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Shen J, Xie E, Shen S, Song Z, Li X, Wang F, Min J. Essentiality of SLC7A11-mediated nonessential amino acids in MASLD. Sci Bull (Beijing) 2024:S2095-9273(24)00669-8. [PMID: 39366830 DOI: 10.1016/j.scib.2024.09.019] [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: 04/14/2024] [Revised: 06/27/2024] [Accepted: 09/13/2024] [Indexed: 10/06/2024]
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) remains a rapidly growing global health burden. Here, we report that the nonessential amino acid (NEAA) transporter SLC7A11 plays a key role in MASLD. In patients with MASLD, we found high expression levels of SLC7A11 that were correlated directly with clinical grade. Using both loss-of-function and gain-of-function genetic models, we found that Slc7a11 deficiency accelerated MASLD progression via classic cystine/cysteine deficiency-induced ferroptosis, while serine deficiency and a resulting impairment in de novo cysteine production were attributed to ferroptosis-induced MASLD progression in mice overexpressing hepatic Slc7a11. Consistent with these findings, we found that both serine supplementation and blocking ferroptosis significantly alleviated MASLD, and the serum serine/glutamate ratio was significantly lower in these preclinical disease models, suggesting that it might serve as a prognostic biomarker for MASLD in patients. These findings indicate that defects in NEAA metabolism are involved in the progression of MASLD and that serine deficiency-triggered ferroptosis may provide a therapeutic target for its treatment.
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Affiliation(s)
- Jie Shen
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Enjun Xie
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China; The Second Affiliated Hospital, School of Public Health, State Key Laboratory of Experimental Hematology, Zhejiang University School of Medicine, Hangzhou 310058, China; School of Public Health, School of Basic Medical Sciences, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China; School of Public Health, School of Basic Medical Sciences, The First Affiliated Hospital, Xinxiang Medical University, Xinxiang 453003, China
| | - Shuying Shen
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Xiaopeng Li
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Fudi Wang
- The Second Affiliated Hospital, School of Public Health, State Key Laboratory of Experimental Hematology, Zhejiang University School of Medicine, Hangzhou 310058, China; School of Public Health, School of Basic Medical Sciences, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China; School of Public Health, School of Basic Medical Sciences, The First Affiliated Hospital, Xinxiang Medical University, Xinxiang 453003, China.
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, Zhejiang University School of Medicine, Hangzhou 310058, China.
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da Silva Rodrigues Marçal E, Borges JB, Bastos GM, Crespo Hirata TD, de Oliveira VF, Gonçalves RM, Faludi AA, Dias França JI, de Oliveira Silva DV, Malaquias VB, Luchessi AD, Silbiger VN, Nakazone MA, Carmo TS, Silva Souza DR, Sampaio MF, Crespo Hirata RD, Hirata MH. Methylation status of LDLR, PCSK9 and LDLRAP1 is associated with cardiovascular events in familial hypercholesterolemia. Epigenomics 2024; 16:809-820. [PMID: 38884343 PMCID: PMC11370914 DOI: 10.1080/17501911.2024.2351792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 04/27/2024] [Indexed: 06/18/2024] Open
Abstract
Aim: Methylation of LDLR, PCSK9 and LDLRAP1 CpG sites was assessed in patients with familial hypercholesterolemia (FH). Methods: DNA methylation of was analyzed by pyrosequencing in 131 FH patients and 23 normolipidemic (NL) subjects.Results: LDLR, PCSK9 and LDLRP1 methylation was similar between FH patients positive (MD) and negative (non-MD) for pathogenic variants in FH-related genes. LDLR and PCSK9 methylation was higher in MD and non-MD groups than NL subjects (p < 0.05). LDLR, PCSK9 and LDLRAP1 methylation profiles were associated with clinical manifestations and cardiovascular events in FH patients (p < 0.05).Conclusion: Differential methylation of LDLR, PCSK9 and LDLRAP1 is associated with hypercholesterolemia and cardiovascular events. This methylation profile maybe useful as a biomarker and contribute to the management of FH.
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Affiliation(s)
- Elisangela da Silva Rodrigues Marçal
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
- Laboratory of Molecular Research in Cardiology, Institute of Cardiology Dante Pazzanese, Sao Paulo, 04012-909, Brazil
| | - Jéssica Bassani Borges
- Department of Research, Hospital Beneficiencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Gisele Medeiros Bastos
- Department of Research, Hospital Beneficiencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Thiago Dominguez Crespo Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Victor Fernandes de Oliveira
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | | | - Andre Arpad Faludi
- Medical Clinic Division, Institute of Cardiology Dante Pazzanese, Sao Paulo, 04012-909, Brazil
| | - João Italo Dias França
- Center for Clinical Trials & Pharmacovigilance, Butantan Institute, Sao Paulo, 05585-000, Brazil
| | - Daiana Vitor de Oliveira Silva
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Vanessa Barbosa Malaquias
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Andre Ducati Luchessi
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
- Graduate Program in Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
| | - Vivian Nogueira Silbiger
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
- Graduate Program in Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
| | - Marcelo Arruda Nakazone
- Department of Cardiology & Cardiovascular Surgery, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Tayanne Silva Carmo
- Department of Biochemistry & Molecular Biology, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Dorotéia Rossi Silva Souza
- Department of Biochemistry & Molecular Biology, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Marcelo Ferraz Sampaio
- Department of Cardiology, Hospital Beneficencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Rosario Dominguez Crespo Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Mario Hiroyuki Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
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3
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Lee HS, Kim B, Park T. Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population. Clin Epigenetics 2024; 16:60. [PMID: 38685121 PMCID: PMC11059751 DOI: 10.1186/s13148-024-01671-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/13/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status. RESULTS We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS. CONCLUSIONS This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.
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Affiliation(s)
- Ho-Sun Lee
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea.
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea
| | - Taesung Park
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea
- Department of Statistics, Seoul National University, Seoul, 08826, Korea
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4
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Li Z, Wang W, Li W, Duan H, Xu C, Tian X, Ning F, Zhang D. Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins. Hum Mol Genet 2024; 33:583-593. [PMID: 38142287 DOI: 10.1093/hmg/ddad207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/29/2023] [Accepted: 12/05/2023] [Indexed: 12/25/2023] Open
Abstract
To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.
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Affiliation(s)
- Zhaoying Li
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
| | - Weilong Li
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, J.B. Winsløws Vej 9 B, st. tv. Odense C DK-5000, Denmark
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Feng Ning
- Qingdao Municipal Center for Disease Control and Prevention, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
- Qingdao Institute of Preventive Medicine, No. 175 Shandong Road, Qingdao 266000, Shandong Province, People's Republic of China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, The College of Public Health of Qingdao University, No. 308 Ning Xia Street, Qingdao 266071, Shandong Province, People's Republic of China
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Nie X, Mu G, Guo Y, Yang S, Wang X, Ye Z, Tan Q, Wang M, Zhou M, Ma J, Chen W. Associations of selenium exposure with blood lipids: Exploring mediating DNA methylation sites in general Chinese urban non-smokers. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161815. [PMID: 36708841 DOI: 10.1016/j.scitotenv.2023.161815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/17/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Selenium (Se) is widely distributed in the total environment and people are commonly exposed to Se, while the potential effects and mechanisms of Se exposure on blood lipids have not been well established. This study aimed to assess the associations of urinary Se (SeU) with blood lipids and explore the potential mediating DNA methylation sites. We included 2844 non-smoke participants from the second follow-up (2017-2018) of the Wuhan-Zhuhai cohort (WHZH) in this study. SeU and blood lipids [i.e., total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL)] for all participants were determined. The associations of SeU with blood lipids were analyzed by generalized linear models. Then, we conducted the blood lipids related epigenome-wide association studies (EWAS) among 221 never smokers, and the mediation analysis was conducted to explore the potential mediating cytosine-phosphoguanine (CpG) sites in the above associations. In this study, the SeU concentration of the participants in this study was 1.40 (0.94, 2.08) μg/mmol Cr. The SeU was positively associated with TC and LDL, and not associated with TG and HDL. We found 131, 3, and 1 new CpG sites related to TC, HDL, and LDL, respectively. Mediation analyses found that the methylation of cg06964030 (within MIR1306) and cg15824094 (within PLCH2) significantly mediated the positive association between SeU and TC. In conclusion, high levels of Se exposure were associated with increased TC and LDL among non-smokers, and the methylation of MIR1306 and PLCH2 partly mediated Se-associated TC increase. These findings provide new insights into the effects and mechanisms of Se exposure on lipids metabolism and highlight the importance of controlling Se exposure and intake for preventing high blood lipids.
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Affiliation(s)
- Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xing Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Mengyi Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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6
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Cheng Y, Gadd DA, Gieger C, Monterrubio-Gómez K, Zhang Y, Berta I, Stam MJ, Szlachetka N, Lobzaev E, Wrobel N, Murphy L, Campbell A, Nangle C, Walker RM, Fawns-Ritchie C, Peters A, Rathmann W, Porteous DJ, Evans KL, McIntosh AM, Cannings TI, Waldenberger M, Ganna A, McCartney DL, Vallejos CA, Marioni RE. Development and validation of DNA methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes. NATURE AGING 2023; 3:450-458. [PMID: 37117793 DOI: 10.1038/s43587-023-00391-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/27/2023] [Indexed: 04/30/2023]
Abstract
Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of cytosine-guanine pairs one-at-a-time and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set ncases = 374, ncontrols = 9,461; test set ncases = 252, ncontrols = 4,526) our best-performing model (area under the receiver operating characteristic curve (AUC) = 0.872, area under the precision-recall curve (PRAUC) = 0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC = 0.839, precision-recall AUC = 0.227). Replication was observed in the German-based KORA study (n = 1,451, ncases = 142, P = 1.6 × 10-5).
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Affiliation(s)
- Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Karla Monterrubio-Gómez
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yufei Zhang
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Imrich Berta
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Michael J Stam
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | | | - Evgenii Lobzaev
- School of Informatics, University of Edinburgh, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Cliff Nangle
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter, Edinburgh, UK
| | - Chloe Fawns-Ritchie
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
- German Centre for Cardiovascular Research, Partner Site Munich Heart Alliance, München, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research, München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Catalina A Vallejos
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- The Alan Turing Institute, London, UK.
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
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7
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van der Linden EL, Meeks KAC, Chilunga F, Hayfron-Benjamin C, Bahendeka S, Klipstein-Grobusch K, Venema A, van den Born BJ, Agyemang C, Henneman P, Adeyemo A. Epigenome-wide association study of plasma lipids in West Africans: the RODAM study. EBioMedicine 2023; 89:104469. [PMID: 36791658 PMCID: PMC10025759 DOI: 10.1016/j.ebiom.2023.104469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
BACKGROUND DNA-methylation has been associated with plasma lipid concentration in populations of diverse ethnic backgrounds, but epigenome-wide association studies (EWAS) in West-Africans are lacking. The aim of this study was to identify DNA-methylation loci associated with plasma lipids in Ghanaians. METHODS We conducted an EWAS using Illumina 450k DNA-methylation array profiles of extracted DNA from 663 Ghanaian participants. Differentially methylated positions (DMPs) were examined for association with plasma total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, and triglycerides concentrations using linear regression models adjusted for age, sex, body mass index, diabetes mellitus, and technical covariates. Findings were replicated in independent cohorts of different ethnicities. FINDINGS We identified one significantly associated DMP with triglycerides (cg19693031 annotated to TXNIP, regression coefficient beta -0.26, false discovery rate adjusted p-value 0.001), which replicated in-silico in South African Batswana, African American, and European populations. From the top five DMPs with the lowest nominal p-values, two additional DMPs for triglycerides (CPT1A, ABCG1), two DMPs for LDL-cholesterol (EPSTI1, cg13781819), and one for TC (TXNIP) replicated. With the exception of EPSTI1, these loci are involved in lipid transport/metabolism or are known GWAS-associated loci. The top 5 DMPs per lipid trait explained 9.5% in the variance of TC, 8.3% in LDL-cholesterol, 6.1% in HDL-cholesterol, and 11.0% in triglycerides. INTERPRETATION The top DMPs identified in this study are in loci that play a role in lipid metabolism across populations, including West-Africans. Future studies including larger sample size, longitudinal study design and translational research is needed to increase our understanding on the epigenetic regulation of lipid metabolism among West-African populations. FUNDING European Commission under the Framework Programme (grant number: 278901).
