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Gene Expression Modifications in Type 2 Diabetes

  • Fernando Suarez-Sanchez
  • Jaime Gomez-Zamudio
Chapter

Abstract

We know that the mammalian genome is extensively transcribed, and the study of the gene expression would be a better tool to understand the molecular mechanisms that underlie the phenotype of the disease. Changes in gene expression are considered an important component of the pathogenesis of diabetes, and they may be the result of the direct effects of decreased insulin action via receptor-mediated signaling, as well as indirect effects secondary to the metabolic and humoral changes associated with the disease.

In this chapter, we will review some data regarding gene expression changes in four tissues that participate in the pathophysiology of obesity and T2D. The pancreas is an organ that is responsible of insulin production and secretion. This hormone is the key player in glucose and energy homeostasis in cells of almost every tissue. The liver is another organ that plays a role in energy metabolism by regulating glycogen storage and lipid metabolism. The adipose tissue has been implicated in the T2D development mainly because its function is not concealed to lipid storage but because it has important endocrine functions. Finally, we will discuss gene expression changes in muscle which is the tissue that consumes a large amount of circulating glucose and become insulin resistant after exposure to negative environments and genetic stimulus.

Keywords

Adipose tissue Pancreas Muscle Liver Gene expression Inflammation Insulin resistance 

Notes

Glossary

3′-UTR region

Untranslated regions (UTRs) at the 3′end of mRNA contain important sequences that are related to the regulation of gene translation. The 3′-UTR plays a critical role in the stability of mRNA and in posttranscriptional regulation.

Apoptosis

Is a process of programmed cell death, which is considered to be important in several processes including normal cell turnover, development and function of immune system, hormone-dependent atrophy, embryonic development, and chemical-induced cell death. Human conditions such as neurodegenerative diseases, ischemic damage, autoimmune disorders, and many types of cancer are related to inappropriate apoptosis.

Bariatric surgery

Is a surgical process employed to reduce weight in obese patients, by restricting the amount of food the stomach can hold, causing malabsorption of nutrients. The most common bariatric surgery procedures are gastric bypass, sleeve gastrectomy, adjustable gastric band, and biliopancreatic diversion with duodenal switch.

Damage-associated molecular patterns (DAMPs)

Are cell-derived molecules that can initiate and perpetuate immunity in response to trauma, ischemia, and other setting of tissue damage in the absence of overt pathogenic infection. DAMPs can be found into the nucleus and cytoplasm (HMGB1), cytoplasm alone (S100 proteins), exosomes (HSP), extracellular matrix (hyaluronic acid), and in plasma such as complement (C3a, C4a, and C5a). Examples of nonprotein DAMPs include ATP, uric acid, heparin sulfate, RNA, and DNA. Increased levels of DAMPs are associated with inflammatory diseases such as sepsis, arthritis, atherosclerosis, systemic lupus erythematosus, Crohn’s disease, and cancer.

Deacetylation

Histones acetylation has been linked to transcriptional activation. The enzymes regulating the histone acetylation are the histone acetyltransferases (HATs). On the contrary, the deacetylation by histone deacetylases (HDACs) is related to transcriptional repression.

DNA hypermethylation

DNA methylation is a heritable epigenetic mark that involves the covalent transfer of a methyl group to a cytosine ring of DNA. The methylation reaction is catalyzed by a family of DNA methyltransferases (DNMTs). DNA methylation is associated with decreased transcriptional activity.

Enhancer

Is a DNA sequence that activators or transcriptional factors bind and increase gene transcription. Its location is variable in the gene; it can be present in the 5′-UTR, 3′-UTR, or into the coding region of the gene.

Epigenetics

Epigenetics is the study of biological mechanisms that switch genes on and off. There are three major levels of epigenetic changes: (1) chemical modification at nucleotide level (DNA methylation and RNA interference), (2) modifications at histone level, and (3) nucleosome remodeling.

Glycosylated hemoglobin (HbA1c)

Is also known as glycated hemoglobin. The glycation of hemoglobin consists in a nonenzymatic interaction between glucose and the amino groups of the valine and lysine residues in hemoglobin. This interaction is irreversible and is a test that indicates the exposition of the proteins to glucose for the last 3 months.

Genome-wide association studies (GWAS)

Are studies that identify DNA markers (SNPs) in the whole genome that are common to the human genome and to determine how these SNPs are distributed across different populations. GWAS are used to determine genetic risk markers associated with a disorder, for example, diabetes, obesity, hypertension, or cancer.

Knockout mice

Is a model used in the laboratory in which a mouse has inactivated or “knocked out” an existing gene by replacing it or disrupting it with an artificial piece of DNA.

Maturity-onset diabetes of the young (MODY)

Is a rare form of diabetes different from both type 1 and type 2 diabetes and runs strongly in families. It is caused by a mutation in a single gene.

