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Abstract
Paraoxonase 1 (PON1), residing almost exclusively on HDL, was discovered because of its hydrolytic activity towards organophosphates. Subsequently, it was also found to hydrolyse a wide range of substrates, including lactones and lipid hydroperoxides. PON1 is critical for the capacity of HDL to protect LDL and outer cell membranes against harmful oxidative modification, but this activity depends on its location within the hydrophobic lipid domains of HDL. It does not prevent conjugated diene formation, but directs lipid peroxidation products derived from these to become harmless carboxylic acids rather than aldehydes which might adduct to apolipoprotein B. Serum PON1 is inversely related to the incidence of new atherosclerotic cardiovascular disease (ASCVD) events, particularly in diabetes and established ASCVD. Its serum activity is frequently discordant with that of HDL cholesterol. PON1 activity is diminished in dyslipidaemia, diabetes, and inflammatory disease. Polymorphisms, most notably Q192R, can affect activity towards some substrates, but not towards phenyl acetate. Gene ablation or over-expression of human PON1 in rodent models is associated with increased and decreased atherosclerosis susceptibility respectively. PON1 antioxidant activity is enhanced by apolipoprotein AI and lecithin:cholesterol acyl transferase and diminished by apolipoprotein AII, serum amyloid A, and myeloperoxidase. PON1 loses this activity when separated from its lipid environment. Information about its structure has been obtained from water soluble mutants created by directed evolution. Such recombinant PON1 may, however, lose the capacity to hydrolyse non-polar substrates. Whilst nutrition and pre-existing lipid modifying drugs can influence PON1 activity there is a cogent need for more specific PON1-raising medication to be developed.
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Affiliation(s)
- Paul N Durrington
- Cardiovascular Research Group, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Bilal Bashir
- Cardiovascular Research Group, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.,Department of Diabetes, Endocrinology and Metabolism, Peter Mount Building, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - Handrean Soran
- Cardiovascular Research Group, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.,Department of Diabetes, Endocrinology and Metabolism, Peter Mount Building, Manchester University NHS Foundation Trust, Manchester, United Kingdom
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Zhang FH, Yin RX, Yao LM, Lin WX, Wu JZ, Yang DZ. Association between the PLTP rs4810479 SNP and Serum Lipid Traits in the Chinese Maonan and Han Populations. Genet Res (Camb) 2021; 2021:9925272. [PMID: 34385888 DOI: 10.1155/2021/9925272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/22/2021] [Indexed: 11/23/2022] Open
Abstract
The association between the phospholipid transfer protein (PLTP) gene rs4810479 single-nucleotide polymorphism (SNP) and serum lipid levels is largely unknown. This investigation aimed to evaluate the relationship between the PLTP rs4810479 SNP, several environmental risk factors, and serum lipid parameters in the Chinese Maonan and Han nationalities. Polymerase chain reaction-restriction fragment length polymorphism, gel electrophoresis, and direct sequencing were employed to determine the PLTP rs4810479 genotypes in 633 Maonan and 646 Han participants. The frequencies of CC, CT, and TT genotypes and the C allele were different between Maonan and Han groups (29.07%, 53.08%, 17.85%, and 55.61% vs. 35.60%, 49.70%, 14.70%, and 60.45%, respectively, P < 0.05). The C allele carriers in the Maonan group had higher high-density lipoprotein cholesterol levels than the C allele noncarriers, but this finding was only found in Maonan males but not in females. The C allele carriers in Han males had lower total cholesterol and low-density lipoprotein cholesterol levels than the C allele noncarriers. Serum lipid profiles were also affected by several traditional cardiovascular risk factors in both populations. There might be an ethnic- and/or sex-specific association between the PLTP rs4810479 SNP and serum lipid traits.
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Prats-Uribe A, Sayols-Baixeras S, Fernández-Sanlés A, Subirana I, Carreras-Torres R, Vilahur G, Civeira F, Marrugat J, Fitó M, Hernáez Á, Elosua R. High-density lipoprotein characteristics and coronary artery disease: a Mendelian randomization study. Metabolism 2020; 112:154351. [PMID: 32891675 DOI: 10.1016/j.metabol.2020.154351] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/25/2020] [Accepted: 08/31/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND To assess whether genetically determined quantitative and qualitative HDL characteristics were independently associated with coronary artery disease (CAD). METHODS We designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I levels, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al. study, n = 24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, n = 184,305). We validated these results by defining our genetic variables in another database (METSIM, n = 8372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits and minimize potential pleiotropy, we used the Multi-trait-based Conditional & Joint analysis. RESULTS Genetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β = 0.27 [95%CI = 0.19; 0.35]), cholesterol levels in very large HDLs (β = 0.29 [95%CI = 0.17; 0.40]), and triglyceride content in very large HDLs (β = 0.14 [95%CI = 0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β = -0.076 [95%CI = -0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. CONCLUSIONS Some qualitative HDL characteristics (related to size, particle distribution, and cholesterol and triglyceride content) are related to CAD risk while HDL cholesterol levels are not.
