Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits

References

• Ehrlich M, Lacey M. DNA methylation and differentiation: silencing, upregulation and modulation of gene expression. Epigenomics. 2013;5:553–26. doi: 10.2217/epi.13.43
   PubMed Web of Science ®Google Scholar
• Schuettengruber B, Bourbon HM, Di Croce L, et al. Genome regulation by Polycomb and trithorax: 70 years and counting. Cell. 2017;171:34–57. doi: 10.1016/j.cell.2017.08.002
   PubMed Web of Science ®Google Scholar
• Yang JH, Hayano M, Griffin PT, et al. Loss of epigenetic information as a cause of mammalian aging. Cell. 2023;186:305–326 e327. doi: 10.1016/j.cell.2022.12.027
   PubMed Web of Science ®Google Scholar
• Trevino LS, Dong J, Kaushal A, et al. Epigenome environment interactions accelerate epigenomic aging and unlock metabolically restricted epigenetic reprogramming in adulthood. Nat Commun. 2020;11:2316. doi: 10.1038/s41467-020-15847-z
   PubMed Web of Science ®Google Scholar
• Donohoe DR, Bultman SJ. Metaboloepigenetics: interrelationships between energy metabolism and epigenetic control of gene expression. J Cell Physiol. 2012;227:3169–3177. doi: 10.1002/jcp.24054
   PubMed Web of Science ®Google Scholar
• Mozhui K, Lu AT, Li CZ, et al. Genetic loci and metabolic states associated with murine epigenetic aging. Elife. 2022;11. doi: 10.7554/eLife.75244.
   PubMed Web of Science ®Google Scholar
• Field AE, Robertson NA, Wang T, et al. DNA methylation clocks in aging: categories, causes, and Consequences. Molecular Cell. 2018;71:882–895. doi: 10.1016/j.molcel.2018.08.008
   PubMed Web of Science ®Google Scholar
• Horvath S. DNA methylation age of human tissues and cell types. Genome Bio. 2013;14:R115. doi: 10.1186/gb-2013-14-10-r115
   PubMed Web of Science ®Google Scholar
• Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging. 2019;11:303–327. doi: 10.18632/aging.101684
   PubMedGoogle Scholar
• Villicana S, Bell JT. Genetic impacts on DNA methylation: research findings and future perspectives. Genome Biol. 2021;22:127. doi: 10.1186/s13059-021-02347-6
   PubMed Web of Science ®Google Scholar
• Lin D, Chen J, Perrone-Bizzozero N, et al. Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia. Genome Med. 2018;10(1). doi: 10.1186/s13073-018-0519-4
   PubMedGoogle Scholar
• Huan T, Joehanes R, Song C, et al. Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nat Commun. 2019;10:4267. doi: 10.1038/s41467-019-12228-z
   PubMed Web of Science ®Google Scholar
• Schadt EE, Lamb J, Yang X, et al. An integrative genomics approach to infer causal associations between gene expression and disease. Nat Genet. 2005;37:710–717. doi: 10.1038/ng1589
   PubMed Web of Science ®Google Scholar
• Kraus WE, Muoio DM, Stevens R, et al. Metabolomic quantitative trait loci (mQTL) mapping Implicates the Ubiquitin Proteasome System in cardiovascular disease Pathogenesis. PLoS Genet. 2015;11:e1005553. doi: 10.1371/journal.pgen.1005553
   PubMed Web of Science ®Google Scholar
• Nath AP, Ritchie SC, Byars SG, et al. An interaction map of circulating metabolites, immune gene networks, and their genetic regulation. Genome Bio. 2017;18:146. doi: 10.1186/s13059-017-1279-y
   PubMed Web of Science ®Google Scholar
• Min JL, Hemani G, Hannon E, et al. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation. Nat Genet. 2021;53:1311–1321. doi: 10.1038/s41588-021-00923-x
   PubMed Web of Science ®Google Scholar
• Hawe JS, Wilson R, Schmid KT, et al. Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function. Nat Genet. 2022;54:18–29. doi: 10.1038/s41588-021-00969-x
   PubMed Web of Science ®Google Scholar
• Ma J, Joehanes R, Liu C, et al. Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease. Sci Rep. 2022;12:19564. doi: 10.1038/s41598-022-24100-0
