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Sex-related differences in single nucleotide polymorphisms associated with dyslipidemia in a Korean population. Lipids Health Dis 2022; 21:124. [PMID: 36419087 PMCID: PMC9685854 DOI: 10.1186/s12944-022-01736-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 11/14/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The prevalence of dyslipidemia has increased steadily in Korea, and the incidence of dyslipidemia differs by sex. In this study, we identified single nucleotide polymorphisms (SNPs) related to dyslipidemia in Korean cohorts through genome-wide association study (GWAS) analysis. METHODS Genotyping was conducted to determine the genotypes of 72,298 participants and investigate genotypes for 7,079,946 SNPs. Sex, age, and BMI were set as covariates for GWAS, and significant SNPs were identified in the discovery and replication stages using logistic regression. RESULTS GWAS of the entire cohort revealed a total of five significant SNPs: rs117026536 (LPL), rs651821 (APOA5), rs9804646 (APOA5), rs9926440 (CETP), and rs429358 (APOE). GWAS of the male subjects revealed a total of four significant SNPs. While rs9804646 (APOA5) and rs429358 (APOE) were significant for all the subjects, rs662799 (APOA5) and rs56156922 (CETP) were significant only for the male subjects. GWAS of the female subjects revealed two significant SNPs, rs651821 (APOA5) and rs9804646 (APOA5), both of which were significant in all the subjects. CONCLUSION This is the first study to identify sex-related differences in genetic polymorphisms in Korean populations with dyslipidemia. Further studies considering environmental variables will be needed to elucidate these sex-related genetic differences in dyslipidemia.
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Polymorphisms of the 11q23.3 Locus Affect the Risk and Mortality of Coronary Artery Disease. J Clin Med 2022; 11:jcm11154532. [PMID: 35956147 PMCID: PMC9369758 DOI: 10.3390/jcm11154532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/29/2022] [Accepted: 08/02/2022] [Indexed: 02/05/2023] Open
Abstract
Background: The present study aimed to determine whether the polymorphisms of the 11q23.3 locus affect the risk and mortality of coronary artery disease in 5-year and 10-year observations. Methods: The study group consisted of 519 subjects: 276 patients with CAD and 243 blood donors as controls. The genotyping of polymorphisms (rs10750097, rs3741298, and rs1729410) was performed using the TaqMan-PCR method. Survival was defined as the period from the angiographic confirmation of CAD to cardiovascular death, and the endpoint was defined as death from cardiovascular causes. Results: The G allele of the rs1729410 polymorphism increased the risk of CAD (OR = 1.55, p = 0.04) and showed a synergistic correlation with overweight/obesity (additive synergy index (SI) = 11.01, p < 0.001). The carriers of the GG genotype and over-normative LDL levels increased the risk of CAD by over 12-fold higher than expected (multiplicative synergy index (SIM) = 12.34, p < 0.001). In the case of the rs10750097 variant, an effect on mortality was shown in both 5-year and 10-year periods. Conclusion: The results revealed that the rs1729410 polymorphism increases the risk of CAD in synergy with traditional risk factors, and the rs10750097 polymorphism of the 11q23.3 locus affects the risk of death in patients with CAD.
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Abumrad NA, Cabodevilla AG, Samovski D, Pietka T, Basu D, Goldberg IJ. Endothelial Cell Receptors in Tissue Lipid Uptake and Metabolism. Circ Res 2021; 128:433-450. [PMID: 33539224 DOI: 10.1161/circresaha.120.318003] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Lipid uptake and metabolism are central to the function of organs such as heart, skeletal muscle, and adipose tissue. Although most heart energy derives from fatty acids (FAs), excess lipid accumulation can cause cardiomyopathy. Similarly, high delivery of cholesterol can initiate coronary artery atherosclerosis. Hearts and arteries-unlike liver and adrenals-have nonfenestrated capillaries and lipid accumulation in both health and disease requires lipid movement from the circulation across the endothelial barrier. This review summarizes recent in vitro and in vivo findings on the importance of endothelial cell receptors and uptake pathways in regulating FAs and cholesterol uptake in normal physiology and cardiovascular disease. We highlight clinical and experimental data on the roles of ECs in lipid supply to tissues, heart, and arterial wall in particular, and how this affects organ metabolism and function. Models of FA uptake into ECs suggest that receptor-mediated uptake predominates at low FA concentrations, such as during fasting, whereas FA uptake during lipolysis of chylomicrons may involve paracellular movement. Similarly, in the setting of an intact arterial endothelial layer, recent and historic data support a role for receptor-mediated processes in the movement of lipoproteins into the subarterial space. We conclude with thoughts on the need to better understand endothelial lipid transfer for fuller comprehension of the pathophysiology of hyperlipidemia, and lipotoxic diseases such as some forms of cardiomyopathy and atherosclerosis.
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Affiliation(s)
- Nada A Abumrad
- Division of Nutritional Sciences, Department of Medicine, Washington University School of Medicine, Saint Louis, MO (N.A.A., D.S., T.P.)
| | - Ainara G Cabodevilla
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, New York University Grossman School of Medicine (A.G.C., D.B., I.J.G.)
| | - Dmitri Samovski
- Division of Nutritional Sciences, Department of Medicine, Washington University School of Medicine, Saint Louis, MO (N.A.A., D.S., T.P.)
| | - Terri Pietka
- Division of Nutritional Sciences, Department of Medicine, Washington University School of Medicine, Saint Louis, MO (N.A.A., D.S., T.P.)
| | - Debapriya Basu
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, New York University Grossman School of Medicine (A.G.C., D.B., I.J.G.)
| | - Ira J Goldberg
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, New York University Grossman School of Medicine (A.G.C., D.B., I.J.G.)
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Hoekstra M, Chen HY, Rong J, Dufresne L, Yao J, Guo X, Tsai MY, Tsimikas S, Post WS, Vasan RS, Rotter JI, Larson MG, Thanassoulis G, Engert JC. Genome-Wide Association Study Highlights APOH as a Novel Locus for Lipoprotein(a) Levels-Brief Report. Arterioscler Thromb Vasc Biol 2021; 41:458-464. [PMID: 33115273 PMCID: PMC7769958 DOI: 10.1161/atvbaha.120.314965] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/12/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Lp(a) (lipoprotein[a]) is an independent risk factor for cardiovascular diseases and plasma levels are primarily determined by variation at the LPA locus. We performed a genome-wide association study in the UK Biobank to determine whether additional loci influence Lp(a) levels. Approach and Results: We included 293 274 White British individuals in the discovery analysis. Approximately 93 095 623 variants were tested for association with natural log-transformed Lp(a) levels using linear regression models adjusted for age, sex, genotype batch, and 20 principal components of genetic ancestry. After quality control, 131 independent variants were associated at genome-wide significance (P≤5×10-8). In addition to validating previous associations at LPA, APOE, and CETP, we identified a novel variant at the APOH locus, encoding β2GPI (beta2-glycoprotein I). The APOH variant rs8178824 was associated with increased Lp(a) levels (β [95% CI] [ln nmol/L], 0.064 [0.047-0.081]; P=2.8×10-13) and demonstrated a stronger effect after adjustment for variation at the LPA locus (β [95% CI] [ln nmol/L], 0.089 [0.076-0.10]; P=3.8×10-42). This association was replicated in a meta-analysis of 5465 European-ancestry individuals from the Framingham Offspring Study and Multi-Ethnic Study of Atherosclerosis (β [95% CI] [ln mg/dL], 0.16 [0.044-0.28]; P=0.0071). CONCLUSIONS In a large-scale genome-wide association study of Lp(a) levels, we identified APOH as a novel locus for Lp(a) in individuals of European ancestry. Additional studies are needed to determine the precise role of β2GPI in influencing Lp(a) levels as well as its potential as a therapeutic target.
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Affiliation(s)
- Mary Hoekstra
- Division of Experimental Medicine, McGill University, Montreal, Quebec
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec
| | - Hao Yu Chen
- Division of Experimental Medicine, McGill University, Montreal, Quebec
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec
| | - Jian Rong
- Boston University’s and NHLBI’s Framingham Heart Study, Boston, Massachusetts
| | - Line Dufresne
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec
| | - 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, California
| | - 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, California
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota
| | - Sotirios Tsimikas
- Division of Cardiovascular Medicine, Sulpizio Cardiovascular Center, University of California San Diego, La Jolla, California
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | | | - 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, California
| | - Martin G. Larson
- Boston University’s and NHLBI’s Framingham Heart Study, Boston, Massachusetts
| | - George Thanassoulis
- Division of Experimental Medicine, McGill University, Montreal, Quebec
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec
| | - James C. Engert
- Division of Experimental Medicine, McGill University, Montreal, Quebec
- Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec
- Department of Human Genetics, McGill University, Montreal, Quebec
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5
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Shou W, Zhang C, Shi J, Wu H, Huang W. Fine genetic mapping of the chromosome 11q23.3 region in a Han Chinese population: insights into the apolipoprotein genes underlying the blood lipid-lipoprotein variances. J Genet Genomics 2020; 47:756-769. [PMID: 33753020 DOI: 10.1016/j.jgg.2020.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/09/2020] [Accepted: 11/20/2020] [Indexed: 12/01/2022]
Abstract
The unusual chromosome 11q23.3 harboring the apolipoprotein (APO) gene cluster has been well documented for its essential roles in plasma lipid-related traits and atherosclerotic cardiovascular diseases. However, its genetic architecture and the potential biological mechanisms underlying complex phenotypes have not been well assessed. We conducted a study for this target region in a Han Chinese population through a stepwise forward framework based on massive parallel sequencing, association analyses, genetic fine mapping, and functional interpretation. The present study identified new meaningful genetic associations that were not simply determined by statistical significance. In addition to the APOA5 gene, we found robust evidence of the genetic commitments of APOC3 and APOA1 to blood lipids. Several variants with high confidence were prioritized along with the potential biological mechanism interpretations in the wake of adaptive fine-mapping analyses. rs2849174 in the APOC3 enhancer was discovered with an unrivaled posterior probability of causality for triglyceride levels and could mediate APOC3 expression through enhancer activity modulated by a combination of histone modifications and transcription factor accessibility. Similarly, multiple lines of evidence converged in favor of rs3741297 as a causal variant influencing high-density lipoprotein cholesterol. Our findings provided novel insights into this genomic locus in the Chinese population.
