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Mera-Charria A, Nieto-Lopez F, Francès MP, Arbex PM, Vila-Vecilla L, Russo V, Silva CCV, De Souza GT. Genetic variant panel allows predicting both obesity risk, and efficacy of procedures and diet in weight loss. Front Nutr 2023; 10:1274662. [PMID: 38035352 PMCID: PMC10687570 DOI: 10.3389/fnut.2023.1274662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/24/2023] [Indexed: 12/02/2023] Open
Abstract
Purpose Obesity is a multifactorial condition with a relevant genetic correlation. Recent advances in genomic research have identified several single nucleotide polymorphisms (SNPs) in genes such as FTO, MCM6, HLA, and MC4R, associated with obesity. This study aimed to evaluate the association of 102 SNPs with BMI and weight loss treatment response in a multi-ethnic population. Methods The study analyzed 9,372 patients for the correlation between SNPs and BMI (dataset A). The correlation between SNP and weight loss was accessed in 474 patients undergoing different treatments (dataset B). Patients in dataset B were further divided into 3 categories based on the type of intervention: dietary therapy, intragastric balloon procedures, or surgeries. SNP association analysis and multiple models of inheritance were performed. Results In dataset A, ten SNPs, including rs9939609 (FTO), rs4988235 (MCM6), and rs2395182 (HLA), were significantly associated with increased BMI. Additionally, other four SNPs, rs7903146 (TCF7L2), (rs6511720), rs5400 (SLC2A2), and rs7498665 (SH2B1), showed sex-specific correlation. For dataset B, SNPs rs2016520 (PPAR-Delta) and rs2419621 (ACSL5) demonstrated significant correlation with weight loss for all treatment types. In patients who adhered to dietary therapy, SNPs rs6544713 (ABCG8) and rs762551 (CYP1A2) were strongly correlated with weight loss. Patients undergoing surgical or endoscopic procedures exhibited differential correlations with several SNPs, including rs1801725 (CASR) and rs12970134 (MC4R), and weight loss. Conclusion This study provides valuable insights into the genetic factors influencing BMI and weight loss response to different treatments. The findings highlight the potential for personalized weight management approaches based on individual genetic profiles.
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Affiliation(s)
| | - Francisco Nieto-Lopez
- Dorsia Clinics, Madrid, Spain
- Catedra UCAM Dorsia, Catholic University San Antonio of Murcia, Guadalupe, Spain
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DiCorpo D, LeClair J, Cole JB, Sarnowski C, Ahmadizar F, Bielak LF, Blokstra A, Bottinger EP, Chaker L, Chen YDI, Chen Y, de Vries PS, Faquih T, Ghanbari M, Gudmundsdottir V, Guo X, Hasbani NR, Ibi D, Ikram MA, Kavousi M, Leonard HL, Leong A, Mercader JM, Morrison AC, Nadkarni GN, Nalls MA, Noordam R, Preuss M, Smith JA, Trompet S, Vissink P, Yao J, Zhao W, Boerwinkle E, Goodarzi MO, Gudnason V, Jukema JW, Kardia SL, Loos RJ, Liu CT, Manning AK, Mook-Kanamori D, Pankow JS, Picavet HSJ, Sattar N, Simonsick EM, Verschuren WM, Willems van Dijk K, Florez JC, Rotter JI, Meigs JB, Dupuis J, Udler MS. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts. Diabetes Care 2022; 45:674-683. [PMID: 35085396 PMCID: PMC8918228 DOI: 10.2337/dc21-1395] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
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Affiliation(s)
- Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jessica LeClair
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Division of Endocrinology, Boston Children’s Hospital, Boston, MA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Anneke Blokstra
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Erwin P. Bottinger
- Hasso Plattner Institute Digital Health, Potsdam, Germany
- Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Layal Chaker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yii-Der I. Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Ye Chen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Tariq Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Dorina Ibi
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hampton L. Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Alanna C. Morrison
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Petra Vissink
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Ruth J.F. Loos
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - H. Susan J. Picavet
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K
| | - Eleanor M. Simonsick
- Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Miriam S. Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
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3
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Blauw LL, Noordam R, van der Laan SW, Trompet S, Kooijman S, van Heemst D, Jukema JW, van Setten J, de Borst GJ, Tybjærg-Hansen A, Pasterkamp G, Berbée JFP, Rensen PCN. Common Genetic Variation in MC4R Does Not Affect Atherosclerotic Plaque Phenotypes and Cardiovascular Disease Outcomes. J Clin Med 2021; 10:jcm10050932. [PMID: 33804309 PMCID: PMC7957774 DOI: 10.3390/jcm10050932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 02/11/2021] [Accepted: 02/23/2021] [Indexed: 12/01/2022] Open
Abstract
We analyzed the effects of the common BMI-increasing melanocortin 4 receptor (MC4R) rs17782313-C allele with a minor allele frequency of 0.22–0.25 on (1) cardiovascular disease outcomes in two large population-based cohorts (Copenhagen City Heart Study and Copenhagen General Population Study, n = 106,018; and UK Biobank, n = 357,426) and additionally in an elderly population at risk for cardiovascular disease (n = 5241), and on (2) atherosclerotic plaque phenotypes in samples of patients who underwent endarterectomy (n = 1439). Using regression models, we additionally analyzed whether potential associations were modified by sex or explained by changes in body mass index. We confirmed the BMI-increasing effects of +0.22 kg/m2 per additional copy of the C allele (p < 0.001). However, we found no evidence for an association of common MC4R genetic variation with coronary artery disease (HR 1.03; 95% CI 0.99, 1.07), ischemic vascular disease (HR 1.00; 95% CI 0.98, 1.03), myocardial infarction (HR 1.01; 95% CI 0.94, 1.08 and 1.02; 0.98, 1.07) or stroke (HR 0.93; 95% CI 0.85, 1.01), nor with any atherosclerotic plaque phenotype. Thus, common MC4R genetic variation, despite increasing BMI, does not affect cardiovascular disease risk in the general population or in populations at risk for cardiovascular disease.
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Affiliation(s)
- Lisanne L. Blauw
- Department Medicine, Division Endocrinology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (L.L.B.); (S.K.); (J.F.P.B.); (P.C.N.R.)
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Raymond Noordam
- Department Medicine, Division Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (S.T.); (D.v.H.)
- Correspondence: ; Tel.: +31-71-52-66640
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands; (S.W.v.d.L.); (G.P.)
| | - Stella Trompet
- Department Medicine, Division Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (S.T.); (D.v.H.)
| | - Sander Kooijman
- Department Medicine, Division Endocrinology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (L.L.B.); (S.K.); (J.F.P.B.); (P.C.N.R.)
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Diana van Heemst
- Department Medicine, Division Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (S.T.); (D.v.H.)
| | - Johan Wouter Jukema
- Department Cardiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands;
| | - Jessica van Setten
- Surgery Specialties, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands;
| | - Gert J. de Borst
- Department Cardiology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands;
| | - Anne Tybjærg-Hansen
- Department Clinical Biochemistry, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark;
- The Copenhagen City Heart Study, Frederiksberg Hospital, Nordre Fasanvej 57, DK-2000 Frederiksberg, Denmark
- The Copenhagen General Population Study and Gentofte Hospital, Herlev Ringvej 75, DK-2730 Herlev, Denmark
- Copenhagen University Hospitals and Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100 Copenhagen, Denmark
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands; (S.W.v.d.L.); (G.P.)
| | - Jimmy F. P. Berbée
- Department Medicine, Division Endocrinology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (L.L.B.); (S.K.); (J.F.P.B.); (P.C.N.R.)
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
| | - Patrick C. N. Rensen
- Department Medicine, Division Endocrinology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; (L.L.B.); (S.K.); (J.F.P.B.); (P.C.N.R.)
