Rene Baudrand1, Mark O Goodarzi2, Anand Vaidya3, Patricia C Underwood3, Jonathan S Williams3, Xavier Jeunemaitre4, Paul N Hopkins5, Nancy Brown6, Benjamin A Raby7, Jessica Lasky-Su7, Gail K Adler3, Jinrui Cui2, Xiuqing Guo8, Kent D Taylor8, Yii-Der I Chen8, Anny Xiang9, Leslie J Raffel10, Thomas A Buchanan11, Jerome I Rotter8, Gordon H Williams3, Luminita H Pojoga12. 1. Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Endocrinology, School Of Medicine, Pontificia Universidad Catolica De Chile, Santiago 8330074, Chile. 2. Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA 90048. 3. Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. 4. Centre Investigation Clinique, Assistance Publique- Georges Pompidou; Institut National de la Sante et de la Recherche Medicale, Unite Mixte de Recherche en Sante 970, Universite Paris Descartes, Paris 75014, France. 5. Cardiovascular Genetics Research Unit, University of Utah School of Medicine Salt Lake City, Utah 84112. 6. Vanderbilt University Medical Center, Nashville, TN 37232. 7. Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115. 8. Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502. 9. Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 91188. 10. Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048. 11. Departments of Medicine and Physiology and Biophysics, University of Southern California Keck School of Medicine, CA 90033. 12. Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. Electronic address: lpojoga@partners.org.
Abstract
CONTEXT AND OBJECTIVE: We examined whether a prevalent caveolin-1 gene (CAV1) variant, previously related to insulin resistance, is associated with metabolic syndrome (MetS). PATIENTS AND METHODS: We included subjects genotyped for the CAV1 variant rs926198 from two cohorts: 735 Caucasians from the HyperPATH multicenter study, and 810 Hispanic participants from the HTN-IR cohort. RESULTS: Minor allele carriers from HyperPATH cohort (57% of subjects) had higher Framingham risk scores, higher odds of diabetes (10.7% vs 5.7%, p=0.016), insulin resistance (44.3% vs 35.1%, p=0.022), low HDL (49.3% vs 39.6%, p=0.018) and MetS (33% vs 20.5%, p<0.001) but similar BMI. Consistently, minor allele carriers exhibited higher odds of MetS, even when adjusted for confounders and relatedness (OR 2.83 (1.73-4.63), p<0.001). The association with MetS was replicated in the Hispanic cohort HTN-IR (OR 1.61, [1.06-2.44], p=0.025). Exploratory analyses suggest that MetS risk is modified by a CAV1 variant-BMI status interaction, whereby the minor allele carrier status strongly predicted MetS (OR 3.86 [2.05-7.27], p<0.001) and diabetes (OR 2.27 [1.07-4.78], p=0.03) in non-obese, but not in obese subjects. In addition, we observed a familial aggregation for MetS diagnosis in minor allele carriers. CONCLUSION: The prevalent CAV1 gene variant rs926198 is associated with MetS in separate Caucasian and Hispanic cohorts. These findings appear to be driven by an interaction between the genetic marker and obesity status, suggesting that the CAV1 variant may improve risk profiling in non-obese subjects. Additional studies are needed to confirm the clinical implications of our results.
CONTEXT AND OBJECTIVE: We examined whether a prevalent caveolin-1 gene (CAV1) variant, previously related to insulin resistance, is associated with metabolic syndrome (MetS). PATIENTS AND METHODS: We included subjects genotyped for the CAV1 variant rs926198 from two cohorts: 735 Caucasians from the HyperPATH multicenter study, and 810 Hispanic participants from the HTN-IR cohort. RESULTS: Minor allele carriers from HyperPATH cohort (57% of subjects) had higher Framingham risk scores, higher odds of diabetes (10.7% vs 5.7%, p=0.016), insulin resistance (44.3% vs 35.1%, p=0.022), low HDL (49.3% vs 39.6%, p=0.018) and MetS (33% vs 20.5%, p<0.001) but similar BMI. Consistently, minor allele carriers exhibited higher odds of MetS, even when adjusted for confounders and relatedness (OR 2.83 (1.73-4.63), p<0.001). The association with MetS was replicated in the Hispanic cohort HTN-IR (OR 1.61, [1.06-2.44], p=0.025). Exploratory analyses suggest that MetS risk is modified by a CAV1 variant-BMI status interaction, whereby the minor allele carrier status strongly predicted MetS (OR 3.86 [2.05-7.27], p<0.001) and diabetes (OR 2.27 [1.07-4.78], p=0.03) in non-obese, but not in obese subjects. In addition, we observed a familial aggregation for MetS diagnosis in minor allele carriers. CONCLUSION: The prevalent CAV1 gene variant rs926198 is associated with MetS in separate Caucasian and Hispanic cohorts. These findings appear to be driven by an interaction between the genetic marker and obesity status, suggesting that the CAV1 variant may improve risk profiling in non-obese subjects. Additional studies are needed to confirm the clinical implications of our results.
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