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Affiliation(s)
- Weihua Shou
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai and Shanghai Academy of Science and Technology, Shanghai 200025, China.
| | - Chenhui Zhang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai and Shanghai Academy of Science and Technology, Shanghai 200025, China
| | - Jinxiu Shi
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai and Shanghai Academy of Science and Technology, Shanghai 200025, China
| | - Hong Wu
- Department of Cardiology, Changhai Hospital, The Second Military Medical University, Shanghai 200433, China
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai and Shanghai Academy of Science and Technology, Shanghai 200025, China.
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6
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Agongo G, Amenga-Etego L, Nonterah EA, Debpuur C, Choudhury A, Bentley AR, Oduro AR, Rotimi CN, Crowther NJ, Ramsay M, H Africa. Candidate Gene Analysis Reveals Strong Association of CETP Variants With High Density Lipoprotein Cholesterol and PCSK9 Variants With Low Density Lipoprotein Cholesterol in Ghanaian Adults: An AWI-Gen Sub-Study. Front Genet 2020; 11:456661. [PMID: 33193594 PMCID: PMC7661969 DOI: 10.3389/fgene.2020.456661] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 09/30/2020] [Indexed: 02/06/2023] Open
Abstract
Variations in lipid levels are attributed partly to genetic factors. Genome-wide association studies (GWASs) mainly performed in European, African American and Asian cohorts have identified variants associated with LDL-C, HDL-C, total cholesterol (TC) and triglycerides (TG), but few studies have been performed in sub-Saharan Africans. This study evaluated the effect of single nucleotide variants (SNVs) in eight candidate loci (ABCA1, LCAT, LPL, PON1, CETP, PCSK9, MVK, and MMAB) on lipid levels among 1855 Ghanaian adults. All lipid levels were measured directly using an automated analyser. DNA was extracted and genotyped using the H3Africa SNV array. Linear regression models were used to test the association between SNVs and log-transformed lipid levels, adjusting for sex, age and waist circumference. In addition Bonferroni correction was performed to account for multiple testing. Several variants of CETP, LCAT, PCSK9, and PON1 (MAF > 0.05) were associated with HDL-C, LDL-C and TC levels at p < 0.05. The lead variants for association with HDL-C were rs17231520 in CETP (β = 0.139, p < 0.0001) and rs1109166 in LCAT (β = −0.044, p = 0.028). Lower LDL-C levels were associated with an intronic variant in PCSK9 (rs11806638 [β = −0.055, p = 0.027]) and increased TC was associated with a variant in PON1 (rs854558 [β = 0.040, p = 0.020]). In silico functional analyses indicated that these variants likely influence gene function through their effect on gene transcription. We replicated a strong association between CETP variants and HDL-C and between PCSK9 variant and LDL-C in West Africans, with two potentially functional variants and identified three novel variants in linkage disequilibrium in PON1 which were associated with increasing TC levels in Ghanaians.
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Affiliation(s)
- Godfred Agongo
- Navrongo Health Research Centre, Navrongo, Ghana.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lucas Amenga-Etego
- Navrongo Health Research Centre, Navrongo, Ghana.,West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana
| | - Engelbert A Nonterah
- Navrongo Health Research Centre, Navrongo, Ghana.,Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, Netherlands
| | | | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States
| | | | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States
| | - Nigel J Crowther
- Department of Chemical Pathology, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - H Africa
- Navrongo Health Research Centre, Navrongo, Ghana.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana.,Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, Netherlands.,Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States.,Department of Chemical Pathology, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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7
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Baldassari AR, Sitlani CM, Highland HM, Arking DE, Buyske S, Darbar D, Gondalia R, Graff M, Guo X, Heckbert SR, Hindorff LA, Hodonsky CJ, Ida Chen YD, Kaplan RC, Peters U, Post W, Reiner AP, Rotter JI, Shohet RV, Seyerle AA, Sotoodehnia N, Tao R, Taylor KD, Wojcik GL, Yao J, Kenny EE, Lin HJ, Soliman EZ, Whitsel EA, North KE, Kooperberg C, Avery CL. Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2020; 13:e002680. [PMID: 32602732 PMCID: PMC7520945 DOI: 10.1161/circgen.119.002680] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 05/26/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci. METHODS We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test. RESULTS We identified 6 novels (CD36, PITX2, EMB, ZNF592, YPEL2, and BC043580) and 87 known loci (adaptive sum of powered score test P<5×10-9). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci. CONCLUSIONS Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.
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Affiliation(s)
- Antoine R Baldassari
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine (C.M.S.), University of Washington, Seattle.xs
| | - Heather M Highland
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (D.E.A.)
| | - Steve Buyske
- Department of Statistics and Biostatistics, Rutgers University, New Brunswick, NJ (S.B.)
| | - Dawood Darbar
- Department of Medicine, University of Illinois at Chicago (D.D.)
| | - Rahul Gondalia
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Misa Graff
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Division of Cardiology, Department of Medicine (S.R.H., N.S.), University of Washington, Seattle
| | - Lucia A Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD (L.A.H.)
| | - Chani J Hodonsky
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | | | - Ulrike Peters
- Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA (U.P., A.P.R., C.K.)
| | - Wendy Post
- Departments of Medicine and Epidemiology, Johns Hopkins University, Baltimore, MD (W.P.)
| | - Alex P Reiner
- Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA (U.P., A.P.R., C.K.)
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | - Ralph V Shohet
- Center for Cardiovascular Research, John A. Burns School of Medicine, Honolulu, HI (R.V.S.)
| | - Amanda A Seyerle
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Department of Medicine (S.R.H., N.S.), University of Washington, Seattle
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University, Nashville, TN (R.T.)
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (G.L.W.)
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | - Eimear E Kenny
- Center for Genomic Health (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY
- Charles Bronfman Institute of Personalized Medicine (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Genetics and Genomic Sciences (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (E.E.K.), Icahn School of Medicine at Mount Sinai, New York, NY
| | - Henry J Lin
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA (X.G., Y.-D.I.C., J.I.R., K.D.T., J.Y., H.J.L.)
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, NC (E.Z.S.)
| | - Eric A Whitsel
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
| | - Kari E North
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
- Carolina Center for Genome Sciences (K.E.N.), University of North Carolina at Chapel Hill
| | - Charles Kooperberg
- Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA (U.P., A.P.R., C.K.)
| | - Christy L Avery
- Gillings School of Global Public Health (A.R.B., H.M.H., R.G., M.G., C.J.H., A.A.S., E.A.W., K.E.N., C.L.A.), University of North Carolina at Chapel Hill
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8
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Fernandez-Rhodes L, Young KL, Lilly AG, Raffield LM, Highland HM, Wojcik GL, Agler C, M Love SA, Okello S, Petty LE, Graff M, Below JE, Divaris K, North KE. Importance of Genetic Studies of Cardiometabolic Disease in Diverse Populations. Circ Res 2020; 126:1816-1840. [PMID: 32496918 PMCID: PMC7285892 DOI: 10.1161/circresaha.120.315893] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Genome-wide association studies have revolutionized our understanding of the genetic underpinnings of cardiometabolic disease. Yet, the inadequate representation of individuals of diverse ancestral backgrounds in these studies may undercut their ultimate potential for both public health and precision medicine. The goal of this review is to describe the imperativeness of studying the populations who are most affected by cardiometabolic disease, to the aim of better understanding the genetic underpinnings of the disease. We support this premise by describing the current variation in the global burden of cardiometabolic disease and emphasize the importance of building a globally and ancestrally representative genetics evidence base for the identification of population-specific variants, fine-mapping, and polygenic risk score estimation. We discuss the important ethical, legal, and social implications of increasing ancestral diversity in genetic studies of cardiometabolic disease and the challenges that arise from the (1) lack of diversity in current reference populations and available analytic samples and the (2) unequal generation of health-associated genomic data and their prediction accuracies. Despite these challenges, we conclude that additional, unprecedented opportunities lie ahead for public health genomics and the realization of precision medicine, provided that the gap in diversity can be systematically addressed. Achieving this goal will require concerted efforts by social, academic, professional and regulatory stakeholders and communities, and these efforts must be based on principles of equity and social justice.
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Affiliation(s)
- Lindsay Fernandez-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Adam G Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Cary Agler
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Shelly-Ann M Love
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Samson Okello
- Department of Internal Medicine, Mbarara University of Science and Technology, Uganda
- University of Virginia, Charlottesville, VA
- Harvard TH Chan School of Public Health, Boston, MA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Vanderbilt, TN
- Department of Genetic Medicine, Vanderbilt University, Vanderbilt, TN
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Vanderbilt, TN
- Department of Genetic Medicine, Vanderbilt University, Vanderbilt, TN
| | - Kimon Divaris
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Center for Genome Sciences, Chapel Hill, NC
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9
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Niculite CM, Enciu AM, Hinescu ME. CD 36: Focus on Epigenetic and Post-Transcriptional Regulation. Front Genet 2019; 10:680. [PMID: 31379931 PMCID: PMC6659770 DOI: 10.3389/fgene.2019.00680] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 06/28/2019] [Indexed: 12/11/2022] Open
Abstract
CD36 is a transmembrane protein involved in fatty acid translocation, scavenging for oxidized fatty acids acting as a receptor for adhesion molecules. It is expressed on macrophages, as well as other types of cells, such as endothelial and adipose cells. CD36 participates in muscle lipid uptake, adipose energy storage, and gut fat absorption. Recently, several preclinical and clinical studies demonstrated that upregulation of CD36 is a prerequisite for tumor metastasis. Cancer metastasis-related research emerged much later and has been less investigated, though it is equally or even more important. CD36 protein expression can be modified by epigenetic changes and post-transcriptional interference from non-coding RNAs. Some data indicate modulation of CD36 expression in specific cell types by epigenetic changes via DNA methylation patterns or histone tails, or through miRNA interference, but this is largely unexplored. The few papers addressing this topic refer mostly to lipid metabolism-related pathologies, whereas in cancer research, data are even more scarce. The aim of this review was to summarize major epigenetic and post-transcriptional mechanisms that impact CD36 expression in relation to various pathologies while highlighting the areas in need of further exploration.