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Affiliation(s)
- Eva L van der Linden
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
| | - Karlijn A C Meeks
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Felix Chilunga
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Charles Hayfron-Benjamin
- Department of Physiology, University of Ghana Medical School, Accra, Ghana; Department of Anesthesia and Critical Care, Korle Bu Teaching Hospital, Accra, Ghana
| | | | - Kerstin Klipstein-Grobusch
- Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands; Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Andrea Venema
- Department of Human Genetics, Genome Diagnostics Laboratory Amsterdam, Reproduction & Development, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bert-Jan van den Born
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Peter Henneman
- Department of Human Genetics, Genome Diagnostics Laboratory Amsterdam, Reproduction & Development, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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8
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Zhang X, Ammous F, Lin L, Ratliff SM, Ware EB, Faul JD, Zhao W, Kardia SLR, Smith JA. The Interplay of Epigenetic, Genetic, and Traditional Risk Factors on Blood Pressure: Findings from the Health and Retirement Study. Genes (Basel) 2022; 13:1959. [PMID: 36360196 PMCID: PMC9689874 DOI: 10.3390/genes13111959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/11/2022] [Accepted: 10/19/2022] [Indexed: 01/21/2023] Open
Abstract
The epigenome likely interacts with traditional and genetic risk factors to influence blood pressure. We evaluated whether 13 previously reported DNA methylation sites (CpGs) are associated with systolic (SBP) or diastolic (DBP) blood pressure, both individually and aggregated into methylation risk scores (MRS), in 3070 participants (including 437 African ancestry (AA) and 2021 European ancestry (EA), mean age = 70.5 years) from the Health and Retirement Study. Nine CpGs were at least nominally associated with SBP and/or DBP after adjusting for traditional hypertension risk factors (p < 0.05). MRSSBP was positively associated with SBP in the full sample (β = 1.7 mmHg per 1 standard deviation in MRSSBP; p = 2.7 × 10-5) and in EA (β = 1.6; p = 0.001), and MRSDBP with DBP in the full sample (β = 1.1; p = 1.8 × 10-6), EA (β = 1.1; p = 7.2 × 10-5), and AA (β = 1.4; p = 0.03). The MRS and BP-genetic risk scores were independently associated with blood pressure in EA. The effects of both MRSs were weaker with increased age (pinteraction < 0.01), and the effect of MRSDBP was higher among individuals with at least some college education (pinteraction = 0.02). In AA, increasing MRSSBP was associated with higher SBP in females only (pinteraction = 0.01). Our work shows that MRS is a potential biomarker of blood pressure that may be modified by traditional hypertension risk factors.
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Affiliation(s)
- Xinman Zhang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
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9
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Wu Z, Chen L, Hong X, Si J, Cao W, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Guo Y, Chen Z, Lv J, Gao W, Li L. Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study. Clin Epigenetics 2022; 14:132. [PMID: 36274151 PMCID: PMC9588246 DOI: 10.1186/s13148-022-01356-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/13/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.
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Affiliation(s)
- Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jiahui Si
- National Institute of Health Data Science at Peking University, Peking University, Beijing, 100191, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, 266033, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, 210008, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, 150090, China
| | - Yu Guo
- Fuwai hospital Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, 100191, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China.
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10
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Liu Y, Wu Y, Jiang M. The emerging roles of PHOSPHO1 and its regulated phospholipid homeostasis in metabolic disorders. Front Physiol 2022; 13:935195. [PMID: 35957983 PMCID: PMC9360546 DOI: 10.3389/fphys.2022.935195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 07/07/2022] [Indexed: 11/25/2022] Open
Abstract
Emerging evidence suggests that phosphoethanolamine/phosphocholine phosphatase 1 (PHOSPHO1), a specific phosphoethanolamine and phosphocholine phosphatase, is involved in energy metabolism. In this review, we describe the structure and regulation of PHOSPHO1, as well as current knowledge about the role of PHOSPHO1 and its related phospholipid metabolites in regulating energy metabolism. We also examine mechanistic evidence of PHOSPHO1- and phospholipid-mediated regulation of mitochondrial and lipid droplets functions in the context of metabolic homeostasis, which could be potentially targeted for treating metabolic disorders.
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Affiliation(s)
- Yi Liu
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Yingting Wu
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Mengxi Jiang
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- *Correspondence: Mengxi Jiang,
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11
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Zheng Y, Joyce B, Hwang SJ, Ma J, Liu L, Allen N, Krefman A, Wang J, Gao T, Nannini D, Zhang H, Jacobs DR, Gross M, Fornage M, Lewis CE, Schreiner PJ, Sidney S, Chen D, Greenland P, Levy D, Hou L, Lloyd-Jones D. Association of Cardiovascular Health Through Young Adulthood With Genome-Wide DNA Methylation Patterns in Midlife: The CARDIA Study. Circulation 2022; 146:94-109. [PMID: 35652342 PMCID: PMC9348746 DOI: 10.1161/circulationaha.121.055484] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 05/04/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD. METHODS In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events. RESULTS We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05). CONCLUSIONS Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well.
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Affiliation(s)
- Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Brian Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jiantao Ma
- Tufts University Friedman School of Nutrition Science and Policy, Boston, Massachusetts, USA
| | - Lei Liu
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Norrina Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Amy Krefman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Drew Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, China
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Dongquan Chen
- Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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12
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Barouti Z, Heidari-Beni M, Shabanian-Boroujeni A, Mohammadzadeh M, Pahlevani V, Poursafa P, Mohebpour F, Kelishadi R. Effects of DNA methylation on cardiometabolic risk factors: a systematic review and meta-analysis. Arch Public Health 2022; 80:150. [PMID: 35655232 PMCID: PMC9161587 DOI: 10.1186/s13690-022-00907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 05/27/2022] [Indexed: 11/10/2022] Open
Abstract
Background Epigenetic changes, especially DNA methylation have a main role in regulating cardiometabolic disorders and their risk factors. This study provides a review of the current evidence on the association between methylation of some genes (LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3, and LEP) and cardiometabolic risk factors. Methods A systematic literature search was conducted in electronic databases including Web of Science, PubMed, EMBASE, Google Scholar and Scopus up to end of 2020. All observational human studies (cross-sectional, case–control, and cohort) were included. Studies that assessed the effect of DNA methylation on cardiometabolic risk factors were selected. Results Among 1398 articles, eight studies and twenty-one studies were included in the meta-analysis and the systematic review, respectively. Our study showed ABCG1 and LINE1 methylation were positively associated with blood pressure (Fisher’s zr = 0.07 (0.06, 0.09), 95% CI: 0.05 to 0.08). Methylation in LINE1, ABCG1, SREBF1, PHOSPHO1 and ADRB3 had no significant association with HDL levels (Fisher’s zr = − 0.05 (− 0.13, 0.03), 95% CI:-0.12 to 0.02). Positive association was existed between LINE1, ABCG1 and LEP methylation and LDL levels (Fisher’s zr = 0.13 (0.04, 0.23), 95% CI: 0.03 to 0.23). Moreover, positive association was found between HbA1C and ABCG1 methylation (Fisher’s zr = 0.11 (0.09, 0.13), 95% CI: 0.09 to 0.12). DNA methylation of LINE1, ABCG1 and SREBF1 genes had no significant association with glucose levels (Fisher’s zr = 0.01 (− 0.12, 0.14), 95% CI:-0.12 to 0.14). Conclusion This meta-analysis showed that DNA methylation was associated with some cardiometabolic risk factors including LDL-C, HbA1C, and blood pressure. Registration Registration ID of the protocol on PROSPERO is CRD42020207677.
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13
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Wang YZ, Zhao W, Ammous F, Song Y, Du J, Shang L, Ratliff SM, Moore K, Kelly KM, Needham BL, Diez Roux AV, Liu Y, Butler KR, Kardia SLR, Mukherjee B, Zhou X, Smith JA. DNA Methylation Mediates the Association Between Individual and Neighborhood Social Disadvantage and Cardiovascular Risk Factors. Front Cardiovasc Med 2022; 9:848768. [PMID: 35665255 PMCID: PMC9162507 DOI: 10.3389/fcvm.2022.848768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/29/2022] [Indexed: 12/14/2022] Open
Abstract
Low socioeconomic status (SES) and living in a disadvantaged neighborhood are associated with poor cardiovascular health. Multiple lines of evidence have linked DNA methylation to both cardiovascular risk factors and social disadvantage indicators. However, limited research has investigated the role of DNA methylation in mediating the associations of individual- and neighborhood-level disadvantage with multiple cardiovascular risk factors in large, multi-ethnic, population-based cohorts. We examined whether disadvantage at the individual level (childhood and adult SES) and neighborhood level (summary neighborhood SES as assessed by Census data and social environment as assessed by perceptions of aesthetic quality, safety, and social cohesion) were associated with 11 cardiovascular risk factors including measures of obesity, diabetes, lipids, and hypertension in 1,154 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). For significant associations, we conducted epigenome-wide mediation analysis to identify methylation sites mediating the relationship between individual/neighborhood disadvantage and cardiovascular risk factors using the JT-Comp method that assesses sparse mediation effects under a composite null hypothesis. In models adjusting for age, sex, race/ethnicity, smoking, medication use, and genetic principal components of ancestry, epigenetic mediation was detected for the associations of adult SES with body mass index (BMI), insulin, and high-density lipoprotein cholesterol (HDL-C), as well as for the association between neighborhood socioeconomic disadvantage and HDL-C at FDR q < 0.05. The 410 CpG mediators identified for the SES-BMI association were enriched for CpGs associated with gene expression (expression quantitative trait methylation loci, or eQTMs), and corresponding genes were enriched in antigen processing and presentation pathways. For cardiovascular risk factors other than BMI, most of the epigenetic mediators lost significance after controlling for BMI. However, 43 methylation sites showed evidence of mediating the neighborhood socioeconomic disadvantage and HDL-C association after BMI adjustment. The identified mediators were enriched for eQTMs, and corresponding genes were enriched in inflammatory and apoptotic pathways. Our findings support the hypothesis that DNA methylation acts as a mediator between individual- and neighborhood-level disadvantage and cardiovascular risk factors, and shed light on the potential underlying epigenetic pathways. Future studies are needed to fully elucidate the biological mechanisms that link social disadvantage to poor cardiovascular health.
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Affiliation(s)
- Yi Zhe Wang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Yanyi Song
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jiacong Du
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Kari Moore
- Urban Health Collaborative, Drexel University, Philadelphia, PA, United States
| | - Kristen M. Kelly
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Belinda L. Needham
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Ana V. Diez Roux
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Kenneth R. Butler
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, United States
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Bhramar Mukherjee
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
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14
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Mazaheri-Tehrani S, Khoshhali M, Heidari-Beni M, Poursafa P, Kelishadi R. A systematic review and metaanalysis of observational studies on the effects of epigenetic factors on serum triglycerides. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2022; 66:407-419. [PMID: 35551677 PMCID: PMC9832862 DOI: 10.20945/2359-3997000000472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 12/22/2021] [Indexed: 11/23/2022]
Abstract
Epigenetic modifications might be associated with serum triglycerides (TG) levels. This study aims to systematically review the studies on the relationship between the methylation of specific cytosine-phosphate-guanine (CpG) sites and serum TG levels. This systematic review and meta-analysis study was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. A systematic literature search was conducted in Medline database (PubMed), Scopus, and Cochrane library up to end of 2020. All observational studies (cross-sectional, case-control, and cohort) were included. Studies that assessed the effect of DNA methylation of different CpG sites of ABCG1, CPT1A, and SREBF1 genes on serum TG levels were selected. The National Institutes of Health (NIH) checklist was used to assess the quality of included articles. Among 2790 articles, ten studies were included in the quantitative analysis and fourteen studies were included in the systematic review. DNA methylation of ABCG1 gene had significant positive association with TG levels (β = 0.05, 95% CI = 0.04, 0.05, P heterogeneity < 0.001). There was significant inverse association between DNA methylation of CPT1A gene and serum TG levels (β = -0.03, 95% CI = -0.03, -0.02, P heterogeneity < 0.001). DNA methylation of SREBF1 gene was positively and significantly associated with serum TG levels (β = 0.03; 95% CI = 0.02-0.04, P heterogeneity < 0.001). DNA methylation of ABCG1 and SREBF1 genes has positive association with serum TG level, whereas this association is opposite for CPT1A gene. The role of epigenetic factors should be considered in some populations with high prevalence of hypertriglyceridemia.
