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Joehanes, Roby

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Joehanes

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Roby

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Joehanes, Roby
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    DNA methylation age of blood predicts all-cause mortality in later life
    (BioMed Central, 2015) Marioni, Riccardo E; Shah, Sonia; McRae, Allan F; Chen, Brian H; Colicino, Elena; Harris, Sarah E; Gibson, Jude; Henders, Anjali K; Redmond, Paul; Cox, Simon R; Pattie, Alison; Corley, Janie; Murphy, Lee; Martin, Nicholas G; Montgomery, Grant W; Feinberg, Andrew P; Fallin, M Daniele; Multhaup, Michael L; Jaffe, Andrew E; Joehanes, Roby; Schwartz, Joel; Just, Allan C.; Lunetta, Kathryn L; Murabito, Joanne M; Starr, John M; Horvath, Steve; Baccarelli, Andrea; Levy, Daniel; Visscher, Peter M; Wray, Naomi R; Deary, Ian J
    Background: DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results: Here we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. Conclusions: DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.
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    Messenger RNA and MicroRNA transcriptomic signatures of cardiometabolic risk factors
    (BioMed Central, 2017) McManus, David D.; Rong, Jian; Huan, Tianxiao; Lacey, Sean; Tanriverdi, Kahraman; Munson, Peter J.; Larson, Martin G.; Joehanes, Roby; Murthy, Venkatesh; Shah, Ravi; Freedman, Jane E.; Levy, Daniel
    Background: Cardiometabolic (CM) risk factors are heritable and cluster in individuals. We hypothesized that CM risk factors are associated with multiple shared and unique mRNA and microRNA (miRNA) signatures. We examined associations of mRNA and miRNA levels with 6 CM traits: body mass index, HDL-cholesterol and triglycerides, fasting glucose, and systolic and diastolic blood pressures through cross-sectional analysis of 2812 Framingham Heart Study who had whole blood collection for RNA isolation for mRNA and miRNA expression studies and who consented to genetic research. We excluded participants taking medication for hypertension, dyslipidemia, or diabetes. We measured mRNA (n = 17,318; using the Affymetrix GeneChip Human Exon 1.0 ST Array) and miRNA (n = 315; using qRT-PCR) expression in whole blood. We used linear regression for mRNA analyses and a combination of linear and logistic regression for miRNA analyses. We conducted miRNA-mRNA coexpression and gene ontology enrichment analyses to explore relations between pleiotropic miRNAs, mRNA expression, and CM trait clustering. Results: We identified hundreds of significant associations between mRNAs, miRNAs, and individual CM traits. Four mRNAs (FAM13A, CSF2RB, HIST1H2AC, WNK1) were associated with all 6 CM traits (FDR < 0.001) and four miRNAs (miR-197-3p, miR-328, miR-505-5p, miR-145-5p) were associated with four CM traits (FDR < 0.05). Twelve mRNAs, including WNK1, that were coexpressed with the four most pleiotropic miRNAs, were also miRNA targets. mRNAs coexpressed with pleiotropic miRNAs were enriched for RNA metabolism (miR-505-5p), ubiquitin-dependent protein catabolism (miR-197-3p, miR-328) and chromatin assembly (miR-328). Conclusions: We identified mRNA and miRNA signatures of individual CM traits and their clustering. Implicated transcripts may play causal roles in CM risk or be downstream consequences of CM risk factors on the transcriptome. Studies are needed to establish whether or not pleiotropic circulating transcripts illuminate causal pathways for CM risk. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3533-9) contains supplementary material, which is available to authorized users.