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands
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4
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Håkansson KEJ, Goossens EAC, Trompet S, van Ingen E, de Vries MR, van der Kwast RVCT, Ripa RS, Kastrup J, Hohensinner PJ, Kaun C, Wojta J, Böhringer S, Le Cessie S, Jukema JW, Quax PHA, Nossent AY. Genetic associations and regulation of expression indicate an independent role for 14q32 snoRNAs in human cardiovascular disease. Cardiovasc Res 2020; 115:1519-1532. [PMID: 30544252 DOI: 10.1093/cvr/cvy309] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 11/30/2018] [Accepted: 12/11/2018] [Indexed: 01/12/2023] Open
Abstract
AIMS We have shown that 14q32 microRNAs are highly involved in vascular remodelling and cardiovascular disease. However, the 14q32 locus also encodes 41 'orphan' small nucleolar RNAs (snoRNAs). We aimed to gather evidence for an independent role for 14q32 snoRNAs in human cardiovascular disease. METHODS AND RESULTS We performed a lookup of the 14q32 region within the dataset of a genome wide association scan in 5244 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Single nucleotide polymorphisms (SNPs) in the snoRNA-cluster were significantly associated with heart failure. These snoRNA-cluster SNPs were not linked to SNPs in the microRNA-cluster or in MEG3, indicating that snoRNAs modify the risk of cardiovascular disease independently. We looked at expression of 14q32 snoRNAs throughout the human cardio-vasculature. Expression profiles of the 14q32 snoRNAs appeared highly vessel specific. When we compared expression levels of 14q32 snoRNAs in human vena saphena magna (VSM) with those in failed VSM-coronary bypasses, we found that 14q32 snoRNAs were up-regulated. SNORD113.2, which showed a 17-fold up-regulation in failed bypasses, was also up-regulated two-fold in plasma samples drawn from patients with ST-elevation myocardial infarction directly after hospitalization compared with 30 days after start of treatment. However, fitting with the genomic associations, 14q32 snoRNA expression was highest in failing human hearts. In vitro studies show that the 14q32 snoRNAs bind predominantly to methyl-transferase Fibrillarin, indicating that they act through canonical mechanisms, but on non-canonical RNA targets. The canonical C/D-box snoRNA seed sequences were highly conserved between humans and mice. CONCLUSION 14q32 snoRNAs appear to play an independent role in cardiovascular pathology. 14q32 snoRNAs are specifically regulated throughout the human vasculature and their expression is up-regulated during cardiovascular disease. Our data demonstrate that snoRNAs merit increased effort and attention in future basic and clinical cardiovascular research.
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Affiliation(s)
- Kjell E J Håkansson
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Eveline A C Goossens
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Eva van Ingen
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Margreet R de Vries
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Reginald V C T van der Kwast
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Rasmus S Ripa
- Department of Cardiology, Rigshospitalet University of Copenhagen, Copenhagen, Denmark
| | - Jens Kastrup
- Department of Cardiology, Rigshospitalet University of Copenhagen, Copenhagen, Denmark
| | | | - Christoph Kaun
- Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Johann Wojta
- Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Stefan Böhringer
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Saskia Le Cessie
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Paul H A Quax
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - A Yaël Nossent
- Department of Surgery, K6-R, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Ludwig Boltzmann Cluster for Cardiovascular Research, Vienna, Austria
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5
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Fuior EV, Gafencu AV. Apolipoprotein C1: Its Pleiotropic Effects in Lipid Metabolism and Beyond. Int J Mol Sci 2019; 20:ijms20235939. [PMID: 31779116 PMCID: PMC6928722 DOI: 10.3390/ijms20235939] [Citation(s) in RCA: 97] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/19/2019] [Accepted: 11/21/2019] [Indexed: 12/20/2022] Open
Abstract
Apolipoprotein C1 (apoC1), the smallest of all apolipoproteins, participates in lipid transport and metabolism. In humans, APOC1 gene is in linkage disequilibrium with APOE gene on chromosome 19, a proximity that spurred its investigation. Apolipoprotein C1 associates with triglyceride-rich lipoproteins and HDL and exchanges between lipoprotein classes. These interactions occur via amphipathic helix motifs, as demonstrated by biophysical studies on the wild-type polypeptide and representative mutants. Apolipoprotein C1 acts on lipoprotein receptors by inhibiting binding mediated by apolipoprotein E, and modulating the activities of several enzymes. Thus, apoC1 downregulates lipoprotein lipase, hepatic lipase, phospholipase A2, cholesterylester transfer protein, and activates lecithin-cholesterol acyl transferase. By controlling the plasma levels of lipids, apoC1 relates directly to cardiovascular physiology, but its activity extends beyond, to inflammation and immunity, sepsis, diabetes, cancer, viral infectivity, and-not last-to cognition. Such correlations were established based on studies using transgenic mice, associated in the recent years with GWAS, transcriptomic and proteomic analyses. The presence of a duplicate gene, pseudogene APOC1P, stimulated evolutionary studies and more recently, the regulatory properties of the corresponding non-coding RNA are steadily emerging. Nonetheless, this prototypical apolipoprotein is still underexplored and deserves further research for understanding its physiology and exploiting its therapeutic potential.
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Affiliation(s)
- Elena V. Fuior
- Institute of Cellular Biology and Pathology “N. Simionescu”, 050568 Bucharest, Romania;
| | - Anca V. Gafencu
- Institute of Cellular Biology and Pathology “N. Simionescu”, 050568 Bucharest, Romania;
- Correspondence:
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6
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Liu W, Cui Z, Xu P, Han H, Zhu J. Conditional GWAS revealing genetic impacts of lifestyle behaviors on low-density lipoprotein (LDL). Comput Biol Chem 2018; 78:497-503. [PMID: 30473251 DOI: 10.1016/j.compbiolchem.2018.11.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Accepted: 11/16/2018] [Indexed: 10/27/2022]
Abstract
BACKGROUND Accumulation of LDL cholesterol (LDL-c) within artery walls is strongly associated with the initiation and progression of atherosclerosis development. This complex trait is affected by multifactor involving polygenes, environments, and their interactions. Uncovering genetic architecture of LDL may help to increase the understanding of the genetic mechanism of cardiovascular diseases. METHODS We used a genetic model to analyze genetic effects including additive, dominance, epistasis, and ethnic interactions for data from the Multi-Ethnic Study of Atherosclerosis (MESA). Three lifestyle behaviors (reading, intentional exercising, smoking) were used as cofactor in conditional models. RESULTS We identified 156 genetic effects of 10 quantitative trait SNPs (QTSs) in base model and three conditional models. The total estimated heritability of these genetic effects was approximately 72.88% in the base model. Five genes (CELSR2, MARK2, ADAMTS12, PFDN4, and MAGI2) have biological functions related to LDL. CONCLUSIONS Compared with the based model LDL, the results in three conditional models revealed that intentional exercising and smoking could have impacts for causing and suppressing some of genetic effects and influence the levels of LDL. Furthermore, these two lifestyles could have different genetic effects for each ethnic group on a specific QTS. As most of the heritability in based model LDL and conditional model LDL|Smk was contributed from epistasis effects, our result indicated that epistasis effects played important roles in determining LDL levels. Our study provided useful insight into the biological mechanisms underlying regulation of LDL and might help in the discovery of novel therapeutic targets for cardiovascular disease.
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Affiliation(s)
- Wenbin Liu
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, China.
| | - Zhendong Cui
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, China
| | - Peng Xu
- Institute of Computational Science and Technology, Guangzhou University, Guangzhou, 510006, China
| | - Henrry Han
- Department of Computer and Information Science, Fordham University, New York, NY, 10458, USA
| | - Jun Zhu
- Institute of Bioinformatics, Zhejiang University, Hangzhou, 310058, China.
