DNA methylation profiling of CD04+/CD08+ T cells reveals pathogenic mechanisms in increasing hyperglycemia: PIRAMIDE pilot study

Giuditta Benincasa, Monica Franzese, Concetta Schiano, Raffaele Marfella, Marco Miceli, Teresa Infante, Celestino Sardu, Mario Zanfardino, Ornella Affinito, Gelsomina Mansueto, Linda Sommese, Giovanni Francesco Nicoletti, Marco Salvatore, Giuseppe Paolisso, Claudio Napoli, Giuditta Benincasa, Monica Franzese, Concetta Schiano, Raffaele Marfella, Marco Miceli, Teresa Infante, Celestino Sardu, Mario Zanfardino, Ornella Affinito, Gelsomina Mansueto, Linda Sommese, Giovanni Francesco Nicoletti, Marco Salvatore, Giuseppe Paolisso, Claudio Napoli

Abstract

Background: DNA methylation can play a pathogenic role in the early stages of hyperglycemia linking homeostasis imbalance and vascular damage.

Material and methods: We investigated DNA methylome by RRBS in CD04+ and CD08+ T cells from healthy subjects (HS) to pre-diabetics (Pre-Diab) and type 2 diabetic (T2D) patients to identify early biomarkers of glucose impairment and vascular damage. Our cross-sectional study enrolled 14 individuals from HS state to increasing hyperglycemia (pilot study, PIRAMIDE trial, NCT03792607).

Results: Globally, differentially methylated regions (DMRs) were mostly annotated to promoter regions. Hypermethylated DMRs were greater than hypomethylated in CD04+ T cells whereas CD08+ T showed an opposite trend. Moreover, DMRs overlapping between Pre-Diab and T2D patients were mostly hypermethylated in both T cells. Interestingly, SPARC was the most hypomethylated gene in Pre-Diab and its methylation level gradually decreased in T2D patients. Besides, SPARC showed a significant positive correlation with DBP (+0.76), HDL (+0.54), Creatinine (+0.83), LVDd (+0.98), LVSD (+0.98), LAD (+0.98), LVPWd (+0.84), AODd (+0.81), HR (+0.72), Triglycerides (+0.83), LAD (+0.69) and AODd (+0.52) whereas a negative correlation with Cholesterol (-0.52) and LDL (-0.71) in T2D.

Conclusion: SPARC hypomethylation in CD08+ T cells may be a useful biomarker of vascular complications in Pre-Diab with a possible role for primary prevention warranting further multicenter clinical trials to validate our findings.

Keywords: Cardiovascular complications; DNA methylation; Prediabetes; T cells; Type 2 diabetes.

Conflict of interest statement

The authors declare no conflict of interest.

© 2020 The Authors.

Figures

Fig. 1
Fig. 1
A) Dynamics of DNA methylation in different stages of impaired glucose homeostasis. PIRAMIDE clinical trial aimed at investigating early epigenetic-sensitive regulatory networks in different stages ranging from normoglycemia to Pre-Diab and conclamate T2D. B–C-D-E) Distribution of overlapping and unique DMRs. Venn diagrams show the distribution of unique and overlapping DMR-related genes which have been identified in our three groups. The number of unique (B and D) and overlapping (C and E) DMRs in both CD04+ and CD08+ T cells is reported.
Fig. 2
Fig. 2
Trend of methylation in overlapping DMR-related genes. The bar plots show the fold change (FC) of methylation level s associated to the top overlapping DMR-related genes in CD04+ (A and B) and CD08+ (C and D) T cells. Red circles indicate DMR-related genes with the higher FC of methylation in HS vs Pre-Diab and T2D (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3
Fig. 3
ChromHMM analysis parameters. In the upper panel, we report the combination of multiple marks (Emission and Transition parameters) (A-C) and the relative genomic annotation (Fold Enrichments Genome_18) from 18 emission states. In the lower panel, the bar plots show the enrichment score (−log10Pvalue) for Human Phenotype GO terms from genes associated to hypo- (D) and hyper-(E) states characterizing hyperglycemic status.
Fig. 4
Fig. 4
A) Association between DNA methylation profile and vascular damage in increasing hyperglycemia. Early modifications of DNA methylation underlying microvascular damages appear in CD04+ T cells of Pre-Diab patients . Otherwise, CD08+ T cells undergo to changes in DNA methylation already in Pre-Diab and persist in T2D state patients leading to abnormalities of micro- and macro-domains in vasculature of hyperglycemic patients. B) GeneMANIA network. GeneMANIA PPI network of the SPARC gene predicted 21 nodes and a total of 537 total links representing physical interactions mainly involved in extracellular matrix organization, platelet activation, and leukocyte migration.