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Affiliation(s)
- Albert Prats-Uribe
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Preventive Medicine and Public Health Unit, Parc de Salut Mar-Universitat Pompeu Fabra-ISGLOBAL, Barcelona, Spain; Centre for Statistics in Medicine, Botnar Research Centre, NDORMS, University of Oxford, Oxford, United Kingdom.
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
| | - Isaac Subirana
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Robert Carreras-Torres
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain.
| | - Gemma Vilahur
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Program-ICCC, Research Institute-Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain.
| | - Fernando Civeira
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Lipid Unit, Hospital Universitario Miguel Servet, IIS Aragon, Zaragoza, Spain.
| | - Jaume Marrugat
- Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Girona Heart Registre Research Group (REGICOR), IMIM, Barcelona, Spain.
| | - Montserrat Fitó
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Álvaro Hernáez
- Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Risk, Nutrition, and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Blanquerna School of Life Sciences, Universitat Ramon Llull, Barcelona, Spain.
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Medicine Department, Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain.
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Yamatani K, Hirayama S, Seino U, Hirayama A, Hori A, Suzuki K, Idei M, Kitahara M, Miida T. Preβ1-high-density lipoprotein metabolism is delayed in patients with chronic kidney disease not on hemodialysis. J Clin Lipidol 2020; 14:730-739. [PMID: 32868248 DOI: 10.1016/j.jacl.2020.07.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Revised: 07/28/2020] [Accepted: 07/28/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Preβ1-high-density lipoprotein (HDL) is a lipid-poor cholesterol acceptor that is converted to lipid-rich HDL by lecithin-cholesterol acyltransferase (LCAT). In patients receiving hemodialysis, preβ1-HDL metabolism is hampered even if HDL cholesterol is normal. Hemodialysis may affect preβ1-HDL metabolism by releasing lipases from the vascular wall due to heparin. OBJECTIVES We investigated whether preβ1-HDL metabolism is delayed in patients with chronic kidney disease (CKD) who are not receiving hemodialysis. METHODS We examined 44 patients with Stage 3 or higher CKD and 22 healthy volunteers (Control group). The patients with CKD were divided into those without renal replacement therapy (CKD group, n = 22) and those undergoing continuous ambulatory peritoneal dialysis (CAPD group, n = 22). Plasma preβ1-HDL concentrations were determined by immunoassay. During incubation at 37°C, we used 5,5-dithio-bis (2-nitrobenzoic acid) (DTNB) to inhibit LCAT activity and defined the conversion halftime of preβ1-HDL (CHTpreβ1) as the time required for the difference in preβ1-HDL concentration in the presence and absence of 5,5-DTNB to reach half the baseline concentration. RESULTS The absolute and relative preβ1-HDL concentrations were higher, and CHTpreβ1 was longer in the CKD and CAPD groups than in the Control group. Preβ1-HDL concentration was significantly correlated with CHTpreβ1 but not with LCAT activity in patients with CKD and CAPD. CONCLUSION Preβ1-HDL metabolism is delayed in patients with CKD who are not on hemodialysis. This preβ1-HDL metabolic delay may progress as renal function declines.
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Affiliation(s)
- Kotoko Yamatani
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan; Research Fellow of the Japan Society for the Promotion of Science, Tokyo, Japan
| | - Satoshi Hirayama
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan.