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Affiliation(s)
- Sadegh Mazaheri-Tehrani
- MD student, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Khoshhali
- PhD of Biostatistics. Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Motahar Heidari-Beni
- Assistant Professor, Department of Nutrition, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non- Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran,
| | - Parnian Poursafa
- MSc Student, Department of Cellular and Molecular Biology, Faculty of Science, University of Isfahan, Isfahan, Iran
| | - Roya Kelishadi
- Professor, Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran,
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15
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Yamazaki M, Yamada H, Munetsuna E, Maeda K, Ando Y, Mizuno G, Fujii R, Tsuboi Y, Ohashi K, Ishikawa H, Hashimoto S, Hamajima N, Suzuki K. DNA methylation level of the gene encoding thioredoxin-interacting protein in peripheral blood cells is associated with metabolic syndrome in the Japanese general population. Endocr J 2022; 69:319-326. [PMID: 34645728 DOI: 10.1507/endocrj.ej21-0339] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Metabolic syndrome (MetS) is cluster of metabolic diseases, including abdominal obesity, hyperglycemia, high blood pressure, and dyslipidemia, that directly escalate the risk of type 2 diabetes, heart disease, and stroke. Thioredoxin-interacting protein (TXNIP) is a binding protein for thioredoxin, a molecule that is a key inhibitor of cellular oxidation, and thus regulates the cellular redox state. Epigenetic alteration of the TXNIP-encoding locus has been associated with components of MetS. In the present study, we sought to determine whether the level of TXNIP methylation in blood is associated with MetS in the general Japanese population. DNA was extracted from the peripheral blood cells of 37 subjects with and 392 subjects without MetS. The level of TXNIP methylation at cg19693031 was assessed by the bisulfite-pyrosequencing method. We observed that TXNIP methylation levels were lower in MetS subjects (median 74.9%, range 71.7-78.4%) than in non-MetS subjects (median 77.7%, range 74.4-80.5%; p = 0.0024). Calculation of the confounding factor-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for hypomethylation revealed that subjects with MetS exhibited significantly higher ORs for hypomethylation than did those without MetS (OR, 2.92; 95% CI, 1.33-6.62; p = 0.009). Our findings indicated that lower levels of TXNIP methylation are associated with MetS in the general Japanese population. Altered levels of DNA methylation in TXNIP at cg19693031 might play an important role in the pathogenesis of MetS.
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Affiliation(s)
- Mirai Yamazaki
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu 761-0123, Japan
| | - Hiroya Yamada
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Eiji Munetsuna
- Department of Biochemistry, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Keisuke Maeda
- Department of Clinical Physiology, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Yoshitaka Ando
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Genki Mizuno
- Department of Joint Research Laboratory of Clinical Medicine, Fujita Health University Hospital, Toyoake 470-1192, Japan
| | - Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Koji Ohashi
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Hiroaki Ishikawa
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya 466-8550, Japan
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
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16
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Miroshnikova VV, Panteleeva AA, Pobozheva IA, Razgildina ND, Polyakova EA, Markov AV, Belyaeva OD, Berkovich OA, Baranova EI, Nazarenko MS, Puzyrev VP, Pchelina SN. ABCA1 and ABCG1 DNA methylation in epicardial adipose tissue of patients with coronary artery disease. BMC Cardiovasc Disord 2021; 21:566. [PMID: 34837967 PMCID: PMC8627066 DOI: 10.1186/s12872-021-02379-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 11/10/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Recent studies have focused on the potential role of epicardial adipose tissue (EAT) in the development of coronary artery disease (CAD). ABCA1 and ABCG1 transporters regulate cell cholesterol content and reverse cholesterol transport. We aimed to determine whether DNA methylation and mRNA levels of the ABCA1 and ABCG1 genes in EAT and subcutaneous adipose tissue (SAT) were associated with CAD. METHODS Paired EAT and SAT samples were collected from 82 patients undergoing elective cardiac surgery either for coronary artery bypass grafting (CAD group, N = 66) or valve surgery (NCAD group, N = 16). ABCA1 and ABCG1 mRNA levels in EAT and SAT samples were analyzed using real time polymerase chain reaction, ABCA1 protein levels in EAT samples were assessed by western blotting. ABCA1 and ABCG1 DNA methylation analysis was performed in 24 samples from the CAD group and 9 samples from the NCAD group via pyrosequencing. RESULTS DNA methylation levels in the ABCA1 promoter and ABCG1 cg27243685 and cg06500161 CpG sites were higher in EAT samples from patients with CAD compared with NCAD (21.92% vs 10.81%, p = 0.003; 71.51% vs 68.42%, p = 0.024; 46.11% vs 37.79%, p = 0.016, respectively). In patients with CAD, ABCA1 and ABCG1 DNA methylation levels were higher in EAT than in SAT samples (p < 0.05). ABCA1 mRNA levels in EAT samples were reduced in the subgroup of patients with CAD and concomitant carotid artery disease or peripheral artery disease compared with the NCAD group (p = 0.024). ABCA1 protein levels in EAT samples tended to be lower in CAD patients than in the NCAD group (p = 0.053). DNA methylation levels at the ABCG1 cg27243685 site positively correlated with plasma triglyceride concentration (r = 0.510, p = 0.008), body mass index (r = 0.556, p = 0.013) and waist-to-hip ratio (r = 0.504, p = 0.012) in SAT samples. CONCLUSION CAD is associated with ABCA1 and ABCG1 DNA hypermethylation in EAT. CAD with concomitant carotid artery disease or peripheral artery disease is accompanied by decreased ABCA1 gene expression in EAT. DNA methylation levels at the ABCG1 cg27243685 locus in SAT are associated with hypertriglyceridemia and obesity.
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Affiliation(s)
- Valentina V Miroshnikova
- Petersburg Nuclear Physics Institute Named By B.P. Konstantinov of National Research Center "Kurchatov Institute", Gatchina, Russian Federation.
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation.
| | - Alexandra A Panteleeva
- Petersburg Nuclear Physics Institute Named By B.P. Konstantinov of National Research Center "Kurchatov Institute", Gatchina, Russian Federation
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
- National Research Centre "Kurchatov Institute", Moscow, Russia
| | - Irina A Pobozheva
- Petersburg Nuclear Physics Institute Named By B.P. Konstantinov of National Research Center "Kurchatov Institute", Gatchina, Russian Federation
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
- National Research Centre "Kurchatov Institute", Moscow, Russia
| | - Natalia D Razgildina
- Petersburg Nuclear Physics Institute Named By B.P. Konstantinov of National Research Center "Kurchatov Institute", Gatchina, Russian Federation
| | - Ekaterina A Polyakova
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
| | - Anton V Markov
- Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk, Russian Federation
| | - Olga D Belyaeva
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
| | - Olga A Berkovich
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
| | - Elena I Baranova
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
| | - Maria S Nazarenko
- Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk, Russian Federation
| | - Valery P Puzyrev
- Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk, Russian Federation
| | - Sofya N Pchelina
- Petersburg Nuclear Physics Institute Named By B.P. Konstantinov of National Research Center "Kurchatov Institute", Gatchina, Russian Federation
- Pavlov First Saint Petersburg State Medical University, St.-Petersburg, Russian Federation
- National Research Centre "Kurchatov Institute", Moscow, Russia
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17
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Hidalgo BA, Minniefield B, Patki A, Tanner R, Bagheri M, Tiwari HK, Arnett DK, Irvin MR. A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies. PLoS One 2021; 16:e0259836. [PMID: 34780523 PMCID: PMC8592434 DOI: 10.1371/journal.pone.0259836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/27/2021] [Indexed: 12/23/2022] Open
Abstract
There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.
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Affiliation(s)
- Bertha A. Hidalgo
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Bre Minniefield
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Amit Patki
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Rikki Tanner
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Minoo Bagheri
- Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Hemant K. Tiwari
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States of America
| | - Marguerite Ryan Irvin
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
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18
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Schiano C, D'Armiento M, Franzese M, Castaldo R, Saccone G, de Nigris F, Grimaldi V, Soricelli A, D'Armiento FP, Zullo F, Napoli C. DNA Methylation Profile of the SREBF2 Gene in Human Fetal Aortas. J Vasc Res 2021; 59:61-68. [PMID: 34535602 DOI: 10.1159/000518513] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 07/13/2021] [Indexed: 11/19/2022] Open
Abstract
Increasing evidence suggests that maternal cholesterol represents an important risk factor for atherosclerotic disease in offspring already during pregnancy, although the underlying mechanisms have not yet been elucidated. Eighteen human fetal aorta samples were collected from the spontaneously aborted fetuses of normal cholesterolemic and hypercholesterolemic mothers. Maternal total cholesterol levels were assessed during hospitalization. DNA methylation profiling of the whole SREBF2 gene CpG island was performed (p value <0.05). The Mann-Whitney U test was used for comparison between the 2 groups. For the first time, our study revealed that in fetal aortas obtained from hypercholesterolemic mothers, the SREBF2 gene shows 4 significant differentially hypermethylated sites in the 5'UTR-CpG island. This finding indicates that more effective long-term primary cardiovascular prevention programs need to be designed for the offspring of mothers with hypercholesterolemia. Further studies should be conducted to clarify the epigenetic mechanisms underlying the association between early atherogenesis and maternal hypercholesterolemia during pregnancy.
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Affiliation(s)
- Concetta Schiano
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli,", Naples, Italy
| | - Maria D'Armiento
- Pathology Unit, Department of Public Health, School of Medicine, University of Naples "Federico II,", Naples, Italy
| | | | | | - Gabriele Saccone
- Gynecology and Obstetrics Unit, Department of Neurosciences, Reproductive Sciences and Dentistry, School of Medicine, University of Naples "Federico II,", Naples, Italy
| | - Filomena de Nigris
- Department of Precision Medicine, University of Campania "L. Vanvitelli,", Naples, Italy
| | | | - Andrea Soricelli
- IRCCS SDN, Naples, Italy.,Department of Exercise and Wellness Sciences, University of Naples "Parthenope,", Naples, Italy
| | - Francesco Paolo D'Armiento
- Pathology Unit, Department of Public Health, School of Medicine, University of Naples "Federico II,", Naples, Italy
| | - Fulvio Zullo
- Gynecology and Obstetrics Unit, Department of Neurosciences, Reproductive Sciences and Dentistry, School of Medicine, University of Naples "Federico II,", Naples, Italy
| | - Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli,", Naples, Italy.,IRCCS SDN, Naples, Italy.,Clinical Department of Internal Medicine and Specialistic Units, Division of Clinical Immunology, Immunohematology, Transfusion Medicine and Transplant Immunology (SIMT), Regional Reference Laboratory of Transplant Immunology (LIT), Azienda Universitaria Policlinico (AOU), Naples, Italy
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19
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Jones AC, Irvin MR, Claas SA, Arnett DK. Lipid Phenotypes and DNA Methylation: a Review of the Literature. Curr Atheroscler Rep 2021; 23:71. [PMID: 34468868 DOI: 10.1007/s11883-021-00965-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Epigenetic modifications via DNA methylation have previously been linked to blood lipid levels, dyslipidemias, and atherosclerosis. The purpose of this review is to discuss current literature on the role of DNA methylation on lipid traits and their associated pathologies. RECENT FINDINGS Candidate gene and epigenome-wide approaches have identified differential methylation of genes associated with lipid traits (particularly CPT1A, ABCG1, SREBF1), and novel approaches are being implemented to further characterize these relationships. Moreover, studies on environmental factors have shown that methylation variations at lipid-related genes are associated with diet and pollution exposure. Further investigation is needed to elucidate the directionality of the associations between the environment, lipid traits, and epigenome. Future studies should also seek to increase the diversity of cohorts, as European and Asian ancestry populations are the predominant study populations in the current literature.
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Affiliation(s)
- Alana C Jones
- Medical Scientist Training Program, University of Alabama-Birmingham, Birmingham, AL, USA.,Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Steven A Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA
| | - Donna K Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA.
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20
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Suhre K, Zaghlool S. Connecting the epigenome, metabolome and proteome for a deeper understanding of disease. J Intern Med 2021; 290:527-548. [PMID: 33904619 DOI: 10.1111/joim.13306] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 12/26/2022]
Abstract
Epigenome-wide association studies (EWAS) identify genes that are dysregulated by the studied clinical endpoints, thereby indicating potential new diagnostic biomarkers, drug targets and therapy options. Combining EWAS with deep molecular phenotyping, such as approaches enabled by metabolomics and proteomics, allows further probing of the underlying disease-associated pathways. For instance, methylation of the TXNIP gene is associated robustly with prevalent type 2 diabetes and further with metabolites that are short-term markers of glycaemic control. These associations reflect TXNIP's function as a glucose uptake regulator by interaction with the major glucose transporter GLUT1 and suggest that TXNIP methylation can be used as a read-out for the organism's exposure to glucose stress. Another case is the association between DNA methylation of the AHRR and F2RL3 genes with smoking and a protein that is involved in the reprogramming of the bronchial epithelium. These examples show that associations between DNA methylation and intermediate molecular traits can open new windows into how the body copes with physiological challenges. This knowledge, if carefully interpreted, may indicate novel therapy options and, together with monitoring of the methylation state of specific methylation sites, may in the future allow the early diagnosis of impending disease. It is essential for medical practitioners to recognize the potential that this field holds in translating basic research findings to clinical practice. In this review, we present recent advances in the field of EWAS with metabolomics and proteomics and discuss both the potential and the challenges of translating epigenetic associations, with deep molecular phenotypes, to biomedical applications.
