| [1] | Yan T, Zhu SJ, Yin XJ, et al. Burden, trends, and inequalities of heart failure globally, 1990 to 2019: a secondary analysis based on the global burden of disease 2019 study. J Am Heart Assoc, 2023; 12, e027852. doi: 10.1161/JAHA.122.027852 |
| [2] | Bui AL, Horwich TB, Fonarow GC. Epidemiology and risk profile of heart failure. Nat Rev Cardiol, 2011; 8, 30−41. doi: 10.1038/nrcardio.2010.165 |
| [3] | Lindgren MP, Pirouzifard M, Smith JG, et al. A Swedish nationwide adoption study of the heritability of heart failure. JAMA Cardiol, 2018; 3, 703−10. doi: 10.1001/jamacardio.2018.1919 |
| [4] | Reza N, Owens AT. Advances in the genetics and genomics of heart failure. Curr Cardiol Rep, 2020; 22, 132. doi: 10.1007/s11886-020-01385-z |
| [5] | Shah S, Henry A, Roselli C, et al. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure. Nat Commun, 2020; 11, 163. doi: 10.1038/s41467-019-13690-5 |
| [6] | Levin MG, Tsao NL, Singhal P, et al. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure. Nat Commun, 2022; 13, 6914. doi: 10.1038/s41467-022-34216-6 |
| [7] | Rasooly D, Peloso GM, Pereira AC, et al. Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure. Nat Commun, 2023; 14, 3826. doi: 10.1038/s41467-023-39253-3 |
| [8] | Luo XT, Li HQ, Liang JQ, et al. RMVar: an updated database of functional variants involved in RNA modifications. Nucleic Acids Res, 2021; 49, D1405−12. doi: 10.1093/nar/gkaa811 |
| [9] | Wiener D, Schwartz S. The epitranscriptome beyond m6A. Nat Rev Genet, 2021; 22, 119−31. |
| [10] | Gomes CPC, Schroen B, Kuster GM, et al. Regulatory RNAs in heart failure. Circulation, 2020; 141, 313−28. doi: 10.1161/CIRCULATIONAHA.119.042474 |
| [11] | Wang X, Lu ZK, Gomez A, et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature, 2014; 505, 117−20. doi: 10.1038/nature12730 |
| [12] | Xiao W, Adhikari S, Dahal U, et al. Nuclear m6A reader YTHDC1 regulates mRNA splicing. Mol Cell, 2016; 61, 507−19. doi: 10.1016/j.molcel.2016.01.012 |
| [13] | Wang X, Zhao BS, Roundtree IA, et al. N6-methyladenosine modulates messenger RNA translation efficiency. Cell, 2015; 161, 1388−99. doi: 10.1016/j.cell.2015.05.014 |
| [14] | Fustin JM, Doi M, Yamaguchi Y, et al. RNA-methylation-dependent RNA processing controls the speed of the circadian clock. Cell, 2013; 155, 793−806. doi: 10.1016/j.cell.2013.10.026 |
| [15] | Berulava T, Buchholz E, Elerdashvili V, et al. Changes in m6A RNA methylation contribute to heart failure progression by modulating translation. Eur J Heart Fail, 2020; 22, 54−66. doi: 10.1002/ejhf.1672 |
| [16] | Kumari R, Ranjan P, Suleiman ZG, et al. mRNA modifications in cardiovascular biology and disease: with a focus on m6A modification. Cardiovasc Res, 2022; 118, 1680−92. doi: 10.1093/cvr/cvab160 |
| [17] | Jian DD, Wang Y, Jian LG, et al. METTL14 aggravates endothelial inflammation and atherosclerosis by increasing FOXO1 N6-methyladeosine modifications. Theranostics, 2020; 10, 8939−56. doi: 10.7150/thno.45178 |
| [18] | Zheng YY, Nie P, Peng D, et al. m6AVar: a database of functional variants involved in m6A modification. Nucleic Acids Res, 2018; 46, D139−45. doi: 10.1093/nar/gkx895 |
| [19] | Ishigaki K, Akiyama M, Kanai M, et al. Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases. Nat Genet, 2020; 52, 669−79. doi: 10.1038/s41588-020-0640-3 |
| [20] | Sakaue S, Kanai M, Tanigawa Y, et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet, 2021; 53, 1415−24. doi: 10.1038/s41588-021-00931-x |
| [21] | Yin LL, Zhang HH, Tang ZS, et al. rMVP: a memory-efficient, visualization-enhanced, and parallel-accelerated tool for genome-wide association study. Genomics Proteomics Bioinformatics, 2021; 19, 619−28. doi: 10.1016/j.gpb.2020.10.007 |
| [22] | Zhou YY, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun, 2019; 10, 1523. doi: 10.1038/s41467-019-09234-6 |
| [23] | Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res, 2012; 40, D930−4. doi: 10.1093/nar/gkr917 |
| [24] | Ko T, Nomura S, Yamada S, et al. Cardiac fibroblasts regulate the development of heart failure via Htra3-TGF-β-IGFBP7 axis. Nat Commun, 2022; 13, 3275. doi: 10.1038/s41467-022-30630-y |