   PubMed Web of Science ®Google Scholar
• Volkov P, Olsson AH, Gillberg L, et al. A Genome-wide mQTL Analysis in human adipose tissue identifies genetic variants associated with DNA methylation, gene expression and metabolic traits. PLoS One. 2016;11:e0157776. doi: 10.1371/journal.pone.0157776
   PubMed Web of Science ®Google Scholar
• McRae AF, Marioni RE, Shah S, et al. Identification of 55,000 replicated DNA methylation QTL. Sci Rep. 2018;8:17605. doi: 10.1038/s41598-018-35871-w
   PubMed Web of Science ®Google Scholar
• Mozhui K, Ciobanu DC, Schikorski T, et al. Dissection of a QTL hotspot on mouse distal chromosome 1 that modulates neurobehavioral phenotypes and gene expression. PLoS Genet. 2008;4:e1000260. doi: 10.1371/journal.pgen.1000260
   PubMed Web of Science ®Google Scholar
• Stadler MB, Murr R, Burger L, et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature. 2011;480:490–495. doi: 10.1038/nature10716
   PubMed Web of Science ®Google Scholar
• Hop PJ, Luijk R, Daxinger L, et al. Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference. Genome Biol. 2020;21:220. doi: 10.1186/s13059-020-02114-z
   PubMed Web of Science ®Google Scholar
• Bonder MJ, Luijk R, Zhernakova DV, et al. Disease variants alter transcription factor levels and methylation of their binding sites. Nat Genet. 2017;49:131–138. doi: 10.1038/ng.3721
   PubMed Web of Science ®Google Scholar
• Suzuki T, Furuhata E, Maeda S, et al. GATA6 is predicted to regulate DNA methylation in an in vitro model of human hepatocyte differentiation. Commun Biol. 2022;5:414. doi: 10.1038/s42003-022-03365-1
   PubMed Web of Science ®Google Scholar
• Gibbs JR, van der Brug MP, Hernandez DG, et al. Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain. PLoS Genet. 2010;6:e1000952. doi: 10.1371/journal.pgen.1000952
   PubMed Web of Science ®Google Scholar
• Bibikova M, Le J, Barnes B, et al. Genome-wide DNA methylation profiling using Infinium ® assay. Epigenomics. 2009;1:177–200. doi: 10.2217/epi.09.14
   PubMed Web of Science ®Google Scholar
• Wong NC, Ng J, Hall NE, et al. Exploring the utility of human DNA methylation arrays for profiling mouse genomic DNA. Genomics. 2013;102:38–46. doi: 10.1016/j.ygeno.2013.04.014
   PubMed Web of Science ®Google Scholar
• Gujar H, Liang JW, Wong NC, et al. Profiling DNA methylation differences between inbred mouse strains on the Illumina human Infinium MethylationEPIC microarray. PLoS One. 2018;13:e0193496. doi: 10.1371/journal.pone.0193496
   PubMed Web of Science ®Google Scholar
• Needhamsen M, Ewing E, Lund H, et al. Usability of human Infinium MethylationEPIC BeadChip for mouse DNA methylation studies. BMC Bioinf. 2017;18:486. doi: 10.1186/s12859-017-1870-y
   PubMed Web of Science ®Google Scholar
• Zhou W, Laird PW, Shen H. Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes. Nucleic Acids Res. 2017;45:e22. doi: 10.1093/nar/gkw967
   PubMed Web of Science ®Google Scholar
• Arneson A, Haghani A, Thompson MJ, et al. A mammalian methylation array for profiling methylation levels at conserved sequences. Nat Commun. 2022;13:783. doi: 10.1038/s41467-022-28355-z
   PubMed Web of Science ®Google Scholar
• Horvath S, Haghani A, Macoretta N, et al. DNA methylation clocks tick in naked mole rats but queens age more slowly than nonbreeders. Nat Aging. 2022;2:46–59. doi: 10.1038/s43587-021-00152-1
   PubMedGoogle Scholar
• Horvath S, Haghani A, Peng S, et al. DNA methylation aging and transcriptomic studies in horses. Nat Commun. 2022;13:40. doi: 10.1038/s41467-021-27754-y
   PubMed Web of Science ®Google Scholar
• Ashbrook DG, Arends D, Prins P, et al. A platform for experimental precision medicine: the extended BXD mouse family. Cell Syst. 2021. doi: 10.1016/j.cels.2020.12.002.