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Affiliation(s)
- Cristina-Mariana Niculite
- Cell Biology Department, "Victor Babes" National Institute of Pathology, Bucharest, Romania.,Department of Cellular and Molecular Biology and Histology, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Enciu
- Cell Biology Department, "Victor Babes" National Institute of Pathology, Bucharest, Romania.,Department of Cellular and Molecular Biology and Histology, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihail Eugen Hinescu
- Cell Biology Department, "Victor Babes" National Institute of Pathology, Bucharest, Romania.,Department of Cellular and Molecular Biology and Histology, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
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10
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Hosseinzadeh N, Mehrabi Y, Daneshpour MS, Zayeri F, Guity K, Azizi F. Identifying new associated pleiotropic SNPs with lipids by simultaneous test of multiple longitudinal traits: An Iranian family-based study. Gene 2019; 692:156-169. [DOI: 10.1016/j.gene.2019.01.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 01/05/2019] [Accepted: 01/11/2019] [Indexed: 02/08/2023]
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11
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Wu J, Yin RX, Zhou YG, Zhang QH, Wu JZ, Chen WX. Association between the MGAT1 rs634501 polymorphism and serum lipid traits in the Chinese Han and Maonan ethnic groups. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2018; 11:5923-5937. [PMID: 31949680 PMCID: PMC6963053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 10/25/2018] [Indexed: 06/10/2023]
Abstract
Little is known about the association of monoacylglycerol acyltransferase 1 gene (MGAT1) rs634501 single nucleotide polymorphism (SNP) and serum lipid profiles in the Chinese populations. The aim of this study was to detect the association of the MGAT1 rs634501 SNP and several environmental factors with serum lipid levels in the Chinese Maonan and Han populations. Genotypes of the SNP in 2014 unrelated participants (Han, 986; Maonan, 1028) were determined by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and confirmed by direct sequencing. The genotypic and allelic frequencies of the MGAT1 rs634501 SNP were significantly different between the Han and Maonan populations as well as between males and females in the Maonan population. The A allele carriers had lower serum apolipoprotein (Apo) A1 levels, the ApoA1/ApoB ratio and higher ApoB levels in Maonans; and lower high-density lipoprotein cholesterol, ApoA1 levels, ApoA1/ApoB ratio, and higher triglyceride levels in Han than the A allele non-carriers. There were also different associations of the MGAT1 rs634501 SNP and serum lipid profiles between males and females in the both ethnic groups. Serum lipid parameters in the two ethnic groups were also associated with several environmental factors. These results suggest that the association of the MGAT1 rs634501 SNP and serum lipid parameters might have ethnic- and/or sex-specificity.
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Affiliation(s)
- Jie Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
| | - Rui-Xing Yin
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
| | - Yong-Gang Zhou
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
| | - Qing-Hui Zhang
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
| | - Jin-Zhen Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
| | - Wu-Xian Chen
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University Nanning, Guangxi, People's Republic of China
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12
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Pikó P, Fiatal S, Kósa Z, Sándor J, Ádány R. Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations. Gene 2018; 686:187-193. [PMID: 30468910 DOI: 10.1016/j.gene.2018.11.067] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 09/28/2018] [Accepted: 11/19/2018] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Large-scale association studies that mainly involve European populations identified many genetic loci related to high-density lipoprotein cholesterol (HDL-C) levels, one of the most important indicators of the risk for cardiovascular diseases. The question with intense speculation of whether the effect estimates obtained from European populations for different HDL-C level-related SNPs are applicable to the Roma ethnicity, the largest minority group in Europe with a South Asian origin, was addressed in the present study. DESIGN The associations between 21 SNPs (in the genes LIPC(G), CETP, GALNT2, HMGCP, ABCA1, KCTD10 and WWOX) and HDL-C levels were examined separately in adults of the Hungarian general (N = 1542) and Roma (N = 646) populations by linear regression. Individual effects (direction and size) of single SNPs on HDL-C levels were computed and compared between the study groups and with data published in the literature. RESULTS Significant associations between SNPs and HDL-C levels were more frequently found in general subjects than in Roma subjects (11 SNPs in general vs. 4 SNPs in Roma). The CETP gene variants rs1532624, rs708272 and rs7499892 consistently showed significant associations with HDL-C levels across the study groups (p ˂ 0.05), indicating a possible causal variant(s) in this region. Although nominally significant differences in effect size were found for three SNPs (rs693 in gene APOB, rs9989419 in gene CETP, and rs2548861 in gene WWOX) by comparing the general and Roma populations, most of these SNPs did not have a significant effect on HDL-C levels. The β coefficients for SNPs in the Roma population were found to be identical both in direction and magnitude to the effect obtained previously in large-scale studies on European populations. CONCLUSIONS The effect of the vast majority of the SNPs on HDL-C levels could be replicated in the Hungarian general and Roma populations, which indicates that the effect size measurements obtained from the literature can be used for risk estimation for both populations.
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Affiliation(s)
- Péter Pikó
- MTA-DE Public Health Research Group of the Hungarian Academy of Sciences, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary; Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary
| | - Szilvia Fiatal
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary; WHO Collaborating Centre on Vulnerability and Health, Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary
| | - Zsigmond Kósa
- Department of Health Visitor Methodology and Public Health, Faculty of Health, University of Debrecen, Nyíregyháza 4400, Hungary
| | - János Sándor
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary; WHO Collaborating Centre on Vulnerability and Health, Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary
| | - Róza Ádány
- MTA-DE Public Health Research Group of the Hungarian Academy of Sciences, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary; Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary; WHO Collaborating Centre on Vulnerability and Health, Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen 4028, Hungary.
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13
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Hebbar P, Nizam R, Melhem M, Alkayal F, Elkum N, John SE, Tuomilehto J, Alsmadi O, Thanaraj TA. Genome-wide association study identifies novel recessive genetic variants for high TGs in an Arab population. J Lipid Res 2018; 59:1951-1966. [PMID: 30108155 DOI: 10.1194/jlr.p080218] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 07/23/2018] [Indexed: 12/12/2022] Open
Abstract
Abnormal blood lipid levels are influenced by genetic and lifestyle/dietary factors. Although many genetic variants associated with blood lipid traits have been identified in Europeans, similar data in Middle Eastern populations are limited. We performed a genome-wide association study with Arab individuals (discovery cohort: 1,353; replication cohort: 1,176) from Kuwait to identify possible associations of genetic variants with high lipid levels. We used Illumina HumanOmniExpress BeadChip and candidate SNP genotyping in the discovery and replication phases, respectively. For association tests, we used genetic models that were based on additive and recessive modes of inheritance. High triglycerides (TGs) were recessively associated with six risk variants (rs1002487/RPS6KA1, rs11805972/LAD1) rs7761746/Or5v1, rs39745/CTTNBP2-LSM8, rs2934952/PGAP3, and rs9626773/RP11-191L9.4-CERK) at genome-wide significance (P 6.12E-09), and another six variants (rs10873925/ST6GALNAC5, rs4663379/SPP2-ARL4C, rs10033119/NPY1R, rs17709449/LINC00911-FLRT2, rs11654954/CDK12-NEUROD2, and rs9972882/STARD3) were associated at borderline significance (P 5.0E-08). High TG was also additively associated with rs11654954. All of the 12 identified markers are novel and are harbored in runs of homozygosity. Literature evidence supports the involvement of these gene loci in lipid-related processes. This study in an Arab population augments international efforts to identify genetic regulation of lipid traits.
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Affiliation(s)
- Prashantha Hebbar
- Dasman Diabetes Institute, Dasman 15462, Kuwait.,Faculty of Medicine, Univerisity of Helsinki, Helsinki, Finland
| | | | | | | | - Naser Elkum
- Dasman Diabetes Institute, Dasman 15462, Kuwait
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14
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Burgess B, Melis M, Scoular K, Driver M, Schaich KM, Keller KL, Tomassini Barbarossa I, Tepper BJ. Effects of CD36 Genotype on Oral Perception of Oleic Acid Supplemented Safflower Oil Emulsions in Two Ethnic Groups: A Preliminary Study. J Food Sci 2018; 83:1373-1380. [PMID: 29660814 PMCID: PMC5969292 DOI: 10.1111/1750-3841.14115] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 02/12/2018] [Accepted: 02/25/2018] [Indexed: 12/16/2022]
Abstract
Previous studies demonstrate humans can detect fatty acids via specialized sensors on the tongue, such as the CD36 receptor. Genetic variation at the common single nucleotide polymorphism rs1761667 of CD36 has been shown to differentially impact the perception of fatty acids, but comparative data among different ethnic groups are lacking. In a small cohort of Caucasian and East Asian young adults, we investigated if: (1) participants could detect oleic acid (C18:1) added to safflower oil emulsions at a constant ratio of 3% (w/v); (2) supplementation of oleic acid to safflower oil emulsions enhanced perception of fattiness and creaminess; and (3) variation at rs1761667 influenced oleic acid detection and fat taste perception. In a 3-alternate forced choice test, 62% of participants detected 2.9 ± 0.7 mM oleic acid (or 0.08% w/v) in a 2.8% safflower oil emulsion. Supplementation of oleic acid did not enhance fattiness and creaminess perception for the cohort as a whole, though East Asians carrying the GG genotype perceived more overall fattiness and creaminess than their AA genotype counterparts (P < 0.001). No differences were observed for the Caucasians. These preliminary findings indicate that free oleic acid can be detected in an oil-in-water emulsion at concentrations found in commercial oils, but it does not increase fattiness or creaminess perception. Additionally, variation at rs1761667 may have ethnic-specific effects on fat taste perception.