| | - Utako Seino
- Pathology Laboratory, Shinraku-en Hospital, Niigata, Niigata, Japan
| | - Akiko Hirayama
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Atsushi Hori
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan; Center for Genomic and Regenerative Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Koya Suzuki
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan; Research Institute for Diseases of Old Age, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Mayumi Idei
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Masaki Kitahara
- The Sulphuric Acid Association of Japan, Minato-ku, Tokyo, Japan
| | - Takashi Miida
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
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Rosenson RS, Brewer HB, Barter PJ, Björkegren JLM, Chapman MJ, Gaudet D, Kim DS, Niesor E, Rye K, Sacks FM, Tardif J, Hegele RA. HDL and atherosclerotic cardiovascular disease: genetic insights into complex biology. Nat Rev Cardiol 2018; 15:9-19. [DOI: 10.1038/nrcardio.2017.115] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Zubair N, Graff M, Luis Ambite J, Bush WS, Kichaev G, Lu Y, Manichaikul A, Sheu WHH, Absher D, Assimes TL, Bielinski SJ, Bottinger EP, Buzkova P, Chuang LM, Chung RH, Cochran B, Dumitrescu L, Gottesman O, Haessler JW, Haiman C, Heiss G, Hsiung CA, Hung YJ, Hwu CM, Juang JMJ, Le Marchand L, Lee IT, Lee WJ, Lin LA, Lin D, Lin SY, Mackey RH, Martin LW, Pasaniuc B, Peters U, Predazzi I, Quertermous T, Reiner AP, Robinson J, Rotter JI, Ryckman KK, Schreiner PJ, Stahl E, Tao R, Tsai MY, Waite LL, Wang TD, Buyske S, Ida Chen YD, Cheng I, Crawford DC, Loos RJF, Rich SS, Fornage M, North KE, Kooperberg C, Carty CL. Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci. Hum Mol Genet 2017; 25:5500-5512. [PMID: 28426890 DOI: 10.1093/hmg/ddw358] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 10/17/2016] [Indexed: 11/13/2022] Open
Abstract
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.
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Affiliation(s)
- Niha Zubair
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Jose Luis Ambite
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - William S Bush
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Gleb Kichaev
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Yingchang Lu
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ani Manichaikul
- Center for Public Health Genomics and Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, USA
| | - Wayne H-H Sheu
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | - Erwin P Bottinger
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lee-Ming Chuang
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ren-Hua Chung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan
| | - Barbara Cochran
- Genetic Laboratory at the University of Texas Health Science Center, University of Texas, Houston, TX, USA
| | - Logan Dumitrescu
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Omri Gottesman
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jeffrey W Haessler
- WHI Clinical Coordinating Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christopher Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Chao A Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan
| | - Yi-Jen Hung
- Division of Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chii-Min Hwu
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Jyh-Ming J Juang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Loic Le Marchand
- Cancer Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, Hawai'i. USA
| | - I-Te Lee
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Li-An Lin
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Danyu Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shih-Yi Lin
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Rachel H Mackey
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lisa W Martin
- Cardiology Division, School of Medicine and Health Sciences, George Washington University, Washington, DC, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Ulrike Peters
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Irene Predazzi
- Knight Cardiovascular Institute, Center for Preventative Cardiology, Oregon Health & Science University, Portland, OR, USA
| | - Thomas Quertermous
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alex P Reiner
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jennifer Robinson
- Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kelli K Ryckman
- Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Pamela J Schreiner
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Eli Stahl
- Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ran Tao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael Y Tsai
- Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Tzung-Dau Wang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Steven Buyske
- Department of Statistics & Biostatistics, Rutgers University, Piscataway, NJ, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Iona Cheng
- Cancer Prevention Institute of California, Fremont, CA, USA
| | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics and Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Charles Kooperberg
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Cara L Carty
- Center for Translational Science, George Washington University, Children's National Medical Center, Washington, DC, USA
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Kuwano T, Bi X, Cipollari E, Yasuda T, Lagor WR, Szapary HJ, Tohyama J, Millar JS, Billheimer JT, Lyssenko NN, Rader DJ. Overexpression and deletion of phospholipid transfer protein reduce HDL mass and cholesterol efflux capacity but not macrophage reverse cholesterol transport. J Lipid Res 2017; 58:731-741. [PMID: 28137768 DOI: 10.1194/jlr.m074625] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Revised: 01/24/2017] [Indexed: 02/07/2023] Open
Abstract
Phospholipid transfer protein (PLTP) may affect macrophage reverse cholesterol transport (mRCT) through its role in the metabolism of HDL. Ex vivo cholesterol efflux capacity and in vivo mRCT were assessed in PLTP deletion and PLTP overexpression mice. PLTP deletion mice had reduced HDL mass and cholesterol efflux capacity, but unchanged in vivo mRCT. To directly compare the effects of PLTP overexpression and deletion on mRCT, human PLTP was overexpressed in the liver of wild-type animals using an adeno-associated viral (AAV) vector, and control and PLTP deletion animals were injected with AAV-null. PLTP overexpression and deletion reduced plasma HDL mass and cholesterol efflux capacity. Both substantially decreased ABCA1-independent cholesterol efflux, whereas ABCA1-dependent cholesterol efflux remained the same or increased, even though preβ HDL levels were lower. Neither PLTP overexpression nor deletion affected excretion of macrophage-derived radiocholesterol in the in vivo mRCT assay. The ex vivo and in vivo assays were modified to gauge the rate of cholesterol efflux from macrophages to plasma. PLTP activity did not affect this metric. Thus, deviations in PLTP activity from the wild-type level reduce HDL mass and ex vivo cholesterol efflux capacity, but not the rate of macrophage cholesterol efflux to plasma or in vivo mRCT.