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Shatwan IM, Winther KH, Ellahi B, Elwood P, Ben-Shlomo Y, Givens I, Rayman MP, Lovegrove JA, Vimaleswaran KS. Association of apolipoprotein E gene polymorphisms with blood lipids and their interaction with dietary factors. Lipids Health Dis 2018; 17:98. [PMID: 29712557 PMCID: PMC5928585 DOI: 10.1186/s12944-018-0744-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2017] [Accepted: 04/13/2018] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. METHODS The population studied for this investigation included 660 individuals from the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ) in PRECISE and a validated semi-quantitative FFQ in the CaPS. Interaction analyses were performed by including the interaction term in the linear regression model adjusted for age, body mass index, sex and country. RESULTS There was no association between dietary factors and blood lipids after Bonferroni correction and adjustment for confounding factors in either cohort. In the PRECISE study, after correction for multiple testing, there was a statistically significant association of the APOE haplotype (rs7412 and rs429358; E2, E3, and E4) and APOE tagSNP rs445925 with total cholesterol (P = 4 × 10- 4 and P = 0.003, respectively). Carriers of the E2 allele had lower total cholesterol concentration (5.54 ± 0.97 mmol/L) than those with the E3 (5.98 ± 1.05 mmol/L) (P = 0.001) and E4 (6.09 ± 1.06 mmol/L) (P = 2 × 10- 4) alleles. The association of APOE haplotype (E2, E3, and E4) and APOE SNP rs445925 with total cholesterol (P = 2 × 10- 6 and P = 3 × 10- 4, respectively) was further replicated in the CaPS. Additionally, significant association was found between APOE haplotype and APOE SNP rs445925 with low density lipoprotein cholesterol in CaPS (P = 4 × 10- 4 and P = 0.001, respectively). After Bonferroni correction, none of the cohorts showed a statistically significant SNP-diet interaction on lipid outcomes. CONCLUSION In summary, our findings from the two cohorts confirm that genetic variations at the APOE locus influence plasma total cholesterol concentrations, however, the gene-diet interactions on lipids require further investigation in larger cohorts.
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Affiliation(s)
- Israa M Shatwan
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.,Food and Nutrition Department, Faculty of Home Economics, King Abdulaziz University, Jeddah, Saudi Arabia
| | | | - Basma Ellahi
- Faculty of Health and Social Care, University of Chester, Chester, CH1 1SL, UK
| | - Peter Elwood
- Department of Epidemiology, Statistics and Public Health, Cardiff University, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, University of Bristol, Bristol, BS8 2PS, UK
| | - Ian Givens
- Institute for Food, Nutrition and Health, University of Reading, Earley Gate, Reading, RG6 6AR, UK
| | - Margaret P Rayman
- Department of Nutritional Sciences Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK
| | - Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.
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8
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Visit-to-visit lipid variability: Clinical significance, effects of lipid-lowering treatment, and (pharmaco) genetics. J Clin Lipidol 2018; 12:266-276.e3. [DOI: 10.1016/j.jacl.2018.01.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 12/30/2017] [Accepted: 01/03/2018] [Indexed: 12/24/2022]
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9
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Shatwan IM, Weech M, Jackson KG, Lovegrove JA, Vimaleswaran KS. Apolipoprotein E gene polymorphism modifies fasting total cholesterol concentrations in response to replacement of dietary saturated with monounsaturated fatty acids in adults at moderate cardiovascular disease risk. Lipids Health Dis 2017; 16:222. [PMID: 29169396 PMCID: PMC5701425 DOI: 10.1186/s12944-017-0606-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 11/05/2017] [Indexed: 12/24/2022] Open
Abstract
Background Consumption of ≤10% total energy from fat as saturated fatty acids (SFA) is recommended for cardiovascular disease risk reduction in the UK; however there is no clear guidance on the optimum replacement nutrient. Lipid-associated single-nucleotide polymorphisms (SNPs) have been shown to modify the lipid responses to dietary fat interventions. Hence, we performed a retrospective analysis in 120 participants from the Dietary Intervention and VAScular function (DIVAS) study to investigate whether lipoprotein lipase (LPL) and apolipoprotein E (APOE) SNPs modify the fasting lipid response to replacement of SFA with monounsaturated (MUFA) or n-6 polyunsaturated (PUFA) fatty acids. Methods The DIVAS study was a randomized, single-blinded, parallel dietary intervention study performed in adults with a moderate cardiovascular risk who received one of three isoenergetic diets rich in SFA, MUFA or n-6 PUFA for 16 weeks. Results After the 16-week intervention, a significant diet-gene interaction was observed for changes in fasting total cholesterol (P = 0.001). For the APOE SNP rs1064725, only TT homozygotes showed a significant reduction in total cholesterol after the MUFA diet (n = 33; −0.71 ± 1.88 mmol/l) compared to the SFA (n = 38; 0.34 ± 0.55 mmol/l) or n-6 PUFA diets (n = 37; −0.08 ± 0.73 mmol/l) (P = 0.004). None of the interactions were statistically significant for the other SNPs. Conclusions In summary, our findings have demonstrated a greater sensitivity of the APOE SNP rs1064725 to dietary fat composition, with a total cholesterol lowering effect observed following substitution of SFA with MUFA but not n-6 PUFA. Further large intervention studies incorporating prospective genotyping are required to confirm or refute our findings. Trial registration The trial was registered at www.clinicaltrials.gov as NCT01478958. Electronic supplementary material The online version of this article (10.1186/s12944-017-0606-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Israa M Shatwan
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food & Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.,Food and Nutrition Department, Faculty of Home Economics, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Michelle Weech
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food & Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK
| | - Kim G Jackson
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food & Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food & Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK
| | - Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food & Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.
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Trompet S, Postmus I, Slagboom PE, Heijmans BT, Smit RAJ, Maier AB, Buckley BM, Sattar N, Stott DJ, Ford I, Westendorp RGJ, de Craen AJM, Jukema JW. Non-response to (statin) therapy: the importance of distinguishing non-responders from non-adherers in pharmacogenetic studies. Eur J Clin Pharmacol 2016; 72:431-7. [PMID: 26686871 PMCID: PMC4792342 DOI: 10.1007/s00228-015-1994-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Accepted: 12/01/2015] [Indexed: 11/16/2022]
Abstract
PURPOSE In pharmacogenetic research, genetic variation in non-responders and high responders is compared with the aim to identify the genetic loci responsible for this variation in response. However, an important question is whether the non-responders are truly biologically non-responsive or actually non-adherent? Therefore, the aim of this study was to describe, within the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), characteristics of both non-responders and high responders of statin treatment in order to possibly discriminate non-responders from non-adherers. METHODS Baseline characteristics of non-responders to statin therapy (≤10 % LDL-C reduction) were compared with those of high responders (>40 % LDL-C reduction) through a linear regression analysis. In addition, pharmacogenetic candidate gene analysis was performed to show the effect of excluding non-responders from the analysis. RESULTS Non-responders to statin therapy were younger (p = 0.001), more often smoked (p < 0.001), had a higher alcohol consumption (p < 0.001), had lower LDL cholesterol levels (p < 0.001), had a lower prevalence of hypertension (p < 0.001), and had lower cognitive function (p = 0.035) compared to subjects who highly responded to pravastatin treatment. Moreover, excluding non-responders from pharmacogenetic studies yielded more robust results, as standard errors decreased. CONCLUSION Our results suggest that non-responders to statin therapy are more likely to actually be non-adherers, since they have more characteristics that are viewed as indicators of high self-perceived health and low disease awareness, possibly making the subjects less adherent to study medication. We suggest that in pharmacogenetic research, extreme non-responders should be excluded to overcome the problem that non-adherence is investigated instead of non-responsiveness.
