DOI: http://dx.doi.org/10.18203/2349-3259.ijct20192094

Perturbation of interactome through micro-RNA and methylome analysis in diabetes endophenotypes: the PIRAMIDE pathogenic clinical study design

Giuditta Benincasa, Raffaele Marfella, Concetta Schiano, Claudio Napoli

Abstract


Background: The main challenge in type 2 diabetes (T2D) is to detect the regulators of pathogenic events during early stages of disease, as well as prevention and progression follow-up of cardiovascular (CV) complications. DNA methylation and micro-RNAs (miRNAs) are major components of the epigenome, which are involved in the diabetic interactome. This study protocol may contribute to advance our knowledge on molecular basis underlying T2D and its CV complications, as well as provide putative useful prognostic biomarkers.

Methods: The perturbation of interactome through micro-RNA and methylome analysis in diabetes endophenotypes: the PIRAMIDE pathogenic clinical study protocol is a cross-sectional research program planned to combine big data and network-based analysis aimed to investigate whether DNA methylation and miRNAs may act as simultaneous regulators of the interactome in T2D patients. Clinical datasets will be aggregate to large-scale DNA methylation, mRNA-Seq, and miRNA-Seq analysis performed both on purified CD4+ and CD8+ T cells isolated from 35 T2D patients and 35 sex and age-matched controls. DNA methylome data will be used as input for the weighted human DNA methylation PPI network (WMPN) algorithm. RNA sequencing data will be used as input data for the TargetScan algorithm. The primary endpoint will be to integrate both DNA methylation and miRNA networks to potentially capture which genes are simultaneously modulate by interactions between epigenetic changes. Then, statistical analysis will be performed to correlate these molecular modifications with development of T2D-related CV complications.

Conclusions: PIRAMIDE pathogenic clinical study protocol will test the hypothesis that simultaneous interactions between DNA methylation and miRNAs may hit T2D-associated candidate genes and predict the development of T2D-related CV complications.

Trial Registration: The ongoing PIRAMIDE pathogenic clinical study protocol has been registered on NIH website (NCT03792607).


Keywords


Type 2 diabetes, Prognostic biomarkers, Cardiovascular complications, Network analysis

Full Text:

PDF

References


American Diabetes Association. Cardiovascular disease and risk management: standards of medical care in diabetes-2018. Diabetes Care. 2018;41:S86-S104.

Low Wang CC, Hess CN, Hiatt WR, Goldfine AB. Clinical update: cardiovascular disease in diabetes mellitus: atherosclerotic cardiovascular disease and heart failure in type 2 diabetes mellitus -mechanisms, management, and clinical considerations. Circulation. 2016;133:2459-62.

Sachdev M, Sun JL, Tsiatis AA, Nelson CL, Mark DB, Jollis JG. The prognostic importance of comorbidity for mortality in patients with stable coronary artery disease. J Am Coll Cardiol. 2004;43:576-82.

Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration. Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol 2014;2:634-47.

Laslett LJ, Alagona P Jr, Clark BA 3rd, Drozda JP Jr, Saldivar F, Wilson SR, et al. The worldwide environment of cardiovascular disease: prevalence, diagnosis, therapy, and policy issues: a report from the American College of Cardiology. J Am Coll Cardiol. 2012;60:1-49.

Selvin E, Rawlings AM, Lutsey PL, Maruthur N, Pankow JS, Steffes M, et al. Fructosamine and glycated albumin and the risk of cardiovascular outcomes and death. Circulation. 2015;132:269-77.

Pradhan AD, Paynter NP, Everett BM, Glynn RJ, Amarenco P, Elam M, et al. Rationale and design of the pemafibrate to reduce cardiovascular outcomes by reducing triglycerides in patients with diabetes (PROMINENT) study. Am Heart J. 2018;206:80-93.

Lambrakis K, French JK, Scott IA, Briffa T, Brieger D, Farkouh ME, et al. The appropriateness of coronary investigation in myocardial injury and type 2 myocardial infarction (ACT-2): a randomized trial design. Am Heart J. 2018;208:11-20.

