Department of Molecular and Functional Genomics
The mission of the Department of Molecular and Functional Genomics (MFG) is to apply advanced laboratory research approaches and techniques to investigate fundamental mechanisms of human disease, with the goal of creating knowledge that leads to improved health. The application of next generation sequencing and other genomic technologies have generated enormous excitement around the potential to use genomic information to guide individual health care, as articulated in the national Precision Medicine Initiative. Interpreting this genomic data presents many challenges, however, and will become a rate-limiting step in using it effectively in the health care arena. Elucidation of the molecular and biological consequences of genetic variation will be required to harness the value of genomic information to improve health.
A major focus of the Department of Molecular and Functional Genomics is to investigate the functional consequences of genetic variation to elucidate the molecular basis of observed gene-phenotype associations. MFG faculty leverage Geisinger’s unique resources, including the MyCode Community Health Initiative, an electronic health record-linked biorepository with more than 200,000 consented participants and a database of more than 92,000 exome sequences. This data is being used to identify genes and pathways associated with a host of important clinical traits and diseases, such as obesity, diabetes, cardiovascular disease, and brain and behavioral disorders. Investigators in the Department of Molecular and Functional Genomics work closely with colleagues in other Geisinger research programs, including the Department of Bioinformatics and Data Science, and Department of Epidemiology and Health Services Research, and clinician-investigators in numerous clinical departments at Geisinger.
David J Carey, PhD, professor and acting chair
- Tooraj Mirshahi, PhD
- Anne Moon, MD, PhD
- Raghu Metpally, PhD
- Uyenlinh Mirshahi, PhD
- Pavan Puvvula, PhD
- Diane Smelser, PhD
Initiatives & Projects
Abdominal Aortic Aneurysm (AAA)
In 2012 the Department of Health of the Commonwealth of Pennsylvania awarded Geisinger a major grant through the PA-CURE Translational Genomics Program. This project creates a score for patients to estimate their risk of developing an abdominal aortic aneurysm (AAA) based on their genetic profile and clinical risk factors such as age, smoking history and presence of other diseases. Estimating risk is critical to diagnosing AAAs, since aneurysms often cause no symptoms until they rupture.
Current guidelines for AAA screening by abdominal ultrasonography often exclude individuals who later develop an AAA. As part of this project, Geisinger's team, in collaboration with a statistical genetics group from University of Pittsburgh, developed and are testing guidelines for population screening that combine genetic risk factor data with a more comprehensive set of clinical risk factor data. The project also includes patient and provider education about AAA screening and genetic testing. Overall, this project will help identify patient, provider and system barriers to AAA screening; develop interventions to overcome these barriers; and implement personalized strategies for prevention, screening and treatment of AAA and similar diseases.
More than three percent of people are born with a congenital heart defect; for some babies, these are life threatening from birth, while other defects are silent until adulthood and then become a source of serious heart problems that require surgery. This project is focused on understanding the developmental origins of congenital heart defects. We have generated the entire spectrum of defects observed in humans as well as in animal models and use these models to discover the genetic and molecular pathways that control normal and abnormal heart development. We have discovered pathways that control both the structural and electrical features of heart. These studies also provide new insight into diseases of other organs such as the lungs, kidneys and brain. The long term goal is to provide better treatment of congenital heart defects and strategies for prevention.
Translational Medicine Initiative
The mission of the Translational Medicine Initiative is to discover the genetic and molecular bases of human disease and to translate this new knowledge into clinical practice. The primary goal is to carry out transformative research into the genetic and molecular bases of human diseases using new and innovative approaches such as phenome-wide association studies (PheWAS). This research identifies novel associations between genes and clinical traits of interest, and performs biological, cellular and molecular studies of gene function to elucidate the disease mechanism. Creation of a novel cell repository and animal models are critical to understanding the origin of human disease and testing novel therapies. Initial projects underway include cardiogenomics studies and investigation of the genomics of pain.
Whole Exome Sequencing Collaboration
Geisinger and the Regeneron Genetic Center are collaborating to perform whole exome sequence analysis of DNA samples from Geisinger patients who consented to participate in the Geisinger MyCode® Community Health Initiative. The collaboration also links the genomic variant data to clinical phenotype data in the participant's electronic medical record (EMR) to facilitate discovery of novel gene-disease associations. The long-term goal is to analyze the exomes of at least 250,000 individuals.
The use of EMR data for this purpose provides enormous flexibility with respect to the number and variety of clinical traits that can be studied, and at reduced cost and accelerated timeframe compared to traditional methods. GHS has substantial experience and expertise in the use of EMR data to identify patients with clinical phenotypes of interest.
The data that are available enable both "phenotype-first' and "genotype-first" approaches to genomic discovery. The former could include genetic association studies of cases and controls for clinical phenotypes of interest. The genome-first approach is based on identification of genomic variants of interest and searching for associated clinical traits. An example is a phenome-wide association study, which looks for associations between genomic variants and an array of clinical traits.