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Affiliation(s)
- S Trompet
- Department of Cardiology, C5-R, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
| | - I Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - P E Slagboom
- Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - B T Heijmans
- Section of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - R A J Smit
- Department of Cardiology, C5-R, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - A B Maier
- Section Gerontology and Geriatrics, Department of Internal Medicine, VU Medical Center, Amsterdam, The Netherlands
| | - B M Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - N Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK
| | - D J Stott
- Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow, UK
| | - I Ford
- Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK
| | - R G J Westendorp
- Faculty of Health and Medical Sciences, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - A J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - J W Jukema
- Department of Cardiology, C5-R, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
- Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
- Interuniversity Cardiology Institute of the Netherlands, Utrecht, the Netherlands
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Association of common variants in TOMM40/APOE/APOC1 region with human longevity in a Chinese population. J Hum Genet 2015; 61:323-8. [PMID: 26657933 DOI: 10.1038/jhg.2015.150] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Revised: 11/01/2015] [Accepted: 11/05/2015] [Indexed: 11/08/2022]
Abstract
Apolipoprotein E (APOE), translocase of outer mitochondrial membrane 40 homolog (TOMM40) and apolipoprotein C-I (APOC1) may extend lifespan by marked delay or escape from age-related diseases. This study aimed to elucidate the association of human longevity with genetic variations in TOMM40/APOE/APOC1 region in a Chinese population. Ten tag single-nucleotide polymorphisms (SNPs) in the TOMM40/APOE/APOC1 region were successfully genotyped in 616 unrelated long-lived individuals and 846 younger controls. Of the 10 SNPs, rs7254892 in 5' upstream of TOMM40 showed significant association with human longevity (G/A-A/A vs G/G: odds ratio (OR)=1.59, 95% confidence interval (CI)=1.20-2.09, P=0.0011, Bonferroni corrected P (Pc)=0.033). The haplotype analysis suggested that individuals carrying the haplotype A-A-A-A-T-A-T-G-C-A (rs7254892-rs157580-rs2075649-rs2075650-rs157582-rs8106922-rs1160985-rs405697-rs439401-rs445925) tended to have longer lifespan than those carrying the most common haplotype G-G-A-A-C-A-C-A-T-G (OR=1.59, 95% CI=1.19-2.12, P=0.0018, Pc=0.0216). These findings indicated that variants in TOMM40/APOE/APOC1 region might be associated with human longevity. Further studies are needed to identify the causal genetic variants influencing human longevity.
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Genome-wide association studies identify genetic loci for low von Willebrand factor levels. Eur J Hum Genet 2015; 24:1035-40. [PMID: 26486471 DOI: 10.1038/ejhg.2015.222] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Revised: 08/23/2015] [Accepted: 09/11/2015] [Indexed: 01/14/2023] Open
Abstract
Low von Willebrand factor (VWF) levels are associated with bleeding symptoms and are a diagnostic criterion for von Willebrand disease, the most common inherited bleeding disorder. To date, it is unclear which genetic loci are associated with reduced VWF levels. Therefore, we conducted a meta-analysis of genome-wide association studies to identify genetic loci associated with low VWF levels. For this meta-analysis, we included 31 149 participants of European ancestry from 11 community-based studies. From all participants, VWF antigen (VWF:Ag) measurements and genome-wide single-nucleotide polymorphism (SNP) scans were available. Each study conducted analyses using logistic regression of SNPs on dichotomized VWF:Ag measures (lowest 5% for blood group O and non-O) with an additive genetic model adjusted for age and sex. An inverse-variance weighted meta-analysis was performed for VWF:Ag levels. A total of 97 SNPs exceeded the genome-wide significance threshold of 5 × 10(-8) and comprised five loci on four different chromosomes: 6q24 (smallest P-value 5.8 × 10(-10)), 9q34 (2.4 × 10(-64)), 12p13 (5.3 × 10(-22)), 12q23 (1.2 × 10(-8)) and 13q13 (2.6 × 10(-8)). All loci were within or close to genes, including STXBP5 (Syntaxin Binding Protein 5) (6q24), STAB5 (stabilin-5) (12q23), ABO (9q34), VWF (12p13) and UFM1 (ubiquitin-fold modifier 1) (13q13). Of these, UFM1 has not been previously associated with VWF:Ag levels. Four genes that were previously associated with VWF levels (VWF, ABO, STXBP5 and STAB2) were also associated with low VWF levels, and, in addition, we identified a new gene, UFM1, that is associated with low VWF levels. These findings point to novel mechanisms for the occurrence of low VWF levels.
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Zanetti D, Carreras-Torres R, Esteban E, Via M, Moral P. Potential Signals of Natural Selection in the Top Risk Loci for Coronary Artery Disease: 9p21 and 10q11. PLoS One 2015; 10:e0134840. [PMID: 26252781 PMCID: PMC4529309 DOI: 10.1371/journal.pone.0134840] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2015] [Accepted: 07/15/2015] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Coronary artery disease (CAD) is a complex disease and the leading cause of death in the world. Populations of different ancestry do not always share the same risk markers. Natural selective processes may be the cause of some of the population differences detected for specific risk mutations. OBJECTIVE In this study, 384 single nucleotide polymorphisms (SNPs) located in four genomic regions associated with CAD (1p13, 1q41, 9p21 and 10q11) are analysed in a set of 19 populations from Europe, Middle East and North Africa and also in Asian and African samples from the 1000 Genomes Project. The aim of this survey is to explore for the first time whether the genetic variability in these genomic regions is better explained by demography or by natural selection. RESULTS The results indicate significant differences in the structure of genetic variation and in the LD patterns among populations that probably explain the population disparities found in markers of susceptibility to CAD. CONCLUSIONS The results are consistent with potential signature of positive selection in the 9p21 region and of balancing selection in the 9p21 and 10q11. Specifically, in Europe three CAD risk markers in the 9p21 region (rs9632884, rs1537371 and rs1333042) show consistent signals of positive selection. The results of this study are consistent with a potential selective role of CAD in the configuration of genetic diversity in current human populations.
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Affiliation(s)
- Daniela Zanetti
- Department of Animal Biology-Anthropology, University of Barcelona, Barcelona, Spain
| | | | - Esther Esteban
- Department of Animal Biology-Anthropology, University of Barcelona, Barcelona, Spain
- Biodiversity Research Institute, University of Barcelona, Spain
| | - Marc Via
- Department of Psychiatry and Clinical Psychobiology and Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Barcelona, Spain
| | - Pedro Moral
- Department of Animal Biology-Anthropology, University of Barcelona, Barcelona, Spain
- Biodiversity Research Institute, University of Barcelona, Spain
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Shahabi P, Dubé MP. Cardiovascular pharmacogenomics; state of current knowledge and implementation in practice. Int J Cardiol 2015; 184:772-795. [DOI: 10.1016/j.ijcard.2015.02.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Revised: 02/17/2015] [Accepted: 02/21/2015] [Indexed: 02/07/2023]
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Hussain Y, Ding Q, Connelly PW, Brunt JH, Ban MR, McIntyre AD, Huff MW, Gros R, Hegele RA, Feldman RD. G-protein estrogen receptor as a regulator of low-density lipoprotein cholesterol metabolism: cellular and population genetic studies. Arterioscler Thromb Vasc Biol 2014; 35:213-21. [PMID: 25395619 DOI: 10.1161/atvbaha.114.304326] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Estrogen deficiency is linked with increased low-density lipoprotein (LDL) cholesterol. The hormone receptor mediating this effect is unknown. G-protein estrogen receptor (GPER) is a recently recognized G-protein-coupled receptor that is activated by estrogens. We recently identified a common hypofunctional missense variant of GPER, namely P16L. However, the role of GPER in LDL metabolism is unknown. Therefore, we examined the association of the P16L genotype with plasma LDL cholesterol level. Furthermore, we studied the role of GPER in regulating expression of the LDL receptor and proprotein convertase subtilisin kexin type 9. APPROACH AND RESULTS Our discovery cohort was a genetically isolated population of Northern European descent, and our validation cohort consisted of normal, healthy women aged 18 to 56 years from London, Ontario. In addition, we examined the effect of GPER on the regulation of proprotein convertase subtilisin kexin type 9 and LDL receptor expression by the treatment with the GPER agonist, G1. In the discovery cohort, GPER P16L genotype was associated with a significant increase in LDL cholesterol (mean±SEM): 3.18±0.05, 3.25±0.08, and 4.25±0.33 mmol/L, respectively, in subjects with CC (homozygous for P16), CT (heterozygotes), and TT (homozygous for L16) genotypes (P<0.05). In the validation cohort (n=339), the GPER P16L genotype was associated with a similar increase in LDL cholesterol: 2.17±0.05, 2.34±0.06, and 2.42±0.16 mmol/L, respectively, in subjects with CC, CT, and TT genotypes (P<0.05). In the human hepatic carcinoma cell line, the GPER agonist, G1, mediated a concentration-dependent increase in LDL receptor expression, blocked by either pretreatment with the GPER antagonist G15 or by shRNA-mediated GPER downregulation. G1 also mediated a GPER- and concentration-dependent decrease in proprotein convertase subtilisin kexin type 9 expression. CONCLUSIONS GPER activation upregulates LDL receptor expression, probably at least, in part, via proprotein convertase subtilisin kexin type 9 downregulation. Furthermore, humans carrying the hypofunctional P16L genetic variant of GPER have increased plasma LDL cholesterol. In aggregate, these data suggest an important role of GPER in the regulation of LDL receptor expression and consequently LDL metabolism.
