NMU DNA methylation in blood is associated with metabolic and inflammatory indices: results from the Moli-sani study

References

• Kassi E, Pervanidou P, Kaltsas G, et al. Metabolic syndrome: definitions and controversies. BMC Med. 2011;9:48.
   Google Scholar
• Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444:860–867.
   Google Scholar
• Martinez VG, O’Driscoll L. Neuromedin U: a multifunctional neuropeptide with pleiotropic roles. Clin Chem. 2015;61:471–482.
   Google Scholar
• Gajjar S, Patel BM. Neuromedin: an insight into its types, receptors and therapeutic opportunities. Pharmacol Rep. 2017;69:438–447.
   Google Scholar
• Moriyama M, Fukuyama S, Inoue H, et al. The neuropeptide neuromedin U activates eosinophils and is involved in allergen-induced eosinophilia. Am J Physiol Lung Cell Mol Physiol. 2006;290:L971–977.
   Google Scholar
• Hedrick JA, Morse K, Shan L, et al. Identification of a human gastrointestinal tract and immune system receptor for the peptide neuromedin U. Mol Pharmacol. 2000;58:870–875.
   Google Scholar
• Klose CSN, Mahlakoiv T, Moeller JB, et al. The neuropeptide neuromedin U stimulates innate lymphoid cells and type 2 inflammation. Nature. 2017;549:282–286.
   Google Scholar
• Grippi C, Izzi B, Gianfagna F, et al. Neuromedin U potentiates ADP- and epinephrine-induced human platelet activation. Thromb Res. 2017;159:100–108.
   Google Scholar
• Hainerova I, Torekov SS, Ek J, et al. Association between neuromedin U gene variants and overweight and obesity. J Clin Endocrinol Metab. 2006;91:5057–5063.
   Google Scholar
• Gianfagna F, Grippi C, Ahrens W, et al. The role of neuromedin U in adiposity regulation. Haplotype analysis in European children from the IDEFICS Cohort. PLoS One. 2017;12:e0172698.
   Google Scholar
• Grippi C, Ahrens W, Buchecker K, et al. Association between variants of neuromedin U gene and taste thresholds and food preferences in European children: results from the IDEFICS study. Appetite. 2019;142:104376.
   Google Scholar
• Gianfagna F, Cugino D, Ahrens W, et al. Understanding the links among neuromedin U gene, beta2-adrenoceptor gene and bone health: an observational study in European children. PLoS One. 2013;8(8):e70632. .
   Google Scholar
• Carson C, Lawson HA. Epigenetics of metabolic syndrome. Physiol Genomics. 2018;50:947–955.
   Google Scholar
• Tobi EW, Lumey LH, Talens RP, et al. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum Mol Genet. 2009;18:4046–4053.
   Google Scholar
• Arpon A, Milagro FI, Ramos-Lopez O, et al. Methylome-wide association study in peripheral white blood cells focusing on central obesity and inflammation. Genes (Basel). 2019;10(6):444. .
   Google Scholar
• Di Castelnuovo A, de Curtis A, Costanzo S, et al. Association of D-dimer levels with all-cause mortality in a healthy adult population: findings from the MOLI-SANI study. Haematologica. 2013;98:1476–1480.
   Google Scholar
• Di Castelnuovo A, Costanzo S, Persichillo M, et al. Distribution of short and lifetime risks for cardiovascular disease in Italians. Eur J Prev Cardiol. 2012;19:723–730.
   Google Scholar
• Pisani P, Faggiano F, Krogh V, et al. Relative validity and reproducibility of a food frequency dietary questionnaire for use in the Italian EPIC centres. Int J Epidemiol. 1997;26(Suppl 1):S152–160.
   Google Scholar
• Trichopoulou A, Costacou T, Bamia C, et al. Adherence to a mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348:2599–2608.
   Google Scholar
• Bener A, Zirie M, Musallam M, et al. Prevalence of metabolic syndrome according to adult treatment panel III and international diabetes federation criteria: a population-based study. Metab Syndr Relat Disord. 2009;7:221–229.
