Impact of gene variants on sex-specific regulation of human Scavenger receptor class B type 1 (SR-BI) expression in liver and association with lipid levels in a population-based study.
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BACKGROUND: Several studies have noted that genetic variants of SCARB1, a lipoprotein receptor involved in reverse cholesterol transport, are associated with serum lipid levels in a sex-dependent fashion. However, the mechanism underlying this gene by sex interaction has not been explored. METHODS: We utilized both epidemiological and molecular methods to study how estrogen and gene variants interact to influence SCARB1 expression and lipid levels. Interaction between 35 SCARB1 haplotype-tagged polymorphisms and endogenous estradiol levels was assessed in 498 postmenopausal Caucasian women from the population-based Rancho Bernardo Study. We further examined associated variants with overall and SCARB1 splice variant (SR-BI and SR-BII) expression in 91 human liver tissues using quantitative real-time PCR. RESULTS: Several variants on a haplotype block spanning intron 11 to intron 12 of SCARB1 showed significant gene by estradiol interaction affecting serum lipid levels, the strongest for rs838895 with HDL-cholesterol (p=9.2x10(-4)) and triglycerides (p=1.3x10(-3)) and the triglyceride:HDL cholesterol ratio (p=2.7x10(-4)). These same variants were associated with expression of the SR-BI isoform in a sex-specific fashion, with the strongest association found among liver tissue from 52 young women<45 years old (p=0.002). CONCLUSIONS: Estrogen and SCARB1 genotype may act synergistically to regulate expression of SCARB1 isoforms and impact serum levels of HDL cholesterol and triglycerides. This work highlights the importance of considering sex-dependent effects of gene variants on serum lipid levels.
Polymorphism, Single Nucleotide
Scavenger Receptors, Class B
Published Version (Please cite this version)10.1186/1471-2350-11-9
Publication InfoBarrett-Connor, E; Chiba-Falek, O; Ginsburg, Geoffrey Steven; Guyton, John Richard; McCarthy, Jeanette Joan; Nichols, M; & Suchindran, Sunil (2010). Impact of gene variants on sex-specific regulation of human Scavenger receptor class B type 1 (SR-BI) expression in liver and association with lipid levels in a population-based study. BMC Med Genet, 11. pp. 9. 10.1186/1471-2350-11-9. Retrieved from https://hdl.handle.net/10161/4353.
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Professor in Neurology
Functional genomics Non-coding regulatory variants in the human genome Genetics of complex neurological diseases
Professor of Medicine
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.
Professor of Medicine
Current research efforts focus on the role of niacin in clinical lipid practice. Despite the ending of a large clinical trial due to lack of benefit, niacin remains the second best lipid-modifying drug after statins. Why this trial did not replicate earlier success with niacin is a matter of great interest. Counterregulatory hormone responses may provide the answer. Another research focus is weight loss counseling in the busy clinic setting. Low glycemic dietary advice achieved average
Adjunct Associate Professor in the Department of Family Medicine and Community Health
As a genetic epidemiologist, I spent the earlier part of my career researching the genetic underpinnings of complex diseases, both infectious and chronic. More recently, I have turned my attention to precision medicine education. As a leading educator in the field of genomic and precision medicine, I now spend my time demystifying genomics for non-technical audiences, including health care providers, patients and other stakeholders. In 2014 I helped launch the first consumer-facing mag
I work in Omic and biomarker research at the Center for Applied Genomics and Precision Medicine at Duke University. My current work focuses on infectious disease and cardiovascular disease. I have also worked on cardiovascular risk prediction, classification, and genome-wide association studies. Some of my work uses risk-prediction models and classification in Omic and other settings, and I give workshops on this topic and others. I am interested in any research that s
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