Frazer Lab Department of Pediatrics, Genome Information Sciences

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Welcome to the Frazer Lab!

Our lab is in the Department of Pediatrics, Division of Genome Information Sciences at UC San Diego.

Located in the Leichtag Biomedical Research Building on UCSD’s main campus, the Frazer Laboratory’s research focuses on the genetics and functional genomics of cardiovascular diseases and cancer. Our research mission is to identify common and rare genetic variants that are associated with human disease in order to functionally assess their role in disease pathogenesis, progression, and prognosis. With our discoveries we hope to accelerate the translation of genomic research into clinical therapies and applications.

Cardiovascular Disease

    A large part of our lab is involved in the CardiPS study. This multi-PI study is funded through the NHLBI and seeks to link cardiac phenotypes to genotypes through the generation of iPSC-derived cardiomyocytes from skin fibroblasts collected from a cohort of 270 individuals. Our cohort consists of normal healthy individuals as well as individuals with cardiovascular diseases such as long QT and left ventricular hypertrophy. With these samples we hope to identify inherited coding and regulatory variants that influence the manifestation of cardiovascular disease and adverse drug reactions.


    We collaborate with Dr. John-Bjarne Hansen at the University of Tromso to study the genetic underpinnings of Venous Thrombosis Embolism (VTE). This multi-PI study is funded through the K.G. Jebsen Medical Foundation to analyze the Tromso cohort, which is comprised of individuals who have been clinically followed for several decades. Our lab has sequenced thousands of individuals in the Tromso cohort and we are now analyzing these data to identify genetic associations with VTE.




Cancer

    We are taking advantage of data generated and made publicly available through large consortia such as The Cancer Genome Atlas (TCGA) to study a variety of cancer types including chronic lymphocytic leukemia (CLL), ovarian and breast. We use innovative bioinformatics and computational approaches to identify and understand the role of inherited variants and somatic mutations in tumor carcinogenesis and tumor progression. With this information we hope to identify novel therapeutic targets and improve disease classification.



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