   Google Scholar
• National Institutes of Health. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults–The evidence report. Obes Res. 1998;6(Suppl 2):51S–209S.
   Google Scholar
• Zeller T, Hughes M, Tuovinen T, et al. BiomarCaRE: rationale and design of the European BiomarCaRE project including 300,000 participants from 13 European countries. Eur J Epidemiol. 2014;29:777–790.
   Google Scholar
• Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–419.
   Google Scholar
• Pounis G, Bonaccio M, Di Castelnuovo A, et al. Polyphenol intake is associated with low-grade inflammation, using a novel data analysis from the Moli-sani study. Thromb Haemost. 2016;2115:344–352.
   Google Scholar
• Gialluisi A, Bonaccio M, Di Castelnuovo A, et al. Lifestyle and biological factors influence the relationship between mental health and low-grade inflammation. Brain Behav Immun. 2020;85:4–13.
   Google Scholar
• Bonaccio M, Di Castelnuovo A, Pounis G, et al. A score of low-grade inflammation and risk of mortality: prospective findings from the Moli-sani study. Haematologica. 2016;101:1434–1441.
   Google Scholar
• Malferrari G, Monferini E, DeBlasio P, et al. High-quality genomic DNA from human whole blood and mononuclear cells. Biotechniques. 2002;33:1228–1230.
   Google Scholar
• Izzi B, Binder AM, Michels KB. Pyrosequencing evaluation of widely available bisulfite conversion methods: considerations for application. Med Epigenet. 2014;2:28–36.
   Google Scholar
• Noro F, Gianfagna F, Gialluisi A, et al. ZBTB12 DNA methylation is associated with coagulation- and inflammation-related blood cell parameters: findings from the Moli-family cohort. Clin Epigenetics. 2019;11(1):74. .
   Google Scholar
• Izzi B, Gianfagna F, Yang WY, et al. Variation of PEAR1 DNA methylation influences platelet and leukocyte function. Clin Epigenetics. 2019;11:151.
   Google Scholar
• Kim JOMC. Factor analysis: statistical method and practical issues. Thousand Oaks, CA: Sage Publications; 1978.
   Google Scholar
• Preacher KJ, Hayes AF. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput. 2004;36:717–731.
   Google Scholar
• Messeguer X, Escudero R, Farre D, et al. PROMO: detection of known transcription regulatory elements using species-tailored searches. Bioinformatics. 2002;18:333–334.
   Google Scholar
• Sniderman AD, Thanassoulis G, Glavinovic T, et al. Apolipoprotein B particles and cardiovascular disease: a narrative review. JAMA Cardiol. 2019;4:1287–1295.
   Google Scholar
• Ingallinella P, Peier AM, Pocai A, et al. PEGylation of neuromedin U yields a promising candidate for the treatment of obesity and diabetes. Bioorg Med Chem. 2012;20:4751–4759.
   Google Scholar
• Ma ML, Li M, Gou JJ, et al. Design, synthesis and biological activity of flavonoid derivatives as selective agonists for neuromedin U 2 receptor. Bioorg Med Chem. 2014;22(21):6117–6123.
   Google Scholar
• De Prins A, Van Eeckhaut A, Smolders I, et al. Neuromedin U and structural analogs: an overview of their structure, function and selectivity. Curr Med Chem. 2020;27(39):6744-6768.
   Google Scholar
• Shetzline SE, Rallapalli R, Dowd KJ, et al. Neuromedin U: a Myb-regulated autocrine growth factor for human myeloid leukemias. Blood. 2004;104:1833–1840.
   Google Scholar
• Gambone JE, Dusaban SS, Loperena R, et al. The c-Myb target gene neuromedin U functions as a novel cofactor during the early stages of erythropoiesis. Blood. 2011;117:5733–5743.
   Google Scholar
• Moriyama M, Sato T, Inoue H, et al. The neuropeptide neuromedin U promotes inflammation by direct activation of mast cells. J Exp Med. 2005;202:217–224.