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Affiliation(s)
- Brenda Burgess
- Dept. of Food Science and Center for Sensory Sciences & Innovation, School of Environmental and Biological Sciences, Rutgers Univ., New Brunswick, N.J., U.S.A
| | - Melania Melis
- Dept. of Biomedical Sciences, Section of Physiology, Univ. of Cagliari, Monserrato, Italy
| | - Katelyn Scoular
- Dept. of Food Science and Center for Sensory Sciences & Innovation, School of Environmental and Biological Sciences, Rutgers Univ., New Brunswick, N.J., U.S.A
| | - Michael Driver
- Dept. of Food Science and Center for Sensory Sciences & Innovation, School of Environmental and Biological Sciences, Rutgers Univ., New Brunswick, N.J., U.S.A
| | - Karen M Schaich
- Dept. of Food Science and Center for Sensory Sciences & Innovation, School of Environmental and Biological Sciences, Rutgers Univ., New Brunswick, N.J., U.S.A
| | - Kathleen L Keller
- Dept. of Nutritional Sciences and Dept. of Food Science, The Pennsylvania State Univ., University Park, Pa., U.S.A
| | | | - Beverly J Tepper
- Dept. of Food Science and Center for Sensory Sciences & Innovation, School of Environmental and Biological Sciences, Rutgers Univ., New Brunswick, N.J., U.S.A
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15
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Hoffmann TJ, Theusch E, Haldar T, Ranatunga DK, Jorgenson E, Medina MW, Kvale MN, Kwok PY, Schaefer C, Krauss RM, Iribarren C, Risch N. A large electronic-health-record-based genome-wide study of serum lipids. Nat Genet 2018; 50:401-413. [PMID: 29507422 PMCID: PMC5942247 DOI: 10.1038/s41588-018-0064-5] [Citation(s) in RCA: 176] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 01/19/2018] [Indexed: 12/16/2022]
Abstract
A genome-wide association study of 94,674 multi-ethnic Kaiser Permanente members utilizing 478,866 longitudinal untreated serum lipid electronic-health-record-derived measurements (EHRs) empowered multiple novel findings: 121 new SNP associations (46 primary, 15 conditional, 60 in meta-analysis with Global Lipids Genetic Consortium); increase of 33-42% in variance explained with multiple measurements; sex differences in genetic impact (greater in females for LDL, HDL, TC, the opposite for TG); differences in variance explained amongst non-Hispanic whites, Latinos, African Americans, and East Asians; genetic dominance and epistasis, with strong evidence for both at ABOxFUT2 for LDL; and eQTL tissue-enrichment implicating the liver, adipose, and pancreas. Utilizing EHR pharmacy data, both LDL and TG genetic risk scores (477 SNPs) were strongly predictive of age-at-initiation of lipid-lowering treatment. These findings highlight the value of longitudinal EHRs for identifying novel genetic features of cholesterol and lipoprotein metabolism with implications for lipid treatment and risk of coronary heart disease.
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Affiliation(s)
- Thomas J Hoffmann
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. .,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
| | | | - Tanushree Haldar
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Dilrini K Ranatunga
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
| | - Marisa W Medina
- Children's Hospital Oakland Research Institute, Oakland, CA, USA
| | - Mark N Kvale
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Pui-Yan Kwok
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Catherine Schaefer
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA, USA
| | - Carlos Iribarren
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
| | - Neil Risch
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. .,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA. .,Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA.
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16
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Insights from population-based analyses of plasma lipids across the allele frequency spectrum. Curr Opin Genet Dev 2018; 50:1-6. [PMID: 29448166 DOI: 10.1016/j.gde.2018.01.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 01/18/2018] [Accepted: 01/22/2018] [Indexed: 12/29/2022]
Abstract
Plasma lipid levels are heritable quantitative risk factors and therapeutic targets for cardiovascular disease. Plasma lipids have been a model for translating genetic observations across the allele frequency spectrum to unique biological and therapeutic insights. Most large studies to date predominately comprised of individuals of European ancestry. This review focuses on contemporary evidence from 2016 to 2017 looking at the effect of genetic variants on plasma lipid levels across the allele frequency spectrum with incrementally larger sample sizes and the contribution of non-European ancestry studies to the genetic etiology of plasma lipid levels. To date, over 250 loci have been associated with plasma lipid levels and several of these loci have additional evidence of association with rare coding variants providing evidence for causal genes at the locus.
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17
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Andaleon A, Mogil LS, Wheeler HE. Gene-based association study for lipid traits in diverse cohorts implicates BACE1 and SIDT2 regulation in triglyceride levels. PeerJ 2018; 6:e4314. [PMID: 29404214 PMCID: PMC5793713 DOI: 10.7717/peerj.4314] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 01/11/2018] [Indexed: 11/29/2022] Open
Abstract
Plasma lipid levels are risk factors for cardiovascular disease, a leading cause of death worldwide. While many studies have been conducted on lipid genetics, they mainly focus on Europeans and thus their transferability to diverse populations is unclear. We performed SNP- and gene-level genome-wide association studies (GWAS) of four lipid traits in cohorts from Nigeria and the Philippines and compared them to the results of larger, predominantly European meta-analyses. Two previously implicated loci met genome-wide significance in our SNP-level GWAS in the Nigerian cohort, rs34065661 in CETP associated with HDL cholesterol (P = 9.0 × 10-10) and rs1065853 upstream of APOE associated with LDL cholesterol (P = 6.6 × 10-9). The top SNP in the Filipino cohort associated with triglyceride levels (rs662799; P = 2.7 × 10-16) and has been previously implicated in other East Asian studies. While this SNP is located directly upstream of well known APOA5, we show it may also be involved in the regulation of BACE1 and SIDT2. Our gene-based association analysis, PrediXcan, revealed decreased expression of BACE1 and decreased expression of SIDT2 in several tissues, all driven by rs662799, significantly associate with increased triglyceride levels in Filipinos (FDR <0.1). In addition, our PrediXcan analysis implicated gene regulation as the mechanism underlying the associations of many other previously discovered lipid loci. Our novel BACE1 and SIDT2 findings were confirmed using summary statistics from the Global Lipids Genetic Consortium (GLGC) meta-GWAS.
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Affiliation(s)
- Angela Andaleon
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
| | - Lauren S. Mogil
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
| | - Heather E. Wheeler
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
- Department of Computer Science, Loyola University Chicago, Chicago, IL, United States of America
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, United States of America
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18
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Graff M, Emery LS, Justice AE, Parra E, Below JE, Palmer ND, Gao C, Duan Q, Valladares-Salgado A, Cruz M, Morrison AC, Boerwinkle E, Whitsel EA, Kooperberg C, Reiner A, Li Y, Rodriguez CJ, Talavera GA, Langefeld CD, Wagenknecht LE, Norris JM, Taylor KD, Papanicolaou G, Kenny E, Loos RJF, Chen YDI, Laurie C, Sofer T, North KE. Genetic architecture of lipid traits in the Hispanic community health study/study of Latinos. Lipids Health Dis 2017; 16:200. [PMID: 29025430 PMCID: PMC5639746 DOI: 10.1186/s12944-017-0591-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/04/2017] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Despite ethnic disparities in lipid profiles, there are few genome-wide association studies investigating genetic variation of lipids in non-European ancestry populations. In this study, we present findings from genetic association analyses for total cholesterol, low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides in a large Hispanic/Latino cohort in the U.S., the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). METHODS We estimated a heritability of approximately 20% for each lipid trait, similar to previous estimates in Europeans. To search for novel lipid loci, we performed conditional association analysis in which the statistical model was adjusted for previously reported SNPs associated with any of the four lipid traits. SNPs that remained genome-wide significant (P < 5 × 10-8) after conditioning on known loci were evaluated for replication. RESULTS We identified eight potentially novel lipid signals with minor allele frequencies <1%, none of which replicated. We tested previously reported SNP-trait associations for generalization to Hispanics/Latinos via a statistical framework. The generalization analysis revealed that approximately 50% of previously established lipid variants generalize to HCHS/SOL based on directional FDR r-value < 0.05. Some failures to generalize were due to lack of power. CONCLUSIONS These results demonstrate that many loci associated with lipid levels are shared across populations.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anne E Justice
- Biomedical and Translational Informatics, Geisinger Health, Danville, PA, USA
| | - Esteban Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbuilt University, Nashville, TN, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, CMNSXX1-IMSS, Mexico City, Mexico
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, CMNSXX1-IMSS, Mexico City, Mexico
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Fred Hutchinson Cancer Research Center, Public Health Sciences, Seattle, WA, USA
| | - Alex Reiner
- Fred Hutchinson Cancer Research Center, Public Health Sciences, Seattle, WA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carlos Jose Rodriguez
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Gregory A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, CA, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Eimear Kenny
- Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Cathy Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
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19
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Rotimi CN, Bentley AR, Doumatey AP, Chen G, Shriner D, Adeyemo A. The genomic landscape of African populations in health and disease. Hum Mol Genet 2017; 26:R225-R236. [PMID: 28977439 PMCID: PMC6075021 DOI: 10.1093/hmg/ddx253] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Revised: 06/19/2017] [Accepted: 06/29/2017] [Indexed: 12/12/2022] Open
Abstract
A deeper appreciation of the complex architecture of African genomes is critical to the global effort to understand human history, biology and differential distribution of disease by geography and ancestry. Here, we report on how the growing engagement of African populations in genome science is providing new insights into the forces that shaped human genomes before and after the Out-of-Africa migrations. As a result of this human evolutionary history, African ancestry populations have the greatest genomic diversity in the world, and this diversity has important ramifications for genomic research. In the case of pharmacogenomics, for instance, variants of consequence are not limited to those identified in other populations, and diversity within African ancestry populations precludes summarizing risk across different African ethnic groups. Exposure of Africans to fatal pathogens, such as Plasmodium falciparum, Lassa Virus and Trypanosoma brucei rhodesiense, has resulted in elevated frequencies of alleles conferring survival advantages for infectious diseases, but that are maladaptive in modern-day environments. Illustrating with cardiometabolic traits, we show that while genomic research in African ancestry populations is still in early stages, there are already many examples of novel and African ancestry-specific disease loci that have been discovered. Furthermore, the shorter haplotypes in African genomes have facilitated fine-mapping of loci discovered in other human ancestry populations. Given the insights already gained from the interrogation of African genomes, it is imperative to continue and increase our efforts to describe genomic risk in and across African ancestry populations.