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Affiliation(s)
- Takashi Kuwano
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Xin Bi
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Eleonora Cipollari
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Tomoyuki Yasuda
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - William R Lagor
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Hannah J Szapary
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Junichiro Tohyama
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - John S Millar
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Jeffrey T Billheimer
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
| | - Nicholas N Lyssenko
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104.
| | - Daniel J Rader
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104; Department of Medicine and Department of Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104
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Ljunggren SA, Helmfrid I, Norinder U, Fredriksson M, Wingren G, Karlsson H, Lindahl M. Alterations in high-density lipoprotein proteome and function associated with persistent organic pollutants. Environ Int 2017; 98:204-211. [PMID: 27865523 DOI: 10.1016/j.envint.2016.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 10/16/2016] [Accepted: 11/05/2016] [Indexed: 06/06/2023]
Abstract
There is a growing body of evidence that persistent organic pollutants (POPs) may increase the risk for cardiovascular disease (CVD), but the mechanisms remain unclear. High-density lipoprotein (HDL) acts protective against CVD by different processes, and we have earlier found that HDL from subjects with CVD contains higher levels of POPs than healthy controls. In the present study, we have expanded analyses on the same individuals living in a contaminated community and investigated the relationship between the HDL POP levels and protein composition/function. HDL from 17 subjects was isolated by ultracentrifugation. HDL protein composition, using nanoliquid chromatography tandem mass spectrometry, and antioxidant activity were analyzed. The associations of 16 POPs, including polychlorinated biphenyls (PCBs) and organochlorine pesticides, with HDL proteins/functions were investigated by partial least square and multiple linear regression analysis. Proteomic analyses identified 118 HDL proteins, of which ten were significantly (p<0.05) and positively associated with the combined level of POPs or with highly chlorinated PCB congeners. Among these, cholesteryl ester transfer protein and phospholipid transfer protein, as well as the inflammatory marker serum amyloid A, were found. The serum paraoxonase/arylesterase 1 activity was inversely associated with POPs. Pathway analysis demonstrated that up-regulated proteins were associated with biological processes involving lipoprotein metabolism, while down-regulated proteins were associated with processes such as negative regulation of proteinases, acute phase response, platelet degranulation, and complement activation. These results indicate an association between POP levels, especially highly chlorinated PCBs, and HDL protein alterations that may result in a less functional particle. Further studies are needed to determine causality and the importance of other environmental factors. Nevertheless, this study provides a first insight into a possible link between exposure to POPs and risk of CVD.
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Affiliation(s)
- Stefan A Ljunggren
- Occupational and Environmental Medicine Center, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Ingela Helmfrid
- Occupational and Environmental Medicine Center, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Ulf Norinder
- Swedish Toxicology Sciences Research Center, Södertälje, Sweden.