   Google Scholar
• Moriyama M, Matsukawa A, Kudoh S, et al. The neuropeptide neuromedin U promotes IL-6 production from macrophages and endotoxin shock. Biochem Biophys Res Commun. 2006;341:1149–1154.
   Google Scholar
• Nagashima H, Mahlakoiv T, Shih HY, et al. Neuropeptide CGRP limits Group 2 innate lymphoid cell responses and constrains type 2 inflammation. Immunity. 2019;51:682–695 e686.
   Google Scholar
• Stols-Goncalves D, Tristao LS, Henneman P, et al. Epigenetic markers and microbiota/metabolite-induced epigenetic modifications in the pathogenesis of obesity, metabolic syndrome, Type 2 diabetes, and non-alcoholic fatty liver disease. Curr Diab Rep. 2019;19:31.
   Google Scholar
• Ligthart S, Marzi C, Aslibekyan S, et al. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol. 2016;17:255.
   Google Scholar
• Marzi C, Holdt LM, Fiorito G, et al. Epigenetic signatures at AQP3 and SOCS3 engage in low-grade inflammation across different tissues. PLoS One. 2016;11:e0166015.
   Google Scholar
• Izzi B, Noro F, Cludts K, et al. Cell-specific PEAR1 methylation studies reveal a locus that coordinates expression of multiple genes. Int J Mol Sci. 2018;19(4):1069.
   Google Scholar
• Morrison FG, Logue MW, Guetta R, et al. Investigation of bidirectional longitudinal associations between advanced epigenetic age and peripheral biomarkers of inflammation and metabolic syndrome. Aging (Albany NY). 2019;11:3487–3504.
   Google Scholar
• Wahl S, Drong A, Lehne B, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature. 2017;541:81–86.
   Google Scholar
• Dick KJ, Nelson CP, Tsaprouni L, et al. DNA methylation and body-mass index: a genome-wide analysis. Lancet. 2014;383:1990–1998.
   Google Scholar
• Feinberg AP, Irizarry RA, Fradin D, et al. Personalized epigenomic signatures that are stable over time and covary with body mass index. Sci Transl Med. 2010;2:49ra67.
   Google Scholar
• Xu X, Su S, Barnes VA, et al. A genome-wide methylation study on obesity: differential variability and differential methylation. Epigenetics. 2013;8:522–533.
   Google Scholar
• Demerath EW, Guan W, Grove ML, et al. Epigenome-wide association study (EWAS) of BMI, BMI change and waist circumference in African American adults identifies multiple replicated loci. Hum Mol Genet. 2015;24:4464–4479.
   Google Scholar
• Singhal A, Subramanian M. Colony stimulating factors (CSFs): complex roles in atherosclerosis. Cytokine. 2019;122:154190.
   Google Scholar
• Quach A, Levine ME, Tanaka T, et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging (Albany NY). 2017;9:419–446.
   Google Scholar
• Moore LD, Le T, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013;38:23–38.
   Google Scholar
• Jimenez MA, Akerblad P, Sigvardsson M, et al. Critical role for Ebf1 and Ebf2 in the adipogenic transcriptional cascade. Mol Cell Biol. 2007;27:743–757. .
   Google Scholar
• Friedman AD. Transcriptional regulation of granulocyte and monocyte development. Oncogene. 2002;21:3377–3390.
   Google Scholar
• Friedman AD. Transcriptional regulation of myelopoiesis. Int J Hematol. 2002;75:466–472.
   Google Scholar
• Jalinot P, Devaux B, Kedinger C. The abundance and in vitro DNA binding of three cellular proteins interacting with the adenovirus EIIa early promoter are not modified by the EIa gene products. Mol Cell Biol. 1987;7:3806–3817.
   Google Scholar
• Ginsberg D, Vairo G, Chittenden T, et al. E2F-4, a new member of the E2F transcription factor family, interacts with p107. Genes Dev. 1994;8:2665–2679.
   Google Scholar
• Laurendi G, Donfrancesco C, Palmieri L, et al. Association of lifestyle and cardiovascular risk factors with lung function in a sample of the adult Italian population: a cross-sectional survey. Respiration. 2015;89:33–40.
   Google Scholar