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Affiliation(s)
- K Suhre
- From the, Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.,Department of Biophysics and Physiology, Weill Cornell Medicine, New York, USA
| | - S Zaghlool
- From the, Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.,Department of Biophysics and Physiology, Weill Cornell Medicine, New York, USA
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21
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Sciarrillo CM, Koemel NA, Keirns BH, Banks NF, Rogers EM, Rosenkranz SK, Kurti SP, Jenkins NDM, Emerson SR. Who would benefit most from postprandial lipid screening? Clin Nutr 2021; 40:4762-4771. [PMID: 34242916 PMCID: PMC10198766 DOI: 10.1016/j.clnu.2021.04.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 03/22/2021] [Accepted: 04/10/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND & AIMS Individuals with fasting triglycerides (TG) <150 mg/dL can experience a deleterious postprandial TG response ≥220 mg/dL to a high-fat meal (HFM). The purpose of this study was to identify individuals based on fasting TG that would benefit most from additional postprandial screening. METHODS We conducted a secondary analysis of 7 studies from our laboratories featuring 156 disease-free participants (64 M, 92 F; age 18-70 years; BMI 18.5-30 kg/m2). Participants observed a 10-12 h overnight fast, after which they consumed an HFM (10-13 kcal/kg body mass; 61-64% kcal from fat). Two methods were used to identify lower and upper fasting TG cut points. Method 1 identified the lower limit as the TG concentration at which ≥90% of individuals presented peak postprandial TG (PPTG) <220 mg/dL and the upper limit as the concentration which ≥90% of individuals presented PPTG ≥220 mg/dL. Method 2 utilized receiver operating characteristic (ROC) curves and identified the lower limit as the fasting TG concentration where sensitivity was ≈95% and the upper limit as the concentration at which specificity was ≈95%. RESULTS In Method 1, 90% of individuals with fasting TG >130 mg/dL (>1.50 mmol/L) exhibited PPTG ≥220 mg/dL (≥2.50 mmol/L), while 100% of individuals with fasting TG <66 mg/dL (0.75 mmol/L) had PPTG that did not exceed 220 mg/dL (2.50 mmol/L). In Method 2, when sensitivity was ≈95%, the corresponding fasting TG concentration was 70 mg/dL (0.79 mmol/L). When specificity was ≈95%, the corresponding fasting TG concentration was 114 mg/dL (1.29 mmol/L). Based on methods 1 and 2, there was a moderate positive association (r = 0.37, p < 0.004) between fasting and PPTG for individuals with fasting TG between 70 and 130 mg/dL (0.79-1.50 mmol/L), in which 24% exhibited PPTG ≥220 mg/dL (≥2.50 mmol/L) while 76% did not. CONCLUSIONS Postprandial TG testing is likely most useful for individuals with fasting TG concentrations between 70 and 130 mg/dL (0.79-1.50 mmol/L). Outside of this range, postprandial TG responses are largely predictable. Establishing a specific patient group for which postprandial TG testing is most useful may lead to earlier risk detection in these individuals.
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Affiliation(s)
| | - Nicholas A Koemel
- Department of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Boden Collaboration for Obesity, Nutrition, Exercise, and Eating Disorders, University of Sydney, Sydney, Australia; Sydney Medical School, The University of Sydney, Sydney, NSW, Australia
| | - Bryant H Keirns
- Department of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA
| | - Nile F Banks
- Department of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA
| | - Emily M Rogers
- Department of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA
| | - Sara K Rosenkranz
- Department of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA
| | - Stephanie P Kurti
- Department of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA; Department of Kinesiology, James Madison University, Harrisonburg, VA, USA
| | - Nathaniel D M Jenkins
- Department of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA
| | - Sam R Emerson
- Department of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Department of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA
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22
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Jhun MA, Mendelson M, Wilson R, Gondalia R, Joehanes R, Salfati E, Zhao X, Braun KVE, Do AN, Hedman ÅK, Zhang T, Carnero-Montoro E, Shen J, Bartz TM, Brody JA, Montasser ME, O'Connell JR, Yao C, Xia R, Boerwinkle E, Grove M, Guan W, Liliane P, Singmann P, Müller-Nurasyid M, Meitinger T, Gieger C, Peters A, Zhao W, Ware EB, Smith JA, Dhana K, van Meurs J, Uitterlinden A, Ikram MA, Ghanbari M, Zhi D, Gustafsson S, Lind L, Li S, Sun D, Spector TD, Chen YDI, Damcott C, Shuldiner AR, Absher DM, Horvath S, Tsao PS, Kardia S, Psaty BM, Sotoodehnia N, Bell JT, Ingelsson E, Chen W, Dehghan A, Arnett DK, Waldenberger M, Hou L, Whitsel EA, Baccarelli A, Levy D, Fornage M, Irvin MR, Assimes TL. A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids. Nat Commun 2021; 12:3987. [PMID: 34183656 PMCID: PMC8238961 DOI: 10.1038/s41467-021-23899-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 05/25/2021] [Indexed: 02/06/2023] Open
Abstract
Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.
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Affiliation(s)
- Min-A Jhun
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
| | - Michael Mendelson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Rahul Gondalia
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Roby Joehanes
- Hebrew SeniorLife, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoping Zhao
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Anh Nguyet Do
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Åsa K Hedman
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Elena Carnero-Montoro
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
- GENYO, Center for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, Granada, Spain
| | - Jincheng Shen
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Chen Yao
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rui Xia
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Megan Grove
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Pfeiffer Liliane
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Paula Singmann
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Thomas Meitinger
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Wei Zhao
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Erin B Ware
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Klodian Dhana
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Joyce van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Andre Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Deugi Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Shengxu Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Dianjianyi Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Yii-der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Coleen Damcott
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Devin M Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine, and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Biostatistics and Epidemiology, MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Donna K Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Myriam Fornage
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- VA Palo Alto Healthcare System, Palo Alto, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
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23
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Gadd DA, Stevenson AJ, Hillary RF, McCartney DL, Wrobel N, McCafferty S, Murphy L, Russ TC, Harris SE, Redmond P, Taylor AM, Smith C, Rose J, Millar T, Spires-Jones TL, Cox SR, Marioni RE. Epigenetic predictors of lifestyle traits applied to the blood and brain. Brain Commun 2021; 3:fcab082. [PMID: 34041477 PMCID: PMC8134833 DOI: 10.1093/braincomms/fcab082] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/02/2021] [Accepted: 03/04/2021] [Indexed: 11/14/2022] Open
Abstract
Modifiable lifestyle factors influence the risk of developing many neurological diseases. These factors have been extensively linked with blood-based genome-wide DNA methylation, but it is unclear if the signatures from blood translate to the target tissue of interest-the brain. To investigate this, we apply blood-derived epigenetic predictors of four lifestyle traits to genome-wide DNA methylation from five post-mortem brain regions and the last blood sample prior to death in 14 individuals in the Lothian Birth Cohort 1936. Using these matched samples, we found that correlations between blood and brain DNA methylation scores for smoking, high-density lipoprotein cholesterol, alcohol and body mass index were highly variable across brain regions. Smoking scores in the dorsolateral prefrontal cortex had the strongest correlations with smoking scores in blood (r = 0.5, n = 14, P = 0.07) and smoking behaviour (r = 0.56, n = 9, P = 0.12). This was also the brain region which exhibited the largest correlations for DNA methylation at site cg05575921 - the single strongest correlate of smoking in blood-in relation to blood (r = 0.61, n = 14, P = 0.02) and smoking behaviour (r = -0.65, n = 9, P = 0.06). This suggested a particular vulnerability to smoking-related differential methylation in this region. Our work contributes to understanding how lifestyle factors affect the brain and suggest that lifestyle-related DNA methylation is likely to be both brain region dependent and in many cases poorly proxied for by blood. Though these pilot data provide a rarely-available opportunity for the comparison of methylation patterns across multiple brain regions and the blood, due to the limited sample size available our results must be considered as preliminary and should therefore be used as a basis for further investigation.
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Affiliation(s)
- Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Sarah McCafferty
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Tom C Russ
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Paul Redmond
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Adele M Taylor
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Jamie Rose
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Tracey Millar
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Tara L Spires-Jones
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
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24
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Palou-Márquez G, Subirana I, Nonell L, Fernández-Sanlés A, Elosua R. DNA methylation and gene expression integration in cardiovascular disease. Clin Epigenetics 2021; 13:75. [PMID: 33836805 PMCID: PMC8034168 DOI: 10.1186/s13148-021-01064-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/29/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. RESULTS Four independent latent factors (9, 19, 21-only in women-and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. CONCLUSIONS Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.
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Affiliation(s)
- Guillermo Palou-Márquez
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Dr Aiguader 88, 08003, Barcelona, Spain
- Pompeu Fabra University (UPF), Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Isaac Subirana
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Dr Aiguader 88, 08003, Barcelona, Spain
- CIBER Epidemiology and Public Health (CIBERESP), Barcelona, Spain
| | - Lara Nonell
- MARGenomics, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Dr Aiguader 88, 08003, Barcelona, Spain
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Dr Aiguader 88, 08003, Barcelona, Spain.
- CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Spain.
- Medicine Department, Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain.
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25
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Lent S, Cardenas A, Rifas-Shiman SL, Perron P, Bouchard L, Liu CT, Hivert MF, Dupuis J. Detecting differentially methylated regions with multiple distinct associations. Epigenomics 2021; 13:451-464. [PMID: 33641349 DOI: 10.2217/epi-2020-0344] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Aim: We evaluated five methods for detecting differentially methylated regions (DMRs): DMRcate, comb-p, seqlm, GlobalP and dmrff. Materials & methods: We used a simulation study and real data analysis to evaluate performance. Additionally, we evaluated the use of an ancestry-matched reference cohort to estimate correlations between CpG sites in cord blood. Results: Several methods had inflated Type I error, which increased at more stringent significant levels. In power simulations with 1-2 causal CpG sites with the same direction of effect, dmrff was consistently among the most powerful methods. Conclusion: This study illustrates the need for more thorough simulation studies when evaluating novel methods. More work must be done to develop methods with well-controlled Type I error that do not require individual-level data.
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Affiliation(s)
- Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, 94704, USA
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School & Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Patrice Perron
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada
| | - Luigi Bouchard
- Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Department of Biochemistry & Functional Genomics, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean, Hôpital de Chicoutimi, Saguenay, QC, G7H 5H6, Canada
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School & Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA.,Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Diabetes Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
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26
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Domingues A, Jolibois J, Marquet de Rougé P, Nivet-Antoine V. The Emerging Role of TXNIP in Ischemic and Cardiovascular Diseases; A Novel Marker and Therapeutic Target. Int J Mol Sci 2021; 22:ijms22041693. [PMID: 33567593 PMCID: PMC7914816 DOI: 10.3390/ijms22041693] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/03/2021] [Accepted: 02/04/2021] [Indexed: 12/17/2022] Open
Abstract
Thioredoxin interacting protein (TXNIP) is a metabolism- oxidative- and inflammation-related marker induced in cardiovascular diseases and is believed to represent a possible link between metabolism and cellular redox status. TXNIP is a potential biomarker in cardiovascular and ischemic diseases but also a novel identified target for preventive and curative medicine. The goal of this review is to focus on the novelties concerning TXNIP. After an overview in TXNIP involvement in oxidative stress, inflammation and metabolism, the remainder of this review presents the clues used to define TXNIP as a new marker at the genetic, blood, or ischemic site level in the context of cardiovascular and ischemic diseases.