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    Epigenome‐wide Association of DNA Methylation in Whole Blood With Bone Mineral Density
    (John Wiley and Sons Inc., 2017) Morris, John A; Tsai, Pei‐Chien; Joehanes, Roby; Zheng, Jie; Trajanoska, Katerina; Soerensen, Mette; Forgetta, Vincenzo; Castillo‐Fernandez, Juan Edgar; Frost, Morten; Spector, Tim D; Christensen, Kaare; Christiansen, Lene; Rivadeneira, Fernando; Tobias, Jonathan H; Evans, David M; Kiel, Douglas; Hsu, Yi‐Hsiang; Richards, J Brent; Bell, Jordana T
    ABSTRACT Genetic and environmental determinants of skeletal phenotypes such as bone mineral density (BMD) may converge through the epigenome, providing a tool to better understand osteoporosis pathophysiology. Because the epigenetics of BMD have been largely unexplored in humans, we performed an epigenome‐wide association study (EWAS) of BMD. We undertook a large‐scale BMD EWAS using the Infinium HumanMethylation450 array to measure site‐specific DNA methylation in up to 5515 European‐descent individuals (NDiscovery = 4614, NValidation = 901). We associated methylation at multiple cytosine‐phosphate‐guanine (CpG) sites with dual‐energy X‐ray absorptiometry (DXA)‐derived femoral neck and lumbar spine BMD. We performed sex‐combined and stratified analyses, controlling for age, weight, smoking status, estimated white blood cell proportions, and random effects for relatedness and batch effects. A 5% false‐discovery rate was used to identify CpGs associated with BMD. We identified one CpG site, cg23196985, significantly associated with femoral neck BMD in 3232 females (p = 7.9 × 10−11) and 4614 females and males (p = 3.0 × 10−8). cg23196985 was not associated with femoral neck BMD in an additional sample of 474 females (p = 0.64) and 901 males and females (p = 0.60). Lack of strong consistent association signal indicates that among the tested probes, no large‐effect epigenetic changes in whole blood associated with BMD, suggesting future epigenomic studies of musculoskeletal traits measure DNA methylation in a different tissue with extended genome coverage. © 2017 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc.
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    Integrative network analysis reveals molecular mechanisms of blood pressure regulation
    (BlackWell Publishing Ltd, 2015) Huan, Tianxiao; Meng, Qingying; Saleh, Mohamed A; Norlander, Allison E; Joehanes, Roby; Zhu, Jun; Chen, Brian H; Zhang, Bin; Johnson, Andrew D; Ying, Saixia; Courchesne, Paul; Raghavachari, Nalini; Wang, Richard; Liu, Poching; O'Donnell, Christopher J; Vasan, Ramachandran; Munson, Peter J; Madhur, Meena S; Harrison, David G; Yang, Xia; Levy, Daniel
    Genome-wide association studies (GWAS) have identified numerous loci associated with blood pressure (BP). The molecular mechanisms underlying BP regulation, however, remain unclear. We investigated BP-associated molecular mechanisms by integrating BP GWAS with whole blood mRNA expression profiles in 3,679 individuals, using network approaches. BP transcriptomic signatures at the single-gene and the coexpression network module levels were identified. Four coexpression modules were identified as potentially causal based on genetic inference because expression-related SNPs for their corresponding genes demonstrated enrichment for BP GWAS signals. Genes from the four modules were further projected onto predefined molecular interaction networks, revealing key drivers. Gene subnetworks entailing molecular interactions between key drivers and BP-related genes were uncovered. As proof-of-concept, we validated SH2B3, one of the top key drivers, using Sh2b3−/− mice. We found that a significant number of genes predicted to be regulated by SH2B3 in gene networks are perturbed in Sh2b3−/− mice, which demonstrate an exaggerated pressor response to angiotensin II infusion. Our findings may help to identify novel targets for the prevention or treatment of hypertension.
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    A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension
    (Public Library of Science, 2015) Huan, Tianxiao; Esko, Tõnu; Peters, Marjolein J.; Pilling, Luke C.; Schramm, Katharina; Schurmann, Claudia; Chen, Brian H.; Liu, Chunyu; Joehanes, Roby; Johnson, Andrew D.; Yao, Chen; Ying, Sai-xia; Courchesne, Paul; Milani, Lili; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Reinmaa, Eva; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G.; Hernandez, Dena G.; Bandinelli, Stefania; Singleton, Andrew; Melzer, David; Metspalu, Andres; Carstensen, Maren; Grallert, Harald; Herder, Christian; Meitinger, Thomas; Peters, Annette; Roden, Michael; Waldenberger, Melanie; Dörr, Marcus; Felix, Stephan B.; Zeller, Tanja; Vasan, Ramachandran; O'Donnell, Christopher J.; Munson, Peter J.; Yang, Xia; Prokisch, Holger; Völker, Uwe; van Meurs, Joyce B. J.; Ferrucci, Luigi; Levy, Daniel
    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.