OLEFT rats

The Otsuka Long-Evans Tokushima Fatty (OLETF) rat is an animal model of spontaneous T2D. This rat model of T2D is characterized by mild obesity with visceral fat accumulation and late-onset insulin resistance. It resembles human obese patients with T2D.

Pathogen-associated molecular patterns (PAMPs)

Are derived from microorganisms and recognized by pattern recognition receptor (PPR)-bearing cells of the innate immune system as well as many epithelial cells. Major PAMPs are microbial nucleic acids, including DNA, double-stranded RNA (dsRNA), single-stranded RNA (ssRNA), and 5′-triphosphate RNA, as well as lipoproteins, surface glycoproteins, and membrane components (peptidoglycans, lipoteichoic acid, lipopolysaccharide, and glycosylphosphatidylinositol).

Promoter

The promoters are sequences in the DNA that define the start point in the transcription of a gene.

Reactive oxygen species (ROS)

Are radical and non-radical oxygen species formed by the partial reduction of oxygen, for example, superoxide anion (O2), hydrogen peroxide (H2O2), and hydroxyl radical (HO•). They are generated endogenously by the oxidative phosphorylation process in the mitochondria or are produced from interactions with exogenous sources such as xenobiotic compounds.

Roux-en-Y gastric bypass (RYGB)

Is often called gastric bypass and is considered the “gold standard” of weight loss surgery. This surgery consists to create a new stomach pouch, using a small portion of the stomach. The smallest stomach is connected directly to the middle portion of the small intestine (jejunum), bypassing the rest of the stomach and the upper portion of the small intestine (duodenum).

Single nucleotide polymorphisms (SNPs)

Are a variation in a single position in a DNA sequence among individuals. This variation has to be present in almost 1% of a population to be considered as a SNP.

Streptozotocin (STZ)-induced diabetes

Streptozotocin is a glucosamine-nitrosourea compound derived from Streptomyces achromogenes. STZ is employed to induce cellular damage specifically in β-cells, resulting in hypoinsulinemia and hyperglycemia.

Transcriptomic

The transcriptome is the complete set of expression products transcribed from the genome in a specified tissue or populations of cells. Transcriptomic has emerged as a powerful technic that analyzes 1000 of genes in one sample using RNA microarrays. This technic has allowed the study of gene expression patterns on several tissues involved in the pathogenesis of the T2D and to identify genetic markers for the early diagnosis of T2D.