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Affiliation(s)
- Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
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20
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Liang Y, Kelemen A. Shared polymorphisms and modifiable behavior factors for myocardial infarction and high cholesterol in a retrospective population study. Medicine (Baltimore) 2017; 96:e7683. [PMID: 28906356 PMCID: PMC5604625 DOI: 10.1097/md.0000000000007683] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Genetic and environmental (behavior, clinical, and demographic) factors are associated with increased risks of both myocardial infarction (MI) and high cholesterol (HC). It is known that HC is major risk factor that may cause MI. However, whether there are common single nucleotide polymorphism (SNPs) associated with both MI and HC is not firmly established, and whether there are modulate and modified effects (interactions of genetic and known environmental factors) on either HC or MI, and whether these joint effects improve the predictions of MI, is understudied.The purpose of this study is to identify novel shared SNPs and modifiable environmental factors on MI and HC. We assess whether SNPs from a metabolic pathway related to MI may relate to HC; whether there are moderate effects among SNPs, lifestyle (smoke and drinking), HC, and MI after controlling other factors [gender, body mass index (BMI), and hypertension (HTN)]; and evaluate prediction power of the joint and modulate genetic and environmental factors influencing the MI and HC.This is a retrospective study with residents of Erie and Niagara counties in New York with a history of MI or with no history of MI. The data set includes environmental variables (demographic, clinical, lifestyle). Thirty-one tagSNPs from a metabolic pathway related to MI are genotyped. Generalized linear models (GLMs) with imputation-based analysis are conducted for examining the common effects of tagSNPs and environmental exposures and their interactions on having a history of HC or MI.MI, BMI, and HTN are significant risk factors for HC. HC shows the strongest effect on risk of MI in addition to HTN; gender and smoking status while drinking status shows protective effect on MI. rs16944 (gene IL-1β) and rs17222772 (gene ALOX) increase the risks of HC, while rs17231896 (gene CETP) has protective effects on HC either with or without the clinical, behavioral, demographic factors with different effect sizes that may indicate the existence of moderate or modifiable effects. Further analysis with the inclusions of gene-gene and gene-environmental interactions shows interactions between rs17231896 (CETP) and rs17222772 (ALOX); rs17231896 (CETP) and gender. rs17237890 (CETP) and rs2070744 (NOS3) are found to be significantly associated with risks of MI adjusted by both SNPs and environmental factors. After multiple testing adjustments, these effects diminished as expected. In addition, an interaction between drinking and smoking status is significant. Overall, the prediction power in successfully classifying MI status is increased to 80% with inclusions of all significant tagSNPs and environmental factors and their interactions compared with environmental factors only (72%).Having a history of either HC or MI has significant effects on each other in both directions, in addition to HTN and gender. Genes/SNPs identified from this analysis that are associated with HC may be potentially linked to MI, which could be further examined and validated through haplotype-pairs analysis with appropriate population stratification corrections, and function/pathway regulation analysis to eliminate the limitations of the current analysis.
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Affiliation(s)
| | - Arpad Kelemen
- Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, MD
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21
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Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, O'Dushlaine C, Van Hout CV, Staples J, Gonzaga-Jauregui C, Metpally R, Pendergrass SA, Giovanni MA, Kirchner HL, Balasubramanian S, Abul-Husn NS, Hartzel DN, Lavage DR, Kost KA, Packer JS, Lopez AE, Penn J, Mukherjee S, Gosalia N, Kanagaraj M, Li AH, Mitnaul LJ, Adams LJ, Person TN, Praveen K, Marcketta A, Lebo MS, Austin-Tse CA, Mason-Suares HM, Bruse S, Mellis S, Phillips R, Stahl N, Murphy A, Economides A, Skelding KA, Still CD, Elmore JR, Borecki IB, Yancopoulos GD, Davis FD, Faucett WA, Gottesman O, Ritchie MD, Shuldiner AR, Reid JG, Ledbetter DH, Baras A, Carey DJ. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science 2017; 354:354/6319/aaf6814. [PMID: 28008009 DOI: 10.1126/science.aaf6814] [Citation(s) in RCA: 368] [Impact Index Per Article: 52.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Accepted: 11/16/2016] [Indexed: 11/02/2022]
Abstract
The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Korey A Kost
- Geisinger Health System, Danville, PA 17822, USA
| | | | | | - John Penn
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
| | | | | | | | | | | | | | | | | | | | - Matthew S Lebo
- Laboratory for Molecular Medicine, Cambridge, MA 02139, USA
| | | | | | | | - Scott Mellis
- Regeneron Pharmaceuticals, Tarrytown, NY 10591, USA
| | | | - Neil Stahl
- Regeneron Pharmaceuticals, Tarrytown, NY 10591, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
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22
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Zubair N, Graff M, Luis Ambite J, Bush WS, Kichaev G, Lu Y, Manichaikul A, Sheu WHH, Absher D, Assimes TL, Bielinski SJ, Bottinger EP, Buzkova P, Chuang LM, Chung RH, Cochran B, Dumitrescu L, Gottesman O, Haessler JW, Haiman C, Heiss G, Hsiung CA, Hung YJ, Hwu CM, Juang JMJ, Le Marchand L, Lee IT, Lee WJ, Lin LA, Lin D, Lin SY, Mackey RH, Martin LW, Pasaniuc B, Peters U, Predazzi I, Quertermous T, Reiner AP, Robinson J, Rotter JI, Ryckman KK, Schreiner PJ, Stahl E, Tao R, Tsai MY, Waite LL, Wang TD, Buyske S, Ida Chen YD, Cheng I, Crawford DC, Loos RJF, Rich SS, Fornage M, North KE, Kooperberg C, Carty CL. Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci. Hum Mol Genet 2017; 25:5500-5512. [PMID: 28426890 DOI: 10.1093/hmg/ddw358] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 10/17/2016] [Indexed: 11/13/2022] Open
Abstract
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.
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Affiliation(s)
- Niha Zubair
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | | | - Jose Luis Ambite
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - William S Bush
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Gleb Kichaev
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Yingchang Lu
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ani Manichaikul
- Center for Public Health Genomics and Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, USA
| | - Wayne H-H Sheu
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | - Erwin P Bottinger
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lee-Ming Chuang
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ren-Hua Chung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan
| | - Barbara Cochran
- Genetic Laboratory at the University of Texas Health Science Center, University of Texas, Houston, TX, USA
| | - Logan Dumitrescu
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Omri Gottesman
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jeffrey W Haessler
- WHI Clinical Coordinating Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christopher Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Chao A Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Miaoli County, Taiwan
| | - Yi-Jen Hung
- Division of Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chii-Min Hwu
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Jyh-Ming J Juang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Loic Le Marchand
- Cancer Epidemiology Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, Hawai'i. USA
| | - I-Te Lee
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Li-An Lin
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Danyu Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shih-Yi Lin
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Rachel H Mackey
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lisa W Martin
- Cardiology Division, School of Medicine and Health Sciences, George Washington University, Washington, DC, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Ulrike Peters
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Irene Predazzi
- Knight Cardiovascular Institute, Center for Preventative Cardiology, Oregon Health & Science University, Portland, OR, USA
| | - Thomas Quertermous
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Alex P Reiner
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jennifer Robinson
- Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kelli K Ryckman
- Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Pamela J Schreiner
- Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Eli Stahl
- Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ran Tao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael Y Tsai
- Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Tzung-Dau Wang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Steven Buyske
- Department of Statistics & Biostatistics, Rutgers University, Piscataway, NJ, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Iona Cheng
- Cancer Prevention Institute of California, Fremont, CA, USA
| | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics and Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Charles Kooperberg
- Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Cara L Carty
- Center for Translational Science, George Washington University, Children's National Medical Center, Washington, DC, USA
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23
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CD36 gene polymorphism is associated with Alzheimer's disease. Biochimie 2017; 135:46-53. [PMID: 28111291 DOI: 10.1016/j.biochi.2017.01.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 01/18/2017] [Indexed: 01/18/2023]
Abstract
CD36 gene encodes a membrane glycoprotein (type B scavenger receptor) present on the surface of many types of cells and having multiple cellular functions ranging from angiogenesis to gustatory perception of fatty acids. Using a case control genetic association approach we have analyzed selected single nucleotide polymorphisms (SNP's) in a total of 859 patients with Alzheimer's disease (AD) and controls and have identified the allele A in rs3211892 polymorphism of CD36 gene as significantly increasing the risk of AD. Additionally we have investigated, in the same sample of control subjects and patients, SNP's in ApoE gene and confirmed that the previously identified AD-associated SNP's indeed increased the risk and decreased the age of onset of AD as reported by others earlier. Based on the current knowledge of CD36 biochemistry we propose that the AD risk-imparting variants of CD36 alter cholesterol homeostasis, oxidation stress or induce pathological inflammatory cascades. The SNP rs3211892 has previously been associated with heart disease and other conditions but the present study is the first to identify a significant association between variations in CD36 gene and the risk of Alzheimer's disease.