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    Epigenome-wide association studies identify DNA methylation associated with kidney function
    (Nature Publishing Group UK, 2017) Chu, Audrey Y.; Tin, Adrienne; Schlosser, Pascal; Ko, Yi-An; Qiu, Chengxiang; Yao, Chen; Joehanes, Roby; Grams, Morgan E.; Liang, Liming; Gluck, Caroline A.; Liu, Chunyu; Coresh, Josef; Hwang, Shih-Jen; Levy, Daniel; Boerwinkle, Eric; Pankow, James S.; Yang, Qiong; Fornage, Myriam; Fox, Caroline S.; Susztak, Katalin; Köttgen, Anna
    Chronic kidney disease (CKD) is defined by reduced estimated glomerular filtration rate (eGFR). Previous genetic studies have implicated regulatory mechanisms contributing to CKD. Here we present epigenome-wide association studies of eGFR and CKD using whole-blood DNA methylation of 2264 ARIC Study and 2595 Framingham Heart Study participants to identify epigenetic signatures of kidney function. Of 19 CpG sites significantly associated (P < 1e-07) with eGFR/CKD and replicated, five also associate with renal fibrosis in biopsies from CKD patients and show concordant DNA methylation changes in kidney cortex. Lead CpGs at PTPN6/PHB2, ANKRD11, and TNRC18 map to active enhancers in kidney cortex. At PTPN6/PHB2 cg19942083, methylation in kidney cortex associates with lower renal PTPN6 expression, higher eGFR, and less renal fibrosis. The regions containing the 243 eGFR-associated (P < 1e-05) CpGs are significantly enriched for transcription factor binding sites of EBF1, EP300, and CEBPB (P < 5e-6). Our findings highlight kidney function associated epigenetic variation.
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    DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases
    (BioMed Central, 2016) Ligthart, Symen; Marzi, Carola; Aslibekyan, Stella; Mendelson, Michael M.; Conneely, Karen N.; Tanaka, Toshiko; Colicino, Elena; Waite, Lindsay L.; Joehanes, Roby; Guan, Weihua; Brody, Jennifer A.; Elks, Cathy; Marioni, Riccardo; Jhun, Min A.; Agha, Golareh; Bressler, Jan; Ward-Caviness, Cavin K.; Chen, Brian H.; Huan, Tianxiao; Bakulski, Kelly; Salfati, Elias L.; Fiorito, Giovanni; Wahl, Simone; Schramm, Katharina; Sha, Jin; Hernandez, Dena G.; Just, Allan C.; Smith, Jennifer A.; Sotoodehnia, Nona; Pilling, Luke C.; Pankow, James S.; Tsao, Phil S.; Liu, Chunyu; Zhao, Wei; Guarrera, Simonetta; Michopoulos, Vasiliki J.; Smith, Alicia K.; Peters, Marjolein J.; Melzer, David; Vokonas, Pantel; Fornage, Myriam; Prokisch, Holger; Bis, Joshua C.; Chu, Audrey Y.; Herder, Christian; Grallert, Harald; Yao, Chen; Shah, Sonia; McRae, Allan F.; Lin, Honghuang; Horvath, Steve; Fallin, Daniele; Hofman, Albert; Wareham, Nicholas J.; Wiggins, Kerri L.; Feinberg, Andrew P.; Starr, John M.; Visscher, Peter M.; Murabito, Joanne M.; Kardia, Sharon L. R.; Absher, Devin M.; Binder, Elisabeth B.; Singleton, Andrew B.; Bandinelli, Stefania; Peters, Annette; Waldenberger, Melanie; Matullo, Giuseppe; Schwartz, Joel; Demerath, Ellen W.; Uitterlinden, André G.; van Meurs, Joyce B. J.; Franco, Oscar H.; Chen, Yii-Der Ida; Levy, Daniel; Turner, Stephen T.; Deary, Ian J.; Ressler, Kerry; Dupuis, Josée; Ferrucci, Luigi; Ong, Ken K.; Assimes, Themistocles L.; Boerwinkle, Eric; Koenig, Wolfgang; Arnett, Donna K.; Baccarelli, Andrea; Benjamin, Emelia J.; Dehghan, Abbas
    Background: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation. Results: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10–7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10–4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10–5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10–3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10–5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants. Conclusion: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1119-5) contains supplementary material, which is available to authorized users.