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Affiliation(s)
- Alison Domingues
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Julia Jolibois
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Perrine Marquet de Rougé
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Valérie Nivet-Antoine
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
- Clinical Biochemistry Department, Assistance Publique des Hôpitaux de Paris, Necker Hospital, 75015 Paris, France
- Correspondence:
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27
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Mulder RH, Neumann A, Cecil CAM, Walton E, Houtepen LC, Simpkin AJ, Rijlaarsdam J, Heijmans BT, Gaunt TR, Felix JF, Jaddoe VWV, Bakermans-Kranenburg MJ, Tiemeier H, Relton CL, van IJzendoorn MH, Suderman M. Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescence. Hum Mol Genet 2021; 30:119-134. [PMID: 33450751 PMCID: PMC8033147 DOI: 10.1093/hmg/ddaa280] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/03/2020] [Accepted: 12/23/2020] [Indexed: 12/21/2022] Open
Abstract
DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5019 blood samples collected at multiple time-points from birth to late adolescence from 2348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases, DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for non-linear change and inter-individual variation in non-linear trajectories was somewhat less common (11 and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. In contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often non-linear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.
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Affiliation(s)
- Rosa H Mulder
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
| | - Alexander Neumann
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Psychology, Institute of Psychology, Psychiatry and Neuroscience, King's College London, London, UK
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Department of Psychology, University of Bath, Bath, UK
| | - Lotte C Houtepen
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew J Simpkin
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland
| | - Jolien Rijlaarsdam
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marinus H van IJzendoorn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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28
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Gomez-Alonso MDC, Kretschmer A, Wilson R, Pfeiffer L, Karhunen V, Seppälä I, Zhang W, Mittelstraß K, Wahl S, Matias-Garcia PR, Prokisch H, Horn S, Meitinger T, Serrano-Garcia LR, Sebert S, Raitakari O, Loh M, Rathmann W, Müller-Nurasyid M, Herder C, Roden M, Hurme M, Jarvelin MR, Ala-Korpela M, Kooner JS, Peters A, Lehtimäki T, Chambers JC, Gieger C, Kettunen J, Waldenberger M. DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures. Clin Epigenetics 2021; 13:7. [PMID: 33413638 PMCID: PMC7789600 DOI: 10.1186/s13148-020-00957-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 10/22/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
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Affiliation(s)
- Monica Del C Gomez-Alonso
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Anja Kretschmer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Liliane Pfeiffer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
| | - Kirstin Mittelstraß
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Pamela R Matias-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
| | - Sacha Horn
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Luis R Serrano-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Microbiology, Technical University of Munich, Freising, Germany
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku University Hospital, Turku, Finland
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101, Mainz, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- UKMRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Mika Ala-Korpela
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- National Heart and Lung Institute, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Johannes Kettunen
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
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Walker RM, Vaher K, Bermingham ML, Morris SW, Bretherick AD, Zeng Y, Rawlik K, Amador C, Campbell A, Haley CS, Hayward C, Porteous DJ, McIntosh AM, Marioni RE, Evans KL. Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles. Genome Med 2021; 13:1. [PMID: 33397400 PMCID: PMC7784364 DOI: 10.1186/s13073-020-00808-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 11/12/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. METHODS Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer's disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. RESULTS We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10-100 ≤ P ≤ 2.44 × 10-8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10-4 ≤ P ≤ 3.01 × 10-2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. CONCLUSIONS APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.
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Affiliation(s)
- Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present Address: Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Kadi Vaher
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present Address: MRC Centre for Reproductive Health, The Queen’s Medical Research Institute, Edinburgh BioQuarter, 47 Little France Crescent, Edinburgh, EH16 4TJ UK
| | - Mairead L. Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Stewart W. Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Andrew D. Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Yanni Zeng
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Present address: Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, 74 Zhongshan 2nd Road, Guangzhou, 510080 China
| | - Konrad Rawlik
- Division of Genetics and Genomics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Roslin, UK
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
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30
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Lai CQ, Parnell LD, Smith CE, Guo T, Sayols-Baixeras S, Aslibekyan S, Tiwari HK, Irvin MR, Bender C, Fei D, Hidalgo B, Hopkins PN, Absher DM, Province MA, Elosua R, Arnett DK, Ordovas JM. Carbohydrate and fat intake associated with risk of metabolic diseases through epigenetics of CPT1A. Am J Clin Nutr 2020; 112:1200-1211. [PMID: 32930325 PMCID: PMC7657341 DOI: 10.1093/ajcn/nqaa233] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Epigenome-wide association studies identified the cg00574958 DNA methylation site at the carnitine palmitoyltransferase-1A (CPT1A) gene to be associated with reduced risk of metabolic diseases (hypertriglyceridemia, obesity, type 2 diabetes, hypertension, metabolic syndrome), but the mechanism underlying these associations is unknown. OBJECTIVES We aimed to elucidate whether carbohydrate and fat intakes modulate cg00574958 methylation and the risk of metabolic diseases. METHODS We examined associations between carbohydrate (CHO) and fat (FAT) intake, as percentages of total diet energy, and the CHO/FAT ratio with CPT1A-cg00574958, and the risk of metabolic diseases in 3 populations (Genetics of Lipid Lowering Drugs and Diet Network, n = 978; Framingham Heart Study, n = 2331; and REgistre GIroní del COR study, n = 645) while adjusting for confounding factors. To understand possible causal effects of dietary intake on the risk of metabolic diseases, we performed meta-analysis, CPT1A transcription analysis, and mediation analysis with CHO and FAT intakes as exposures and cg00574958 methylation as the mediator. RESULTS We confirmed strong associations of cg00574958 methylation with metabolic phenotypes (BMI, triglyceride, glucose) and diseases in all 3 populations. Our results showed that CHO intake and CHO/FAT ratio were positively associated with cg00574958 methylation, whereas FAT intake was negatively correlated with cg00574958 methylation. Meta-analysis further confirmed this strong correlation, with β = 58.4 ± 7.27, P = 8.98 x 10-16 for CHO intake; β = -36.4 ± 5.95, P = 9.96 x 10-10 for FAT intake; and β = 3.30 ± 0.49, P = 1.48 x 10-11 for the CHO/FAT ratio. Furthermore, CPT1A mRNA expression was negatively associated with CHO intake, and positively associated with FAT intake, and metabolic phenotypes. Mediation analysis supports the hypothesis that CHO intake induces CPT1A methylation, hence reducing the risk of metabolic diseases, whereas FAT intake inhibits CPT1A methylation, thereby increasing the risk of metabolic diseases. CONCLUSIONS Our results suggest that the proportion of total energy supplied by CHO and FAT can have a causal effect on the risk of metabolic diseases via the epigenetic status of CPT1A.Study registration at https://www.clinicaltrials.gov/: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)-NCT01023750; and the Framingham Heart Study (FHS)-NCT00005121.
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Affiliation(s)
- Chao-Qiang Lai
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Laurence D Parnell
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Caren E Smith
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Tao Guo
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain
- Molecular Epidemiology, Department of Medical Sciences, Uppsala Universitet, Uppsala, Sweden
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Carl Bender
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - David Fei
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Paul N Hopkins
- Department of Cardiovascular Genetics, University of Utah, Salt Lake City, UT, USA
| | - Devin M Absher
- Hudson Alpha Institute for Biotechnology, Huntsville, AL, USA
| | - Michael A Province
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
- IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
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31
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Suchacki KJ, Morton NM, Vary C, Huesa C, Yadav MC, Thomas BJ, Turban S, Bunger L, Ball D, Barrios-Llerena ME, Guntur AR, Khavandgar Z, Cawthorn WP, Ferron M, Karsenty G, Murshed M, Rosen CJ, MacRae VE, Millán JL, Farquharson C. PHOSPHO1 is a skeletal regulator of insulin resistance and obesity. BMC Biol 2020; 18:149. [PMID: 33092598 PMCID: PMC7584094 DOI: 10.1186/s12915-020-00880-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 09/25/2020] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND The classical functions of the skeleton encompass locomotion, protection and mineral homeostasis. However, cell-specific gene deletions in the mouse and human genetic studies have identified the skeleton as a key endocrine regulator of metabolism. The bone-specific phosphatase, Phosphatase, Orphan 1 (PHOSPHO1), which is indispensable for bone mineralisation, has been recently implicated in the regulation of energy metabolism in humans, but its role in systemic metabolism remains unclear. Here, we probe the mechanism underlying metabolic regulation by analysing Phospho1 mutant mice. RESULTS Phospho1-/- mice exhibited improved basal glucose homeostasis and resisted high-fat-diet-induced weight gain and diabetes. The metabolic protection in Phospho1-/- mice was manifested in the absence of altered levels of osteocalcin. Osteoblasts isolated from Phospho1-/- mice were enriched for genes associated with energy metabolism and diabetes; Phospho1 both directly and indirectly interacted with genes associated with glucose transport and insulin receptor signalling. Canonical thermogenesis via brown adipose tissue did not underlie the metabolic protection observed in adult Phospho1-/- mice. However, the decreased serum choline levels in Phospho1-/- mice were normalised by feeding a 2% choline rich diet resulting in a normalisation in insulin sensitivity and fat mass. CONCLUSION We show that mice lacking the bone mineralisation enzyme PHOSPHO1 exhibit improved basal glucose homeostasis and resist high-fat-diet-induced weight gain and diabetes. This study identifies PHOSPHO1 as a potential bone-derived therapeutic target for the treatment of obesity and diabetes.
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Affiliation(s)
- Karla J Suchacki
- Roslin Institute, R(D)SVS, University of Edinburgh, Edinburgh, Scotland, UK. .,Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, Scotland, UK.
| | - Nicholas M Morton
- Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, Scotland, UK
| | - Calvin Vary
- Center for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, ME, USA
| | - Carmen Huesa
- Roslin Institute, R(D)SVS, University of Edinburgh, Edinburgh, Scotland, UK.,MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, Scotland, UK
| | - Manisha C Yadav
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, USA
| | - Benjamin J Thomas
- Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, Scotland, UK
| | - Sophie Turban
- Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, Scotland, UK
| | - Lutz Bunger
- Scottish Rural College, Edinburgh, Scotland, UK
| | - Derek Ball
- Medical Sciences and Nutrition, School of Medicine, University of Aberdeen, Aberdeen, Scotland, UK
| | | | - Anyonya R Guntur
- Center for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, ME, USA
| | - Zohreh Khavandgar
- Department of Medicine and Faculty of Dentistry, McGill University, Montreal, Canada
| | - William P Cawthorn
- Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, Scotland, UK
| | - Mathieu Ferron
- Molecular Physiology Research Unit, Institut de recherches cliniques de Montréal, Montreal, Canada
| | - Gérard Karsenty
- Department of Genetics and Development, Columbia University Medical Center, New York, USA
| | - Monzur Murshed
- Department of Medicine and Faculty of Dentistry, McGill University, Montreal, Canada
| | - Clifford J Rosen
- Center for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, ME, USA
| | - Vicky E MacRae
- Roslin Institute, R(D)SVS, University of Edinburgh, Edinburgh, Scotland, UK
| | - Jose Luis Millán
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, USA
| | - Colin Farquharson
- Roslin Institute, R(D)SVS, University of Edinburgh, Edinburgh, Scotland, UK
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32
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Kho M, Zhao W, Ratliff SM, Ammous F, Mosley TH, Shang L, Kardia SLR, Zhou X, Smith JA. Epigenetic loci for blood pressure are associated with hypertensive target organ damage in older African Americans from the genetic epidemiology network of Arteriopathy (GENOA) study. BMC Med Genomics 2020; 13:131. [PMID: 32917208 PMCID: PMC7488710 DOI: 10.1186/s12920-020-00791-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 09/03/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Hypertension is a major modifiable risk factor for arteriosclerosis that can lead to target organ damage (TOD) of heart, kidneys, and peripheral arteries. A recent epigenome-wide association study for blood pressure (BP) identified 13 CpG sites, but it is not known whether DNA methylation at these sites is also associated with TOD. METHODS In 1218 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study, a cohort of hypertensive sibships, we evaluated the associations between methylation at these 13 CpG sites measured in peripheral blood leukocytes and five TOD traits assessed approximately 5 years later. RESULTS Ten significant associations were found after adjustment for age, sex, blood cell counts, time difference between CpG and TOD measurement, and 10 genetic principal components (FDR q < 0.1): two with estimated glomerular filtration rate (eGFR, cg06690548, cg10601624), six with urinary albumin-to-creatinine ratio (UACR, cg16246545, cg14476101, cg19693031, cg06690548, cg00574958, cg22304262), and two with left ventricular mass indexed to height (LVMI, cg19693031, cg00574958). All associations with eGFR and four associations with UACR remained significant after further adjustment for body mass index (BMI), smoking status, and diabetes. We also found significant interactions between cg06690548 and BMI on UACR, and between 3 CpG sites (cg19693031, cg14476101, and cg06690548) and diabetes on UACR (FDR q < 0.1). Mediation analysis showed that 4.7% to 38.1% of the relationship between two CpG sites (cg19693031 and cg00574958) and two TOD measures (UACR and LVMI) was mediated by blood pressure (Bonferroni-corrected P < 0.05). Mendelian randomization analysis suggests that methylation at two sites (cg16246545 and cg14476101) in PHGDH may causally influence UACR. CONCLUSIONS In conclusion, we found compelling evidence for associations between arteriosclerotic traits of kidney and heart and previously identified blood pressure-associated DNA methylation sites. This study may lend insight into the role of DNA methylation in pathological mechanisms underlying target organ damage from hypertension.
