Nashville, Tenn.
"The deployment of EMRs offers the hope of improving routine care, not only by enhancing individual practitioner access to patient information but also by aggregating information for clinical research," said Roden. "EMRs contain large populations with diverse diseases and have the potential to act as platforms for rapid and inexpensive creation of large inclusive patient sets."
Roden and colleagues, who specialized in informatics and in genome science, sought to examine whether large biorepositories containing DNA samples linked to EMRs might be useful for discovering and incorporating new genotype-phenotype associations.
"Implementing such a vision requires that major obstacles be overcome, including technological, computational, ethical and financial issues and determining whether genomic information will meaningfully inform clinical decision making and healthcare outcomes," he said.
The team of researchers used BioVU, the Vanderbilt DNA databank, to detect known common genetic variants associated with five diseases: atrial fibrillation, Crohn's disease, multiple sclerosis, rheumatoid arthritis and type 2 diabetes. It took only four months to generate a set of nearly 10,000 records from which the cases and controls were identified. Although the process of accessing and defining the samples was technically complex, for each of the five phenotypes, at least one previously reported genetic association was replicated.
The results support the use of DNA resources coupled to EMR systems as a valuable tool for clinical research, according to the authors.
"Our data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research and for discovery in genome science," Roden said.