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    Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach
    (Public Library of Science, 2017) Mendelson, Michael M.; Marioni, Riccardo E.; Joehanes, Roby; Liu, Chunyu; Hedman, Åsa K.; Aslibekyan, Stella; Demerath, Ellen W.; Guan, Weihua; Zhi, Degui; Yao, Chen; Huan, Tianxiao; Willinger, Christine; Chen, Brian; Courchesne, Paul; Multhaup, Michael; Irvin, Marguerite R.; Cohain, Ariella; Schadt, Eric E.; Grove, Megan L.; Bressler, Jan; North, Kari; Sundström, Johan; Gustafsson, Stefan; Shah, Sonia; McRae, Allan F.; Harris, Sarah E.; Gibson, Jude; Redmond, Paul; Corley, Janie; Murphy, Lee; Starr, John M.; Kleinbrink, Erica; Lipovich, Leonard; Visscher, Peter M.; Wray, Naomi R.; Krauss, Ronald M.; Fallin, Daniele; Feinberg, Andrew; Absher, Devin M.; Fornage, Myriam; Pankow, James S.; Lind, Lars; Fox, Caroline; Ingelsson, Erik; Arnett, Donna K.; Boerwinkle, Eric; Liang, Liming; Levy, Daniel; Deary, Ian J.
    Background: The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain. Methods and Findings: We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination. Conclusions: We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.
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    Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies
    (BioMed Central, 2017) Joehanes, Roby; Zhang, Xiaoling; Huan, Tianxiao; Yao, Chen; Ying, Sai-xia; Nguyen, Quang Tri; Demirkale, Cumhur Yusuf; Feolo, Michael L.; Sharopova, Nataliya R.; Sturcke, Anne; Schäffer, Alejandro A.; Heard-Costa, Nancy; Chen, Han; Liu, Po-ching; Wang, Richard; Woodhouse, Kimberly A.; Tanriverdi, Kahraman; Freedman, Jane E.; Raghavachari, Nalini; Dupuis, Josée; Johnson, Andrew D.; O’Donnell, Christopher J.; Levy, Daniel; Munson, Peter J.
    Background: Identification of single nucleotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative trait loci (eQTLs), may improve understanding of the functional role of phenotype-associated SNPs in genome-wide association studies (GWAS). The small sample sizes of some previous eQTL studies have limited their statistical power. We conducted an eQTL investigation of microarray-based gene and exon expression levels in whole blood in a cohort of 5257 individuals, exceeding the single cohort size of previous studies by more than a factor of 2. Results: We detected over 19,000 independent lead cis-eQTLs and over 6000 independent lead trans-eQTLs, targeting over 10,000 gene targets (eGenes), with a false discovery rate (FDR) < 5%. Of previously published significant GWAS SNPs, 48% are identified to be significant eQTLs in our study. Some trans-eQTLs point toward novel mechanistic explanations for the association of the SNP with the GWAS-related phenotype. We also identify 59 distinct blocks or clusters of trans-eQTLs, each targeting the expression of sets of six to 229 distinct trans-eGenes. Ten of these sets of target genes are significantly enriched for microRNA targets (FDR < 5%). Many of these clusters are associated in GWAS with multiple phenotypes. Conclusions: These findings provide insights into the molecular regulatory patterns involved in human physiology and pathophysiology. We illustrate the value of our eQTL database in the context of a recent GWAS meta-analysis of coronary artery disease and provide a list of targeted eGenes for 21 of 58 GWAS loci. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1142-6) contains supplementary material, which is available to authorized users.
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    Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies
    (Lippincott Williams & Wilkins, 2017) Hedman, Åsa K.; Mendelson, Michael; Marioni, Riccardo E.; Gustafsson, Stefan; Joehanes, Roby; Irvin, Marguerite R.; Zhi, Degui; Sandling, Johanna K.; Yao, Chen; Liu, Chunyu; Liang, Liming; Huan, Tianxiao; McRae, Allan F.; Demissie, Serkalem; Shah, Sonia; Starr, John M.; Cupples, L. Adrienne; Deloukas, Panos; Spector, Timothy D.; Sundström, Johan; Krauss, Ronald M.; Arnett, Donna K.; Deary, Ian J.; Lind, Lars; Levy, Daniel; Ingelsson, Erik
    Background— Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications. Methods and Results— To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine–guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15–1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (PTC=0.004, PHDL-C=0.008 and Ptriglycerides=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol–related differentially methylated locus. Conclusions— We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol transport in blood in relation to occurrence of cardiovascular disease events.