   PubMed Web of Science ®Google Scholar
• Mulligan MK, Mozhui K, Prins P, et al. GeneNetwork: a toolbox for systems genetics. Methods Mol Biol. 2017;1488:75–120. doi: 10.1007/978-1-4939-6427-7_4
   PubMedGoogle Scholar
• Roy S, Sleiman MB, Jha P, et al. Gene-by-environment modulation of lifespan and weight gain in the murine BXD family. Nat Metab. 2021;3:1217–1227. doi: 10.1038/s42255-021-00449-w
   PubMedGoogle Scholar
• Wang X, Pandey AK, Mulligan MK, et al. Joint mouse–human phenome-wide association to test gene function and disease risk. Nat Commun. 2016;7:10464. doi: 10.1038/ncomms10464
   PubMed Web of Science ®Google Scholar
• Taylor BA, Heiniger HJ, Meier H. Genetic analysis of resistance to cadmium-induced testicular damage in mice. Proc Soc Exp Biol Med. 1973;143:629–633. doi: 10.3181/00379727-143-37380
   PubMed Web of Science ®Google Scholar
• Taylor BA, Wnek C, Kotlus BS, et al. Genotyping new BXD recombinant inbred mouse strains and comparison of BXD and consensus maps. Mamm Genome. 1999;10(4):335–348. doi: 10.1007/s003359900998
   PubMed Web of Science ®Google Scholar
• Peirce JL, Lu L, Gu J, et al. A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 2004;5(1):7. doi: 10.1186/1471-2156-5-7
   PubMedGoogle Scholar
• Hook M, Roy S, Williams EG, et al. Genetic cartography of longevity in humans and mice: current landscape and horizons. Biochim Biophys Acta. 2018;1864:2718–2732. doi: 10.1016/j.bbadis.2018.01.026
   Web of Science ®Google Scholar
• Williams EG, Pfister N, Roy S, et al. Multiomic profiling of the liver across diets and age in a diverse mouse population. Cell Syst. 2022;13:43–57 e46. doi: 10.1016/j.cels.2021.09.005
   PubMed Web of Science ®Google Scholar
• Warner HR, Ingram D, Miller RA, et al. Program for testing biological interventions to promote healthy aging. Mech Ageing Dev. 2000;115:199–207. doi: 10.1016/S0047-6374(00)00118-4
   PubMedGoogle Scholar
• Sandoval-Sierra JV, Helbing AHB, Williams EG, et al. Body weight and high-fat diet are associated with epigenetic aging in female members of the BXD murine family. Aging Cell. 2020;19:e13207. doi: 10.1111/acel.13207
   PubMed Web of Science ®Google Scholar
• Ashbrook DG, Arends D, Prins P, et al. A platform for experimental precision medicine: the extended BXD mouse family. Cell Syst. 2021;12:235–247 e239. doi: 10.1016/j.cels.2020.12.002
   PubMed Web of Science ®Google Scholar
• Maegawa S, Hinkal G, Kim HS, et al. Widespread and tissue specific age-related DNA methylation changes in mice. Genome Res. 2010;20:332–340. doi: 10.1101/gr.096826.109
   PubMed Web of Science ®Google Scholar
• Broman KW, Gatti DM, Simecek P, et al. R/qtl2: software for mapping quantitative trait loci with high-dimensional data and multiparent populations. Genetics. 2019;211:495–502. doi: 10.1534/genetics.118.301595
   PubMed Web of Science ®Google Scholar
• Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nat Methods. 2012;9:215–216. doi: 10.1038/nmeth.1906
   PubMed Web of Science ®Google Scholar
• Gorkin DU, Barozzi I, Zhao Y, et al. An atlas of dynamic chromatin landscapes in mouse fetal development. Nature. 2020;583:744–751. doi: 10.1038/s41586-020-2093-3
   PubMed Web of Science ®Google Scholar
• Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinf. 2008;9:559. doi: 10.1186/1471-2105-9-559
   PubMed Web of Science ®Google Scholar
• Langfelder P, Horvath S. Eigengene networks for studying the relationships between co-expression modules. BMC Syst Biol. 2007;1(54). doi: 10.1186/1752-0509-1-54
   PubMedGoogle Scholar
• Mozhui K, Smith AK, Tylavsky FA, et al. Ancestry dependent DNA methylation and influence of maternal nutrition. PLoS One. 2015;10:e0118466. doi: 10.1371/journal.pone.0118466
   PubMed Web of Science ®Google Scholar
• Horvath S, Zhang Y, Langfelder P, et al. Aging effects on DNA methylation modules in human brain and blood tissue. Genome Bio. 2012;13:R97. doi: 10.1186/gb-2012-13-10-r97
   PubMed Web of Science ®Google Scholar
• Zhou X, Stephens M. Genome-wide efficient mixed-model analysis for association studies. Nature Genet. 2012;44:821–824. doi: 10.1038/ng.2310
   PubMed Web of Science ®Google Scholar
• Zhou X, Stephens M. Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nat Methods. 2014;11:407–409. doi: 10.1038/nmeth.2848
   PubMed Web of Science ®Google Scholar
• http://genenetwork.org.