References

  1. 1.
    Kim AY, Park YJ, Pan X, Shin KC, Kwak SH, Bassas AF, et al. Obesity-induced DNA hypermethylation of the adiponectin gene mediates insulin resistance. Nat commun. 2015;6:7585.PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Houde AA, Legare C, Hould FS, Lebel S, Marceau P, Tchernof A, et al. Cross-tissue comparisons of leptin and adiponectin: DNA methylation profiles. Adipocytes. 2014;3(2):132–40.CrossRefGoogle Scholar
  3. 3.
    Wrann CD, Rosen ED. New insights into adipocyte-specific leptin gene expression. Adipocytes. 2012;1(3):168–72.CrossRefGoogle Scholar
  4. 4.
    Liu CW, Yang SY, Lin CK, Liu HS, Ho LT, Wu LY, et al. The forkhead transcription factor FOXO1 stimulates the expression of the adipocyte resistin gene. Gen Comp Endocrinol. 2014;196:41–51.PubMedCrossRefGoogle Scholar
  5. 5.
    Hoggard N, Cruickshank M, Moar KM, Bashir S, Mayer CD. Using gene expression to predict differences in the secretome of human omental vs. subcutaneous adipose tissue. Obesity (Silver Spring). 2012;20(6):1158–67.CrossRefGoogle Scholar
  6. 6.
    Gustafson B, Hammarstedt A, Hedjazifar S, Hoffmann JM, Svensson PA, Grimsby J, et al. BMP4 and BMP antagonists regulate human white and beige adipogenesis. Diabetes. 2015;64(5):1670–81.PubMedCrossRefGoogle Scholar
  7. 7.
    Muir LA, Neeley CK, Meyer KA, Baker NA, Brosius AM, Washabaugh AR, et al. Adipose tissue fibrosis, hypertrophy, and hyperplasia: correlations with diabetes in human obesity. Obesity (Silver Spring). 2016;24(3):597–605.CrossRefGoogle Scholar
  8. 8.
    Laramie JM, Wilk JB, Williamson SL, Nagle MW, Latourelle JC, Tobin JE, et al. Multiple genes influence BMI on chromosome 7q31–34: the NHLBI family heart study. Obesity (Silver Spring). 2009;17(12):2182–9.CrossRefGoogle Scholar
  9. 9.
    Wong JC, Krueger KC, Costa MJ, Aggarwal A, Du H, McLaughlin TL, et al. A glucocorticoid- and diet-responsive pathway toggles adipocyte precursor cell activity in vivo. Sci Signaling. 2016;9(451):ra103.CrossRefGoogle Scholar
  10. 10.
    Zhong QQ, Wang X, Li YF, Peng LJ, Jiang ZS. Secretory leukocyte protease inhibitor promising protective roles in obesity-associated atherosclerosis. Exp Biol Med (Maywood). 2017;242(3):250–7.CrossRefGoogle Scholar
  11. 11.
    Moreno-Navarrete JM, Ortega F, Serrano M, Rodriguez-Hermosa JI, Ricart W, Mingrone G, et al. CIDEC/FSP27 and PLIN1 gene expression run in parallel to mitochondrial genes in human adipose tissue, both increasing after weight loss. Int J Obes. 2013;38(6):865–72.Google Scholar
  12. 12.
    Sarkaria IS, Rizk NP, Grosser R, Goldman D, Finley DJ, Ghanie A, et al. Attaining proficiency in robotic-assisted minimally invasive esophagectomy while maximizing safety during procedure development. Innovations (Phila). 2016;11(4):268–73.CrossRefGoogle Scholar
  13. 13.
    Campbell KL, Foster-Schubert KE, Makar KW, Kratz M, Hagman D, Schur EA, et al. Gene expression changes in adipose tissue with diet- and/or exercise-induced weight loss. Cancer Prev Res (Phila). 2013;6(3):217–31.CrossRefGoogle Scholar
  14. 14.
    Pettersson AM, Acosta JR, Bjork C, Kratzel J, Stenson B, Blomqvist L, et al. MAFB as a novel regulator of human adipose tissue inflammation. Diabetologia. 2015;58(9):2115–23.PubMedCrossRefGoogle Scholar
  15. 15.
    Tran MT, Hamada M, Nakamura M, Jeon H, Kamei R, Tsunakawa Y, et al. MafB deficiency accelerates the development of obesity in mice. FEBS Open Bio. 2016;6(6):540–7.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Gogebakan O, Osterhoff MA, Schuler R, Pivovarova O, Kruse M, Seltmann AC, et al. GIP increases adipose tissue expression and blood levels of MCP-1 in humans and links high energy diets to inflammation: a randomised trial. Diabetologia. 2015;58(8):1759–68.PubMedCrossRefGoogle Scholar
  17. 17.
    Sindhu S, Thomas R, Shihab P, Sriraman D, Behbehani K, Ahmad R. Obesity is a positive modulator of IL-6R and IL-6 expression in the subcutaneous adipose tissue: significance for metabolic inflammation. PLoS One. 2015;10(7):e0133494.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Qatanani M, Lazar MA. Mechanisms of obesity-associated insulin resistance: many choices on the menu. Genes Dev. 2007;21(12):1443–55.PubMedCrossRefGoogle Scholar
  19. 19.
    Moreno-Navarrete JM, Moreno M, Vidal M, Ortega F, Ricart W, Fernandez-Real JM. DBC1 is involved in adipocyte inflammation and is a possible marker of human adipose tissue senescence. Obesity (Silver Spring). 2015;23(3):519–22.CrossRefGoogle Scholar
  20. 20.
