Understanding the genetic etiology of diseases, both common and rare, is paramount to the application of genetics in "personalized medicine." All diseases are the result of a combination of environmental and/or genetic factors. The amount of variation in a disease/trait that is due to a genetic contribution is called "heritability." Conducing genetic/genomic studies is difficult without evidence of a strong genetic component by heritability measurements. Heritability can be measured in twins or other family structures, but is challenged by the resources required to collect the limited available families with appropriate phenotypic data. Moreover, even when these families are identified, heritability measurements are typically restricted to a single disease. The proposed research addresses these challenges by applying well-developed statistical methods in novel ways to simultaneously calculate heritability for many diseases using data available in the electronic medical record (EMR). The proposed project will test the hypothesis that thousands of clinical phenotypes, defined by patient medical records in families, can be used to measure heritability to direct further genetic/genomic studies. We call this novel bioinformatic method Phenome-wide Scan of Heritability (PheSH). The PheSH concept resulted from my work on Phenome-Wide Association Studies (PheWAS) conducted during my NLM-supported mentored training. Both PheWAS and PheSH are phenotype- independent approaches that allow for the genetic study of many clinical diseases or traits simultaneously. In the independent phase of my career, I plan to continue developing phenotype-independent techniques, including PheSH, to study the genetic etiology of human disease.

Public Health Relevance

All diseases are the result of a combination of genetic factors, also known as heritable factors, and/or environmental factors. This study is designed to measure the heritability of thousands of clinically significant diseases using multiple family structures and electronic medical records. The goal of this project is to identify genetic mutations that explain the strong heritability measurements so that genetics can be applied in personalized medicine.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Career Transition Award (K22)
Project #
1K22LM011938-01
Application #
8679493
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Ye, Jane
Project Start
2014-06-01
Project End
2017-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
1
Fiscal Year
2014
Total Cost
$130,645
Indirect Cost
$9,570
Name
Marshfield Clinic Research Foundation
Department
Type
DUNS #
074776030
City
Marshfield
State
WI
Country
United States
Zip Code
54449
Mayer, John; Kitchner, Terrie; Ye, Zhan et al. (2014) Use of an electronic medical record to create the marshfield clinic twin/multiple birth cohort. Genet Epidemiol 38:692-8