   Google Scholar
• McLean CY, Bristor D, Hiller M, et al. GREAT improves functional interpretation of cis-regulatory regions. Nature Biotechnol. 2010;28:495–501. doi: 10.1038/nbt.1630
   PubMed Web of Science ®Google Scholar
• Gu Z, Hubschmann D, Marschall T. rGREAT: an R/bioconductor package for functional enrichment on genomic regions. Bioinformatics. 2023;39: doi: 10.1093/bioinformatics/btac745
   Web of Science ®Google Scholar
• de Macedo MP, Glanzner WG, Gutierrez K, et al. Chromatin role in early programming of embryos. Anim Front. 2021;11:57–65. doi: 10.1093/af/vfab054
   PubMed Web of Science ®Google Scholar
• Pinheiro I, Margueron R, Shukeir N, et al. Prdm3 and Prdm16 are H3K9me1 methyltransferases required for mammalian heterochromatin integrity. Cell. 2012;150:948–960. doi: 10.1016/j.cell.2012.06.048
   PubMed Web of Science ®Google Scholar
• Chuikov S, Levi BP, Smith ML, et al. Prdm16 promotes stem cell maintenance in multiple tissues, partly by regulating oxidative stress. Nat Cell Biol. 2010;12:999–1006. doi: 10.1038/ncb2101
   PubMed Web of Science ®Google Scholar
• Ito S, D’Alessio AC, Taranova OV, et al. Role of tet proteins in 5mC to 5hmC conversion, ES-cell self-renewal and inner cell mass specification. Nature. 2010;466:1129–1133. doi: 10.1038/nature09303
   PubMed Web of Science ®Google Scholar
• Su YR, Gu S-M, Liu Y-R, et al. Partial cellular reprogramming stably restores the stemness of senescent epidermal stem cells. Eur Rev Med Pharmacol Sci. 2023;27:5397–5409. doi: 10.26355/eurrev_202306_32774
   PubMed Web of Science ®Google Scholar
• Bell E, Curry EW, Megchelenbrink W, et al. Dynamic CpG methylation delineates subregions within super-enhancers selectively decommissioned at the exit from naive pluripotency. Nat Commun. 2020;11:1112. doi: 10.1038/s41467-020-14916-7
   PubMed Web of Science ®Google Scholar
• Tsui D, Vessey JP, Tomita H, et al. FoxP2 regulates neurogenesis during embryonic cortical development. J Neurosci. 2013;33:244–258. doi: 10.1523/JNEUROSCI.1665-12.2013
   PubMed Web of Science ®Google Scholar
• Kaji K, Nichols J, Hendrich B. Mbd3, a component of the NuRD co-repressor complex, is required for development of pluripotent cells. Development. 2007;134:1123–1132. doi: 10.1242/dev.02802
   PubMed Web of Science ®Google Scholar
• Zhu JN, Jiang L, Jiang J-H, et al. Hepatocyte nuclear factor-1beta enhances the stemness of hepatocellular carcinoma cells through activation of the notch pathway. Sci Rep. 2017;7:4793. doi: 10.1038/s41598-017-04116-7
   PubMed Web of Science ®Google Scholar
• Verdin E, Dequiedt F, Kasler HG. Class II histone deacetylases: versatile regulators. Trends Genet. 2003;19:286–293. doi: 10.1016/S0168-9525(03)00073-8
   PubMed Web of Science ®Google Scholar
• Ng PC, Henikoff S. Predicting deleterious amino acid substitutions. Genome Res. 2001;11:863–874. doi: 10.1101/gr.176601
   PubMed Web of Science ®Google Scholar
• von Mering C, Jensen LJ, Snel B, et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005;33:D433–437. doi: 10.1093/nar/gki005
   PubMed Web of Science ®Google Scholar
• Dohda T, Kaneoka H, Inayoshi Y, et al. Transcriptional coactivators CBP and p300 cooperatively enhance HNF-1alpha-mediated expression of the albumin gene in hepatocytes. J Biochem. 2004;136:313–319. doi: 10.1093/jb/mvh123
   PubMed Web of Science ®Google Scholar
• Kumar S, Mitnik C, Valente G, et al. Expansion and molecular evolution of the interferon-induced 2’-5’ oligoadenylate synthetase gene family. Mol Biol Evol. 2000;17:738–750. doi: 10.1093/oxfordjournals.molbev.a026352
   PubMed Web of Science ®Google Scholar
• Rodriguez-Hidalgo M, Luna-Sánchez M, Hidalgo-Gutiérrez A, et al. Reduction in the levels of CoQ biosynthetic proteins is related to an increase in lifespan without evidence of hepatic mitohormesis. Sci Rep. 2018;8:14013. doi: 10.1038/s41598-018-32190-y