| | - Mats Fredriksson
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Gun Wingren
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Helen Karlsson
- Occupational and Environmental Medicine Center, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Mats Lindahl
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
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Jones GT, Tromp G, Kuivaniemi H, Gretarsdottir S, Baas AF, Giusti B, Strauss E, Van't Hof FNG, Webb TR, Erdman R, Ritchie MD, Elmore JR, Verma A, Pendergrass S, Kullo IJ, Ye Z, Peissig PL, Gottesman O, Verma SS, Malinowski J, Rasmussen-Torvik LJ, Borthwick KM, Smelser DT, Crosslin DR, de Andrade M, Ryer EJ, McCarty CA, Böttinger EP, Pacheco JA, Crawford DC, Carrell DS, Gerhard GS, Franklin DP, Carey DJ, Phillips VL, Williams MJA, Wei W, Blair R, Hill AA, Vasudevan TM, Lewis DR, Thomson IA, Krysa J, Hill GB, Roake J, Merriman TR, Oszkinis G, Galora S, Saracini C, Abbate R, Pulli R, Pratesi C, Saratzis A, Verissimo AR, Bumpstead S, Badger SA, Clough RE, Cockerill G, Hafez H, Scott DJA, Futers TS, Romaine SPR, Bridge K, Griffin KJ, Bailey MA, Smith A, Thompson MM, van Bockxmeer FM, Matthiasson SE, Thorleifsson G, Thorsteinsdottir U, Blankensteijn JD, Teijink JAW, Wijmenga C, de Graaf J, Kiemeney LA, Lindholt JS, Hughes A, Bradley DT, Stirrups K, Golledge J, Norman PE, Powell JT, Humphries SE, Hamby SE, Goodall AH, Nelson CP, Sakalihasan N, Courtois A, Ferrell RE, Eriksson P, Folkersen L, Franco-Cereceda A, Eicher JD, Johnson AD, Betsholtz C, Ruusalepp A, Franzén O, Schadt EE, Björkegren JLM, Lipovich L, Drolet AM, Verhoeven EL, Zeebregts CJ, Geelkerken RH, van Sambeek MR, van Sterkenburg SM, de Vries JP, Stefansson K, Thompson JR, de Bakker PIW, Deloukas P, Sayers RD, Harrison SC, van Rij AM, Samani NJ, Bown MJ. Meta-Analysis of Genome-Wide Association Studies for Abdominal Aortic Aneurysm Identifies Four New Disease-Specific Risk Loci. Circ Res 2016; 120:341-353. [PMID: 27899403 PMCID: PMC5253231 DOI: 10.1161/circresaha.116.308765] [Citation(s) in RCA: 130] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Revised: 10/28/2016] [Accepted: 11/21/2016] [Indexed: 02/06/2023]
Abstract
Supplemental Digital Content is available in the text. Rationale: Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA. Objective: To identify additional AAA risk loci using data from all available genome-wide association studies. Methods and Results: Through a meta-analysis of 6 genome-wide association study data sets and a validation study totaling 10 204 cases and 107 766 controls, we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches, we observed no new associations between the lead AAA single nucleotide polymorphisms and coronary artery disease, blood pressure, lipids, or diabetes mellitus. Network analyses identified ERG, IL6R, and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9. Conclusions: The 4 new risk loci for AAA seem to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease.
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Affiliation(s)
| | - Gerard Tromp
- For the author affiliations, please see the Appendix
| | | | | | | | - Betti Giusti
- For the author affiliations, please see the Appendix
| | - Ewa Strauss
- For the author affiliations, please see the Appendix
| | | | - Thomas R Webb
- For the author affiliations, please see the Appendix
| | - Robert Erdman
- For the author affiliations, please see the Appendix
| | | | | | - Anurag Verma
- For the author affiliations, please see the Appendix
| | | | | | - Zi Ye
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | | | | | | | | | - Evan J Ryer
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | | | | | - David J Carey
- For the author affiliations, please see the Appendix
| | | | | | - Wenhua Wei
- For the author affiliations, please see the Appendix
| | - Ross Blair
- For the author affiliations, please see the Appendix
| | - Andrew A Hill
- For the author affiliations, please see the Appendix
| | | | - David R Lewis
- For the author affiliations, please see the Appendix
| | - Ian A Thomson
- For the author affiliations, please see the Appendix
| | - Jo Krysa
- For the author affiliations, please see the Appendix
| | | | - Justin Roake
- For the author affiliations, please see the Appendix
| | | | | | - Silvia Galora
- For the author affiliations, please see the Appendix
| | | | | | | | - Carlo Pratesi
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | | | - Hany Hafez
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | - Marc A Bailey
- For the author affiliations, please see the Appendix
| | - Alberto Smith
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | | | | | | | | | | | | | - Anne Hughes
- For the author affiliations, please see the Appendix
| | | | | | | | - Paul E Norman
- For the author affiliations, please see the Appendix
| | | | | | | | | | | | | | | | | | - Per Eriksson
- For the author affiliations, please see the Appendix
| | | | | | - John D Eicher
- For the author affiliations, please see the Appendix
| | | | | | | | - Oscar Franzén
- For the author affiliations, please see the Appendix
| | - Eric E Schadt
- For the author affiliations, please see the Appendix
| | | | | | - Anne M Drolet
- For the author affiliations, please see the Appendix
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10