| [25] | Flam E, Jang C, Murashige D, et al. Integrated landscape of cardiac metabolism in end-stage human nonischemic dilated cardiomyopathy. Nat Cardiovasc Res, 2022; 1, 817−29. |
| [26] | Nomura S, Satoh M, Fujita T, et al. Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure. Nat Commun, 2018; 9, 4435. doi: 10.1038/s41467-018-06639-7 |
| [27] | Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res, 2015; 43, e47. doi: 10.1093/nar/gkv007 |
| [28] | Carter AR, Sanderson E, Hammerton G, et al. Mendelian randomisation for mediation analysis: current methods and challenges for implementation. Eur J Epidemiol, 2021; 36, 465−78. doi: 10.1007/s10654-021-00757-1 |
| [29] | MacKinnon DP, Lockwood CM, Hoffman JM, et al. A comparison of methods to test mediation and other intervening variable effects. Psychol Methods, 2002; 7, 83−104. doi: 10.1037/1082-989X.7.1.83 |
| [30] | Ferkingstad E, Sulem P, Atlason BA, et al. Large-scale integration of the plasma proteome with genetics and disease. Nat Genet, 2021; 53, 1712−21. doi: 10.1038/s41588-021-00978-w |
| [31] | Hemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife, 2018; 7, e34408. doi: 10.7554/eLife.34408 |
| [32] | Sproviero W, Winchester L, Newby D, et al. High blood pressure and risk of dementia: a two-sample mendelian randomization study in the UK biobank. Biol Psychiatry, 2021; 89, 817−24. doi: 10.1016/j.biopsych.2020.12.015 |
| [33] | Tofighi D, MacKinnon DP. RMediation: an R package for mediation analysis confidence intervals. Behav Res Methods, 2011; 43, 692−700. doi: 10.3758/s13428-011-0076-x |
| [34] | Mo XB, Lei SF, Zhang YH, et al. Examination of the associations between m6A-associated single-nucleotide polymorphisms and blood pressure. Hypertens Res, 2019; 42, 1582−9. doi: 10.1038/s41440-019-0277-8 |
| [35] | Mo XB, Lei SF, Zhang YH, et al. Detection of M6A-associated SNPs as potential functional variants for coronary artery disease. Epigenomics, 2018; 10, 1279−87. doi: 10.2217/epi-2018-0007 |
| [36] | Surendran P, Feofanova EV, Lahrouchi N, et al. Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. Nat Genet, 2020; 52, 1314−32. doi: 10.1038/s41588-020-00713-x |
| [37] | Harper AR, Goel A, Grace C, et al. Common genetic variants and modifiable risk factors underpin hypertrophic cardiomyopathy susceptibility and expressivity. Nat Genet, 2021; 53, 135−42. doi: 10.1038/s41588-020-00764-0 |
| [38] | Yu MY, Harper AR, Aguirre M, et al. Genetic determinants of the interventricular septum are linked to ventricular septal defects and hypertrophic cardiomyopathy. Circ Genom Precis Med, 2023; 16, 207−15. doi: 10.1161/CIRCGEN.122.003708 |
| [39] | Tane S, Ikenishi A, Okayama H, et al. CDK inhibitors, p21Cip1 and p27Kip1, participate in cell cycle exit of mammalian cardiomyocytes. Biochem Biophys Res Commun, 2014; 443, 1105−9. doi: 10.1016/j.bbrc.2013.12.109 |
| [40] | Hauck L, Grothe D, Billia F. p21CIP1/WAF1-dependent inhibition of cardiac hypertrophy in response to Angiotensin II involves Akt/Myc and pRb signaling. Peptides, 2016; 83, 38−48. doi: 10.1016/j.peptides.2016.07.003 |
| [41] | Guimarães-Camboa N, Stowe J, Aneas I, et al. HIF1α represses cell stress pathways to allow proliferation of hypoxic fetal cardiomyocytes. Dev Cell, 2015; 33, 507−21. doi: 10.1016/j.devcel.2015.04.021 |
| [42] | Vekich JA, Belmont PJ, Thuerauf DJ, et al. Protein disulfide isomerase-associated 6 is an ATF6-inducible ER stress response protein that protects cardiac myocytes from ischemia/reperfusion-mediated cell death. J Mol Cell Cardiol, 2012; 53, 259−67. doi: 10.1016/j.yjmcc.2012.05.005 |
| [43] | Ma N, Xu H, Zhang WH, et al. Genome-wide analysis revealed the dysregulation of RNA binding protein-correlated alternative splicing events in myocardial ischemia reperfusion injury. BMC Med Genomics, 2023; 16, 251. doi: 10.1186/s12920-023-01706-5 |
| [44] | Weng L, Ye JJ, Yang FH, et al. TGF-β1/SMAD3 regulates programmed cell death 5 that suppresses cardiac fibrosis post-myocardial infarction by inhibiting HDAC3. Circ Res, 2023; 133, 237−51. doi: 10.1161/CIRCRESAHA.123.322596 |
| [45] | Chen BJ, Huang SB, Su Y, et al. Macrophage Smad3 protects the infarcted heart, stimulating phagocytosis and regulating inflammation. Circ Res, 2019; 125, 55−70. doi: 10.1161/CIRCRESAHA.119.315069 |