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24
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Love-Gregory L, Kraja AT, Allum F, Aslibekyan S, Hedman ÅK, Duan Y, Borecki IB, Arnett DK, McCarthy MI, Deloukas P, Ordovas JM, Hopkins PN, Grundberg E, Abumrad NA. Higher chylomicron remnants and LDL particle numbers associate with CD36 SNPs and DNA methylation sites that reduce CD36. J Lipid Res 2016; 57:2176-2184. [PMID: 27729386 DOI: 10.1194/jlr.p065250] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 09/28/2016] [Indexed: 12/18/2022] Open
Abstract
Cluster of differentiation 36 (CD36) variants influence fasting lipids and risk of metabolic syndrome, but their impact on postprandial lipids, an independent risk factor for cardiovascular disease, is unclear. We determined the effects of SNPs within a ∼410 kb region encompassing CD36 and its proximal and distal promoters on chylomicron (CM) remnants and LDL particles at fasting and at 3.5 and 6 h following a high-fat meal (Genetics of Lipid Lowering Drugs and Diet Network study, n = 1,117). Five promoter variants associated with CMs, four with delayed TG clearance and five with LDL particle number. To assess mechanisms underlying the associations, we queried expression quantitative trait loci, DNA methylation, and ChIP-seq datasets for adipose and heart tissues that function in postprandial lipid clearance. Several SNPs that associated with higher serum lipids correlated with lower adipose and heart CD36 mRNA and aligned to active motifs for PPARγ, a major CD36 regulator. The SNPs also associated with DNA methylation sites that related to reduced CD36 mRNA and higher serum lipids, but mixed-model analyses indicated that the SNPs and methylation independently influence CD36 mRNA. The findings support contributions of CD36 SNPs that reduce adipose and heart CD36 RNA expression to inter-individual variability of postprandial lipid metabolism and document changes in CD36 DNA methylation that influence both CD36 expression and lipids.
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Affiliation(s)
- Latisha Love-Gregory
- Department of Medicine, Center for Human Nutrition Washington University School of Medicine, St. Louis, MO 63110
| | - Aldi T Kraja
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO 63110
| | - Fiona Allum
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama, Birmingham, AL 35294
| | - Åsa K Hedman
- Departments of Medical Sciences and Molecular Epidemiology, and Science for Life Laboratory, Uppsala University, Uppsala 75185, Sweden
| | - Yanan Duan
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO 63110
| | - Ingrid B Borecki
- Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO 63110
| | - Donna K Arnett
- Department of Epidemiology, University of Alabama, Birmingham, AL 35294
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK, and Oxford Centre for Diabetes, Endocrinology, and Metabolism and Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford OX3 7JU, UK
| | - Panos Deloukas
- William Harvey Research Institute, Queen Mary University of London, EC1M 6BQ London, UK
| | - Jose M Ordovas
- JM-USDA-Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111
| | - Paul N Hopkins
- Cardiovascular Genetics Research, University of Utah, Salt Lake City, UT 84132
| | - Elin Grundberg
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Nada A Abumrad
- Department of Medicine, Center for Human Nutrition Washington University School of Medicine, St. Louis, MO 63110
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25
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Chami N, Chen MH, Slater AJ, Eicher JD, Evangelou E, Tajuddin SM, Love-Gregory L, Kacprowski T, Schick UM, Nomura A, Giri A, Lessard S, Brody JA, Schurmann C, Pankratz N, Yanek LR, Manichaikul A, Pazoki R, Mihailov E, Hill WD, Raffield LM, Burt A, Bartz TM, Becker DM, Becker LC, Boerwinkle E, Bork-Jensen J, Bottinger EP, O'Donoghue ML, Crosslin DR, de Denus S, Dubé MP, Elliott P, Engström G, Evans MK, Floyd JS, Fornage M, Gao H, Greinacher A, Gudnason V, Hansen T, Harris TB, Hayward C, Hernesniemi J, Highland HM, Hirschhorn JN, Hofman A, Irvin MR, Kähönen M, Lange E, Launer LJ, Lehtimäki T, Li J, Liewald DCM, Linneberg A, Liu Y, Lu Y, Lyytikäinen LP, Mägi R, Mathias RA, Melander O, Metspalu A, Mononen N, Nalls MA, Nickerson DA, Nikus K, O'Donnell CJ, Orho-Melander M, Pedersen O, Petersmann A, Polfus L, Psaty BM, Raitakari OT, Raitoharju E, Richard M, Rice KM, Rivadeneira F, Rotter JI, Schmidt F, Smith AV, Starr JM, Taylor KD, Teumer A, Thuesen BH, Torstenson ES, Tracy RP, Tzoulaki I, Zakai NA, Vacchi-Suzzi C, van Duijn CM, van Rooij FJA, Cushman M, Deary IJ, Velez Edwards DR, Vergnaud AC, Wallentin L, Waterworth DM, White HD, Wilson JG, Zonderman AB, Kathiresan S, Grarup N, Esko T, Loos RJF, Lange LA, Faraday N, Abumrad NA, Edwards TL, Ganesh SK, Auer PL, Johnson AD, Reiner AP, Lettre G. Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits. Am J Hum Genet 2016; 99:8-21. [PMID: 27346685 PMCID: PMC5005438 DOI: 10.1016/j.ajhg.2016.05.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Accepted: 05/03/2016] [Indexed: 11/24/2022] Open
Abstract
Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.
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Affiliation(s)
- Nathalie Chami
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Ming-Huei Chen
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Andrew J Slater
- Genetics Target Sciences, GlaxoSmithKline, Research Triangle Park, NC 27709, USA; OmicSoft Corporation, Cary, NC 27513, USA
| | - John D Eicher
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Salman M Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Latisha Love-Gregory
- Department of Medicine, Center of Human Nutrition, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Tim Kacprowski
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine, Greifswald and Ernst-Mortiz-Arndt University Greifswald, Greifswald 17475, Germany; DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald QA, Germany
| | - Ursula M Schick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Akihiro Nomura
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Division of Cardiovascular Medicine, Kanazawa University, Graduate School of Medical Science, Kanazawa, Ishikawa 9200942, Japan
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Samuel Lessard
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Jennifer A Brody
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55454, USA
| | - Lisa R Yanek
- Department of Medicine/Division of General Internal Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD 21205, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Raha Pazoki
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Amber Burt
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Diane M Becker
- Department of Medicine/Division of General Internal Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD 21205, USA
| | - Lewis C Becker
- Department of Medicine/Divisions of Cardiology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jette Bork-Jensen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Michelle L O'Donoghue
- TIMI Study Group, Cardiovascular Division, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - David R Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
| | - Simon de Denus
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada; Faculty of Pharmacy, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Marie-Pierre Dubé
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Gunnar Engström
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - He Gao
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Torben Hansen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Tamara B Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Jussi Hernesniemi
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland; University of Tampere, School of Medicine, Tampere 33014, Finland
| | - Heather M Highland
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Joel N Hirschhorn
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Endocrinology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35233, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33521, Finland; Department of Clinical Physiology, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Ethan Lange
- Departments of Genetics and Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Jin Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, School of Medicine, Palo Alto, CA 94305, USA
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Allan Linneberg
- Research Centre for Prevention and Health, The Capital Region of Denmark, Copenhagen 2600, Denmark; Department of Clinical Experimental Research, Rigshospitalet, Glostrup 2100, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Yongmei Liu
- Center for Human Genetics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Rasika A Mathias
- Department of Medicine, Divisions of Allergy and Clinical Immunology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA
| | - Kjell Nikus
- University of Tampere, School of Medicine, Tampere 33014, Finland; Department of Cardiology, Heart Center, Tampere University Hospital, Tampere 33521, Finland
| | - Chris J O'Donnell
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA; Cardiology Section and Center for Population Genomics, Boston Veteran's Administration (VA) Healthcare, Boston, MA 02118, USA
| | - Marju Orho-Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö 221 00, Sweden; Skåne University Hospital, Malmö 222 41, Sweden
| | - Oluf Pedersen
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Astrid Petersmann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Linda Polfus
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine Epidemiology and Health Services, University of Washington, Seattle, WA 98101, USA; Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20521, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere 33014, Finland
| | - Melissa Richard
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus, MC Rotterdam 3000, the Netherlands; Department of Internal Medicine, Erasmus MC, Rotterdam 3000, the Netherlands; Netherlands Consortium for Healthy Ageing (NCHA), Rotterdam 3015, the Netherlands
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA 90502, USA; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Frank Schmidt
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine, Greifswald and Ernst-Mortiz-Arndt University Greifswald, Greifswald 17475, Germany
| | - Albert Vernon Smith
- Icelandic Heart Association, 201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Alzheimer Scotland Research Centre, Edinburgh EH8 9JZ, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA 90502, USA; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
| | - Betina H Thuesen
- Research Centre for Prevention and Health, The Capital Region of Denmark, Copenhagen 2600, Denmark
| | - Eric S Torstenson
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Russell P Tracy
- Departments of Pathology and Laboratory Medicine and Biochemistry, University of Vermont College of Medicine, Colchester, VT 05446, USA
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece
| | - Neil A Zakai
- Departments of Medicine and Pathology, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Caterina Vacchi-Suzzi
- Department of Family Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | | | | | - Mary Cushman
- Departments of Medicine and Pathology, University of Vermont College of Medicine, Burlington, VT 05405, USA
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Digna R Velez Edwards
- Vanderbilt Epidemiology Center, Department of Obstetrics & Gynecology, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37203, USA
| | - Anne-Claire Vergnaud
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Lars Wallentin
- Department of Medical Sciences, Cardiology and Uppsala Clinical Research Center, Uppsala University, Uppsala 751 85, Sweden
| | - Dawn M Waterworth
- Genetics Target Sciences, GlaxoSmithKline, King of Prussia, PA 19406, USA
| | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland 1142, New Zealand
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Sekar Kathiresan
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Niels Grarup
- The Novo Nordisk Foundation, Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Tõnu Esko
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10069, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Nauder Faraday
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nada A Abumrad
- Department of Medicine, Center of Human Nutrition, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37235, USA
| | - Santhi K Ganesh
- Departments of Internal Medicine and Human Genetics, University of Michigan, Ann Arbor, MI 48108, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53205, USA
| | - Andrew D Johnson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
| | - Guillaume Lettre
- Department of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Montreal Heart Institute, Montréal, QC H1T 1C8, Canada.