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Affiliation(s)
- Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Thomas H. Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS 39216 USA
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
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Stevenson AJ, McCartney DL, Hillary RF, Campbell A, Morris SW, Bermingham ML, Walker RM, Evans KL, Boutin TS, Hayward C, McRae AF, McColl BW, Spires-Jones TL, McIntosh AM, Deary IJ, Marioni RE. Characterisation of an inflammation-related epigenetic score and its association with cognitive ability. Clin Epigenetics 2020; 12:113. [PMID: 32718350 PMCID: PMC7385981 DOI: 10.1186/s13148-020-00903-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 07/09/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Chronic systemic inflammation has been associated with incident dementia, but its association with age-related cognitive decline is less clear. The acute responses of many inflammatory biomarkers mean they may provide an unreliable picture of the chronicity of inflammation. Recently, a large-scale epigenome-wide association study identified DNA methylation correlates of C-reactive protein (CRP)-a widely used acute-phase inflammatory biomarker. DNA methylation is thought to be relatively stable in the short term, marking it as a potentially useful signature of exposure. METHODS We utilise a DNA methylation-based score for CRP and investigate its trajectories with age, and associations with cognitive ability in comparison with serum CRP and a genetic CRP score in a longitudinal study of older adults (n = 889) and a large, cross-sectional cohort (n = 7028). RESULTS We identified no homogeneous trajectories of serum CRP with age across the cohorts, whereas the epigenetic CRP score was consistently found to increase with age (standardised β = 0.07 and 0.01) and to do so more rapidly in males compared to females. Additionally, the epigenetic CRP score had higher test-retest reliability compared to serum CRP, indicating its enhanced temporal stability. Higher serum CRP was not found to be associated with poorer cognitive ability (standardised β = - 0.08 and - 0.05); however, a consistent negative association was identified between cognitive ability and the epigenetic CRP score in both cohorts (standardised β = - 0.15 and - 0.08). CONCLUSIONS An epigenetic proxy of CRP may provide a more reliable signature of chronic inflammation, allowing for more accurate stratification of individuals, and thus clearer inference of associations with incident health outcomes.
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Affiliation(s)
- Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.,Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Mairead L Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Thibaud S Boutin
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Barry W McColl
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.,Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Tara L Spires-Jones
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.,Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.,Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. .,Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
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Fan J, Cai Q, Zhang D, Weinstock J, Qu X, Jiang S. PHOSPHO1 Gene DNA Methylations are Associated with a Change in HDL-C Response to Simvastatin Treatment. Curr Pharm Des 2020; 26:4944-4952. [PMID: 32693758 DOI: 10.2174/1381612826666200720234604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 06/24/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Our aim was to detect the effects of DNA methylations in the phosphoethanolamine/ phosphocholine phosphatase (PHOSPHO1) gene on the therapeutic efficacy of simvastatin. METHODS We used an extreme sampling approach by selecting 211 individuals from approximately the top and bottom 15% of adjusted lipid-lowering response residuals to simvastatin (n=104 for the high response group and n=107 for the low response group) from a total of 734 subjects with hyperlipidemia. They received a daily oral dose of 20 mg simvastatin for eight consecutive weeks. DNA methylation loci at the PHOSPHO1 gene were measured using high-throughput next-generation sequencing-based sequencing technology. Fasting serum lipids were measured at baseline and after eight weeks of simvastatin treatment. RESULTS Mean PHOSPHO1 DNA methylation had a significant negative correlation with high-density lipoprotein cholesterol (HDL-C) variation (β=-0.014, P=0.045) in the high response group. After stratifying by body mass index (BMI), the associations between the PHOSPHO1 DNA methylations and the change in HDL-C in response to simvastatin were more significant in obese subjects with a BMI of 25 kg/m2 or higher (β=-0.027, P=0.002). Mean PHOSPHO1 methylation and traditional predictors could explain up to 24.7% (adjusted R2) of the change in HDL-C response in obese patients. There was a statistically significant additive interaction term (P=0.028) between BMI and mean PHOSPHO1 methylation in the model of the change in HDL-C in response to simvastatin. CONCLUSION Our findings suggest that PHOSPHO1 DNA methylations are associated with a change in HDL-C in response to simvastatin treatment, and this association is especially dependent on the extent of patient obesity.
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Affiliation(s)
- Juanlin Fan
- School of Life Sciences, Anhui University, Hefei, China
| | - Qianru Cai
- School of Life Sciences, Anhui University, Hefei, China
| | - Di Zhang
- School of Life Sciences, Anhui University, Hefei, China
| | - Justin Weinstock
- Department of Statistics, University of Virginia, Charlottesville, VA, United States
| | - Xiaoxiao Qu
- Center for Genetics & Genomics Analysis, Genesky Biotechnologies Inc., Shanghai, China
| | - Shanqun Jiang
- School of Life Sciences, Anhui University, Hefei, China
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Ouidir M, Zeng X, Workalemahu T, Shrestha D, Grantz KL, Mendola P, Zhang C, Tekola-Ayele F. Early pregnancy dyslipidemia is associated with placental DNA methylation at loci relevant for cardiometabolic diseases. Epigenomics 2020; 12:921-934. [PMID: 32677467 PMCID: PMC7466909 DOI: 10.2217/epi-2019-0293] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
Aim: To identify placental DNA methylation changes that are associated with early pregnancy maternal dyslipidemia. Materials & methods: We analyzed placental genome-wide DNA methylation (n = 262). Genes annotating differentially methylated CpGs were evaluated for gene expression in placenta (n = 64). Results: We found 11 novel significant differentially methylated CpGs associated with high total cholesterol, low-density lipoprotein cholesterol and triglycerides, and low high-density lipoprotein cholesterol. High triglycerides were associated with decreased methylation of cg02785814 (ALX4) and decreased expression of ALX4 in placenta. Genes annotating the differentially methylated CpGs play key roles in lipid metabolism and were enriched in dyslipidemia pathways. Functional annotation found cis-methylation quantitative trait loci for genetic loci in ALX4 and EXT2. Conclusion: Our findings lend novel insights into potential placental epigenetic mechanisms linked with maternal dyslipidemia. Trial Registration: ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Xuehuo Zeng
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Katherine L. Grantz
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Pauline Mendola
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
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36
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Rong J, Xu X, Xiang Y, Yang G, Ming X, He S, Liang B, Zhang X, Zheng F. Thioredoxin-interacting protein promotes activation and inflammation of monocytes with DNA demethylation in coronary artery disease. J Cell Mol Med 2020; 24:3560-3571. [PMID: 32039564 PMCID: PMC7131938 DOI: 10.1111/jcmm.15045] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 01/13/2020] [Accepted: 01/22/2020] [Indexed: 12/19/2022] Open
Abstract
Numerous studies have demonstrated that thioredoxin‐interacting protein (TXNIP) expression of peripheral blood leucocytes is increased in coronary artery disease (CAD). However, the molecular mechanism of this phenomenon remained unclear. DNA methylation plays important roles in the regulation of gene expression. Therefore, we speculated there might be a close association between the expression of TXNIP and methylation. In this study, we found that compared with controls, DNA methylation at cg19693031 was decreased in CAD, while mRNA expressions of TXNIP and inflammatory factors, NLRP3, IL‐1β, IL‐18, were increased. Methylation at cg19693031 was negatively associated with TXNIP expression in the cohort, THP‐1 and macrophages/foam cells. Furthermore, Transwell assay and co‐cultured adhesion assay were performed to investigate functions of TXNIP on the migration of THP‐1 or the adhesion of THP‐1 on the surface of endothelial cells, respectively. Notably, overexpressed TXNIP promoted the migration and adhesion of THP‐1 cells and expressions of NLRP3, IL‐18 and IL‐1β. Oppositely, knock‐down TXNIP inhibited the migration and adhesion of THP‐1 and expressions of NLRP3, IL‐18. In conclusion, increased TXNIP expression, related to cg19693031 demethylation orientates monocytes towards an inflammatory status through the NLRP3 inflammasome pathway involved in the development of CAD.
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Affiliation(s)
- Jialing Rong
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xianqun Xu
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yang Xiang
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guohua Yang
- Demonstration Center for Experimental Basic Medicine Education of Wuhan University, Wuhan, China
| | - Xinliang Ming
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Siying He
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bin Liang
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaokang Zhang
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Fang Zheng
- Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, China
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37
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Qin X, Li J, Wu T, Wu Y, Tang X, Gao P, Li L, Wang M, Wu Y, Wang X, Chen D, Hu Y. Overall and sex-specific associations between methylation of the ABCG1 and APOE genes and ischemic stroke or other atherosclerosis-related traits in a sibling study of Chinese population. Clin Epigenetics 2019; 11:189. [PMID: 31823830 PMCID: PMC6902418 DOI: 10.1186/s13148-019-0784-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 11/21/2019] [Indexed: 12/14/2022] Open
Abstract
Background Identifying subjects with a high risk of ischemic stroke is fundamental for prevention of the disease. Both genetic and environmental risk factors contribute to ischemic stroke, but the underlying epigenetic mechanisms which mediate genetic and environmental risk effects are not fully understood. The aim of this study was to explore whether DNA methylation loci located in the ATP-binding cassette G1 (ABCG1) and apolipoprotein E (APOE) genes, both involved in the metabolism of lipids in the body, are related to ischemic stroke, using the Fangshan/Family-based Ischemic Stroke Study in China. We also tested if these CpG sites were associated with early signs of cardiovascular atherosclerosis (carotid intima–media thickness (cIMT), ankle–brachial index (ABI), and brachial–ankle pulse wave velocity (baPWV)). Results DNA methylation at the cg02494239 locus in ABCG1 was correlated with ischemic stroke after adjusting for gender, previous history of diabetes and hypertension, smoking, drinking, body mass index, and blood lipid levels (above vs below mean, OR = 2.416, 95% CI 1.024–5.700, P = 0.044; 75–100% percentile vs 0–25% percentile, OR = 4.461, 95% CI 1.226–16.225, P = 0.023). No statistically significant associations were observed for the cg06500161 site in ABCG1 and the cg14123992 site in APOE with ischemic stroke. The study detected that hypermethylation of the ABCG1 gene was significantly associated with cIMT, hypermethylation of the APOE gene was significantly related to ABI, and methylation of the APOE gene was statistically negatively correlated with baPWV. The above relationships demonstrated gender differences. Conclusions These findings suggest that epigenetic modification of ABCG1 and APOE may play a role in the pathway from disturbed blood lipid levels to the development of cardiovascular diseases. Future prospective validation of these findings is warranted.
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Affiliation(s)
- Xueying Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
| | - Jin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yiqun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xun Tang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Pei Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Lin Li
- Department of Endocrinology, The PLA Rocket Force Characteristic Medical Center, Beijing, 100085, China
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xiaowen Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Dafang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
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Sun D, Zhang T, Su S, Hao G, Chen T, Li QZ, Bazzano L, He J, Wang X, Li S, Chen W. Body Mass Index Drives Changes in DNA Methylation: A Longitudinal Study. Circ Res 2019; 125:824-833. [PMID: 31510868 DOI: 10.1161/circresaha.119.315397] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
RATIONALE Previous EWASs (Epigenome-Wide Association Studies) suggest that obesity may be the cause, not a consequence, of changes in DNA methylation (DNAm). However, longitudinal observations are lacking. OBJECTIVE To identify 5'-cytosine-phosphate-guanine-3' in DNA (CpG) sites associated with body mass index (BMI) and examine the temporal relationship between dynamic changes in DNAm and BMI in a longitudinal cohort. METHODS AND RESULTS Race-specific EWASs were performed in 995 whites and 490 blacks from the Bogalusa Heart Study. Suggestive CpG sites were further replicated in 252 whites and 228 blacks from the Georgia Stress and Heart Study. Cross-lagged panel analysis was used to examine the temporal relationship between DNAm and BMI in 439 whites and 201 blacks who were examined twice 6.2 years apart. In discovery and replication samples, 349 CpG sites (266 novel) in whites and 36 (21 novel) in blacks were identified to be robustly associated with BMI, with 8 (1 novel) CpG sites overlapping between the 2 races. Cross-lagged panel analyses showed significant unidirectional paths (PFDR <0.05) from baseline BMI to follow-up DNAm at 18 CpG sites in whites and 7 in blacks; no CpG sites showed significant paths from DNAm at baseline to BMI at follow-up. Baseline BMI was associated with a DNAm score (calculated from DNAm levels at the associated CpG sites) at follow-up (P<0.001 both in blacks and in whites). CONCLUSIONS The findings provide strong evidence that obesity is the cause, not a consequence, of changes in DNAm over time.
