Truong et al. (2017) (11 Truong V, Huang S, Dennis J, Lemire M, Zwingerman N, Aïssi D, et al. Blood triglyceride levels are associated with DNA methylation at the serine metabolism gene PHGDH. Sci Rep. 2017;7(1):11207.) |
Canada |
Cross-sectional |
Discovery set |
n = 199 (47%) |
39.6 ± 16.9 |
26.8 ± 6.1 |
1 |
Age, sex, and cell type proportions |
Positive association |
Good |
|
|
|
Replication set |
n = 324 (22%) |
44.1 ± 14.3 |
24.2 ± 4.4 |
|
|
|
|
Braun et al. (2017) (1212 Braun KVE, Dhana K, de Vries PS, Voortman T, van Meurs JBJ, Uitterlinden AG, et al. Epigenome-wide association study (EWAS) on lipids: the Rotterdam Study. Clin Epigenetics. 2017;9:15.) |
Netherland |
Cohort |
Discovery set |
n = 725 (46%) |
59.9 ± 8.2 |
27.6 ± 4.6 |
1, 7, 8, 12 |
Age, sex, current smoking, leukocyte proportions, lipid-lowering medication use, adjusted for waist circumference and other serum lipids |
Negative association for CPT1A and positive association for SREBF1 & ABCG1
|
Good |
|
|
|
Replication set |
n = 760 (42%) |
67.7 ± 5.9 |
27.8 ± 4.2 |
|
Campanella et al. (2018) (2323 Campanella G, Gunter MJ, Polidoro S, Krogh V, Palli D, Panico S, et al. Epigenome-wide association study of adiposity and future risk of obesity-related diseases. Int J Obes (Lond). 2018;42(12):2022-35.) |
USA |
Pooled analysis of Cohorts |
NA |
n = 1941 (30%) |
NA |
NA |
1, 2, 7, 12 |
Sex, age, and status such as cancers, MI, BMI & WHR |
Negative association for CPT1A and positive association for SREBF1 & ABCG1
|
Good |
Dayeh et al. (2016) (1919 Dayeh T, Tuomi T, Almgren P, Perfilyev A, Jansson PA, de Mello VD, et al. DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk. Epigenetics. 2016;11(7):482-8.) |
Finland |
Cohort |
NA |
n = 209 |
NA |
NA |
1 |
Age, gender, fasting glucose, and family relation |
Positive association |
Fair |
Pfeiffer et al. (2015) (1515 Pfeiffer L, Wahl S, Pilling LC, Reischl E, Sandling JK, Kunze S, et al. DNA methylation of lipid-related genes affects blood lipid levels. Circ Cardiovasc Genet. 2015;8(2):334-42.) |
Germany |
Cohort |
Discovery set (KORA F4 study) |
n = 1776 (49%) |
60.8 ± 8.9 |
28.2 ± 4.8 |
1, 2, 3, 7, 12, 13 |
Age, sex, BMI, smoking, alcohol, lipid-lowering drugs, physical activity, history of MI, current hypertension, HbA1c levels, C-reactive protein, and white blood cell count |
Negative association for CPT1A positive association for ABCG1 & SREBF1
|
Good |
Replication set (KORA F3 study) |
n = 499 (52%) |
52.9 ± 9.6 |
27.2 ± 4.5 |
Replication set (InCHIANTI study) |
n = 472 (45%) |
71.2 ± 16 |
27 ± 4.3 |
Guay et al. (2014) (1111 Guay SP, Brisson D, Lamarche B, Gaudet D, Bouchard L. Epipolymorphisms within lipoprotein genes contribute independently to plasma lipid levels in familial hypercholesterolemia. Epigenetics. 2014;9(5):718-29.) |
Canada |
Cross-sectional |
In women |
n = 37 |
39.6 ± 2 |
24.7 ± 0.8 |
ABCG1-CPG3 |
Age, waist circumference, and fasting blood TG |
Positive association in women but no association in men |
Fair |
In men |
n = 61 |
46.3 ± 1.7 |
27.3 ± 0.5 |
Peng et al. (2014) (1313 Peng P, Wang L, Yang X, Huang X, Ba Y, Chen X, et al. A preliminary study of the relationship between promoter methylation of the ABCG1, GALNT2 and HMGCR genes and coronary heart disease. PLoS One. 2014;9(8):e102265.) |
China |
Cross-sectional |
NA |
n = 139 (64%) |
NA |
NA |
ABCG1
|
Age, sex, smoking, lipid level, history of hypertension, and history of diabetes |
No significant association |
Good |