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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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Lanktree MB, Elbers CC, Li Y, Zhang G, Duan Q, Karczewski KJ, Guo Y, Tragante V, North KE, Cushman M, Asselbergs FW, Wilson JG, Lange LA, Drenos F, Reiner AP, Barnes MR, Keating BJ. Genetic meta-analysis of 15,901 African Americans identifies variation in EXOC3L1 is associated with HDL concentration. J Lipid Res 2015. [PMID: 26199122 DOI: 10.1194/jlr.p059477] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Meta-analyses of European populations has successfully identified genetic variants in over 150 loci associated with lipid levels, but results from additional ethnicities remain limited. Previously, we reported two novel lipid loci identified in a sample of 7,657 African Americans using a gene-centric array including 50,000 SNPs in 2,100 candidate genes. Initial discovery and follow-up of signals with P < 10(-5) in additional African American samples confirmed CD36 and ICAM1. Using an additional 8,244 African American female samples from the Women's Health Initiative SNP Health Association Resource genome-wide association study dataset, we further examined the previous meta-analyses results by attempting to replicate 20 additional putative lipid signals with P < 10(-4). Replication confirmed rs868213, located in a splice donor region of exocyst complex component 3-like 1 (EXOC3L1) as a novel signal for HDL (additive allelic effect β = 0.02; P = 1.4 × 10(-8); meta-analyses of discovery and replication). EXOC3L1 is strongly expressed in vascular endothelium and forms part of the exocyst complex, a key facilitator of the trafficking of lipid receptors. Increasing sample sizes for genetic studies in nonEuropean populations will continue to improve our understanding of lipid metabolism.
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Affiliation(s)
| | - Clara C Elbers
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA Complex Genetics Section, Department of Medical Genetics (DBG), University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Guosheng Zhang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Qing Duan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Vinicius Tragante
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kari E North
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Mary Cushman
- Departments of Medicine and Pathology,University of Vermont, Colchester, VT
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS
| | - Leslie A Lange
- Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, NC
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kindom
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Michael R Barnes
- William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London, United Kindom
| | - Brendan J Keating
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA Division of Transplantation, Department of Surgery, University of Pennsylvania, Philadelphia, PA
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28
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Abdullah MMH, Jones PJH, Eck PK. Nutrigenetics of cholesterol metabolism: observational and dietary intervention studies in the postgenomic era. Nutr Rev 2015; 73:523-43. [PMID: 26117841 DOI: 10.1093/nutrit/nuv016] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Cholesterol metabolism is a well-defined responder to dietary intakes and a classic biomarker of cardiovascular health. For this reason, circulating cholesterol levels have become key in shaping nutritional recommendations by health authorities worldwide for better management of cardiovascular disease, a leading cause of mortality and one of the most costly health problems globally. Data from observational and dietary intervention studies, however, highlight a marked between-individual variability in the response of cholesterol metabolism to similar dietary protocols, a phenomenon linked to genetic heterogeneity. This review summarizes the postgenomic evidence of polymorphisms within cholesterol-associated genes relative to fasting circulating cholesterol levels under diverse nutritional conditions. A number of cholesterol-related gene-diet interactions are confirmed, which may have clinical importance, supporting a deeper look into the rapidly emerging field of nutrigenetics for meaningful conclusions that may eventually lead to genetically targeted dietary recommendations in the era of personalized nutrition.
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Affiliation(s)
- Mohammad M H Abdullah
- M.M.H. Abdullah, P.J.H. Jones, and P.K. Eck are with the Department of Human Nutritional Sciences and the Richardson Centre for Functional Foods and Nutraceuticals (RCFFN), University of Manitoba, Winnipeg, Manitoba, Canada. P.J.H. Jones is with the Department of Food Science, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Peter J H Jones
- M.M.H. Abdullah, P.J.H. Jones, and P.K. Eck are with the Department of Human Nutritional Sciences and the Richardson Centre for Functional Foods and Nutraceuticals (RCFFN), University of Manitoba, Winnipeg, Manitoba, Canada. P.J.H. Jones is with the Department of Food Science, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Peter K Eck
- M.M.H. Abdullah, P.J.H. Jones, and P.K. Eck are with the Department of Human Nutritional Sciences and the Richardson Centre for Functional Foods and Nutraceuticals (RCFFN), University of Manitoba, Winnipeg, Manitoba, Canada. P.J.H. Jones is with the Department of Food Science, University of Manitoba, Winnipeg, Manitoba, Canada.
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Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach. Am J Hum Genet 2015; 96:740-52. [PMID: 25892113 DOI: 10.1016/j.ajhg.2015.03.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2014] [Accepted: 03/10/2015] [Indexed: 01/21/2023] Open
Abstract
Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.
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Wu J, Yin RX, Guo T, Lin QZ, Shi GY, Sun JQ, Shen SW, Wang YM, Li H, Wu JZ. Association between the MARS rs6782181 polymorphism and serum lipid levels. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2015; 8:1855-1866. [PMID: 25973078 PMCID: PMC4396269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/23/2014] [Accepted: 01/28/2015] [Indexed: 06/04/2023]
Abstract
Little is known about the association between the muscle Ras (MRAS) gene rs6782181 polymorphism and serum lipid levels. The aim of the present study was to investigate the association between the MRAS rs6782181 polymorphism and serum lipid levels in the Mulao and Han populations. A total of 632 subjects of Han and 629 unrelated subjects of Mulao nationalities were randomly selected from our previous stratified randomized samples. Genotypes of the MARS rs6782181 polymorphism were determined via polymerase chain reaction and restriction fragment length polymorphism. The subjects with GG genotype had higher serum total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein (Apo) B levels in Han, and higher serum TC and LDL-C levels in Mulao than the subjects with AA/AG genotypes (P < 0.05-0.01). Subgroup analyses showed that the subjects with GG genotype had higher TC, TG, high-density lipoprotein cholesterol (HDL-C), LDL-C, ApoAI and ApoB in Han males, lower ApoAI and the ratio of ApoAI to ApoB in Han females; and higher LDL-C levels in Mulao males but not in Mulao females than the subjects with AG/AA genotypes. The association of the MARS rs6782181 polymorphism and serum lipid levels is different between the Mulao and Han populations, or between males and females in the both ethnic groups. There may be an ethnic- and/or sex-specific association between the MRAS rs6782181 polymorphism and serum lipid levels in our study populations.
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Affiliation(s)
- Jian Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Rui-Xing Yin
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Tao Guo
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Quan-Zhen Lin
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Guang-Yuan Shi
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Jia-Qi Sun
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Shao-Wen Shen
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Yi-Ming Wang
- Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
| | - Hui Li
- Clinical Laboratory of The Affiliated Cancer Hospital, Guangxi Medical UniversityNanning 530021, People’s Republic of China
| | - Jin-Zhen Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University22 Shuangyong Road, Nanning 530021, Guangxi, People’s Republic of China
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Li YR, Keating BJ. Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations. Genome Med 2014; 6:91. [PMID: 25473427 PMCID: PMC4254423 DOI: 10.1186/s13073-014-0091-5] [Citation(s) in RCA: 124] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Genome-wide association studies (GWASs) are the method most often used by geneticists to interrogate the human genome, and they provide a cost-effective way to identify the genetic variants underpinning complex traits and diseases. Most initial GWASs have focused on genetically homogeneous cohorts from European populations given the limited availability of ethnic minority samples and so as to limit population stratification effects. Transethnic studies have been invaluable in explaining the heritability of common quantitative traits, such as height, and in examining the genetic architecture of complex diseases, such as type 2 diabetes. They provide an opportunity for large-scale signal replication in independent populations and for cross-population meta-analyses to boost statistical power. In addition, transethnic GWASs enable prioritization of candidate genes, fine-mapping of functional variants, and potentially identification of SNPs associated with disease risk in admixed populations, by taking advantage of natural differences in genomic linkage disequilibrium across ethnically diverse populations. Recent efforts to assess the biological function of variants identified by GWAS have highlighted the need for large-scale replication, meta-analyses and fine-mapping across worldwide populations of ethnically diverse genetic ancestries. Here, we review recent advances and new approaches that are important to consider when performing, designing or interpreting transethnic GWASs, and we highlight existing challenges, such as the limited ability to handle heterogeneity in linkage disequilibrium across populations and limitations in dissecting complex architectures, such as those found in recently admixed populations.
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Affiliation(s)
- Yun R Li
- />The Center for Applied Genomics, 1,016 Abramson Building, The Children’s Hospital of Philadelphia, Philadelphia, 19104 PA USA
- />Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
| | - Brendan J Keating
- />The Center for Applied Genomics, 1,016 Abramson Building, The Children’s Hospital of Philadelphia, Philadelphia, 19104 PA USA
- />Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
- />Department of Surgery, Division of Transplantation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104 PA USA
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Amerindian-specific regions under positive selection harbour new lipid variants in Latinos. Nat Commun 2014; 5:3983. [PMID: 24886709 PMCID: PMC4062071 DOI: 10.1038/ncomms4983] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2014] [Accepted: 04/29/2014] [Indexed: 12/13/2022] Open
Abstract
Dyslipidemia and obesity are especially prevalent in populations with Amerindian
backgrounds, such as Mexican–Americans, which predispose these populations to
cardiovascular disease. Here we design an approach, known as the cross-population allele
screen (CPAS), which we conduct prior to a genome-wide association study (GWAS) in 19,273
Europeans and Mexicans, in order to identify Amerindian risk genes in Mexicans. Utilizing
CPAS to restrict the GWAS input variants to only those differing in frequency between the
two populations, we identify novel Amerindian lipid genes, receptor-related orphan receptor alpha (RORA) and salt-inducible kinase
3 (SIK3), and three
loci previously unassociated with dyslipidemia or obesity. We also detect lipoprotein lipase (LPL) and apolipoprotein
A5 (APOA5)
harbouring specific Amerindian signatures of risk variants and haplotypes. Notably, we
observe that SIK3 and one novel
lipid locus underwent positive selection in Mexicans. Furthermore, after a high-fat meal,
the SIK3 risk variant carriers
display high triglyceride levels. These findings suggest that Amerindian-specific genetic
architecture leads to a higher incidence of dyslipidemia and obesity in modern Mexicans. Dyslipidemia and obesity have a high prevalence in populations with
Amerindian backgrounds, such as Mexican–Americans. Here, the authors design an approach
to identify Amerindian risk genes in Mexicans and identify five genomic loci, which include
RORA and SIK3 that may contribute to the risk of dyslipidemia and obesity in
Amerindian populations.
