Abstract

A major effort of Core A is to analyze human and mouse plasmas and serum for lipoproteins and their component lipids and apolipoproteins. The lipid analyses employ automated micro-method techniques to determine levels of total cholesterol, HDL* cholesterol, unesterified cholesterol, triacyglycerols, glycerol banks, and unesterified fatty acids. Human plasma LDL and VLDL concentrations including apoB, apoAI, apoAII, and Lp(a). In addition to the measurement of lipids, lipoproteins, and apolipoproteins, the Phenotypic Marker Core also determines levels of several other plasma factors related to lipid/lipoprotein metabolism and atherosclerosis, including plasma concentrations of insulin, glucose, leptin, and the enzymatic activities of lipoprotein lipase and hepatic lipase. All of the assays required to determine the phenotypes proposed in this Program Project are currently in use in our laboratory.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Program Projects (P01)
Project #
2P01HL028481-16A1
Application #
6302152
Study Section
Project Start
2000-04-18
Project End
2001-03-31
Budget Start
Budget End
Support Year
16
Fiscal Year
2000
Total Cost
$234,836
Indirect Cost

  Institution

Name
University of California Los Angeles
Department
Type
DUNS #
119132785
City
Los Angeles
State
CA
Country
United States
Zip Code
90095

  Publications

Small, Kerrin S; Todor?evi?, Marijana; Civelek, Mete et al. (2018) Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition. Nat Genet 50:572-580
Mangul, Serghei; Yang, Harry Taegyun; Strauli, Nicolas et al. (2018) ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues. Genome Biol 19:36
Cantor, Rita; Navarro, Linda; Pan, Calvin (2018) Identifying fenofibrate responsive CpG sites. BMC Proc 12:43
Rahmani, Elior; Schweiger, Regev; Shenhav, Liat et al. (2018) BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference. Genome Biol 19:141
Goldberg, Ira J; Reue, Karen; Abumrad, Nada A et al. (2018) Deciphering the Role of Lipid Droplets in Cardiovascular Disease: A Report From the 2017 National Heart, Lung, and Blood Institute Workshop. Circulation 138:305-315
Hui, Simon T; Kurt, Zeyneb; Tuominen, Iina et al. (2018) The Genetic Architecture of Diet-Induced Hepatic Fibrosis in Mice. Hepatology 68:2182-2196
Kang, Eun Yong; Lee, Cue Hyunkyu; Furlotte, Nicholas A et al. (2018) An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures. Genetics 209:685-698
Seldin, Marcus M; Koplev, Simon; Rajbhandari, Prashant et al. (2018) A Strategy for Discovery of Endocrine Interactions with Application to Whole-Body Metabolism. Cell Metab 27:1138-1155.e6
Lang, Jennifer M; Pan, Calvin; Cantor, Rita M et al. (2018) Impact of Individual Traits, Saturated Fat, and Protein Source on the Gut Microbiome. MBio 9:
Cherlin, Svetlana; Wang, Maggie Haitian; Bickeböller, Heike et al. (2018) Detecting responses to treatment with fenofibrate in pedigrees. BMC Genet 19:64

Showing the most recent 10 out of 518 publications