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Affiliation(s)
- Yasin Hussain
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Qingming Ding
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Philip W Connelly
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - J Howard Brunt
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Matthew R Ban
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Adam D McIntyre
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Murray W Huff
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Robert Gros
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Robert A Hegele
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.)
| | - Ross D Feldman
- From the Robarts Research Institute (Y.H., Q.D., M.R.B., A.D.M., M.W.H., R.G., R.A.H., R.D.F.) and Departments of Medicine (M.W.H., R.G., R.A.H., R.D.F.), Physiology and Pharmacology (R.G., R.A.H., R.D.F.), and Biochemistry (M.W.H.), Western University, London, Ontario, Canada; Department of Medicine, University of Toronto, Toronto, Ontario, Canada (P.W.C.); and Department of Public Health and Social Policy, University of Victoria, Victoria, British Columbia, Canada (J.H.B.).
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Postmus I, Johnson PCD, Trompet S, de Craen AJM, Slagboom PE, Devlin JJ, Shiffman D, Sacks FM, Kearney PM, Stott DJ, Buckley BM, Sattar N, Ford I, Westendorp RGJ, Jukema JW. In search for genetic determinants of clinically meaningful differential cardiovascular event reduction by pravastatin in the PHArmacogenetic study of Statins in the Elderly at risk (PHASE)/PROSPER study. Atherosclerosis 2014; 235:58-64. [PMID: 24816038 DOI: 10.1016/j.atherosclerosis.2014.04.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2013] [Revised: 02/12/2014] [Accepted: 04/07/2014] [Indexed: 12/26/2022]
Abstract
BACKGROUND Statin therapy is widely used in the prevention and treatment of cardiovascular events and is associated with significant risk reductions. However, there is considerable variation in response to statin therapy both in terms of LDL cholesterol reduction and clinical outcomes. It has been hypothesized that genetic variation contributes importantly to this individual drug response. METHODS AND RESULTS We investigated the interaction between genetic variants and pravastatin or placebo therapy on the incidence of cardiovascular events by performing a genome-wide association study in the participants of the PROspective Study of Pravastatin in the Elderly at Risk for vascular disease--PHArmacogenetic study of Statins in the Elderly at risk (PROSPER/PHASE) study (n = 5244). We did not observe genome-wide significant associations with a clinically meaningful differential cardiovascular event reduction by pravastatin therapy. In addition, SNPs with p-values lower than 1 × 10(-4) were assessed for replication in a case-only analysis within two randomized placebo controlled pravastatin trials, CARE (n = 711) and WOSCOPS (n = 522). rs7102569, on chromosome 11 near the ODZ4 gene, was replicated in the CARE study (p = 0.008), however the direction of effect was opposite. This SNP was not associated in WOSCOPS. In addition, none of the SNPs replicated significantly after correcting for multiple testing. CONCLUSIONS We could not identify genetic variation that was significantly associated at genome-wide level with a clinically meaningful differential event reduction by pravastatin treatment in a large prospective study. We therefore assume that in daily practice the use of genetic characteristics to personalize pravastatin treatment to improve prevention of cardiovascular disease will be limited.
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Affiliation(s)
- Iris Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands; Netherlands Consortium for Healthy Ageing, PO Box 9600, 2300 RC Leiden, The Netherlands.
| | - Paul C D Johnson
- Robertson Center for Biostatistics, University of Glasgow, United Kingdom.
| | - Stella Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands; Netherlands Consortium for Healthy Ageing, PO Box 9600, 2300 RC Leiden, The Netherlands; Department of Cardiology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
| | - Anton J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands; Netherlands Consortium for Healthy Ageing, PO Box 9600, 2300 RC Leiden, The Netherlands.
| | - P Eline Slagboom
- Netherlands Consortium for Healthy Ageing, PO Box 9600, 2300 RC Leiden, The Netherlands; Department of Molecular Epidemiology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
| | | | | | - Frank M Sacks
- Department of Nutrition, Harvard School of Public Health, Boston, MA, United States; Channing Division of Network Medicine, Brigham & Women's Hospital, Boston, MA, United States.
| | - Patricia M Kearney
- Department of Epidemiology and Public Health, University College Cork, Ireland.
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, United Kingdom.
| | - Brendan M Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Ireland.
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, United Kingdom.
| | - Ian Ford
- Robertson Center for Biostatistics, University of Glasgow, United Kingdom.
| | - Rudi G J Westendorp
- Department of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands; Netherlands Consortium for Healthy Ageing, PO Box 9600, 2300 RC Leiden, The Netherlands; Leyden Academy of Vitality and Ageing, Leiden, The Netherlands.
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands; Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands; Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands.
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17
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Pharmacogenomics, lipid disorders, and treatment options. Clin Pharmacol Ther 2014; 96:36-47. [PMID: 24722394 DOI: 10.1038/clpt.2014.82] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2014] [Accepted: 04/07/2014] [Indexed: 01/14/2023]
Abstract
Statins form the backbone of lipid-lowering therapy in the prevention of cardiovascular disease. Numerous studies have evaluated the effect of genomics on the clinical efficacy and adverse effects of statins. Several gene variants that can be linked to either the pharmacokinetics or pharmacodynamics of statins have been identified as potentially important, although there are some discrepant findings among studies. Effect sizes are modest for lipid-lowering efficacy and perhaps somewhat larger for risk of myopathy, although results are inconsistent. Pharmacogenomics of nonstatin lipid-lowering agents have not been evaluated to the same extent, given their relatively limited use, although there are some promising candidate genes for further study. Finally, with several new classes of lipid-lowering therapies soon becoming available, there may be a potential application for pharmacogenomics to identify patients ideally suited to receive-or those who should avoid-specific medications.
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18
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Gelissen IC, McLachlan AJ. The pharmacogenomics of statins. Pharmacol Res 2013; 88:99-106. [PMID: 24365577 DOI: 10.1016/j.phrs.2013.12.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2013] [Revised: 12/06/2013] [Accepted: 12/12/2013] [Indexed: 12/24/2022]
Abstract
The statin class of cholesterol-lowering drugs have been used for decades to successfully lower plasma cholesterol concentrations and cardiovascular risk. Adverse effects of statins are generally considered mild, but increase with age of patients and polypharmacy. One aspect of statin therapy that is still difficult for prescribers to predict is the individual's response to statin therapy. Recent advances in the field of pharmacogenomics have indicated variants of candidate genes that affect statin efficacy and safety. In this review, a number of candidates that affect statin pharmacokinetics and pharmacodynamics are discussed. Some of these candidates, in particular those involved in import and efflux of statins, have now been linked to increased risk of side effects. Furthermore, pharmacogenomic studies continue to reveal new players that are involved in the fine-tuning of the complex regulation of cholesterol homeostasis and response to statins.
