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12:00 AM - NextGen UGM 2025
Pathology Visions 2025
2025-10-05 - 2025-10-07    
8:00 am - 5:00 pm
Elevate Patient Care: Discover the Power of DP & AI Pathology Visions unites 800+ digital pathology experts and peers tackling today's challenges and shaping tomorrow's [...]
AHIMA25  Conference
2025-10-12 - 2025-10-14    
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Register for AHIMA25  Conference Today! HI professionals—Minneapolis is calling! Join us October 12-14 for AHIMA25 Conference, the must-attend HI event of the year. In a city known for its booming [...]
Federal EHR Annual Summit
2025-10-21 - 2025-10-23    
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The Federal Electronic Health Record Modernization (FEHRM) office brings together clinical staff from the Department of Defense, Department of Veterans Affairs, Department of Homeland Security’s [...]
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2025-11-02 - 2025-11-05    
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NextGen UGM 2025 is set to take place in Nashville, TN, from November 2 to 5 at the Gaylord Opryland Resort & Convention Center. This [...]
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12 Oct 25
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2 Nov 25
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Events

research papers

Researchers repurpose genetic data, EMR to perform large-scale PheWAS study

genetic data

Vanderbilt University Medical Center researchers and co-authors from four other U.S. institutions from the Electronic Medical Records and Genomics (eMERGE) Network are repurposing genetic data and electronic medical records to perform the first large-scale phenome-wide association study (PheWAS), released today in Nature Biotechnology.

Traditional genetic studies start with one phenotype and look at one or many genotypes, PheWAS does the inverse by looking at many diseases for one genetic variant or genotype.

“This study broadly shows that we can take decades of off-the-shelf electronic medical record data, link them to DNA, and quickly validate known associations across hundreds of previous studies,” said lead author Josh Denny, M.D., M.S., Vanderbilt Associate Professor of Biomedical Informatics and Medicine. “And, at the same time, we can discover many new associations.

“A third important finding is that our method does not select any particular disease – it is searches simultaneously for more than a thousand diseases that bring one to the doctor. By doing this, we were able to show some genes that are associated several diseases or traits, while others are not,” he added.

Researchers used genotype data from 13,835 individuals of European descent, exhibiting 1,358 diseases collectively. The team then ran PheWAS on 3,144 single-nucleotide polymorphisms (SNP’s), checking each SNP’s association with each of the 1,358 disease phenotypes.

As a result, study authors reported 63 previously unknown SNP-disease associations, the strongest of which related to skin diseases.

“The key result is that the method works,” Denny said. “This is a robust test of PheWAS across all domains of disease, showing that you can see all types of phenotypes in the electronic medical record – cancers, diabetes, heart diseases, brain diseases, etc. – and replicate what’s known about their associations with various SNPs.”

An online PheWAS catalog spawned by the study may help investigators understand the influence of many common genetic variants on human conditions.

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