    Gillum MP, Kotas ME, Erion DM, Kursawe R, Chatterjee P, Nead KT, et al. SirT1 regulates adipose tissue inflammation. Diabetes. 2011;60(12):3235–45.PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Yin Z, Deng T, Peterson LE, Yu R, Lin J, Hamilton DJ, et al. Transcriptome analysis of human adipocytes implicates the NOD-like receptor pathway in obesity-induced adipose inflammation. Mol Cell Endocrinol. 2014;394(1–2):80–7.PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Kim Y, Wang W, Okla M, Kang I, Moreau R, Chung S. Suppression of NLRP3 inflammasome by gamma-tocotrienol ameliorates type 2 diabetes. J Lipid Res. 2016;57(1):66–76.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Healy NP, Kirwan AM, McArdle MA, Holohan K, Nongonierma AB, Keane D, et al. A casein hydrolysate protects mice against high-fat diet induced hyperglycemia by attenuating NLRP3 inflammasome-mediated inflammation and improving insulin signaling. Mol Nutr Food Res. 2016;60:2421.PubMedCrossRefGoogle Scholar
  24. 24.
    Ahmad F, Chung YW, Tang Y, Hockman SC, Liu S, Khan Y, et al. Phosphodiesterase 3B (PDE3B) regulates NLRP3 inflammasome in adipose tissue. Sci Rep. 2016;6:28056.PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Zhang SY, Lv Y, Zhang H, Gao S, Wang T, Feng J, et al. Adrenomedullin 2 improves early obesity-induced adipose insulin resistance by inhibiting the class II MHC in adipocytes. Diabetes. 2016;65(8):2342–55.PubMedCrossRefGoogle Scholar
  26. 26.
    Cho KW, Morris DL, DelProposto JL, Geletka L, Zamarron B, Martinez-Santibanez G, et al. An MHC II-dependent activation loop between adipose tissue macrophages and CD4+ T cells controls obesity-induced inflammation. Cell Rep. 2014;9(2):605–17.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Xiao L, Yang X, Lin Y, Li S, Jiang J, Qian S, et al. Large adipocytes function as antigen-presenting cells to activate CD4(+) T cells via upregulating MHCII in obesity. Int J Obes. 2016;40(1):112–20.CrossRefGoogle Scholar
  28. 28.
    van Greevenbroek MM, Ghosh S, van der Kallen CJ, Brouwers MC, Schalkwijk CG, Stehouwer CD. Up-regulation of the complement system in subcutaneous adipocytes from nonobese, hypertriglyceridemic subjects is associated with adipocyte insulin resistance. J Clin Endocrinol Metab. 2012;97(12):4742–52.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Olsson M, Olsson B, Jacobson P, Thelle DS, Bjorkegren J, Walley A, et al. Expression of the selenoprotein S (SELS) gene in subcutaneous adipose tissue and SELS genotype are associated with metabolic risk factors. Metabolism. 2011;60(1):114–20.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Lee YH, Tharp WG, Maple RL, Nair S, Permana PA, Pratley RE. Amyloid precursor protein expression is upregulated in adipocytes in obesity. Obesity (Silver Spring). 2008;16(7):1493–500.CrossRefGoogle Scholar
  31. 31.
    Curtis JM, Grimsrud PA, Wright WS, Xu X, Foncea RE, Graham DW, et al. Downregulation of adipose glutathione S-transferase A4 leads to increased protein carbonylation, oxidative stress, and mitochondrial dysfunction. Diabetes. 2010;59(5):1132–42.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Monk JM, Liddle DM, De Boer AA, Brown MJ, Power KA, Ma DW, et al. Fish-oil-derived n-3 PUFAs reduce inflammatory and chemotactic adipokine-mediated cross-talk between co-cultured murine splenic CD8+ T cells and adipocytes. J Nutr. 2015;145(4):829–38.PubMedCrossRefGoogle Scholar
  33. 33.
    Ronn T, Volkov P, Tornberg A, Elgzyri T, Hansson O, Eriksson KF, et al. Extensive changes in the transcriptional profile of human adipose tissue including genes involved in oxidative phosphorylation after a 6-month exercise intervention. Acta physiologica (Oxf). 2014;211(1):188–200.CrossRefGoogle Scholar
  34. 34.
    Mardinoglu A, Heiker JT, Gartner D, Bjornson E, Schon MR, Flehmig G, et al. Extensive weight loss reveals distinct gene expression changes in human subcutaneous and visceral adipose tissue. Sci Rep. 2015;5:14841.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Puri V, Ranjit S, Konda S, Nicoloro SM, Straubhaar J, Chawla A, et al. Cidea is associated with lipid droplets and insulin sensitivity in humans. Proc Natl Acad Sci U S A. 2008;105(22):7833–8.PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Wieser V, Adolph TE, Enrich B, Moser P, Moschen AR, Tilg H. Weight loss induced by bariatric surgery restores adipose tissue PNPLA3 expression. Liver Int. 2016;37(2):299–306.Google Scholar
  37. 37.
    Donkor J, Sparks LM, Xie H, Smith SR, Reue K. Adipose tissue lipin-1 expression is correlated with peroxisome proliferator-activated receptor alpha gene expression and insulin sensitivity in healthy young men. J Clin Endocrinol Metab. 2008;93(1):233–9.PubMedCrossRefGoogle Scholar