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Affiliation(s)
| | - Andrew J McLachlan
- Faculty of Pharmacy, University of Sydney, NSW, Australia; Centre for Education and Research on Ageing, Concord Hospital, Sydney, NSW, Australia
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19
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Mangravite LM, Engelhardt BE, Medina MW, Smith JD, Brown CD, Chasman DI, Mecham BH, Howie B, Shim H, Naidoo D, Feng Q, Rieder MJ, Chen YDI, Rotter JI, Ridker PM, Hopewell JC, Parish S, Armitage J, Collins R, Wilke RA, Nickerson DA, Stephens M, Krauss RM. A statin-dependent QTL for GATM expression is associated with statin-induced myopathy. Nature 2013; 502:377-80. [PMID: 23995691 PMCID: PMC3933266 DOI: 10.1038/nature12508] [Citation(s) in RCA: 166] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Accepted: 07/26/2013] [Indexed: 01/28/2023]
Abstract
Statins are prescribed widely to lower plasma low-density lipoprotein (LDL) concentrations and cardiovascular disease risk and have been shown to have beneficial effects in a broad range of patients. However, statins are associated with an increased risk, albeit small, of clinical myopathy and type 2 diabetes. Despite evidence for substantial genetic influence on LDL concentrations, pharmacogenomic trials have failed to identify genetic variations with large effects on either statin efficacy or toxicity, and have produced little information regarding mechanisms that modulate statin response. Here we identify a downstream target of statin treatment by screening for the effects of in vitro statin exposure on genetic associations with gene expression levels in lymphoblastoid cell lines derived from 480 participants of a clinical trial of simvastatin treatment. This analysis identified six expression quantitative trait loci (eQTLs) that interacted with simvastatin exposure, including rs9806699, a cis-eQTL for the gene glycine amidinotransferase (GATM) that encodes the rate-limiting enzyme in creatine synthesis. We found this locus to be associated with incidence of statin-induced myotoxicity in two separate populations (meta-analysis odds ratio = 0.60). Furthermore, we found that GATM knockdown in hepatocyte-derived cell lines attenuated transcriptional response to sterol depletion, demonstrating that GATM may act as a functional link between statin-mediated lowering of cholesterol and susceptibility to statin-induced myopathy.
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Affiliation(s)
- Lara M Mangravite
- Sage Bionetworks, 1100 Fairview Avenue North, Seattle, Washington 98109, USA.
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20
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Bradley DT, Hughes AE, Badger SA, Jones GT, Harrison SC, Wright BJ, Bumpstead S, Baas AF, Grétarsdóttir S, Burnand K, Child AH, Clough RE, Cockerill G, Hafez H, Scott DJA, Ariëns RA, Johnson A, Sohrabi S, Smith A, Thompson MM, van Bockxmeer FM, Waltham M, Matthíasson SE, Thorleifsson G, Thorsteinsdottir U, Blankensteijn JD, Teijink JA, Wijmenga C, de Graaf J, Kiemeney LA, Wild JB, Edkins S, Gwilliam R, Hunt SE, Potter S, Lindholt JS, Golledge J, Norman PE, van Rij A, Powell JT, Eriksson P, Stefánsson K, Thompson JR, Humphries SE, Sayers RD, Deloukas P, Samani NJ, Bown MJ. A Variant in
LDLR
Is Associated With Abdominal Aortic Aneurysm. ACTA ACUST UNITED AC 2013; 6:498-504. [DOI: 10.1161/circgenetics.113.000165] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background—
Abdominal aortic aneurysm (AAA) is a common cardiovascular disease among older people and demonstrates significant heritability. In contrast to similar complex diseases, relatively few genetic associations with AAA have been confirmed. We reanalyzed our genome-wide study and carried through to replication suggestive discovery associations at a lower level of significance.
Methods and Results—
A genome-wide association study was conducted using 1830 cases from the United Kingdom, New Zealand, and Australia with infrarenal aorta diameter ≥30 mm or ruptured AAA and 5435 unscreened controls from the 1958 Birth Cohort and National Blood Service cohort from the Wellcome Trust Case Control Consortium. Eight suggestive associations with
P
<1×10
−4
were carried through to in silico replication in 1292 AAA cases and 30 503 controls. One single-nucleotide polymorphism associated with
P
<0.05 after Bonferroni correction in the in silico study underwent further replication (706 AAA cases and 1063 controls from the United Kingdom, 507 AAA cases and 199 controls from Denmark, and 885 AAA cases and 1000 controls from New Zealand). Low-density lipoprotein receptor (
LDLR
) rs6511720 A was significantly associated overall and in 3 of 5 individual replication studies. The full study showed an association that reached genome-wide significance (odds ratio, 0.76; 95% confidence interval, 0.70–0.83;
P
=2.08×10
−10
).
Conclusions—
LDLR rs6511720 is associated with AAA. This finding is consistent with established effects of this variant on coronary artery disease. Shared causal pathways with other cardiovascular diseases may present novel opportunities for preventative and therapeutic strategies for AAA.
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21
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Cardelli M, Marchegiani F, Corsonello A, Lattanzio F, Provinciali M. A review of pharmacogenetics of adverse drug reactions in elderly people. Drug Saf 2013; 35 Suppl 1:3-20. [PMID: 23446782 DOI: 10.1007/bf03319099] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Older adults are more susceptible to the prevalence of therapeutic failure and adverse drug reactions (ADRs). Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and genes responsible for a compound's mechanism of action, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. The interindividual variations of these genes may account for the differences observed in drug efficacy and the appearance of ADRs in elderly people. The advent of whole genome mapping techniques has allowed researchers to begin to characterize the genetic components underlying serious ADRs. The identification and validation of these genetic markers will enable the screening of patients at risk of serious ADRs and to establish personalized treatment regimens.The aim of this review was to provide an update on the recent developments in geriatric pharmacogenetics in clinical practice by reviewing the available evidence in the PubMed database to September 2012. A Pubmed search was performed (years 1999-2012) using the following two search strategies: ('pharmacogenomic' OR 'pharmacogenetic ') AND ('geriatric' or 'elderly ') AND 'adverse drug reactions'; [gene name] AND ('geriatric' or 'elderly ') AND 'adverse drug reactions', in which the gene names were those contained in the Table of Pharmacogenomic Biomarkers in Drug Labels published online by the US Food and Drug Administration ( http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm ). Reference lists of included original articles and relevant review articles were also screened. The search was limited to studies published in the English language.
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Affiliation(s)
- Maurizio Cardelli
- Advanced Technology Center for Aging Research, Scientific Technological Area, IRCCS-INRCA, Via Birarelli 8, 60121, Ancona, Italy
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22
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Subirana I, González JR. Genetic association analysis and meta-analysis of imputed SNPs in longitudinal studies. Genet Epidemiol 2013; 37:465-77. [PMID: 23595425 PMCID: PMC4273087 DOI: 10.1002/gepi.21719] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2012] [Revised: 01/10/2013] [Accepted: 02/05/2013] [Indexed: 11/12/2022]
Abstract
In this paper we propose a new method to analyze time-to-event data in longitudinal genetic studies. This method address the fundamental problem of incorporating uncertainty when analyzing survival data and imputed single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS). Our method incorporates uncertainty in the likelihood function, the opposite of existing methods that incorporate the uncertainty in the design matrix. Through simulation studies and real data analyses, we show that our proposed method is unbiased and provides powerful results. We also show how combining results from different GWAS (meta-analysis) may lead to wrong results when effects are not estimated using our approach. The model is implemented in an R package that is designed to analyze uncertainty not only arising from imputed SNPs, but also from copy number variants.