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Kim DS, Li YK, Bell GA, Burt AA, Vaisar T, Hutchins PM, Furlong CE, Otvos JD, Polak JF, Arnan MK, Kaufman JD, McClelland RL, Longstreth WT, Jarvik GP. Concentration of Smaller High-Density Lipoprotein Particle (HDL-P) Is Inversely Correlated With Carotid Intima Media Thickening After Confounder Adjustment: The Multi Ethnic Study of Atherosclerosis (MESA). J Am Heart Assoc 2016; 5:JAHA.115.002977. [PMID: 27207961 PMCID: PMC4889175 DOI: 10.1161/jaha.115.002977] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Background Recent studies have failed to establish a causal relationship between high‐density lipoprotein cholesterol levels (HDL‐C) and cardiovascular disease (CVD), shifting focus to other HDL measures. We previously reported that smaller/denser HDL levels are protective against cerebrovascular disease. This study sought to determine which of small+medium HDL particle concentration (HDL‐P) or large HDL‐P was more strongly associated with carotid intima‐media thickening (cIMT) in an ethnically diverse cohort. Methods and Results In cross‐sectional analyses of participants from the Multi Ethnic Study of Atherosclerosis (MESA), we evaluated the associations of nuclear magnetic resonance spectroscopy–measured small+medium versus large HDL‐P with cIMT measured in the common and internal carotid arteries, through linear regression. After adjustment for CVD confounders, low‐density lipoprotein cholesterol (LDL‐C), HDL‐C, and small+medium HDL‐P remained significantly and inversely associated with common (coefficient=−1.46 μm; P=0.00037; n=6512) and internal cIMT (coefficient=−3.82 μm; P=0.0051; n=6418) after Bonferroni correction for 4 independent tests (threshold for significance=0.0125; α=0.05/4). Large HDL‐P was significantly and inversely associated with both cIMT outcomes before HDL‐C adjustment; however, after adjustment for HDL‐C, the association of large HDL‐P with both common (coefficient=1.55 μm; P=0.30; n=6512) and internal cIMT (coefficient=4.84 μm; P=0.33; n=6418) was attenuated. In a separate sample of 126 men, small/medium HDL‐P was more strongly correlated with paraoxonase 1 activity (rp=0.32; P=0.00023) as compared to both total HDL‐P (rp=0.27; P=0.0024) and large HDL‐P (rp=0.02; P=0.41) measures. Conclusions Small+medium HDL‐P is significantly and inversely correlated with cIMT measurements. Correlation of small+medium HDL‐P with cardioprotective paraoxonase 1 activity may reflect a functional aspect of HDL responsible for this finding.
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Affiliation(s)
- Daniel Seung Kim
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA Department of Biostatistics, University of Washington School of Public Health, Seattle, WA
| | - Yatong K Li
- Department of Biostatistics, University of Washington School of Public Health, Seattle, WA
| | - Griffith A Bell
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Amber A Burt
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Tomas Vaisar
- Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Patrick M Hutchins
- Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA TSI Incorporated, Shoreview, MN
| | - Clement E Furlong
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA
| | | | - Joseph F Polak
- Department of Radiology, Tufts University School of Medicine, Boston, MA
| | | | - Joel D Kaufman
- Division of General Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, WA Department of Epidemiology, University of Washington School of Public Health, Seattle, WA Department of Environmental and Occupational Health Sciences, University of Washington School of Public Health, Seattle, WA
| | - Robyn L McClelland
- Department of Biostatistics, University of Washington School of Public Health, Seattle, WA
| | - W T Longstreth
- Department of Neurology, Wake Forest School of Medicine, Winston-Salem, NC Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Gail P Jarvik
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA
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11
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Rosenson RS. The High-Density Lipoprotein Puzzle: Why Classic Epidemiology, Genetic Epidemiology, and Clinical Trials Conflict? Arterioscler Thromb Vasc Biol 2016; 36:777-82. [PMID: 26966281 DOI: 10.1161/atvbaha.116.307024] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 03/01/2016] [Indexed: 12/23/2022]
Abstract
Classical epidemiology has established the incremental contribution of the high-density lipoprotein (HDL) cholesterol measure in the assessment of atherosclerotic cardiovascular disease risk; yet, genetic epidemiology does not support a causal relationship between HDL cholesterol and the future risk of myocardial infarction. Therapeutic interventions directed toward cholesterol loading of the HDL particle have been based on epidemiological studies that have established HDL cholesterol as a biomarker of atherosclerotic cardiovascular risk. However, therapeutic interventions such as niacin, cholesteryl ester transfer protein inhibitors increase HDL cholesterol in patients treated with statins, but have repeatedly failed to reduce cardiovascular events. Statin therapy interferes with ATP-binding cassette transporter-mediated macrophage cholesterol efflux via miR33 and thus may diminish certain HDL functional properties. Unraveling the HDL puzzle will require continued technical advances in the characterization and quantification of multiple HDL subclasses and their functional properties. Key mechanistic criteria for clinical outcomes trials with HDL-based therapies include formation of HDL subclasses that improve the efficiency of macrophage cholesterol efflux and compositional changes in the proteome and lipidome of the HDL particle that are associated with improved antioxidant and anti-inflammatory properties. These measures require validation in genetic studies and clinical trials of HDL-based therapies on the background of statins.