  38. 38.
    Mocanu AO, Mulya A, Huang H, Dan O, Shimizu H, Batayyah E, et al. Effect of Roux-en-Y gastric bypass on the NLRP3 inflammasome in adipose tissue from obese rats. PLoS One. 2015;10(10):e0139764.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Monte SV, Caruana JA, Ghanim H, Sia CL, Korzeniewski K, Schentag JJ, et al. Reduction in endotoxemia, oxidative and inflammatory stress, and insulin resistance after Roux-en-Y gastric bypass surgery in patients with morbid obesity and type 2 diabetes mellitus. Surgery. 2012;151(4):587–93.PubMedCrossRefGoogle Scholar
  40. 40.
    Nilsson E, Jansson PA, Perfilyev A, Volkov P, Pedersen M, Svensson MK, et al. Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes. Diabetes. 2014;63(9):2962–76.PubMedCrossRefGoogle Scholar
  41. 41.
    Danielsson A, Ponten F, Fagerberg L, Hallstrom BM, Schwenk JM, Uhlen M, et al. The human pancreas proteome defined by transcriptomics and antibody-based profiling. PLoS One. 2014;9(12):e115421.PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Yang J, Li L, Raptis D, Li X, Li F, Chen B, et al. Pancreatic stone protein/regenerating protein (PSP/reg): a novel secreted protein up-regulated in type 2 diabetes mellitus. Endocrine. 2015;48(3):856–62.PubMedCrossRefGoogle Scholar
  43. 43.
    Pedica F, Beccari S, Pedron S, Montagna L, Piccoli P, Doglioni C, et al. PDX-1 (pancreatic/duodenal homeobox-1 protein 1). Pathologica. 2014;106(4):315–21.PubMedGoogle Scholar
  44. 44.
    Miyazaki S, Tashiro F, Miyazaki J. Transgenic expression of a single transcription factor Pdx1 induces transdifferentiation of pancreatic acinar cells to endocrine cells in adult mice. PLoS One. 2016;11(8):e0161190.PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Ardestani A, Paroni F, Azizi Z, Kaur S, Khobragade V, Yuan T, et al. MST1 is a key regulator of beta cell apoptosis and dysfunction in diabetes. Nat Med. 2014;20(4):385–97.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Bugliani M, Liechti R, Cheon H, Suleiman M, Marselli L, Kirkpatrick C, et al. Microarray analysis of isolated human islet transcriptome in type 2 diabetes and the role of the ubiquitin-proteasome system in pancreatic beta cell dysfunction. Mol Cell Endocrinol. 2013;367(1–2):1–10.PubMedCrossRefGoogle Scholar
  47. 47.
    Igoillo-Esteve M, Marselli L, Cunha DA, Ladriere L, Ortis F, Grieco FA, et al. Palmitate induces a pro-inflammatory response in human pancreatic islets that mimics CCL2 expression by beta cells in type 2 diabetes. Diabetologia. 2010;53(7):1395–405.PubMedCrossRefGoogle Scholar
  48. 48.
    He TT, Cao XP, Chen RZ, Zhu XN, Wang XL, Li YB, et al. Down-regulation of peroxisome proliferator-activated receptor gamma coactivator-1alpha expression in fatty acid-induced pancreatic beta-cell apoptosis involves nuclear factor-kappaB pathway. Chin Med J. 2011;124(22):3657–63.PubMedGoogle Scholar
  49. 49.
    Kelpe CL, Moore PC, Parazzoli SD, Wicksteed B, Rhodes CJ, Poitout V. Palmitate inhibition of insulin gene expression is mediated at the transcriptional level via ceramide synthesis. J Biol Chem. 2003;278(32):30015–21.PubMedCrossRefGoogle Scholar
  50. 50.
    Taneera J, Lang S, Sharma A, Fadista J, Zhou Y, Ahlqvist E, et al. A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets. Cell Metab. 2012;16(1):122–34.PubMedCrossRefGoogle Scholar
  51. 51.
    Bonnavion R, Jaafar R, Kerr-Conte J, Assade F, van Stralen E, Leteurtre E, et al. Both PAX4 and MAFA are expressed in a substantial proportion of normal human pancreatic alpha cells and deregulated in patients with type 2 diabetes. PLoS One. 2013;8(8):e72194.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Jo W, Endo M, Ishizu K, Nakamura A, Tajima T. A novel PAX4 mutation in a Japanese patient with maturity-onset diabetes of the young. Tohoku J Exp Med. 2011;223(2):113–8.PubMedCrossRefGoogle Scholar
  53. 53.
    Liu T, Zhao Y, Tang N, Feng R, Yang X, Lu N, et al. Pax6 directly down-regulates Pcsk1n expression thereby regulating PC1/3 dependent proinsulin processing. PLoS One. 2012;7(10):e46934.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Heddad Masson M, Poisson C, Guerardel A, Mamin A, Philippe J, Gosmain Y. Foxa1 and Foxa2 regulate alpha-cell differentiation, glucagon biosynthesis, and secretion. Endocrinology. 2014;155(10):3781–92.PubMedCrossRefGoogle Scholar
  55. 55.