Dorcely B, Katz K, Jagannathan R, Chiang SS, Oluwadare B, Goldberg IJ, Bergman M. Novel biomarkers for prediabetes, diabetes, and associated complications. Diabetes Metab Syndr Obes. 2017;10:345-61.

Basu S, Sussman JB, Berkowitz SA, Hayward RA, Yudkin JS. Development and validation of risk equations for complications of type 2 diabetes (RECODe) using individual participant data from randomised trials. Lancet Diabetes Endocrinol. 2017;5:788-798.

Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007;445:881-5.

Scott LJ, Mohlke KL, Bonnycastle LL, Willer CJ, Li Y, Duren WL, Erdos MR, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science. 2007;316:1341-5.

Meigs JB, Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 2008;359:2208-19.

Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840-6.

Feinberg AP. The key role of epigenetics in human disease prevention and mitigation. N Engl J Med 2018;378:1323-1334.

Barroso M, Florindo C, Kalwa H, Silva Z, Turanov AA, Carlson B, et al. Inhibition of cellular methyltransferases promotes endothelial cell activation by suppressing glutathione peroxidase 1 protein expression. J Biol Chem. 2014;289:15350-62.

Sommese L, Zullo A, Mancini FP, Fabbricini R, Soricelli A, Napoli C, et al. Clinical relevance of epigenetics in the onset and management of type 2 diabetes mellitus. Epigenetics. 2017;12:401-15.

Sommese L, Benincasa G, Lanza M, Sorriento A, Schiano C, Lucchese R, et al. Novel epigenetic-sensitive clinical challenges both in type 1 and type 2 diabetes. J Diabetes Complications. 2018;32:1076-84.

Keating ST, Plutzky J, El-Osta A. Epigenetic changes in diabetes and cardiovascular risk. Circ Res. 2016;118:1706-22.

Wei Y, Yang CR, Wei YP, Zhao ZA, Hou Y, Schatten H, et al. Paternally induced transgenerational inheritance of susceptibility to diabetes in mammals. Proc Natl Acad Sci U S A. 2014;111:1873-8.

De Nigris F, Cacciatore F, Mancini FP, Vitale DF, Mansueto G, D'Armiento FP, et al. Epigenetic hallmarks of fetal early atherosclerotic lesions in humans. JAMA Cardiol. 2018;3:1184-91.

Napoli C, Infante T, Casamassimi A. Maternal-foetal epigenetic interactions in the beginning of cardiovascular damage. Cardiovasc Res. 2011;92:367-374.

Napoli C, Crudele V, Soricelli A, Al-Omran M, Vitale N, Infante T, et al. Primary prevention of atherosclerosis: a clinical challenge for the reversal of epigenetic mechanisms? Circulation. 2012;125:2363-73.

Santolini M, Barabási AL. Predicting perturbation patterns from the topology of biological networks. Proc Natl Acad Sci U S A. 2018;115:6375-83.

Barabási AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet. 2011;12:56-68.

Barabási AL. Network medicine-from obesity to the "diseasome". N Engl J Med. 2007;357:404-7.

Sharma A, Halu A, Decano JL, Padi M, Liu YY, Prasad RB, et al. Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates type 2 diabetes associated genes. NPJ Syst Biol Appl. 2018;4:25.

Liu H, Wang T, Liu H, Wei Y, Zhao G, Su J, et al. Detection of type 2 diabetes related modules and genes based on epigenetic networks. BMC Syst Biol. 2014;8:1-5.

Gong R, Chen M, Zhang C, Chen M, Haibin L. A comparison of gene expression profiles in patients with coronary artery disease, type 2 diabetes, and their coexisting conditions. Diagn Pathol. 2017;12:44.

Willmer T, Johnson R, Louw J, Pheiffer C. Blood-based DNA methylation biomarkers for type 2 diabetes: potential for clinical applications. Front Endocrinol (Lausanne). 2018;9:744.

Selbach M, Schwanhäusser B, Thierfelder N, Fang Z, Khanin R, Rajewsky N. Widespread changes in protein synthesis induced by microRNAs. Nature. 2008;455:58-63.