   PubMed Web of Science ®Google Scholar
• Ji Z, Liu GH, Qu J. Mitochondrial sirtuins, metabolism, and aging. J Genet Genomics. 2022;49:287–298. doi: 10.1016/j.jgg.2021.11.005
   PubMed Web of Science ®Google Scholar
• Morrow G, Tanguay RM. Drosophila melanogaster Hsp22: a mitochondrial small heat shock protein influencing the aging process. Front Genet. 2015;6:1026. doi: 10.3389/fgene.2015.00103
   PubMed Web of Science ®Google Scholar
• Blanchette M, Kent WJ, Riemer C, et al. Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res. 2004;14:708–715. doi: 10.1101/gr.1933104
   PubMed Web of Science ®Google Scholar
• Li G, Margueron R, Ku M, et al. Jarid2 and PRC2, partners in regulating gene expression. Genes Dev. 2010;24:368–380. doi: 10.1101/gad.1886410
   PubMed Web of Science ®Google Scholar
• Paaby AB, Rockman MV. The many faces of pleiotropy. Trends Genet. 2013;29:66–73. doi: 10.1016/j.tig.2012.10.010
   PubMed Web of Science ®Google Scholar
• Tyler AL, Asselbergs FW, Williams SM, et al. Shadows of complexity: what biological networks reveal about epistasis and pleiotropy. BioEssays. 2009;31:220–227. doi: 10.1002/bies.200800022
   PubMed Web of Science ®Google Scholar
• Li H, Wang X, Rukina D, et al. An integrated systems genetics and omics toolkit to probe gene function. Cell Syst. 2018;6:90–102 e104. doi: 10.1016/j.cels.2017.10.016
   PubMed Web of Science ®Google Scholar
• https://systems-genetics.org/phewas.
   Google Scholar
• Groves MG, Rosenstreich DL, Taylor BA, et al. Host defenses in experimental scrub typhus: mapping the gene that controls natural resistance in mice. J Immunol. 1980;125(3):1395–1399. doi: 10.4049/jimmunol.125.3.1395
   PubMed Web of Science ®Google Scholar
• Ito J, Roy S, Liu Y, et al. Whisker barrel cortex delta oscillations and gamma power in the awake mouse are linked to respiration. Nat Commun. 2014;5:3572. doi: 10.1038/ncomms4572
   PubMed Web of Science ®Google Scholar
• Poon A, Goldowitz D. Identification of genetic loci that modulate cell proliferation in the adult rostral migratory stream using the expanded panel of BXD mice. BMC Genomics. 2014;15:206. doi: 10.1186/1471-2164-15-206
   PubMed Web of Science ®Google Scholar
• Dogan A, Lasch P, Neuschl C, et al. ATR-FTIR spectroscopy reveals genomic loci regulating the tissue response in high fat diet fed BXD recombinant inbred mouse strains. BMC Genomics. 2013;14:386. doi: 10.1186/1471-2164-14-386
   PubMed Web of Science ®Google Scholar
• Andreux PA, Williams EG, Koutnikova H, et al. Systems genetics of metabolism: the use of the BXD murine reference panel for multiscalar integration of traits. Cell. 2012;150:1287–1299. doi: 10.1016/j.cell.2012.08.012
   PubMed Web of Science ®Google Scholar
• Leandro J, Violante S, Argmann CA, et al. Mild inborn errors of metabolism in commonly used inbred mouse strains. Mol Genet Metab. 2019;126:388–396. doi: 10.1016/j.ymgme.2019.01.021
   PubMed Web of Science ®Google Scholar
• Watanabe K, Stringer S, Frei O, et al. A global overview of pleiotropy and genetic architecture in complex traits. Nat Genet. 2019;51:1339–1348. doi: 10.1038/s41588-019-0481-0
   PubMed Web of Science ®Google Scholar
• Sollis E, Mosaku A, Abid A, et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res. 2022;51(D1):D977–D985. doi: 10.1093/nar/gkac1010
   Web of Science ®Google Scholar
• Wojcik GL, Graff M, Nishimura KK, et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature. 2019;570:514–518. doi: 10.1038/s41586-019-1310-4
   PubMed Web of Science ®Google Scholar
• Kanai M, Akiyama M, Takahashi A, et al. Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. Nat Genet. 2018;50:390–400. doi: 10.1038/s41588-018-0047-6
