Charles R. Bronfman Institute for Personalized Medicine

Mount Sinai’s strategic plan provides a road map for major investments in research and infrastructure to establish a series of 12 new Institutes, including The Charles Bronfman Institute for Personalized Medicine (IPM).

The Institute is dedicated to advance personalized health and health care with three core objectives:

  • Provide clinical and translational investigators with greater and easier access to high quality, standardized biospecimen collections, linked with full clinical information.
  • Provide an academic research home and technology support for discovering clinically important genotype-phenotype associations through interdisciplinary, translational genomics programs.
  • Facilitate clinical development of gene-based diagnostics and risk assessment algorithms and evaluate their impact on health care delivery at the patient and population level.

The Institute is home to research faculty pursuing studies in the clinical areas of pharmacogenomics, obesity and metabolic traits, cardiovascular and kidney disease. Institute faculty generate innovations and new paradigms in mapping of complex traits in diverse populations, clinical knowledge representation and phenomics, and personalized medicine clinical decision support

Headed by Dr. Erwin Bottinger, IPM provides full and sole support for the IPM Biobank including the Biobank Informatics and Genomic Data Analysis Services Center (BIGDASC).

IPM Biobank

To discover better treatments, researchers are seeking to unravel the complexity of disease at the most basic level through “molecular” studies. The donation of samples from many thousands of individuals is essential to such studies. The Mount Sinai IPM Biobank project is a biobank program of the Charles Bronfman Institute for Personalized Medicine at Mount Sinai. IPM Biobank is dedicated to advancing the application of human blood-derived biospecimen and clinical data to life science research to accelerate the development of personalized healthcare and medical solutions.

Since September 2007, over 22,000 Mount Sinai Health System patients have enrolled in the Electronic Medical Record-linked IPM Biobank program. It is designed to generate a large collection of DNA and plasma samples, and genomic data, which are stored in a way that protects patient’s privacy. The three major self-reported racial/ethnic populations include 34% EA (European Ancestry), 26% AA (African Ancestry, 37% HA (Hispanic Ancestry). At the same time, it enables research to be performed on de-identified, comprehensive, electronic clinical information extracted from the Mount Sinai Data Warehouse (MSDW). To accomplish its goal, we created a comprehensive data management and analysis environment called the Biobank Informatics and Genomic Data Analysis Center (BIGDASC), encompassing clinical phenotype and genotype information and allowing phenotype/genotype data to be linked for research. BIGDASC provides approved investigators access to de-identified (or with PHI if IRB-approved) clinical information in the MSDW, linked with genomic information in the Biobank Genomics database.

Led by IPM, Mount Sinai is a member site to several large NIH-funded research networks, including the eMERGE II Network (electronic medical records and genomics), the eMERGE-Pharmacogenetics Research Network (PGRN) research partnership, the CKD Biomarker Consortium, among others.

The IPM Biobank contributes under collaborative agreements with international research consortia and collaborations, including:

  1. GIANT (Genetic Investigation of Anthropometric Traits) – GWAS data contributed for analysis and workgroup participation
  2. CKDGen (Chronic Kidney Disease Genetics) – GWAS data contributed for analysis and workgroup participation
  3. COGENT BP (Continental Origins and Genetic Epidemiology Network) – GWAS data contributed for analysis and workgroup participation
  4. GHBP (Genomics in Hispanics for Blood Pressure) – GWAS data contributed for analysis and workgroup participation
  5. Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (John Guttag):  Predictive Modeling and Personalized Health Decision Support Tools
  6. Genetics of Obesity and related traits in African Americans – GWAS data contributed for analysis and workgroup participation
  7. African American Type 2 Diabetes Genetics Consortium – GWAS data contributed for analysis and workgroup participation

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Last Updated:  June 15, 2012