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Affiliation(s)
- Isaac Subirana
- CIBER Epidemiology and Public Health (CIBERESP), Spain
- Cardiovascular Epidemiology & Genetics group, Inflammatory and Cardiovascular Disease Programme, IMIM, Parc de Salut Mar, Spain
- Department of Statistics, University of Barcelona, Spain
| | - Juan R González
- CIBER Epidemiology and Public Health (CIBERESP), Spain
- Center for Research in Environmental Epidemiology (CREAL), Spain
- Department of Mathematics, Universitat Autònoma de Barcelona (UAB), Spain
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23
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Postmus I, Trompet S, de Craen AJM, Buckley BM, Ford I, Stott DJ, Sattar N, Slagboom PE, Westendorp RGJ, Jukema JW. PCSK9 SNP rs11591147 is associated with low cholesterol levels but not with cognitive performance or noncardiovascular clinical events in an elderly population. J Lipid Res 2013. [PMID: 23300213 DOI: 10.1194/jlr.m033969] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Proprotein convertase subtilisin-like/kexin type 9 (PCSK9) is a protein involved in LDL-cholesterol metabolism. The single-nucleotide polymorphism (SNP) rs11591147 has been associated with lower LDL-cholesterol and a lower risk of coronary heart disease. Because PCSK9 has high affinity to the LDL receptor, inhibiting PCSK9 is a testable therapeutic target for lipid-lowering therapy. Currently, several approaches to inhibit PCSK9 are under development, but it is unknown what the effects of those inhibitors will be on cognition or noncardiovascular clinical events. In this study, we assessed the association between rs11591147 and cognitive performance, activities of daily living (ADL), and noncardiovascular clinical events within 5,777 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Rs11591147 was associated with 10% to 16% lower LDL cholesterol levels (P = 3.62 × 10(-12)), but was not associated with cognitive performance, ADL, or noncardiovascular clinical events in the PROSPER study. Our findings suggest that lower cholesterol levels due to genetic variation in the PCSK9 gene are not associated with cognitive performance, functional status, or noncardiovascular clinical events.
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Affiliation(s)
- Iris Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
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24
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Postmus I, Trompet S, de Craen AJM, Buckley BM, Ford I, Stott DJ, Sattar N, Slagboom PE, Westendorp RGJ, Jukema JW. PCSK9 SNP rs11591147 is associated with low cholesterol levels but not with cognitive performance or noncardiovascular clinical events in an elderly population. J Lipid Res 2013; 54:561-6. [PMID: 23300213 DOI: 10.1194/jlr.p033969] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Proprotein convertase subtilisin-like/kexin type 9 (PCSK9) is a protein involved in LDL-cholesterol metabolism. The single-nucleotide polymorphism (SNP) rs11591147 has been associated with lower LDL-cholesterol and a lower risk of coronary heart disease. Because PCSK9 has high affinity to the LDL receptor, inhibiting PCSK9 is a testable therapeutic target for lipid-lowering therapy. Currently, several approaches to inhibit PCSK9 are under development, but it is unknown what the effects of those inhibitors will be on cognition or noncardiovascular clinical events. In this study, we assessed the association between rs11591147 and cognitive performance, activities of daily living (ADL), and noncardiovascular clinical events within 5,777 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Rs11591147 was associated with 10% to 16% lower LDL cholesterol levels (P = 3.62 × 10(-12)), but was not associated with cognitive performance, ADL, or noncardiovascular clinical events in the PROSPER study. Our findings suggest that lower cholesterol levels due to genetic variation in the PCSK9 gene are not associated with cognitive performance, functional status, or noncardiovascular clinical events.
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Affiliation(s)
- Iris Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
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25
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Johnson JA, Cavallari LH. Pharmacogenetics and cardiovascular disease--implications for personalized medicine. Pharmacol Rev 2013; 65:987-1009. [PMID: 23686351 DOI: 10.1124/pr.112.007252] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The past decade has seen tremendous advances in our understanding of the genetic factors influencing response to a variety of drugs, including those targeted at treatment of cardiovascular diseases. In the case of clopidogrel, warfarin, and statins, the literature has become sufficiently strong that guidelines are now available describing the use of genetic information to guide treatment with these therapies, and some health centers are using this information in the care of their patients. There are many challenges in moving from research data to translation to practice; we discuss some of these barriers and the approaches some health systems are taking to overcome them. The body of literature that has led to the clinical implementation of CYP2C19 genotyping for clopidogrel, VKORC1, CYP2C9; and CYP4F2 for warfarin; and SLCO1B1 for statins is comprehensively described. We also provide clarity for other genes that have been extensively studied relative to these drugs, but for which the data are conflicting. Finally, we comment briefly on pharmacogenetics of other cardiovascular drugs and highlight β-blockers as the drug class with strong data that has not yet seen clinical implementation. It is anticipated that genetic information will increasingly be available on patients, and it is important to identify those examples where the evidence is sufficiently robust and predictive to use genetic information to guide clinical decisions. The review herein provides several examples of the accumulation of evidence and eventual clinical translation in cardiovascular pharmacogenetics.
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Affiliation(s)
- Julie A Johnson
- Center for Pharmacogenomics, Department of Pharmacotherapy and Translational Research, University of Florida, Box 100486, Gainesville, FL 32610-0486, USA.
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26
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Sorich MJ, Wiese MD, O'Shea RL, Pekarsky B. Review of the cost effectiveness of pharmacogenetic-guided treatment of hypercholesterolaemia. PHARMACOECONOMICS 2013; 31:377-391. [PMID: 23568333 DOI: 10.1007/s40273-013-0045-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Hypercholesterolaemia is a highly prevalent condition that has major health and cost implications for society. Pharmacotherapy is an important and effective treatment modality for hypercholesterolaemia, with 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors ('statins') the most commonly used class of drugs. Over the past decade, there has been intensive research to identify pharmacogenetic markers to guide treatment of hypercholesterolaemia. This study aimed to review the evidence of incremental cost, effect and cost effectiveness of pharmacogenetic-guided treatment of hypercholesterolaemia. Three cost-effectiveness analyses (CEAs) were identified that studied the value of screening for genotypes of angiotensin I converting enzyme (ACE), cholesteryl ester transfer protein (CETP), and kinesin family member 6 (KIF6) prior to initiating statin therapy. For all three CEAs, a major limitation identified was the reproducibility of the evidence supporting the clinical effect of screening for the pharmacogenetic marker. Associated issues included the uncertain value of pharmacogenetic markers over or in addition to existing approaches for monitoring lipid levels, and the lack of evidence to assess the effectiveness of alternative therapeutic options for individuals identified as poor responders to statin therapy. Finally, the economic context of the market for diagnostic tests (is it competitive or is there market power?) and the practicality of large-scale screening programmes to inform prescribing in a complex and varied market may limit the generalizability of the results of the specific CEAs to policy outcomes. The genotype of solute carrier organic anion transporter family member 1B1 (SLCO1B1) has recently been associated with increased risk of muscle toxicity with statin therapy and the review identified that exploration of cost effectiveness of this pharmacogenetic marker is likely warranted.
