Mittelstrass K, Waldenberger M. DNA methylation in human lipid metabolism and related diseases. Curr Opin Lipidol. 2018;29(2):116–24.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jhun MA, Mendelson M, Wilson R, Gondalia R, Joehanes R, Salfati E, Zhao X, Braun KVE, Do AN, Hedman AK, et al. A multiethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids. Nat Commun. 2021;12(1):3987.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sayols-Baixeras S, Subirana I, Fernandez-Sanles A, Senti M, Lluis-Ganella C, Marrugat J, Elosua R. DNA methylation and obesity traits: an epigenome-wide association study. The REGICOR study. Epigenetics. 2017;12(10):909–16.

Article  PubMed  PubMed Central  Google Scholar 

Hong X, Miao K, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, et al. Association between DNA methylation and blood pressure: a 5-year longitudinal twin study. Hypertension. 2023;80(1):169–81.

Article  CAS  PubMed  Google Scholar 

Han L, Liu Y, Duan S, Perry B, Li W, He Y. DNA methylation and hypertension: emerging evidence and challenges. Brief Funct Genomics. 2016;15(6):460–9.

CAS  PubMed  Google Scholar 

Nuotio ML, Pervjakova N, Joensuu A, Karhunen V, Hiekkalinna T, Milani L, Kettunen J, Jarvelin MR, Jousilahti P, Metspalu A, et al. An epigenome-wide association study of metabolic syndrome and its components. Sci Rep. 2020;10(1):20567.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Akinyemiju T, Do AN, Patki A, Aslibekyan S, Zhi D, Hidalgo B, Tiwari HK, Absher D, Geng X, Arnett DK, et al. Epigenome-wide association study of metabolic syndrome in African-American adults. Clin Epigenet. 2018;10:49.

Article  Google Scholar 

Yamazaki M, Yamada H, Munetsuna E, Maeda K, Ando Y, Mizuno G, Fujii R, Tsuboi Y, Ohashi K, Ishikawa H, et al. 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(3):319–26.

Article  CAS  PubMed  Google Scholar 

Gratten J, Visscher PM. Genetic pleiotropy in complex traits and diseases: implications for genomic medicine. Genome Med. 2016;8(1):78.

Article  PubMed  PubMed Central  Google Scholar 

Liu RK, Lin X, Wang Z, Greenbaum J, Qiu C, Zeng CP, Zhu YY, Shen J, Deng HW. Identification of novel functional CpG-SNPs associated with Type 2 diabetes and birth weight. Aging (Albany NY). 2021;13(7):10619–58.

Article  CAS  PubMed  Google Scholar 

Villicana S, Bell JT. Genetic impacts on DNA methylation: research findings and future perspectives. Genome Biol. 2021;22(1):127.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Islam SA, Goodman SJ, MacIsaac JL, Obradovic J, Barr RG, Boyce WT, Kobor MS. Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation. Epigenet Chromatin. 2019;12(1):1.

Article  Google Scholar 

Lee HS, Kim Y, Park T. New common and rare variants influencing metabolic syndrome and its individual components in a Korean population. Sci Rep. 2018;8(1):5701.

Article  PubMed  PubMed Central  Google Scholar 

Huan T, Joehanes R, Song C, Peng F, Guo Y, Mendelson M, Yao C, Liu C, Ma J, Richard M, et al. Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nat Commun. 2019;10(1):4267.

Article  PubMed  PubMed Central  Google Scholar 

Kim Y, Han BG. Ko GESg: cohort profile: the Korean Genome and Epidemiology Study (KoGES) Consortium. Int J Epidemiol. 2017;46(2):e20.

Article  PubMed  Google Scholar 

Morris TJ, Butcher LM, Feber A, Teschendorff AE, Chakravarthy AR, Wojdacz TK, Beck S. ChAMP: 450k chip analysis methylation pipeline. Bioinformatics. 2014;30(3):428–30.

Article  CAS  PubMed  Google Scholar 

Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, Beck S. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29(2):189–96.