   PubMed Web of Science ®Google Scholar
• Han X, Ong J-S, An J, et al. Using Mendelian randomization to evaluate the causal relationship between serum C-reactive protein levels and age-related macular degeneration. Eur J Epidemiol. 2020;35:139–146. doi: 10.1007/s10654-019-00598-z
   PubMed Web of Science ®Google Scholar
• Sakaue S, Kanai M, Tanigawa Y, et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet. 2021;53:1415–1424. doi: 10.1038/s41588-021-00931-x
   PubMed Web of Science ®Google Scholar
• Shin SY, Fauman EB, Petersen A-K, et al. An atlas of genetic influences on human blood metabolites. Nat Genet. 2014;46:543–550. doi: 10.1038/ng.2982
   PubMed Web of Science ®Google Scholar
• Siewert KM, Voight BF. Bivariate Genome-wide association scan identifies 6 novel loci associated with lipid levels and coronary artery disease. Circ Genom Precis Med. 2018;11:e002239. doi: 10.1161/CIRCGEN.118.002239
   PubMed Web of Science ®Google Scholar
• Graham SE, Clarke SL, Wu K-H-H, et al. The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021;600:675–679. doi: 10.1038/s41586-021-04064-3
   PubMed Web of Science ®Google Scholar
• Kichaev G, Bhatia G, Loh P-R, et al. Leveraging polygenic functional enrichment to improve GWAS power. Am J Hum Genet. 2019;104:65–75. doi: 10.1016/j.ajhg.2018.11.008
   PubMed Web of Science ®Google Scholar
• Day FR, Thompson DJ, Helgason H, et al. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat Genet. 2017;49:834–841. doi: 10.1038/ng.3841
   PubMed Web of Science ®Google Scholar
• Warrington NM, Beaumont RN, Horikoshi M, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 2019;51:804–814. doi: 10.1038/s41588-019-0403-1
   PubMed Web of Science ®Google Scholar
• Mahajan A, Taliun D, Thurner M, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet. 2018;50:1505–1513. doi: 10.1038/s41588-018-0241-6
   PubMed Web of Science ®Google Scholar
• Parra EJ, Below JE, Krithika S, et al. Genome-wide association study of type 2 diabetes in a sample from mexico city and a meta-analysis of a Mexican-American sample from Starr County, Texas. Diabetologia. 2011;54:2038–2046. doi: 10.1007/s00125-011-2172-y
   PubMed Web of Science ®Google Scholar
• Yashin AI, Wu D, Arbeev KG, et al. Joint influence of small-effect genetic variants on human longevity. Aging. 2010;2:612–620. doi: 10.18632/aging.100191
   PubMedGoogle Scholar
• Field AE, Adams PD. Targeting chromatin aging - the epigenetic impact of longevity-associated interventions. Exp Gerontol. 2017;94:29–33. doi: 10.1016/j.exger.2016.12.010
   PubMed Web of Science ®Google Scholar
• Riera CE, Merkwirth C, De Magalhaes Filho CD, et al. Signaling networks Determining life span. Annu Rev Biochem. 2016;85:35–64. doi: 10.1146/annurev-biochem-060815-014451
   PubMed Web of Science ®Google Scholar
• Lau HH, Ng NHJ, Loo LSW, et al. The molecular functions of hepatocyte nuclear factors - in and beyond the liver. J Hepatol. 2018;68:1033–1048. doi: 10.1016/j.jhep.2017.11.026
   PubMed Web of Science ®Google Scholar
• Duncan SA, Navas MA, Dufort D, et al. Regulation of a transcription factor network required for differentiation and metabolism. Science. 1998;281:692–695. doi: 10.1126/science.281.5377.692
   PubMed Web of Science ®Google Scholar
• Junnila RK, List EO, Berryman DE, et al. The GH/IGF-1 axis in ageing and longevity. Nat Rev Endocrinol. 2013;9:366–376. doi: 10.1038/nrendo.2013.67
   PubMed Web of Science ®Google Scholar
• Yamagata K, Oda N, Kaisaki PJ, et al. Mutations in the hepatocyte nuclear factor-1α gene in maturity-onset diabetes of the young (MODY3). Nature. 1996;384:455–458. doi: 10.1038/384455a0
   PubMed Web of Science ®Google Scholar