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Affiliation(s)
- Dianjianyi Sun
- From the Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (D.S.).,Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.).,Department of Biostatistics, School of Public Health, Shandong University, Jinan, China (T.Z.)
| | - Shaoyong Su
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Guang Hao
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Tao Chen
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Quan-Zhen Li
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Lydia Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Xiaoling Wang
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Hospitals and Clinics of Minnesota, Minneapolis (S.L.)
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
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Sayols-Baixeras S, Fernández-Sanlés A, Prats-Uribe A, Subirana I, Plusquin M, Künzli N, Marrugat J, Basagaña X, Elosua R. Association between long-term air pollution exposure and DNA methylation: The REGICOR study. ENVIRONMENTAL RESEARCH 2019; 176:108550. [PMID: 31260916 DOI: 10.1016/j.envres.2019.108550] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 06/14/2019] [Accepted: 06/18/2019] [Indexed: 05/17/2023]
Abstract
INTRODUCTION Limited evidence suggests that epigenetic mechanisms may partially mediate the adverse effects of air pollution on health. Our aims were to identify new genomic loci showing differential DNA methylation associated with long-term exposure to air pollution and to replicate loci previously identified in other studies. METHODS A two-stage epigenome-wide association study was designed: 630 individuals from the REGICOR study were included in the discovery and 454 participants of the EPIC-Italy study in the validation stage. DNA methylation was assessed using the Infinium HumanMethylation450 BeadChip. NOX, NO2, PM10, PM2.5, PMcoarse, traffic intensity and traffic load exposure were measured according to the ESCAPE protocol. A systematic review was undertaken to identify those cytosine-phosphate-guanine (CpGs) associated with air pollution in previous studies and we screened for them in the discovery study. RESULTS In the discovery stage of the epigenome-wide association study, 81 unique CpGs were associated with air pollution (p-value <10-5) but none of them were validated in the replication sample. Furthermore, we identified 15 CpGs in the systematic review showing differential methylation with a p-value fulfilling the Bonferroni criteria and 1673 CpGs fulfilling the false discovery rate criteria, all of which were related to PM2.5 or NO2. None of them was replicated in the discovery study, in which the top hits were located in an intergenic region on chromosome 1 (cg10893043, p-value = 6.79·10-5) and in the LRRC45 and PXK genes (cg05088605, p-value = 2.15·10-04; cg16560256, p-value = 2.23·10-04). CONCLUSIONS Neither new genomic loci associated with long-term air pollution were identified, nor previously identified loci were replicated. Continued efforts to test this potential association are warranted.
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Affiliation(s)
- Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; CIBER Cardiovascular Diseases (CIBERCV), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Albert Prats-Uribe
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; Preventive Medicine and Public Health Training Unit, Parc de Salut Mar-Universitat Pompeu Fabra-Agència de Salut Pública de Barcelona (UDMPiSP PSMar-UPF-ASPB), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Isaac Subirana
- CIBER Epidemiology and Public Health (CIBERESP), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Michelle Plusquin
- Department of Epidemiology and Biostatics, The School of Public Health, Imperial College London, Medical School Building, St Mary's Hospital, Norfolk Place, London, W2 1PG, United Kingdom; Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, St Mary's Campus, Imperial College, Paddington, London, W2 1PG, United Kingdom; Centre for Environmental Sciences, Hasselt University, Campus Hasselt, Martelarenlaan 42, BE3500, Hasselt, Belgium
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051, Basel, Switzerland; University of Basel, Klingelbergstrasse 61, 4056, Basel, Switzerland
| | - Jaume Marrugat
- REGICOR Research Group, IMIM (Hospital del Mar Medical Research Institute), DR Aiguader 88, 08003 Barcelona, Catalonia, Spain; CIBER Cardiovascular Diseases (CIBERCV), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Xavier Basagaña
- ISGlobal (Institute for Global Health), Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; CIBER Epidemiology and Public Health (CIBERESP), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; CIBER Cardiovascular Diseases (CIBERCV), Dr Aiguader 88, 08003 Barcelona, Catalonia, Spain; Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Carretera de Roda 70, 08500 Vic, Catalonia, Spain.
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40
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Dillon S, Staines KA, Millán JL, Farquharson C. How To Build a Bone: PHOSPHO1, Biomineralization, and Beyond. JBMR Plus 2019; 3:e10202. [PMID: 31372594 PMCID: PMC6659447 DOI: 10.1002/jbm4.10202] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 04/15/2019] [Accepted: 05/05/2019] [Indexed: 12/11/2022] Open
Abstract
Since its characterization two decades ago, the phosphatase PHOSPHO1 has been the subject of an increasing focus of research. This work has elucidated PHOSPHO1's central role in the biomineralization of bone and other hard tissues, but has also implicated the enzyme in other biological processes in health and disease. During mineralization PHOSPHO1 liberates inorganic phosphate (Pi) to be incorporated into the mineral phase through hydrolysis of its substrates phosphocholine (PCho) and phosphoethanolamine (PEA). Localization of PHOSPHO1 within matrix vesicles allows accumulation of Pi within a protected environment where mineral crystals may nucleate and subsequently invade the organic collagenous scaffold. Here, we examine the evidence for this process, first discussing the discovery and characterization of PHOSPHO1, before considering experimental evidence for its canonical role in matrix vesicle–mediated biomineralization. We also contemplate roles for PHOSPHO1 in disorders of dysregulated mineralization such as vascular calcification, along with emerging evidence of its activity in other systems including choline synthesis and homeostasis, and energy metabolism. © 2019 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Scott Dillon
- The Roslin Institute and Royal (Dick) School of Veterinary Studies University of Edinburgh, Easter Bush Midlothian UK
| | | | - José Luis Millán
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla CA USA
| | - Colin Farquharson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies University of Edinburgh, Easter Bush Midlothian UK
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41
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Krause C, Sievert H, Geißler C, Grohs M, El Gammal AT, Wolter S, Ohlei O, Kilpert F, Krämer UM, Kasten M, Klein C, Brabant GE, Mann O, Lehnert H, Kirchner H. Critical evaluation of the DNA-methylation markers ABCG1 and SREBF1 for Type 2 diabetes stratification. Epigenomics 2019; 11:885-897. [PMID: 31169416 DOI: 10.2217/epi-2018-0159] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Validation of epigenome-wide association studies is sparse. Therefore, we evaluated the methylation markers cg06500161 (ABCG1) and cg11024682 (SREBF1) as classifiers for diabetes stratification. Patients & methods: DNA methylation was measured in blood (n = 167), liver (n = 99) and visceral adipose tissue (n = 99) of nondiabetic or Type 2 diabetic subjects by bisulfite pyrosequencing. Results: DNA methylation at cg11024682 in blood and liver correlated with BMI. Methylation at cg06500161 was influenced by the adjacent SNP rs9982016. Insulin-resistant and sensitive subjects could be stratified by DNA methylation status in blood or visceral adipose tissue. Conclusion: DNA methylation at both loci in blood presents a promising approach for risk group stratification and could be valuable for personalized Type 2 diabetes risk prediction in the future.
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Affiliation(s)
- Christin Krause
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Helen Sievert
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Cathleen Geißler
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Martina Grohs
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Alexander T El Gammal
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Wolter
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Integrative & Experimental Genomics, University of Lübeck, Lübeck, Germany
| | - Fabian Kilpert
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Integrative & Experimental Genomics, University of Lübeck, Lübeck, Germany
| | - Ulrike M Krämer
- Department of Neurology, University of Lübeck, Lübeck, Germany.,Institute of Psychology II, University of Lübeck, Lübeck, Germany
| | - Meike Kasten
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany.,Department of Psychiatry & Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Georg E Brabant
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Oliver Mann
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hendrik Lehnert
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Henriette Kirchner
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
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42
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Geng X, Irvin MR, Hidalgo B, Aslibekyan S, Srinivasasainagendra V, An P, Frazier-Wood AC, Tiwari HK, Dave T, Ryan K, Ordovas JM, Straka RJ, Feitosa MF, Hopkins PN, Borecki I, Province MA, Mitchell BD, Arnett DK, Zhi D. An Exome-Wide Sequencing Study of the GOLDN Cohort Reveals Novel Associations of Coding Variants and Fasting Plasma Lipids. Front Genet 2019; 10:158. [PMID: 30863429 PMCID: PMC6399202 DOI: 10.3389/fgene.2019.00158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Accepted: 02/13/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Associations of both common and rare genetic variants with fasting blood lipids have been extensively studied. However, most of the rare coding variants associated with lipids are population-specific, and exploration of genetic data from diverse population samples may enhance the identification of novel associations with rare variants. Results: We searched for novel coding genetic variants associated with fasting lipid levels in 894 samples from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) with exome-wide sequencing-based genotype data. In single variant tests, one variant (rs11171663 in ITGA7) was associated with fasting triglyceride levels (P = 7.66E-08), explaining approximately 3.2% of the total trait variance. In gene-based tests, we found statistically significant associations between ITGA7 (P = 1.77E-07) and SLCO2A1 (P = 7.18E-07) and triglycerides, as well as between POT1 (P = 3.00E-07) and low-density lipoprotein cholesterol. In another independent replication cohort consisting of 3,183 African American samples from Hypertension Genetic Epidemiology Network (HyperGEN) and the Genetic Epidemiology Network of Arteriopathy (GENOA), the top genes achieved P-values of 0.04 (ITGA7), 0.08 (SLCO2A1), and 0.02 (POT1). In GOLDN, gene transcript levels of ITGA7 and SLCO2A1 were associated with fasting triglycerides (P = 0.07 and P = 0.02), highlighting functional relevance of our findings. Conclusion: In this study, we present preliminary evidence of novel rare variant determinants of fasting lipids, and reveal potential underlying molecular mechanisms. Moreover, these results were replicated in an independent cohort. Our findings may inform novel biomarkers of disease risk and treatment targets.
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Affiliation(s)
- Xin Geng
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.,BGI-Shenzhen, Shenzhen, China
| | - Marguerite R Irvin
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Bertha Hidalgo
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Stella Aslibekyan
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | | | - Ping An
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Hemant K Tiwari
- Department of Biostatistics, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Tushar Dave
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Kathleen Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States.,IMDEA Alimentación, Madrid, Spain.,Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Robert J Straka
- Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, United States
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Paul N Hopkins
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, United States
| | - Ingrid Borecki
- Genetic Analysis Center, Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States
| | - Degui Zhi
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.,School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
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43
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van der Linden E, Meeks K, Beune E, de-Graft Aikins A, Addo J, Owusu-Dabo E, Mockenhaupt FP, Bahendeka S, Danquah I, Schulze MB, Spranger J, Klipstein-Grobusch K, Appiah LT, Smeeth L, Agyemang C. Dyslipidaemia among Ghanaian migrants in three European countries and their compatriots in rural and urban Ghana: The RODAM study. Atherosclerosis 2019; 284:83-91. [PMID: 30875497 DOI: 10.1016/j.atherosclerosis.2019.02.030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 02/18/2019] [Accepted: 02/27/2019] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND AIMS African populations have a favourable lipid profile compared to European populations. However, the extent to which they differ between rural and urban settings in Africa and upon migration to Europe is unknown. We assessed the lipid profiles of Ghanaians living in rural- and urban-Ghana and Ghanaian migrants living in three European countries. METHODS We used data from a multi-centre, cross-sectional study among Ghanaian adults residing in rural- and urban-Ghana and London, Amsterdam and Berlin (n = 5482). Dyslipidaemias were defined using the 2012 European Guidelines on Cardiovascular Prevention. Comparisons between groups were made using age-standardised prevalence and prevalence ratios (PRs) with adjustments for important covariates. RESULTS In both sexes, the age-standardised prevalence of high total cholesterol (TC) and LDL-cholesterol (LDL-C) was lower in rural- than in urban-Ghana and Ghanaian migrants in Europe. Adjusted PRs of high TC and LDL-C were higher in urban-Ghana (TC PR = 2.15, 95%confidence interval 1.69-2.73) and Ghanaian migrant men (TC PR = 2.03 (1.56-2.63)) compared to rural-Ghana, but there was no difference between rural- and Ghanaian migrant women (TC PR = 1.01 (0.84-1.22)). High triglycerides levels were as prevalent in rural-Ghana (11.6%) as in urban-Ghana (12.8%), but were less prevalent in Ghanaian migrant women (2.0%). In both sexes, low HDL-cholesterol was most prevalent in rural-Ghana (50.1%) and least prevalent in Europe (12.9%). CONCLUSION The lipid profile varied among ethnically homogeneous African populations living in different geographical locations in Africa and Europe. Additional research is needed to identify factors driving these differential risks to assist prevention efforts.