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Affiliation(s)
- Robert S Rosenson
- From the Icahn School of Medicine at Mount Sinai, Medicine/Cardiology, New York, NY.
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12
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Hellberg S, Silvola JMU, Kiugel M, Liljenbäck H, Metsälä O, Viljanen T, Metso J, Jauhiainen M, Saukko P, Nuutila P, Ylä-Herttuala S, Knuuti J, Roivainen A, Saraste A. Type 2 diabetes enhances arterial uptake of choline in atherosclerotic mice: an imaging study with positron emission tomography tracer ¹⁸F-fluoromethylcholine. Cardiovasc Diabetol 2016; 15:26. [PMID: 26852231 PMCID: PMC4744438 DOI: 10.1186/s12933-016-0340-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 01/18/2016] [Indexed: 01/13/2023] Open
Abstract
Background Diabetes is a risk factor for atherosclerosis associated with oxidative stress, inflammation and cell proliferation. The purpose of this study was to evaluate arterial choline uptake and its relationship to atherosclerotic inflammation in diabetic and non-diabetic hypercholesterolemic mice. Methods Low-density lipoprotein-receptor deficient mice expressing only apolipoprotein B100, with or without type 2 diabetes caused by pancreatic overexpression of insulin-like growth factor II (IGF-II/LDLR−/−ApoB100/100 and LDLR−/−ApoB100/100) were studied. Distribution kinetics of choline analogue 18F-fluoromethylcholine (18F-FMCH) was assessed in vivo by positron emission tomography (PET) imaging. Then, aortic uptakes of 18F-FMCH and glucose analogue 18F-fluorodeoxyglucose (18F-FDG), were assessed ex vivo by gamma counting and autoradiography of tissue sections. The 18F-FMCH uptake in atherosclerotic plaques was further compared with macrophage infiltration and the plasma levels of cytokines and metabolic markers. Results The aortas of all hypercholesterolemic mice showed large, macrophage-rich atherosclerotic plaques. The plaque burden and densities of macrophage subtypes were similar in diabetic and non-diabetic animals. The blood clearance of 18F-FMCH was rapid. Both the absolute 18F-FMCH uptake in the aorta and the aorta-to-blood uptake ratio were higher in diabetic than in non-diabetic mice. In autoradiography, the highest 18F-FMCH uptake co-localized with macrophage-rich atherosclerotic plaques. 18F-FMCH uptake in plaques correlated with levels of total cholesterol, insulin, C-peptide and leptin. In comparison with 18F-FDG, 18F-FMCH provided similar or higher plaque-to-background ratios in diabetic mice. Conclusions Type 2 diabetes enhances the uptake of choline that reflects inflammation in atherosclerotic plaques in mice. PET tracer 18F-FMCH is a potential tool to study vascular inflammation associated with diabetes. Electronic supplementary material The online version of this article (doi:10.1186/s12933-016-0340-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sanna Hellberg
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Johanna M U Silvola
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Max Kiugel
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Heidi Liljenbäck
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Turku Center for Disease Modeling, University of Turku, Kiinamyllynkatu 10, 20520, Turku, Finland.
| | - Olli Metsälä
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Tapio Viljanen
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Jari Metso
- Genomics and Biomarkers Unit, National Institute for Health and Welfare, Haartmaninkatu 8, 00250, Helsinki, Finland.
| | - Matti Jauhiainen
- Genomics and Biomarkers Unit, National Institute for Health and Welfare, Haartmaninkatu 8, 00250, Helsinki, Finland.
| | - Pekka Saukko
- Department of Pathology and Forensic Medicine, University of Turku, Kiinamyllynkatu 10, 20520, Turku, Finland.
