Genetic Architecture of the Cardiovascular Risk Proteome. Issue 11 (13th March 2018)

• Record Type: Journal Article
• Authors: Benson, Mark D.; Yang, Qiong; Ngo, Debby; Zhu, Yineng; Shen, Dongxiao; Farrell, Laurie A.; Sinha, Sumita; Keyes, Michelle J.; Vasan, Ramachandran S.; Larson, Martin G.; Smith, J. Gustav; Wang, Thomas J.; Gerszten, Robert E.
• Is Part Of: Circulation. Volume 137:Issue 11(2018)
• Publication Date: 2018-03-13
• Subjects: APOE -- cardiovascular genomics -- genome-wide analysis -- proteomics -- systems biology; Blood -- Circulation -- Periodicals; Cardiovascular system -- Periodicals; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; 616.1
• DOI: 10.1161/CIRCULATIONAHA.117.029536
• Languages: English
• ISSNs: 0009-7322

Abstract

Abstract : Background: We recently identified 156 proteins in human plasma that were each associated with the net Framingham Cardiovascular Disease Risk Score using an aptamer-based proteomic platform in Framingham Heart Study Offspring participants. Here we hypothesized that performing genome-wide association studies and exome array analyses on the levels of each of these 156 proteins might identify genetic determinants of risk-associated circulating factors and provide insights into early cardiovascular pathophysiology. Methods: We studied the association of genetic variants with the plasma levels of each of the 156 Framingham Cardiovascular Disease Risk Score–associated proteins using linear mixed-effects models in 2 population-based cohorts. We performed discovery analyses on plasma samples from 759 participants of the Framingham Heart Study Offspring cohort, an observational study of the offspring of the original Framingham Heart Study and their spouses, and validated these findings in plasma samples from 1421 participants of the MDCS (Malmö Diet and Cancer Study). To evaluate the utility of this strategy in identifying new biological pathways relevant to cardiovascular disease pathophysiology, we performed studies in a cell-model system to experimentally validate the functional significance of an especially novel genetic association with circulating apolipoprotein E levels. Results: We identified 120 locus-protein associations in genome-wide analyses and 41 associations in exome array analyses, the majority of which have not been described previously. These loci explained up to 66% of interindividual plasma protein-level variation and, on average, accounted for 3 times the amount of variation explained by common clinical factors, such as age, sex, and diabetes mellitus status. We described overlap among many of these loci and cardiovascular disease genetic risk variants. Finally, we experimentally validated a novel association between circulating apolipoprotein E levels and the transcription factor phosphatase 1G. Knockdown of phosphatase 1G in a human liver cell model resulted in decreased apolipoprotein E transcription and apolipoprotein E protein levels in cultured supernatants. Conclusions: We identified dozens of novel genetic determinants of proteins associated with the Framingham Cardiovascular Disease Risk Score and experimentally validated a new role for phosphatase 1G in lipoprotein biology. Further, genome-wide and exome array data for each protein have been made publicly available as a resource for cardiovascular disease research. Abstract : Supplemental Digital Content is available in the text.