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Affiliation(s)
- Eva van der Linden
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.
| | - Karlijn Meeks
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Erik Beune
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Ama de-Graft Aikins
- Regional Institute for Population Studies, University of Ghana, Legon, Ghana
| | - Juliet Addo
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ellis Owusu-Dabo
- School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Frank P Mockenhaupt
- Institute of Tropical Medicine and International Health, Charité Universitätsmedizin Berlin, Berlin, Germany
| | | | - Ina Danquah
- Institute for Social Medicine, Epidemiology and Health Economics, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin, Germany; Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Joachim Spranger
- Department of Endocrinology and Metabolism, Charité Universitätsmedizin Berlin, Berlin, Germany; Center for Cardiovascular Research (CCR), Charité Universitaetsmedizin Berlin, Berlin, Germany
| | - Kerstin Klipstein-Grobusch
- Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands; Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Liam Smeeth
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Charles Agyemang
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
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44
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Metabolic and Immunological Shifts during Mid-to-Late Gestation Influence Maternal Blood Methylation of CPT1A and SREBF1. Int J Mol Sci 2019; 20:ijms20051066. [PMID: 30823689 PMCID: PMC6429071 DOI: 10.3390/ijms20051066] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 02/19/2019] [Accepted: 02/25/2019] [Indexed: 01/08/2023] Open
Abstract
Mid-to-late gestation is a unique period in which women experience dynamic changes in lipid metabolism. Although the recent intensive epigenome-wide association studies (EWAS) using peripheral leukocytes have revealed that lipid-related traits alter DNA methylation, the influence of pregnancy-induced metabolic changes on the methylation levels of these differentially methylated sites is not well known. In this study, we performed a prospective cohort study of pregnant women (n = 52) using the MassARRAY EpiTYPER assay and analyzed the methylation levels of variably methylated sites, including CPT1A intron 1 and SREBF1 intron 1 CpGs, which were previously verified to be robustly associated with adiposity traits. Although methylation of SREBF1 was associated with body mass index (BMI) and low-density lipoprotein cholesterol at mid-gestation, this association was attenuated at late gestation, which was consistent with the metabolic switch from an anabolic to a catabolic state. However, the BMI association with CPT1A intron 1 methylation appeared to strengthen at late gestation; this association was mediated by pre-pregnancy BMI-dependent change in the leukocyte proportion during mid-to-late gestation. Thus, the methylation of adiposity-related differentially methylated regions was sensitive to metabolic and immunological changes during mid-to-late gestation.
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45
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He Y, Kothari V, Bornfeldt KE. High-Density Lipoprotein Function in Cardiovascular Disease and Diabetes Mellitus. Arterioscler Thromb Vasc Biol 2019; 38:e10-e16. [PMID: 29367232 DOI: 10.1161/atvbaha.117.310222] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Yi He
- From the Division of Metabolism, Endocrinology and Nutrition, Department of Medicine (Y.H., V.K., K.E.B.) and Department of Pathology (K.E.B.), University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle
| | - Vishal Kothari
- From the Division of Metabolism, Endocrinology and Nutrition, Department of Medicine (Y.H., V.K., K.E.B.) and Department of Pathology (K.E.B.), University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle
| | - Karin E Bornfeldt
- From the Division of Metabolism, Endocrinology and Nutrition, Department of Medicine (Y.H., V.K., K.E.B.) and Department of Pathology (K.E.B.), University of Washington Medicine Diabetes Institute, University of Washington School of Medicine, Seattle.
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46
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McCartney DL, Hillary RF, Stevenson AJ, Ritchie SJ, Walker RM, Zhang Q, Morris SW, Bermingham ML, Campbell A, Murray AD, Whalley HC, Gale CR, Porteous DJ, Haley CS, McRae AF, Wray NR, Visscher PM, McIntosh AM, Evans KL, Deary IJ, Marioni RE. Epigenetic prediction of complex traits and death. Genome Biol 2018; 19:136. [PMID: 30257690 PMCID: PMC6158884 DOI: 10.1186/s13059-018-1514-1] [Citation(s) in RCA: 109] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 08/22/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications. RESULTS Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios. CONCLUSIONS DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.
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Affiliation(s)
- Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Anna J. Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Stuart J. Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Qian Zhang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Stewart W. Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Mairead L. Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Alison D. Murray
- Aberdeen Biomedical Imaging Centre, Lilian Sutton Building, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD UK
| | - Heather C. Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Catharine R. Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Allan F. McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Peter M. Visscher
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD Australia
| | - Andrew M. McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - 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
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
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Sarnowski C, Lent S, Dupuis J. Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels. BMC Genet 2018; 19:83. [PMID: 30255771 PMCID: PMC6156838 DOI: 10.1186/s12863-018-0640-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Background Genome-wide association studies performed on triglycerides (TGs) have not accounted for epigenetic mechanisms that may partially explain trait heritability. Results Parent-of-origin (POO) effect association analyses using an agnostic approach or a candidate approach were performed for pretreatment TG levels, posttreatment TG levels, and pre- and posttreatment TG-level differences in the real GAW20 family data set. We detected 22 genetic variants with suggestive POO effects with at least 1 phenotype (P ≤ 10− 5). We evaluated the association of these 22 significant genetic variants showing POO effects with close DNA methylation probes associated with TGs. A total of 18 DNA methylation probes located in the vicinity of the 22 SNPs were associated with at least 1 phenotype and 6 SNP-probe pairs were associated with DNA methylation probes at the nominal level of P < 0.05, among which 1 pair presented evidence of POO effect. Our analyses identified a paternal effect of SNP rs301621 on the difference between pre- and posttreatment TG levels (P = 1.2 × 10− 5). This same SNP showed evidence for a maternal effect on methylation levels of a nearby probe (cg10206250; P = 0.01). Using a causal inference test we established that the observed POO effect of rs301621 was not mediated by DNA methylation at cg10206250. Conclusions We performed POO effect association analyses of SNPs with TGs, as well as association analyses of SNPs with DNA methylation probes. These analyses, which were followed by a causal inference test, established that the paternal effect at the SNP rs301621 is induced by treatment and is not mediated by methylation level at cg10206250.
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Affiliation(s)
- Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA.
| | - Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA, 02118, USA
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48
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Sayols-Baixeras S, Tiwari HK, Aslibekyan SW. Disentangling associations between DNA methylation and blood lipids: a Mendelian randomization approach. BMC Proc 2018; 12:23. [PMID: 30275879 PMCID: PMC6157243 DOI: 10.1186/s12919-018-0119-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND DNA methylation is an epigenetic mechanism that has been proposed as a possible link between genetic and environmental determinants of disease. Prior studies reported robust associations between the methylation of specific cytosine-phosphate-guanine (CpG) sites and plasma lipids, namely triglycerides (TGs) and high-density lipoprotein cholesterol (HDL-C). However, the causality of the observed association remains elusive, hampered by weak instrumental variables for methylation status. AIM We present a novel application of the elastic net approach to implement a bidirectional Mendelian randomization approach to inferring causal relationships between candidate CpGs and plasma lipids in GAW20 data. METHODS We used DNA methylation, TGs, and HDL-C measured during the visit 2. Based on prior findings, we selected 5 methylation markers (cg00574958, cg07504977, cg06690548, cg19693031, and cg03717755) related to TGs, 2 markers (cg09572125 and cg02650017) related to HDL-C, and 2 markers (cg06500161 and cg11024682) related to both traits. We implemented an elastic net approach to improve the selection of the genetic instrument for the methylation markers, followed by bidirectional Mendelian randomization 2-stage least-squares regression. RESULTS We observed causal effects of blood fasting TGs on the methylation levels of cg00574958 (CPT1A) and cg06690548 (SLC7A11). For cg00574958, our findings were also consistent with the reverse direction of association, that is, from CPT1A methylation to TGs. CONCLUSIONS Current evidence does not rule out either direction of association between the methylation of the cg00574958 CPT1A locus and plasma TGs, highlighting the complexity of lipid homeostasis. We also demonstrated a novel approach to improve instrument selection in DNA methylation studies.
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Affiliation(s)
- Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), 88 Dr. Aiguader Street, 08003 Barcelona, Catalonia Spain
- Universitat Pompeu Fabra (UPF), 80 Dr. Aiguader Street, 08003 Barcelona, Catalonia Spain
- CIBER Cardiovascular Diseases (CIVERCV), 88 Dr. Aiguader Street, 08003 Barcelona, Catalonia Spain
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL USA
| | - Stella W. Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL USA
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Abdalla BA, Chen J, Nie Q, Zhang X. Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model. Front Genet 2018; 9:262. [PMID: 30073018 PMCID: PMC6060281 DOI: 10.3389/fgene.2018.00262] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 06/28/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken.
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Affiliation(s)
- Bahareldin A. Abdalla
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Jie Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Qinghua Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Xiquan Zhang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
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van der Laan SW, Harshfield EL, Hemerich D, Stacey D, Wood AM, Asselbergs FW. From lipid locus to drug target through human genomics. Cardiovasc Res 2018; 114:1258-1270. [PMID: 29800275 DOI: 10.1093/cvr/cvy120] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 05/16/2018] [Indexed: 12/14/2022] Open
Abstract
In the last decade, over 175 genetic loci have robustly been associated to levels of major circulating blood lipids. Most loci are specific to one or two lipids, whereas some (SUGP1, ZPR1, TRIB1, HERPUD1, and FADS1) are associated to all. While exposing the polygenic architecture of circulating lipids and the underpinnings of dyslipidaemia, these genome-wide association studies (GWAS) have provided further evidence of the critical role that lipids play in coronary heart disease (CHD) risk, as indicated by the 2.7-fold enrichment for macrophage gene expression in atherosclerotic plaques and the association of 25 loci (such as PCSK9, APOB, ABCG5-G8, KCNK5, LPL, HMGCR, NPC1L1, CETP, TRIB1, ABO, PMAIP1-MC4R, and LDLR) with CHD. These GWAS also confirmed known and commonly used therapeutic targets, including HMGCR (statins), PCSK9 (antibodies), and NPC1L1 (ezetimibe). As we head into the post-GWAS era, we offer suggestions for how to move forward beyond genetic risk loci, towards refining the biology behind the associations and identifying causal genes and therapeutic targets. Deep phenotyping through lipidomics and metabolomics will refine and increase the resolution to find causal and druggable targets, and studies aimed at demonstrating gene transcriptional and regulatory effects of lipid associated loci will further aid in identifying these targets. Thus, we argue the need for deeply phenotyped, large genetic association studies to reduce costs and failures and increase the efficiency of the drug discovery pipeline. We conjecture that in the next decade a paradigm shift will tip the balance towards a data-driven approach to therapeutic target development and the application of precision medicine where human genomics takes centre stage.
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Affiliation(s)
- Sander W van der Laan
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Eric L Harshfield
- Department of Public Health and Primary Care, University of Cambridge, 2 Worts Causeway, Cambridge CB1 8RN, UK
- Department of Clinical Neurosciences, University of Cambridge, R3, Box 83, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Daiane Hemerich
- Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
- CAPES Foundation, Ministry of Education of Brazil, Brasília, Brazil
| | - David Stacey
- Department of Public Health and Primary Care, University of Cambridge, 2 Worts Causeway, Cambridge CB1 8RN, UK
| | - Angela M Wood
- Department of Public Health and Primary Care, University of Cambridge, 2 Worts Causeway, Cambridge CB1 8RN, UK
| | - Folkert W Asselbergs
- Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
- Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, the Netherlands
- Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London, UK
- Farr Institute of Health Informatics Research, Institute of Health Informatics, University College London, London, UK
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