• Byrne MM, Sturis J, Menzel S, et al. Altered insulin secretory responses to glucose in diabetic and nondiabetic subjects with mutations in the diabetes susceptibility gene MODY3 on chromosome 12. Diabetes. 1996;45:1503–1510. doi: 10.2337/diab.45.11.1503
   PubMed Web of Science ®Google Scholar
• Li LM, Jiang BG, Sun LL. HNF1A: From Monogenic diabetes to type 2 diabetes and Gestational diabetes Mellitus. Front Endocrinol. 2022;13:829565. doi: 10.3389/fendo.2022.829565
   PubMedGoogle Scholar
• Hegele RA, Cao H, Harris SB, et al. The hepatic nuclear factor-1alpha G319S variant is associated with early-onset type 2 diabetes in Canadian Oji-Cree. J Clin Endocrinol Metab. 1999;84:1077–1082. doi: 10.1210/jc.84.3.1077
   PubMed Web of Science ®Google Scholar
• Lee YH, Sauer B, Gonzalez FJ. Laron dwarfism and non-insulin-dependent diabetes mellitus in the Hnf-1alpha knockout mouse. Mol Cell Biol. 1998;18:3059–3068. doi: 10.1128/MCB.18.5.3059
   PubMed Web of Science ®Google Scholar
• Yang X, Song JH, Cheng Y, et al. Long non-coding RNA HNF1A-AS1 regulates proliferation and migration in oesophageal adenocarcinoma cells. Gut. 2014;63:881–890. doi: 10.1136/gutjnl-2013-305266
   PubMed Web of Science ®Google Scholar
• Liu Z, Wei X, Zhang A, et al. Long non-coding RNA HNF1A-AS1 functioned as an oncogene and autophagy promoter in hepatocellular carcinoma through sponging hsa-miR-30b-5p. Biochem Biophys Res Commun. 2016;473:1268–1275. doi: 10.1016/j.bbrc.2016.04.054
   PubMed Web of Science ®Google Scholar
• Luco RF, Maestro MA, Sadoni N, et al. Targeted deficiency of the transcriptional activator Hnf1α alters subnuclear positioning of its genomic targets. PLoS Genet. 2008;4:e1000079. doi: 10.1371/journal.pgen.1000079
   PubMed Web of Science ®Google Scholar
• Yagi S, Hirabayashi K, Sato S, et al. DNA methylation profile of tissue-dependent and differentially methylated regions (T-DMRs) in mouse promoter regions demonstrating tissue-specific gene expression. Genome Res. 2008;18:1969–1978. doi: 10.1101/gr.074070.107
   PubMed Web of Science ®Google Scholar
• de Magalhaes JP. Ageing as a software design flaw. Genome Biol. 2023;24:51. doi: 10.1186/s13059-023-02888-y
   PubMed Web of Science ®Google Scholar
• de Magalhaes JP, Church GM. Genomes optimize reproduction: aging as a consequence of the developmental program. Physiology. 2005;20:252–259. doi: 10.1152/physiol.00010.2005
   PubMed Web of Science ®Google Scholar
• Singh PB, Zhakupova A. Age reprogramming: cell rejuvenation by partial reprogramming. Development. 2022;149: doi: 10.1242/dev.200755
   Web of Science ®Google Scholar
• Zhang W, Qu J, Liu GH, et al. The ageing epigenome and its rejuvenation. Nat Rev Mol Cell Biol. 2020;21:137–150. doi: 10.1038/s41580-019-0204-5
   PubMed Web of Science ®Google Scholar
• Lu Y, Brommer B, Tian X, et al. Reprogramming to recover youthful epigenetic information and restore vision. Nature. 2020;588:124–129. doi: 10.1038/s41586-020-2975-4
   PubMed Web of Science ®Google Scholar
• Ocampo A, Reddy P, Martinez-Redondo P, et al. In vivo amelioration of age-associated hallmarks by partial reprogramming. Cell. 2016;167:1719–1733 e1712. doi: 10.1016/j.cell.2016.11.052
   PubMed Web of Science ®Google Scholar
• Beucher A, Miguel-Escalada I, Balboa D, et al. The HASTER lncRNA promoter is a cis-acting transcriptional stabilizer of HNF1A. Nat Cell Biol. 2022;24:1528–1540. doi: 10.1038/s41556-022-00996-8
   PubMed Web of Science ®Google Scholar
• Liu Y, Zhao F, Tan F, et al. HNF1A-AS1: a tumor-associated long non-coding RNA. Curr Pharm Des. 2022;28:1720–1729. doi: 10.2174/1381612828666220520113846
   PubMed Web of Science ®Google Scholar
• Wang Y, Xie Y, Li L, et al. EZH2 RIP-seq Identifies tissue-specific long non-coding RNAs. Curr Gene Ther. 2018;18:275–285. doi: 10.2174/1566523218666181008125010
