Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals
Autoři:
Monta Ustinova aff001; Ivars Silamikelis aff001; Ineta Kalnina aff001; Laura Ansone aff001; Vita Rovite aff001; Ilze Elbere aff001; Ilze Radovica-Spalvina aff001; Davids Fridmanis aff001; Jekaterina Aladyeva aff001; Ilze Konrade aff002; Valdis Pirags aff001; Janis Klovins aff001
Působiště autorů:
Latvian Biomedical Research and Study Centre, Riga, Latvia
aff001; Riga Stradins University, Riga, Latvia
aff002
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224835
Souhrn
Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin’s action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.
Klíčová slova:
CD coreceptors – Gastrointestinal tract – Gene expression – Gene ontologies – Immune response – Insulin – RNA sequencing – Transcriptome analysis
Zdroje
1. Standards of Medical Care in Diabetes-2017: Summary of Revisions. Diabetes Care. 2017;40(Suppl 1):S4–S5. doi: 10.2337/dc17-S003 27979887
2. Johnson JA, Simpson SH, Toth EL, Majumdar SR. Reduced cardiovascular morbidity and mortality associated with metformin use in subjects with Type 2 diabetes. Diabet Med. 2005;22(4):497–502. doi: 10.1111/j.1464-5491.2005.01448.x 15787679
3. Quinn BJ, Kitagawa H, Memmott RM, Gills JJ, Dennis PA. Repositioning metformin for cancer prevention and treatment. Trends Endocrinol Metab. 2013;24(9):469–80. doi: 10.1016/j.tem.2013.05.004 23773243
4. Currie CJ, Poole CD, Jenkins-Jones S, Gale EA, Johnson JA, Morgan CL. Mortality after incident cancer in people with and without type 2 diabetes: impact of metformin on survival. Diabetes Care. 2012;35(2):299–304. doi: 10.2337/dc11-1313 22266734
5. Velazquez EM, Mendoza S, Hamer T, Sosa F, Glueck CJ. Metformin therapy in polycystic ovary syndrome reduces hyperinsulinemia, insulin resistance, hyperandrogenemia, and systolic blood pressure, while facilitating normal menses and pregnancy. Metabolism. 1994;43(5):647–54. doi: 10.1016/0026-0495(94)90209-7 8177055
6. Tang T, Lord JM, Norman RJ, Yasmin E, Balen AH. Insulin-sensitising drugs (metformin, rosiglitazone, pioglitazone, D-chiro-inositol) for women with polycystic ovary syndrome, oligo amenorrhoea and subfertility. Cochrane Database Syst Rev. 2012(5):CD003053. doi: 10.1002/14651858.CD003053.pub5 22592687
7. Gupta A, Bisht B, Dey CS. Peripheral insulin-sensitizer drug metformin ameliorates neuronal insulin resistance and Alzheimer's-like changes. Neuropharmacology. 2011;60(6):910–20. doi: 10.1016/j.neuropharm.2011.01.033 21277873
8. Asadbegi M, Yaghmaei P, Salehi I, Ebrahim-Habibi A, Komaki A. Neuroprotective effects of metformin against Abeta-mediated inhibition of long-term potentiation in rats fed a high-fat diet. Brain Res Bull. 2016;121:178–85. doi: 10.1016/j.brainresbull.2016.02.005 26861514
9. Mendelsohn AR, Larrick JW. Rapamycin as an antiaging therapeutic?: targeting mammalian target of rapamycin to treat Hutchinson-Gilford progeria and neurodegenerative diseases. Rejuvenation Res. 2011;14(4):437–41. doi: 10.1089/rej.2011.1238 21851176
10. Zhou G, Myers R, Li Y, Chen Y, Shen X, Fenyk-Melody J, et al. Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Invest. 2001;108(8):1167–74. doi: 10.1172/JCI13505 11602624
11. Miller RA, Chu Q, Xie J, Foretz M, Viollet B, Birnbaum MJ. Biguanides suppress hepatic glucagon signalling by decreasing production of cyclic AMP. Nature. 2013;494(7436):256–60. doi: 10.1038/nature11808 23292513
12. El-Mir MY, Nogueira V, Fontaine E, Averet N, Rigoulet M, Leverve X. Dimethylbiguanide inhibits cell respiration via an indirect effect targeted on the respiratory chain complex I. J Biol Chem. 2000;275(1):223–8. doi: 10.1074/jbc.275.1.223 10617608
13. Wu H, Esteve E, Tremaroli V, Khan MT, Caesar R, Manneras-Holm L, et al. Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nat Med. 2017;23(7):850–8. doi: 10.1038/nm.4345 28530702
14. Cook MN, Girman CJ, Stein PP, Alexander CM. Initial monotherapy with either metformin or sulphonylureas often fails to achieve or maintain current glycaemic goals in patients with Type 2 diabetes in UK primary care. Diabet Med. 2007;24(4):350–8. doi: 10.1111/j.1464-5491.2007.02078.x 17335466
15. Kahn SE, Haffner SM, Heise MA, Herman WH, Holman RR, Jones NP, et al. Glycemic durability of rosiglitazone, metformin, or glyburide monotherapy. N Engl J Med. 2006;355(23):2427–43. doi: 10.1056/NEJMoa066224 17145742
16. Garber AJ, Duncan TG, Goodman AM, Mills DJ, Rohlf JL. Efficacy of metformin in type II diabetes: results of a double-blind, placebo-controlled, dose-response trial. Am J Med. 1997;103(6):491–7. doi: 10.1016/s0002-9343(97)00254-4 9428832
17. Zhou K, Donnelly L, Yang J, Li M, Deshmukh H, Van Zuydam N, et al. Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis. Lancet Diabetes Endocrinol. 2014;2(6):481–7. doi: 10.1016/S2213-8587(14)70050-6 24731673