    Shimo N, Matsuoka TA, Miyatsuka T, Takebe S, Tochino Y, Takahara M, et al. Short-term selective alleviation of glucotoxicity and lipotoxicity ameliorates the suppressed expression of key beta-cell factors under diabetic conditions. Biochem Biophys Res Commun. 2015;467(4):948–54.PubMedCrossRefGoogle Scholar
  56. 56.
    Cnop M, Abdulkarim B, Bottu G, Cunha DA, Igoillo-Esteve M, Masini M, et al. RNA sequencing identifies dysregulation of the human pancreatic islet transcriptome by the saturated fatty acid palmitate. Diabetes. 2014;63(6):1978.PubMedCrossRefGoogle Scholar
  57. 57.
    Hall E, Volkov P, Dayeh T, Bacos K, Ronn T, Nitert MD, et al. Effects of palmitate on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets. BMC Med. 2014;12:103.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Guo S, Dai C, Guo M, Taylor B, Harmon JS, Sander M, et al. Inactivation of specific beta cell transcription factors in type 2 diabetes. J Clin Invest. 2013;123(8):3305–16.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Huang C, Yuan L, Cao S. Endogenous GLP-1 as a key self-defense molecule against lipotoxicity in pancreatic islets. Int J Mol Med. 2015;36(1):173–85.PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Yang Y, Tong Y, Gong M, Lu Y, Wang C, Zhou M, et al. Activation of PPARbeta/delta protects pancreatic beta cells from palmitate-induced apoptosis by upregulating the expression of GLP-1 receptor. Cell Signal. 2014;26(2):268–78.PubMedCrossRefGoogle Scholar
  61. 61.
    Dayeh T, Volkov P, Salo S, Hall E, Nilsson E, Olsson AH, et al. Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion. PLoS Genet. 2014;10(3):e1004160.PubMedPubMedCentralCrossRefGoogle Scholar
  62. 62.
    Ling C, Del Guerra S, Lupi R, Rönn T, Granhall C, Luthman H, et al. Epigenetic regulation of PPARGC1A in human type 2 diabetic islets and effect on insulin secretion. Diabetologia. 2008;51(4):615–22.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Fadista J, Vikman P, Laakso EO, Mollet IG, Esguerra JL, Taneera J, et al. Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism. Proc Natl Acad Sci U S A. 2014;111(38):13924–9.PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Morán I, Akerman İ, van de Bunt M, Xie R, Benazra M, Nammo T, et al. Human β cell transcriptome analysis uncovers lncRNAs that are tissue-specific, dynamically regulated, and abnormally expressed in type 2 diabetes. Cell Metab. 2012;16(4):435–48.PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Nogueira TC, Paula FM, Villate O, Colli ML, Moura RF, Cunha DA, et al. GLIS3, a susceptibility gene for type 1 and type 2 diabetes, modulates pancreatic beta cell apoptosis via regulation of a splice variant of the BH3-only protein Bim. PLoS Genet. 2013;9(5):e1003532.PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Ao D, Wang HJ, Wang LF, Song JY, Yang HX, Wang Y. The rs2237892 polymorphism in KCNQ1 influences gestational diabetes mellitus and glucose levels: a case-control study and meta-analysis. PLoS One. 2015;10(6):e0128901.PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Wang H, Miao K, Zhao J, Liu L, Cui G, Chen C, et al. Common variants in KCNQ1 confer increased risk of type 2 diabetes and contribute to the diabetic epidemic in East Asians: a replication and meta-analysis. Ann Hum Genet. 2013;77(5):380–91.PubMedCrossRefGoogle Scholar
  68. 68.
    Thakur N, Tiwari VK, Thomassin H, Pandey RR, Kanduri M, Gondor A, et al. An antisense RNA regulates the bidirectional silencing property of the Kcnq1 imprinting control region. Mol Cell Biol. 2004;24(18):7855–62.PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Arnes L, Akerman I, Balderes DA, Ferrer J. betalinc1 encodes a long noncoding RNA that regulates islet beta-cell formation and function. Gene Dev. 2016;30(5):502–7.PubMedCrossRefGoogle Scholar
  70. 70.
    Arnes L, Sussel L. Epigenetic modifications and long noncoding RNAs influence pancreas development and function. Trends Genet. 2015;31(6):290–9.PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    Montoya-Morales DS, de los Angeles Tapia-Gonzalez M, Alamilla-Lugo L, Sosa-Caballero A, Munoz-Solis A, Jimenez-Sanchez M. Alterations of the thyroid function in patients with morbid obesity. Rev Med Inst Mex Seguro Soc. 2015;53(Suppl 1):S18–22.PubMedGoogle Scholar
  72. 72.
    Palsgaard J, Brons C, Friedrichsen M, Dominguez H, Jensen M, Storgaard H, et al. Gene expression in skeletal muscle biopsies from people with type 2 diabetes and relatives: differential regulation of insulin signaling pathways. PLoS One. 2009;4(8):e6575.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Sreekumar R, Halvatsiotis P, Schimke JC, Nair KS. Gene expression profile in skeletal muscle of type 2 diabetes and the effect of insulin treatment. Diabetes. 2002;51(6):1913–20.PubMedCrossRefGoogle Scholar