   PubMed Web of Science ®Google Scholar
• Beerman I, Bock C, Garrison B, et al. Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging. Cell Stem Cell. 2013;12:413–425. doi: 10.1016/j.stem.2013.01.017
   PubMed Web of Science ®Google Scholar
• Dozmorov MG. Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes. Epigenetics. 2015;10:484–495. doi: 10.1080/15592294.2015.1040619
   PubMed Web of Science ®Google Scholar
• Mozhui K, Pandey AK. Conserved effect of aging on DNA methylation and association with EZH2 polycomb protein in mice and humans. Mech Ageing Dev. 2017;162:27–37. doi: 10.1016/j.mad.2017.02.006
   PubMed Web of Science ®Google Scholar
• Sandoval-Sierra JV, Helbing AH, Williams EG, et al. Body weight and high-fat diet are associated with epigenetic aging in female members of the BXD murine family. Aging Cell. 2020;e13207. doi: 10.1111/acel.13207
   PubMed Web of Science ®Google Scholar
• Guevara-Aguirre J, Balasubramanian P, Guevara-Aguirre M, et al. Growth hormone receptor deficiency is associated with a major reduction in pro-aging signaling, cancer, and diabetes in humans. Sci Transl Med. 2011;3:70ra13. doi: 10.1126/scitranslmed.3001845
   PubMed Web of Science ®Google Scholar
• Aguiar-Oliveira MH, Bartke A. Growth hormone deficiency: health and longevity. Endocr Rev. 2019;40:575–601. doi: 10.1210/er.2018-00216
   PubMed Web of Science ®Google Scholar
• Laron Z. Do deficiencies in growth hormone and insulin-like growth factor-1 (IGF-1) shorten or prolong longevity? Mech Ageing Dev. 2005;126:305–307. doi: 10.1016/j.mad.2004.08.022
   PubMed Web of Science ®Google Scholar
• Laron Z, Kauli R, Lapkina L, et al. IGF-I deficiency, longevity and cancer protection of patients with Laron syndrome. Mutat Res Rev Mutat Res. 2017;772:123–133. doi: 10.1016/j.mrrev.2016.08.002
   PubMed Web of Science ®Google Scholar
• Petkova SB, Yuan R, Tsaih S-W, et al. Genetic influence on immune phenotype revealed strain-specific variations in peripheral blood lineages. Physiol Genomics. 2008;34:304–314. doi: 10.1152/physiolgenomics.00185.2007
   PubMed Web of Science ®Google Scholar
• Wang T, Tsui B, Kreisberg JF, et al. Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment. Genome Bio. 2017;18(1). doi: 10.1186/s13059-017-1186-2
   Google Scholar
• Statham AL, Strbenac D, Coolen MW, et al. Repitools: an R package for the analysis of enrichment-based epigenomic data. Bioinformatics. 2010;26:1662–1663. doi: 10.1093/bioinformatics/btq247
   PubMed Web of Science ®Google Scholar
• Dennis G Jr., Sherman BT, Hosack DA, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4(5):3. doi: 10.1186/gb-2003-4-5-p3
   PubMed Web of Science ®Google Scholar
• Szklarczyk D, Gable AL, Nastou KC, et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49:D605–D612. doi: 10.1093/nar/gkaa1074
   PubMed Web of Science ®Google Scholar
• Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–D613. doi: 10.1093/nar/gky1131
   PubMed Web of Science ®Google Scholar
• Keane TM, Goodstadt L, Danecek P, et al. Mouse genomic variation and its effect on phenotypes and gene regulation. Nature. 2011;477:289–294. doi: 10.1038/nature10413
   PubMed Web of Science ®Google Scholar
• Yalcin B, Wong K, Agam A, et al. Sequence-based characterization of structural variation in the mouse genome. Nature. 2011;477:326–329. doi: 10.1038/nature10432
   PubMed Web of Science ®Google Scholar
• Blake JA, Baldarelli R, Kadin JA, et al. Mouse Genome database (MGD): knowledgebase for mouse–human comparative biology. Nucleic Acids Res. 2021;49:D981–D987. doi: 10.1093/nar/gkaa1083
   PubMed Web of Science ®Google Scholar
• Cunningham F, Allen JE, Allen J, et al. Ensembl 2022. Nucleic Acids Res. 2022;50:D988–D995. doi: 10.1093/nar/gkab1049
   PubMed Web of Science ®Google Scholar