Wei & Wu. (2018) (1010 Wei R, Wu Y. Modification effect of fenofibrate therapy, a longitudinal epigenomic-wide methylation study of triglycerides levels in the GOLDN study. BMC Genet. 2018;19(Suppl 1):75.) |
USA |
Cross-sectional |
NA |
n = 995 |
NA |
NA |
1, 7, 8, 10 |
Age, sex, study center, family relations |
Negative association for CPT1A and positive association for ABCG1
|
Good |
Sayols-Baixeras et al. (2016) (99 Sayols-Baixeras S, Subirana I, Lluis-Ganella C, Civeira F, Roquer J, Do AN, et al. Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study. Hum Mol Genet. 2016;25(20):4556-65.) |
Spain |
Cohort |
Discovery set |
n = 645 (49%) |
63.2 ± 11.7 |
26.9 ± 4.1 |
1, 2, 4, 5, 7, 12 |
age, gender, smoking exposure, batch effect, estimated cell count and surrogate variables |
Negative association for CPT1A and positive association for ABCG1 & SREBF1
|
Good |
Replication set |
n = 2542 (46%) |
66.3 ± 8.9 |
28.2 ± 5.4 |
Irvin et al. (2014) (1616 Irvin MR, Zhi D, Joehanes R, Mendelson M, Aslibekyan S, Claas SA, et al. Epigenome-wide association study of fasting blood lipids in the Genetics of Lipid-lowering Drugs and Diet Network study. Circulation. 2014;130(7):565-72.) |
USA |
Cohort |
Discovery set |
n = 991 (48%) |
48.8 ± 16 |
NA |
7, 8, 9, 10 |
Age, gender, study site, cell purity, pedigree |
Negative association Results of cg00574958 methylation were replicated, and same association observed |
Good |
Replication set |
n = 1261 (40%) |
NA |
NA |
Romanescu et al. (2018) (3030 Romanescu RG, Espin-Garcia O, Ma J, Bull SB. Integrating epigenetic, genetic, and phenotypic data to uncover gene-region associations with triglycerides in the GOLDN study. BMC Proc. 2018;12(Suppl 9):57.) |
USA |
Cross-sectional |
NA |
n = 995 |
NA |
NA |
7, 8, 9, 10, 11 |
NA |
Significant association |
Good |
Hedman et al. (2017) (1414 Hedman ÅK, Mendelson MM, Marioni RE, Gustafsson S, Joehanes R, Irvin MR, et al. Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies. Circ Cardiovasc Genet. 2017;10(1):e001487.) |
USA |
Pooled analysis of Cohorts |
Discovery set |
n = 2306 (47%) |
NA |
NA |
1, 2, 6, 7, 8, 9, 12, 14 |
Both discovery and replication sets, were analyzed in two models: – primary model: age, sex, white cell counts and batch effects – secondary model: primary model + BMI |
Negative association for CPT1A and positive association for ABCG1 & SREBF1 - cg08129017 & cg01176028 were novel CpGs, had not found before |
Good |
Replication set |
n = 1955 |
NA |
NA |
Gagnon et al. (2014) (3131 Gagnon F, Aïssi D, Carrié A, Morange PE, Trégouët DA. Robust validation of methylation levels association at CPT1A locus with lipid plasma levels. J Lipid Res. 2014;55(7):1189-91.) |
France |
Cross-sectional |
MARTHA study |
n = 327 (21%) |
44.1 ± 14.2 |
NA |
7, 8 |
Age, gender, cell type, batch, and chip effects |
Negative association |
Fair |
F5L-pedigrees study |
n = 199 (47%) |
39.6 ± 16.9 |
NA |
Lai et al. (2016) (2424 Lai CQ, Wojczynski MK, Parnell LD, Hidalgo BA, Irvin MR, Aslibekyan S, et al. Epigenome-wide association study of triglyceride postprandial responses to a high-fat dietary challenge. J Lipid Res. 2016;57(12):2200-7.) |
USA |
Cross-sectional |
Discovery set |
n = 653 (48%) |
48 ± 16.2 |
28.2 ± 5.6 |
1, 7, 8, 9, 10, 12 |
age, sex, study site, baseline TG |
Negative association between CPT1A and TG-AUC, and positive association between ABCG1 & SREBF1, and TG-AUC * This study assesses the TG-AUC |
Good |
Replication set |
n = 326 (48%) |
48.8 ± 16.9 |
28.3 ± 5.8 |