  74. 74.
    Wang M, Wang XC, Zhao L, Zhang Y, Yao LL, Lin Y, et al. Oligonucleotide microarray analysis reveals dysregulation of energy-related metabolism in insulin-sensitive tissues of type 2 diabetes patients. Genet Mol Res. 2014;13(2):4494–504.PubMedCrossRefGoogle Scholar
  75. 75.
    Yechoor VK, Patti ME, Saccone R, Kahn CR. Coordinated patterns of gene expression for substrate and energy metabolism in skeletal muscle of diabetic mice. Proc Natl Acad Sci U S A. 2002;99(16):10587–92.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Patti ME, Butte AJ, Crunkhorn S, Cusi K, Berria R, Kashyap S, et al. Coordinated reduction of genes of oxidative metabolism in humans with insulin resistance and diabetes: potential role of PGC1 and NRF1. Proc Natl Acad Sci U S A. 2003;100(14):8466–71.PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Bravard A, Lefai E, Meugnier E, Pesenti S, Disse E, Vouillarmet J, et al. FTO is increased in muscle during type 2 diabetes, and its overexpression in myotubes alters insulin signaling, enhances lipogenesis and ROS production, and induces mitochondrial dysfunction. Diabetes. 2011;60(1):258–68.PubMedCrossRefGoogle Scholar
  78. 78.
    Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003;34(3):267–73.PubMedCrossRefGoogle Scholar
  79. 79.
    Patti ME. Gene expression in humans with diabetes and prediabetes: what have we learned about diabetes pathophysiology? Curr Opin Clin Nutr Metab Care. 2004;7(4):383–90.PubMedCrossRefGoogle Scholar
  80. 80.
    Rome S, Clement K, Rabasa-Lhoret R, Loizon E, Poitou C, Barsh GS, et al. Microarray profiling of human skeletal muscle reveals that insulin regulates approximately 800 genes during a hyperinsulinemic clamp. J Biol Chem. 2003;278(20):18063–8.PubMedCrossRefGoogle Scholar
  81. 81.
    Wu X, Wang J, Cui X, Maianu L, Rhees B, Rosinski J, et al. The effect of insulin on expression of genes and biochemical pathways in human skeletal muscle. Endocrine. 2007;31(1):5–17.PubMedCrossRefGoogle Scholar
  82. 82.
    Zhang F, Xu X, Zhang Y, Zhou B, He Z, Zhai Q. Gene expression profile analysis of type 2 diabetic mouse liver. PLoS One. 2013;8(3):e57766.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Haeusler RA, Camastra S, Astiarraga B, Nannipieri M, Anselmino M, Ferrannini E. Decreased expression of hepatic glucokinase in type 2 diabetes. Mol Metab. 2015;4(3):222–6.PubMedCrossRefGoogle Scholar
  84. 84.
    Takamura T, Honda M, Sakai Y, Ando H, Shimizu A, Ota T, et al. Gene expression profiles in peripheral blood mononuclear cells reflect the pathophysiology of type 2 diabetes. Biochem Biophys Res Commun. 2007;361(2):379–84.PubMedCrossRefGoogle Scholar
  85. 85.
    Misu H, Takamura T, Matsuzawa N, Shimizu A, Ota T, Sakurai M, et al. Genes involved in oxidative phosphorylation are coordinately upregulated with fasting hyperglycaemia in livers of patients with type 2 diabetes. Diabetologia. 2007;50(2):268–77.PubMedCrossRefGoogle Scholar
  86. 86.
    Manoel-Caetano FS, Xavier DJ, Evangelista AF, Takahashi P, Collares CV, Puthier D, et al. Gene expression profiles displayed by peripheral blood mononuclear cells from patients with type 2 diabetes mellitus focusing on biological processes implicated on the pathogenesis of the disease. Gene. 2012;511(2):151–60.PubMedCrossRefGoogle Scholar
  87. 87.
    Hayashi Y, Kajimoto K, Iida S, Sato Y, Mizufune S, Kaji N, et al. DNA microarray analysis of whole blood cells and insulin-sensitive tissues reveals the usefulness of blood RNA profiling as a source of markers for predicting type 2 diabetes. Biol Pharm Bull. 2010;33(6):1033–42.PubMedCrossRefGoogle Scholar
  88. 88.
    Zhang J, Li S, Li L, Li M, Guo C, Yao J, et al. Exosome and exosomal microRNA: trafficking, sorting, and function. Genomics Proteomics Bioinformatics. 2015;13(1):17–24.PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    Tang X, Tang G, Ozcan S. Role of microRNAs in diabetes. Biochim Biophys Acta. 2008;1779(11):697–701.PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Wang C, Wan S, Yang T, Niu D, Zhang A, Yang C, et al. Increased serum microRNAs are closely associated with the presence of microvascular complications in type 2 diabetes mellitus. Sci Rep. 2016;6:20032.PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Thomou T, Mori MA, Dreyfuss JM, Konishi M, Sakaguchi M, Wolfrum C, et al. Adipose-derived circulating miRNAs regulate gene expression in other tissues. Nature. 2017;542(7642):450–5.PubMedPubMedCentralCrossRefGoogle Scholar