Article  CAS  PubMed  Google Scholar 

Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8(1):118–27.

Article  PubMed  Google Scholar 

Rahmani E, Yedidim R, Shenhav L, Schweiger R, Weissbrod O, Zaitlen N, Halperin E. GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array data. Bioinformatics. 2017;33(12):1870–2.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Rahmani E, Zaitlen N, Baran Y, Eng C, Hu D, Galanter J, Oh S, Burchard EG, Eskin E, Zou J, et al. Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies. Nat Methods. 2016;13(5):443–5.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Van Iterson M, Van Zwet EW, Consortium B, Heijmans BT. Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome Biol. 2017;18(1):19.

Article  PubMed  PubMed Central  Google Scholar 

Peters TJ, Buckley MJ, Statham AL, Pidsley R, Samaras K, Lord VR, Clark SJ, Molloy PL. De novo identification of differentially methylated regions in the human genome. Epigenet Chromatin. 2015;8:6.

Article  Google Scholar 

Chinn CA, Ren H, Morival JLP, Nie Q, Wood MA, Downing TL. Examining age-dependent DNA methylation patterns and gene expression in the male and female mouse hippocampus. Neurobiol Aging. 2021;108:223–35.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pedersen BS, Schwartz DA, Yang IV, Kechris KJ. Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P values. Bioinformatics. 2012;28(22):2986–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gu Z, Hubschmann D. rGREAT: an R/bioconductor package for functional enrichment on genomic regions. Bioinformatics. 2023;39(1):btac745.

Article  CAS  PubMed  Google Scholar 

Roadmap Epigenomics C, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi-Moussavi A, Kheradpour P, Zhang Z, Wang J, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518(7539):317–30.

Article  Google Scholar 

Jonkman TH, Dekkers KF, Slieker RC, Grant CD, Ikram MA, van Greevenbroek MMJ, Franke L, Veldink JH, Boomsma DI, Slagboom PE, et al. Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression. Genome Biol. 2022;23(1):24.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

Article  PubMed  PubMed Central  Google Scholar 

Haeussler M, Zweig AS, Tyner C, Speir ML, Rosenbloom KR, Raney BJ, Lee CM, Lee BT, Hinrichs AS, Gonzalez JN, et al. The UCSC Genome Browser database: 2019 update. Nucleic Acids Res. 2019;47(D1):D853–8.

Article  CAS  PubMed  Google Scholar 

Shabalin AA. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics. 2012;28(10):1353–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Minelli C, Del Greco MF, van der Plaat DA, Bowden J, Sheehan NA, Thompson J. The use of two-sample methods for Mendelian randomization analyses on single large datasets. Int J Epidemiol. 2021;50(5):1651–9.

Article  PubMed  PubMed Central  Google Scholar 

Yavorska OO, Burgess S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46(6):1734–9.

Article  PubMed  PubMed Central  Google Scholar 

Xiang Y, Wang Z, Hui Q, Gwinn M, Vaccarino V, Sun YV. DNA methylation of TXNIP independently associated with inflammation and diabetes mellitus in twins. Twin Res Hum Genet. 2021;24(5):273–80.

Article  PubMed  PubMed Central  Google Scholar 

Zhang D, Cheng C, Cao M, Wang T, Chen X, Zhao Y, Wang B, Ren Y, Liu D, Liu L, et al. TXNIP hypomethylation and its interaction with obesity and hypertriglyceridemia increase type 2 diabetes mellitus risk: a nested case-control study. J Diabetes. 2020;12(7):512–20.

Article  CAS  PubMed  Google Scholar 

Somineni HK, Venkateswaran S, Kilaru V, Marigorta UM, Mo A, Okou DT, Kellermayer R, Mondal K, Cobb D, Walters TD, et al. Blood-derived DNA methylation signatures of Crohns disease and severity of intestinal inflammation. Gastroenterology. 2019;156(8):2254–65.

Article  CAS  PubMed