| | - Pirjo Nuutila
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Seppo Ylä-Herttuala
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Neulaniementie 2, 70210, Kuopio, Finland. .,Science Service Center, Kuopio University Hospital, Puijonlaaksontie 2, 70210, Kuopio, Finland.
| | - Juhani Knuuti
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Anne Roivainen
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Turku Center for Disease Modeling, University of Turku, Kiinamyllynkatu 10, 20520, Turku, Finland. .,Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
| | - Antti Saraste
- Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Turku PET Centre, Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland. .,Heart Center, Turku University Hospital, Hämeentie 11, 20520, Turku, Finland.
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13
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Dullaart RPF, Gruppen EG, Dallinga-Thie GM. Paraoxonase-1 activity is positively related to phospholipid transfer protein activity in type 2 diabetes mellitus: Role of large HDL particles. Clin Biochem 2015; 49:508-510. [PMID: 26656640 DOI: 10.1016/j.clinbiochem.2015.11.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 11/25/2015] [Accepted: 11/26/2015] [Indexed: 11/15/2022]
Abstract
OBJECTIVES High density lipoprotein (HDL)-associated paraoxonase-1 (PON-1) exerts anti-oxidative properties, whereas phospholipid transfer protein (PLTP) is able to convert mature HDL into larger and smaller HDL particles. Here we tested associations of PON-1 with PLTP in type 2 diabetes mellitus (T2DM), a condition characterized by lower PON-1 activity and higher PLTP activity. DESIGN AND METHODS Serum PON-1 (arylesterase activity), plasma PLTP activity (liposome-vesicle HDL system), and (apo)lipoproteins were measured in 81 T2DM subjects (mean age 59±9years; 31 women; no insulin treatment). In 48 participants, HDL subfractions were measured by nuclear magnetic resonance spectroscopy. RESULTS In univariate correlation analysis, PON-1 activity was positively related to PLTP activity (r=0.348, p=0.001). PLTP activity was positively related to blood pressure, body mass index and triglycerides, whereas PON-1 activity was positively to HDL cholesterol and apoA-I (p<0.05 to <0.01 for each). Both PLTP activity and PON-I activity were positively related to large HDL particles (r=0.379, p=0.008 and r=0.411, p=0.004, respectively). In multivariable linear regression analysis, PON-1 activity was associated with PLTP activity independent of clinical covariates and HDL cholesterol or apoA-I (β=0.340, p=0.001 and β=0.320, p=0.003, respectively). The association of PON-1 activity with PLTP activity was lost in analysis which included large HDL particles (large HDL: β=0.411, p=0.004). CONCLUSIONS PON-1 activity is positively related to PLTP activity in T2DM, raising the possibility that PLTP could act to maintain PON-1. This association may in part be attributable to a common relationship of PON-1 and PLTP with large HDL particles.
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Affiliation(s)
- Robin P F Dullaart
- Department of Endocrinology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
| | - Eke G Gruppen
- Department of Endocrinology, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Geesje M Dallinga-Thie
- Department of Experimental Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands
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14
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Abstract
Reverse cholesterol transport (RCT) is the pathway for removal of peripheral tissue cholesterol and involves transport of cholesterol back to liver for excretion, starting from cellular cholesterol efflux facilitated by lipid-free apolipoprotein A1 (ApoA1) or other lipidated high-density lipoprotein (HDL) particles within the interstitial space. Extracellular cholesterol then is picked up and transported through the lymphatic vasculature before entering into bloodstream. There is increasing evidence supporting a role for enhanced macrophage cholesterol efflux and RCT in ameliorating atherosclerosis, and recent data suggest that these processes may serve as better diagnostic biomarkers than plasma HDL levels. Hence, it is important to better understand the processes governing ApoA1 and HDL influx into peripheral tissues from the bloodstream, modification and facilitation of cellular cholesterol removal within the interstitial space, and transport through the lymphatic vasculature. New findings will complement therapeutic strategies for the treatment of atherosclerotic vascular disease.
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Affiliation(s)
- Li-Hao Huang
- Department of Pathology and Immunology, Washington University School of Medicine , St. Louis, MO, USA
| | - Andrew Elvington
- Department of Pathology and Immunology, Washington University School of Medicine , St. Louis, MO, USA
| | - Gwendalyn J Randolph
- Department of Pathology and Immunology, Washington University School of Medicine , St. Louis, MO, USA
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