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Woo JG, Morrison JA, Stroop DM, Aronson Friedman L, Martin LJ. Genetic architecture of lipid traits changes over time and differs by race: Princeton Lipid Follow-up Study. J Lipid Res 2014; 55:1515-24. [PMID: 24859784 DOI: 10.1194/jlr.m049932] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Indexed: 11/20/2022] Open
Abstract
Dyslipidemia is a major risk factor for CVD. Previous studies on lipid heritability have largely focused on white populations assessed after the obesity epidemic. Given secular trends and racial differences in lipid levels, this study explored whether lipid heritability is consistent across time and between races. African American and white nuclear families had fasting lipids measured in the 1970s and 22-30 years later. Heritability was estimated, and bivariate analyses between visits were conducted by race using variance components analysis. A total of 1,454 individuals (age 14.1/40.6 for offspring/parents at baseline; 39.6/66.5 at follow-up) in 373 families (286 white, 87 African American) were included. Lipid trait heritabilities were typically stronger during the 1970s than the 2000s. At baseline, additive genetic variation for LDL was significantly lower in African Americans than whites (P = 0.015). Shared genetic contribution to lipid variability over time was significant in both whites (all P < 0.0001) and African Americans (P ≤ 0.05 for total, LDL, and HDL cholesterol). African American families demonstrated shared environmental contributions to lipid variation over time (all P ≤ 0.05). Lower heritability, lower LDL genetic variance, and durable environmental effects across the obesity epidemic in African American families suggest race-specific approaches are needed to clarify the genetic etiology of lipids.
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Affiliation(s)
- Jessica G Woo
- Divisions of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - John A Morrison
- The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Davis M Stroop
- Hematology/Oncology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | | | - Lisa J Martin
- Divisions of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
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Zhang GM, Zhu Y, Luo L, Zhang HL, Gu CY, Sun LJ, Ye DW. Prevalence of dyslipidaemia in patients with renal cell carcinoma: a case-control study in China. BJU Int 2014; 113:E75-81. [PMID: 24274674 DOI: 10.1111/bju.12581] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
OBJECTIVE To examine the prevalence of dyslipidaemia in patients with renal cell carcinoma (RCC) in a Chinese population. PATIENTS AND METHODS In all, 550 histologically confirmed RCC cases and 570 controls, matched for age and sex were included. Total cholesterol, triglyceride, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) were assessed before treatment using standard techniques. The lipid profiles were defined as 'normal', 'borderline high', 'high' and 'low' according to Chinese Guidelines on Adult Dyslipidaemia. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression in both unadjusted and adjusted models. RESULTS Abnormal LDL elevation was common in RCC cases compared with controls (P < 0.001). Results for total cholesterol, triglyceride and HDL levels between groups were insignificant. The OR for RCC for high levels of LDL (≥160 mg/dL) compared with those with a normal LDL profile was 4.675 (95% CI 1.900-11.500). After adjustment for age, gender, body mass index, smoking status, hypertension, diabetes, total cholesterol and triglyceride, the coexistence of high levels of LDL and RCC was large and statistically significant (OR 8.955, 95% CI 3.371-23.786). There was a significant coexistence of RCC for participants with high LDL levels when subgroups of cases with clear cell subtypes and advanced T stages were compared with controls. CONCLUSION Abnormal LDL elevation was prevalent in Chinese patients with RCC. The results remain to be evaluated in prospective cohorts.
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Affiliation(s)
- Gui-Ming Zhang
- Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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Coram M, Duan Q, Hoffmann T, Thornton T, Knowles J, Johnson N, Ochs-Balcom H, Donlon T, Martin L, Eaton C, Robinson J, Risch N, Zhu X, Kooperberg C, Li Y, Reiner A, Tang H. Genome-wide characterization of shared and distinct genetic components that influence blood lipid levels in ethnically diverse human populations. Am J Hum Genet 2013; 92:904-16. [PMID: 23726366 DOI: 10.1016/j.ajhg.2013.04.025] [Citation(s) in RCA: 101] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2012] [Revised: 01/18/2013] [Accepted: 04/26/2013] [Indexed: 11/26/2022] Open
Abstract
Blood lipid concentrations are heritable risk factors associated with atherosclerosis and cardiovascular diseases. Lipid traits exhibit considerable variation among populations of distinct ancestral origin as well as between individuals within a population. We performed association analyses to identify genetic loci influencing lipid concentrations in African American and Hispanic American women in the Women's Health Initiative SNP Health Association Resource. We validated one African-specific high-density lipoprotein cholesterol locus at CD36 as well as 14 known lipid loci that have been previously implicated in studies of European populations. Moreover, we demonstrate striking similarities in genetic architecture (loci influencing the trait, direction and magnitude of genetic effects, and proportions of phenotypic variation explained) of lipid traits across populations. In particular, we found that a disproportionate fraction of lipid variation in African Americans and Hispanic Americans can be attributed to genomic loci exhibiting statistical evidence of association in Europeans, even though the precise genes and variants remain unknown. At the same time, we found substantial allelic heterogeneity within shared loci, characterized both by population-specific rare variants and variants shared among multiple populations that occur at disparate frequencies. The allelic heterogeneity emphasizes the importance of including diverse populations in future genetic association studies of complex traits such as lipids; furthermore, the overlap in lipid loci across populations of diverse ancestral origin argues that additional knowledge can be gleaned from multiple populations.
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Abstract
PURPOSE OF REVIEW This review summarizes recently published large-scale efforts elucidating the genetic architecture of lipid levels. A supplemental file with all genetic loci is provided for research purposes and we performed bioinformatic analyses of the genetic variants to give an oversight of involved pathways. RECENT FINDINGS In total, 52 genes for HDL cholesterol, 42 genes for LDL cholesterol, 59 genes for total cholesterol, and 39 genes for triglycerides have been identified. Genetic overlap is present between the different traits and similar pathways are involved. Most of the SNPs that were detected in the European studies could be replicated in other ethnicities and these SNPs show the same direction of effect suggesting that the underlying genetic architecture of blood lipids is similar between ethnicities. SUMMARY Genetic studies have identified many loci associated with plasma lipids and have provided insight into the underlying mechanisms of lipid homeostasis. Future research is needed to determine whether these loci may be novel targets for lipid-lowering therapy and for reducing cardiovascular disease risk. In addition, the proportion of genetic variance explained by these lipid loci is still limited and new large-scale genetic studies are ongoing to identify additional common and rare variants associated with lipid levels.
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Affiliation(s)
- Folkert W. Asselbergs
- Division of Heart and Lungs, Department of Cardiology
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht
- Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
| | - Ruth C. Lovering
- Centre for Cardiovascular Genetics, BHF Laboratories, Institute of Cardiovascular Sciences, University College London, London, UK
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, BHF Laboratories, Institute of Cardiovascular Sciences, University College London, London, UK
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Huang KK, Yin RX, Zeng XN, Huang P, Lin QZ, Wu J, Guo T, Wang W, Yang DZ, Lin WX. Association of the rs7395662 SNP in the MADD-FOLH1 and several environmental factors with serum lipid levels in the Mulao and Han populations. Int J Med Sci 2013; 10:1537-46. [PMID: 24046529 PMCID: PMC3775112 DOI: 10.7150/ijms.6421] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2013] [Accepted: 08/12/2013] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The rs7395662 single nucleotide polymorphism (SNP) in the MADD-FOLH1 has been associated with serum lipid traits, but the results are inconsistent in different populations. The present study was undertaken to investigate the association of rs7395662 SNP and several environmental factors with serum lipid levels in the Guangxi Mulao and Han populations. METHOD A total of 721 subjects of Mulao and 727 subjects of Han Chinese were randomly selected from our previous stratified randomized samples. Genotyping of the SNP was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and confirmed by direct sequencing. RESULTS Serum apolipoprotein (Apo) B levels were higher in Mulao than in Han (P < 0.01). The allelic and genotypic frequencies in Han were different between males and females (P < 0.05 for each), but there was no difference between Mulao and Han or between Mulao males and females. The levels of low-density lipoprotein cholesterol (LDL-C) and ApoB in Mulao females were different among the genotypes (P < 0.05), the G allele carriers had higher LDL-C and ApoB levels than the G allele non-carriers. The levels of total cholesterol (TC), triglyceride (TG), LDL-C and ApoB in Han males and TC, TG and high-density lipoprotein cholesterol (HDL-C) in Han females were different among the genotypes (P < 0.05-0.01), the subjects with GG genotype in Han males had higher TC, TG, and ApoB and lower LDL-C levels than the subjects with AA or AG genotype, and the G allele carriers in Han females had lower TC and HDL-C levels than the G allele non-carriers. The levels of LDL-C and ApoB in Mulao females were correlated with the genotypes (P < 0.05 for each). The levels of HDL-C and ApoAI in Han males and HDL-C in Han females were correlated with genotypes (P < 0.05-0.001). Serum lipid parameters were also correlated with several environmental factors in both ethnic groups (P < 0.05-0.01). CONCLUSION The association of rs7395662 SNP and serum lipid levels is different between the Mulao and Han populations, and between males and females in both ethnic groups.
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Affiliation(s)
- Ke-Ke Huang
- 1. Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, 22 Shuangyong Road, Nanning 530021, Guangxi, People's Republic of China
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