References

    1. Tabàk A.G., Herder C., Rathmann W. Prediabetes: a high-risk state for developing diabetes. Lancet. 2012;379:2279–2290.
    1. Rao Kondapally Seshasai S., Kaptoge S., Thompson A. Diabetes mellitus, fasting glucose, and risk of cause-specific death. Engl J Med. 2011;364:829–841. doi: 10.1056/NEJMoa1008862.
    1. Liu H.H., Cao Y.X., Li S. Impacts of prediabetes mellitus alone or plus hypertension on the coronary severity and cardiovascular outcomes. Hypertension. 2018;71:1039–1046.
    1. Caballero A.E., Arora S., Saouaf R. Microvascular and macrovascular reactivity is reduced in subjects at risk for type 2 diabetes. Diabetes. 1999;48:1856–1862.
    1. García-Fernández A., Esteve-Pastor M.A., Rabadán I.R. Relationship of adverse events to quality of anticoagulation control in atrial fibrillation patients with diabetes: real-world data from the FANTASIIA registry. Ann. Med. 2020:1–22. doi: 10.1080/07853890.2020.1778176.
    1. Jones P.A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 2012;13:484–492. doi: 10.1038/nrg3230.
    1. Napoli C., Benincasa G., Schiano C. Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients. Eur Heart J Cardiovasc Pharmacother. 2020;6(4):239–247. doi: 10.1093/ehjcvp/pvz062.
    1. Sommese L., Benincasa G., Lanza M. Novel epigenetic-sensitive clinical challenges both in type 1 and type 2 diabetes. J. Diabet. Complicat. 2018;32:1076–1084. doi: 10.1016/j.jdiacomp.2018.08.012.
    1. Sommese L., Zullo A., Mancini F.P. Clinical relevance of epigenetics in the onset and management of type 2 diabetes mellitus. Epigenetics. 2017;12:401–415. doi: 10.1080/15592294.2016.1278097.
    1. Hidalgo B., Irvin M.R., Sha J., Zhi D. Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study. Diabetes. 2014;63:801–807. doi: 10.2337/db13-1100.
    1. Hwang J.Y., Lee H.J., Go M.J. Genome-wide methylation analysis identifies ELOVL5 as an epigenetic biomarker for the risk of type 2 diabetes mellitus. Sci. Rep. 2018;8:14862. doi: 10.1038/s41598-018-33238-9.
    1. Mudry J.M., Lassiter D.G., Nylén C. Insulin and glucose alter death-associated protein kinase 3 (DAPK3) DNA methylation in human skeletal muscle. Diabetes. 2017;66:651–662. doi: 10.2337/db16-0882.
    1. Simar D., Versteyhe S., Donkin I. DNA methylation is altered in B and NK lymphocytes in obese and type 2 diabetic human. Metabolism. 2014;63:1188–1197. doi: 10.1016/j.metabol.2014.05.014.
    1. de Nigris F., Cacciatore F., Mancini F.P. Epigenetic hallmarks of fetal early atherosclerotic lesions in humans. JAMA Cardiol. 2018;3:1184–1191. doi: 10.1001/jamacardio.2018.3546.
    1. Infante T., Forte E., Punzo B. Correlation of circulating miR-765, miR-93-5p, and miR-433-3p to obstructive coronary heart disease evaluated by cardiac computed tomography. Am. J. Cardiol. 2019;124:176–182. doi: 10.1016/j.amjcard.2019.04.016.
    1. Infante T., Forte E., Schiano C. Evidence of association of circulating epigenetic-sensitive biomarkers with suspected coronary heart disease evaluated by cardiac computed tomography. PloS One. 2019;14 doi: 10.1371/journal.pone.0210909.