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Affiliation(s)
- Michael J Sorich
- School of Pharmacy and Medical Sciences and Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
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27
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Non-homologous end-joining pathway associated with occurrence of myocardial infarction: gene set analysis of genome-wide association study data. PLoS One 2013; 8:e56262. [PMID: 23457540 PMCID: PMC3574159 DOI: 10.1371/journal.pone.0056262] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2012] [Accepted: 01/07/2013] [Indexed: 01/28/2023] Open
Abstract
PURPOSE DNA repair deficiencies have been postulated to play a role in the development and progression of cardiovascular disease (CVD). The hypothesis is that DNA damage accumulating with age may induce cell death, which promotes formation of unstable plaques. Defects in DNA repair mechanisms may therefore increase the risk of CVD events. We examined whether the joints effect of common genetic variants in 5 DNA repair pathways may influence the risk of CVD events. METHODS The PLINK set-based test was used to examine the association to myocardial infarction (MI) of the DNA repair pathway in GWAS data of 866 subjects of the GENetic DEterminants of Restenosis (GENDER) study and 5,244 subjects of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) study. We included the main DNA repair pathways (base excision repair, nucleotide excision repair, mismatch repair, homologous recombination and non-homologous end-joining (NHEJ)) in the analysis. RESULTS The NHEJ pathway was associated with the occurrence of MI in both GENDER (P = 0.0083) and PROSPER (P = 0.014). This association was mainly driven by genetic variation in the MRE11A gene (PGENDER = 0.0001 and PPROSPER = 0.002). The homologous recombination pathway was associated with MI in GENDER only (P = 0.011), for the other pathways no associations were observed. CONCLUSION This is the first study analyzing the joint effect of common genetic variation in DNA repair pathways and the risk of CVD events, demonstrating an association between the NHEJ pathway and MI in 2 different cohorts.
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28
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Postmus I, Verschuren JJW, de Craen AJM, Slagboom PE, Westendorp RGJ, Jukema JW, Trompet S. Pharmacogenetics of statins: achievements, whole-genome analyses and future perspectives. Pharmacogenomics 2012; 13:831-40. [PMID: 22594514 DOI: 10.2217/pgs.12.25] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Statins are the most commonly prescribed class of drug worldwide and therapy is highly effective in reducing low-density lipoprotein cholesterol levels and cardiovascular events. However, there is large variability in clinical response to statin treatment. Recent research provides evidence that genetic variation contributes to this variable response to statin treatment. Until recently, pharmacogenetic studies have used mainly candidate gene approaches to investigate these effects. Since candidate gene studies explain only a small part of the observed variation and results have often been inconsistent, genome-wide association (GWA) studies may be a better approach. In this paper the most important candidate gene studies and the first published GWA studies assessing statin response are discussed. Moreover, we describe the PHASE study, an EU-funded GWA study that will investigate the genetic variation responsible for the variation in response to pravastatin in a large randomized clinical trial.
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Affiliation(s)
- Iris Postmus
- Department of Gerontology & Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
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29
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Kim DK, Cho MH, Hersh CP, Lomas DA, Miller BE, Kong X, Bakke P, Gulsvik A, Agustí A, Wouters E, Celli B, Coxson H, Vestbo J, MacNee W, Yates JC, Rennard S, Litonjua A, Qiu W, Beaty TH, Crapo JD, Riley JH, Tal-Singer R, Silverman EK. Genome-wide association analysis of blood biomarkers in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2012; 186:1238-47. [PMID: 23144326 DOI: 10.1164/rccm.201206-1013oc] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
RATIONALE A genome-wide association study (GWAS) for circulating chronic obstructive pulmonary disease (COPD) biomarkers could identify genetic determinants of biomarker levels and COPD susceptibility. OBJECTIVES To identify genetic variants of circulating protein biomarkers and novel genetic determinants of COPD. METHODS GWAS was performed for two pneumoproteins, Clara cell secretory protein (CC16) and surfactant protein D (SP-D), and five systemic inflammatory markers (C-reactive protein, fibrinogen, IL-6, IL-8, and tumor necrosis factor-α) in 1,951 subjects with COPD. For genome-wide significant single nucleotide polymorphisms (SNPs) (P < 1 × 10(-8)), association with COPD susceptibility was tested in 2,939 cases with COPD and 1,380 smoking control subjects. The association of candidate SNPs with mRNA expression in induced sputum was also elucidated. MEASUREMENTS AND MAIN RESULTS Genome-wide significant susceptibility loci affecting biomarker levels were found only for the two pneumoproteins. Two discrete loci affecting CC16, one region near the CC16 coding gene (SCGB1A1) on chromosome 11 and another locus approximately 25 Mb away from SCGB1A1, were identified, whereas multiple SNPs on chromosomes 6 and 16, in addition to SNPs near SFTPD, had genome-wide significant associations with SP-D levels. Several SNPs affecting circulating CC16 levels were significantly associated with sputum mRNA expression of SCGB1A1 (P = 0.009-0.03). Several SNPs highly associated with CC16 or SP-D levels were nominally associated with COPD in a collaborative GWAS (P = 0.001-0.049), although these COPD associations were not replicated in two additional cohorts. CONCLUSIONS Distant genetic loci and biomarker-coding genes affect circulating levels of COPD-related pneumoproteins. A subset of these protein quantitative trait loci may influence their gene expression in the lung and/or COPD susceptibility. Clinical trial registered with www.clinicaltrials.gov (NCT 00292552).
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Affiliation(s)
- Deog Kyeom Kim
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
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Deshmukh HA, Colhoun HM, Johnson T, McKeigue PM, Betteridge DJ, Durrington PN, Fuller JH, Livingstone S, Charlton-Menys V, Neil A, Poulter N, Sever P, Shields DC, Stanton AV, Chatterjee A, Hyde C, Calle RA, DeMicco DA, Trompet S, Postmus I, Ford I, Jukema JW, Caulfield M, Hitman GA. Genome-wide association study of genetic determinants of LDL-c response to atorvastatin therapy: importance of Lp(a). J Lipid Res 2012; 53:1000-1011. [PMID: 22368281 PMCID: PMC3329377 DOI: 10.1194/jlr.p021113] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We carried out a genome-wide association study (GWAS) of LDL-c response to statin using data from participants in the Collaborative Atorvastatin Diabetes Study (CARDS; n = 1,156), the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT; n = 895), and the observational phase of ASCOT (n = 651), all of whom were prescribed atorvastatin 10 mg. Following genome-wide imputation, we combined data from the three studies in a meta-analysis. We found associations of LDL-c response to atorvastatin that reached genome-wide significance at rs10455872 (P = 6.13 × 10(-9)) within the LPA gene and at two single nucleotide polymorphisms (SNP) within the APOE region (rs445925; P = 2.22 × 10(-16) and rs4420638; P = 1.01 × 10(-11)) that are proxies for the ε2 and ε4 variants, respectively, in APOE. The novel association with the LPA SNP was replicated in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial (P = 0.009). Using CARDS data, we further showed that atorvastatin therapy did not alter lipoprotein(a) [Lp(a)] and that Lp(a) levels accounted for all of the associations of SNPs in the LPA gene and the apparent LDL-c response levels. However, statin therapy had a similar effect in reducing cardiovascular disease (CVD) in patients in the top quartile for serum Lp(a) levels (HR = 0.60) compared with those in the lower three quartiles (HR = 0.66; P = 0.8 for interaction). The data emphasize that high Lp(a) levels affect the measurement of LDL-c and the clinical estimation of LDL-c response. Therefore, an apparently lower LDL-c response to statin therapy may indicate a need for measurement of Lp(a). However, statin therapy seems beneficial even in those with high Lp(a).
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Affiliation(s)
| | | | - Toby Johnson
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | | | | | | | | | | | | | - Andrew Neil
- University of Oxford, Oxford, United Kingdom
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, United Kingdom
| | - Peter Sever
- International Centre for Circulatory Health, Imperial College London, United Kingdom
| | - Denis C Shields
- Complex and Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland
| | | | | | | | | | | | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands and
| | - Iris Postmus
- Department of Geriatrics and Gerontology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom; and
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands and; Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - Mark Caulfield
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Graham A Hitman
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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