Suggested/Further Reading

  1. Bugliani M, Liechti R, Cheon H, Suleiman M, Marselli L, Kirkpatrick C, et al. Microarray analysis of isolated human islet transcriptome in type 2 diabetes and the role of the ubiquitin-proteasome system in pancreatic beta cell dysfunction. Mol Cell Endocrinol. 2013;367(1–2):1–10. (This paper highlights the importance of the ubiquitin-proteasome system in beta cell dysfunction in human T2D).PubMedCrossRefGoogle Scholar
  2. Danielsson A, Ponten F, Fagerberg L, Hallstrom BM, Schwenk JM, Uhlen M, et al. The human pancreas proteome defined by transcriptomics and antibody-based profiling. PLoS One. 2014;9(12):e115421. (They employed genome-wide RNA sequencing to identify genes with elevated expression in pancreas).PubMedPubMedCentralCrossRefGoogle Scholar
  3. Hayashi Y, Kajimoto K, Iida S, Sato Y, Mizufune S, Kaji N, et al. DNA microarray analysis of whole blood cells and insulin-sensitive tissues reveals the usefulness of blood RNA profiling as a source of markers for predicting type 2 diabetes. Biol Pharm Bull. 2010;33(6):1033–42. In this paper compare the expression pattern of different insulin sensitive tissues with RNA expression in blood samples from diabetic patients.PubMedCrossRefGoogle Scholar
  4. Hoggard N, Cruickshank M, Moar KM, Bashir S, Mayer CD. Using gene expression to predict differences in the secretome of human omental vs. subcutaneous adipose tissue. Obesity (Silver Spring). 2012;20(6):1158–67. This paper get light into the proteins that are secreted by adipose tissue and their putative role as signaling molecules.CrossRefGoogle Scholar
  5. Igoillo-Esteve M, Marselli L, Cunha DA, Ladriere L, Ortis F, Grieco FA, et al. Palmitate induces a pro-inflammatory response in human pancreatic islets that mimics CCL2 expression by beta cells in type 2 diabetes. Diabetologia. 2010;53(7):1395–405. This paper highlights the role of saturated fatty acids in inflammation and its effect on beta cell.PubMedCrossRefGoogle Scholar
  6. Jenkinson CP, Göring HH, Arya R, Blangero J, Duggirala R, DeFronzo RA. Transcriptomics in type 2 diabetes: Bridging the gap between genotype and phenotype. Genomics Data. 2016;8:25–36. This paper described the importance of the transcriptome to identify genes related to diabetes development.PubMedCrossRefGoogle Scholar
  7. Patti ME. Gene expression in humans with diabetes and prediabetes: what have we learned about diabetes pathophysiology? Curr Opin Clin Nutr Metab Care. 2004;7(4):383–90. This paper review about gene expression of genes related to diabetes pathogenesis.PubMedCrossRefGoogle Scholar
  8. Wang M, Wang XC, Zhao L, Zhang Y, Yao LL, Lin Y, et al. Oligonucleotide microarray analysis reveals dysregulation of energy-related metabolism in insulin-sensitive tissues of type 2 diabetes patients. Genet Mol Res. 2014;13(2):4494–504. In this paper compare the expression pattern of different insulin sensitive tissues from diabetic patients.PubMedCrossRefGoogle Scholar
  9. Wang C, Wan S, Yang T, Niu D, Zhang A, Yang C, et al. Increased serum microRNAs are closely associated with the presence of microvascular complications in type 2 diabetes mellitus. Sci Rep. 2016;6:20032. This paper focuses on the importance to study the miRNAs expression in blood circulation created to diabetes and vascular complications.PubMedPubMedCentralCrossRefGoogle Scholar
  10. Yin Z, Deng T, Peterson LE, Yu R, Lin J, Hamilton DJ, et al. Transcriptome analysis of human adipocytes implicates the NOD-like receptor pathway in obesity-induced adipose inflammation. Mol Cell Endocrinol. 2014;394(1–2):80–7. This paper describes the role of NOD-like receptor pathway in adipose inflammation.PubMedPubMedCentralCrossRefGoogle Scholar
  11. Jiang C, Qu A, Matsubara T, Chanturiya T, Jou W, Gavrilova O, Shah YM, Gonzalez FJ. Disruption of hypoxia-inducible factor 1 in adipocytes improves insulin sensitivity and decreases adiposity in high-fat diet-fed mice. Diabetes. 2011;60(10):2484–95.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Fernando Suarez-Sanchez
    • 1
  • Jaime Gomez-Zamudio
    • 1
  1. 1.Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI IMSSMexico CityMexico

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