    1. Schiano C., Costa V., Aprile M. Heart failure: pilot transcriptomic analysis of cardiac tissue by RNA-sequencing. Cardiol. J. 2017;24:539–553. doi: 10.5603/CJ.a2017.0052.
    1. Eberle C., Merki E., Yamashita T. Maternal immunization affects in utero programming of insulin resistance and type 2 diabetes. PloS One. 2012;7 doi: 10.1371/journal.pone.0045361.
    1. Napoli C., Crudele V., Soricelli A. Primary prevention of atherosclerosis: a clinical challenge for the reversal of epigenetic mechanisms? Circulation. 2012;125:2363–2373. doi: 10.1161/CIRCULATIONAHA.111.085787.
    1. Napoli C., Infante T., Casamassimi A. Maternal-foetal epigenetic interactions in the beginning of cardiovascular damage. Cardiovasc. Res. 2011;92:367–374. doi: 10.1093/cvr/cvr201.
    1. Napoli C., Lerman L.O., de Nigris F. Rethinking primary prevention of atherosclerosis-related diseases. Circulation. 2006;114:2517–2527. doi: 10.1161/CIRCULATIONAHA.105.570358.
    1. Benincasa G., Marfella R., Schiano C. Perturbation of interactome through micro-RNA and methylome analysis in diabetes endophenotypes: the PIRAMIDE pathogenic clinical study design. Int. J. Clin. Trials. 2019;6:117–121.
    1. Li J., Zhu X., Yu K. Genome-wide analysis of DNA methylation and acute coronary syndrome. Circ. Res. 2017;120:1754–1767. doi: 10.1161/CIRCRESAHA.116.310324.
    1. Ferreiro J.L., Angiolillo D.J. Diabetes and antiplatelet therapy in acute coronary syndrome. Circulation. 2011;123:798–813. doi: 10.1161/CIRCULATIONAHA.109.913376.
    1. Tang T.T., Zhu Y.C., Dong N.G. Pathologic T-cell response in ischaemic failing hearts elucidated by T-cell receptor sequencing and phenotypic characterization. Eur. Heart J. 2019;40:3924–3933. doi: 10.1093/eurheartj/ehz516.
    1. Arbore G., West E.E., Rahman J. Complement receptor CD46 co-stimulates optimal human CD8+ T cell effector function via fatty acid metabolism. Nat. Commun. 2018;9:4186. doi: 10.1038/s41467-018-06706-z.
    1. Guo H., Zhu P., Guo F. Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing. Nat. Protoc. 2015;10:645–659.
    1. Benincasa G., Mansueto G., Napoli C. Fluid-based assays and precision medicine of cardiovascular diseases: the 'hope' for Pandora's box? J. Clin. Pathol. 2019;72:785–799. doi: 10.1136/jclinpath-2019-206178.
    1. Disclosures: standards of medical care in diabetes-2019. Diabetes Care. 2019;42:184–186. doi: 10.2337/dc19-Sdis01.
    1. Akalin A., Kormaksson M., Li S. MethylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol. 2012;13:87. doi: 10.1186/gb-2012-13-10-r87.
    1. Yu G., Wang L.G., He Q.Y. ChIPseeker: a R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 2015;31:2382–2383. doi: 10.1093/bioinformatics/btv145.
    1. Ernst J., Kellis M. Chromatin-state discovery and genome annotation with ChromHMM. Nat. Protoc. 2017;12:2478–2492. doi: 10.1038/nprot.2017.124.
    1. Warde-Farley David, Donaldson Sylva L., Comes Ovi. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38:214–220. doi: 10.1093/nar/gkq537.
    1. Marfella R., Amarelli C., Cacciatore F. Lipid accumulation in hearts transplanted from nondiabetic donors to diabetic recipients. J. Am. Coll. Cardiol. 2020;75:1249–1262. doi: 10.1016/j.jacc.2020.01.018.
    1. Yang B.T., Dayeh T.A., Volkov P.A. Increased DNA methylation and decreased expression of PDX-1 in pancreatic islets from patients with type 2 diabetes. Mol. Endocrinol. 2012;26:1203–1212. doi: 10.1210/me.2012-1004.
    1. Nilsson E., Jansson P.A., Perfilyev A. Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes. Diabetes. 2014;63:2962–2976. doi: 10.2337/db13-1459.
    1. Curran M., Campbell J., Drayson M., Andrews R., Narendran P. Type 1 diabetes impairs the mobilisation of highly-differentiated CD8+T cells during a single bout of acute exercise. Exerc. Immunol. Rev. 2019;25:64–82.
    1. Pedersen B.S., Schwartz D.A., Yang I.V. Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics. 2012;28:2986–2988.
    1. Kos K., Wilding J.P. SPARC: a key player in the pathologies associated with obesity and diabetes. Nat. Rev. Endocrinol. 2010;6:225–235. doi: 10.1038/nrendo.2010.18.
    1. Xu L., Ping F., Yin J. Elevated plasma SPARC levels are associated with insulin resistance, dyslipidemia, and inflammation in gestational diabetes mellitus. PloS One. 2013;8 doi: 10.1371/journal.pone.0081615.
    1. Xu L., Niu M., Yu W. Associations between FGF21, osteonectin and bone turnover markers in type 2 diabetic patients with albuminuria. J. Diabet. Complicat. 2017;31:583–588. doi: 10.1016/j.jdiacomp.2016.11.012.
    1. Benjamin L.E. Glucose, VEGF-A, and diabetic complications. Am. J. Pathol. 2001;158:1181‐4. doi: 10.1016/S0002-9440(10)64066-7.
    1. Schiano C, Benincasa G, Infante T, Franzese M, Castaldo R, Fiorito C, Mansueto G, Grimaldi V, Della Valle G, Fatone G, Soricelli A, Nicoletti GF, Ruocco A, Mauro C, Salvatore M, Napoli C. Integrated analysis of DNA methylation profile of HLA-G gene and imaging in coronary heart disease: Pilot study. PLoS One. 2020 Aug;1315(8) doi: 10.1371/journal.pone.0236951.
    1. Pepin ME, Infante T, Benincasa G, Schiano C, Miceli M, Ceccarelli S, Megiorni F, Anastasiadou E, Della Valle G, Fatone G, Faenza M, Docimo L, Nicoletti GF, Marchese C, Wende AR, Napoli C. Differential DNA Methylation Encodes Proliferation and Senescence Programs in Human Adipose-Derived Mesenchymal Stem Cells. Front Genet. 2020 Apr 15;11:346. doi: 10.3389/fgene.2020.00346.
    1. Benincasa G, Marfella R, Della Mura N, Schiano C, Napoli C. Strengths and Opportunities of Network Medicine in Cardiovascular Diseases. Circ J. 2020 Jan 24;84(2):144-152. doi: 10.1253/circj.CJ-19-0879.
    1. Schiano C, Benincasa G, Franzese M, Della Mura N, Pane K, Salvatore M, Napoli C. Epigenetic-sensitive pathways in personalized therapy of major cardiovascular diseases. Pharmacol Ther. 2020 Jun;210:107514. doi: 10.1016/j.pharmthera.2020.107514.

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