18. Tkac I, Klimcakova L, Javorsky M, Fabianova M, Schroner Z, Hermanova H, et al. Pharmacogenomic association between a variant in SLC47A1 gene and therapeutic response to metformin in type 2 diabetes. Diabetes Obes Metab. 2013;15(2):189–91. doi: 10.1111/j.1463-1326.2012.01691.x 22882994
19. Shikata E, Yamamoto R, Takane H, Shigemasa C, Ikeda T, Otsubo K, et al. Human organic cation transporter (OCT1 and OCT2) gene polymorphisms and therapeutic effects of metformin. J Hum Genet. 2007;52(2):117–22. doi: 10.1007/s10038-006-0087-0 17111267
20. Choi JH, Yee SW, Ramirez AH, Morrissey KM, Jang GH, Joski PJ, et al. A common 5'-UTR variant in MATE2-K is associated with poor response to metformin. Clin Pharmacol Ther. 2011;90(5):674–84. doi: 10.1038/clpt.2011.165 21956618
21. Chen L, Pawlikowski B, Schlessinger A, More SS, Stryke D, Johns SJ, et al. Role of organic cation transporter 3 (SLC22A3) and its missense variants in the pharmacologic action of metformin. Pharmacogenet Genomics. 2010;20(11):687–99. doi: 10.1097/FPC.0b013e32833fe789 20859243
22. Jablonski KA, McAteer JB, de Bakker PI, Franks PW, Pollin TI, Hanson RL, et al. Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the diabetes prevention program. Diabetes. 2010;59(10):2672–81. doi: 10.2337/db10-0543 20682687
23. Rotroff DM, Yee SW, Zhou K, Marvel SW, Shah HS, Jack JR, et al. Genetic Variants in CPA6 and PRPF31 Are Associated With Variation in Response to Metformin in Individuals With Type 2 Diabetes. Diabetes. 2018;67(7):1428–40. doi: 10.2337/db17-1164 29650774
24. GoDarts, Group UDPS, Wellcome Trust Case Control C, Zhou K, Bellenguez C, Spencer CC, et al. Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet. 2011;43(2):117–20. doi: 10.1038/ng.735 21186350
25. Niu N, Liu T, Cairns J, Ly RC, Tan X, Deng M, et al. Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines. Hum Mol Genet. 2016;25(21):4819–34. doi: 10.1093/hmg/ddw301 28173075
26. Pawlyk AC, Giacomini KM, McKeon C, Shuldiner AR, Florez JC. Metformin pharmacogenomics: current status and future directions. Diabetes. 2014;63(8):2590–9. doi: 10.2337/db13-1367 25060887
27. Guo J, Zhou Y, Cheng Y, Fang W, Hu G, Wei J, et al. Metformin-Induced Changes of the Coding Transcriptome and Non-Coding RNAs in the Livers of Non-Alcoholic Fatty Liver Disease Mice. Cell Physiol Biochem. 2018;45(4):1487–505. doi: 10.1159/000487575 29466788
28. Martin-Montalvo A, Mercken EM, Mitchell SJ, Palacios HH, Mote PL, Scheibye-Knudsen M, et al. Metformin improves healthspan and lifespan in mice. Nat Commun. 2013;4:2192. doi: 10.1038/ncomms3192 23900241
29. Padilla J, Thorne PK, Martin JS, Rector RS, Akter S, Davis JW, et al. Transcriptomic effects of metformin in skeletal muscle arteries of obese insulin-resistant rats. Exp Biol Med (Maywood). 2017;242(6):617–24.
30. Udhane SS, Legeza B, Marti N, Hertig D, Diserens G, Nuoffer JM, et al. Combined transcriptome and metabolome analyses of metformin effects reveal novel links between metabolic networks in steroidogenic systems. Sci Rep. 2017;7(1):8652. doi: 10.1038/s41598-017-09189-y 28819133
31. Sacco F, Silvestri A, Posca D, Pirro S, Gherardini PF, Castagnoli L, et al. Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State. Cell Syst. 2016;2(3):159–71. doi: 10.1016/j.cels.2016.02.005 27135362
32. Rovite V, Wolff-Sagi Y, Zaharenko L, Nikitina-Zake L, Grens E, Klovins J. Genome Database of the Latvian Population (LGDB): Design, Goals, and Primary Results. J Epidemiol. 2018.
33. Zhang M, Liu YH, Chang CS, Zhi H, Wang S, Xu W, et al. Quantification of gene expression while taking into account RNA alternative splicing. Genomics. 2018.
34. Zhou X, Lindsay H, Robinson MD. Robustly detecting differential expression in RNA sequencing data using observation weights. Nucleic Acids Res. 2014;42(11):e91. doi: 10.1093/nar/gku310 24753412
35. Benjamini YaH, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society, Series B (Methodological). 1995;57(1).
36. Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11(2):R14. doi: 10.1186/gb-2010-11-2-r14 20132535
37. P JEOTP. SciPy: Open Source Scientific Tools for Python. Computing in Science & Engineering. 2007;9:10–20.
38. Hunter JD. Matplotlib: A 2D graphics environment. Computing in Science & Engineering. 2007;9:99–104.
39. Vila IK, Song SJ, Song MS. A new duet in cancer biology: AMPK the typical and UBE2O the atypical. Mol Cell Oncol. 2017;4(3):e1304846. doi: 10.1080/23723556.2017.1304846 28616582
40. Lee MS, Han HJ, Han SY, Kim IY, Chae S, Lee CS, et al. Loss of the E3 ubiquitin ligase MKRN1 represses diet-induced metabolic syndrome through AMPK activation. Nat Commun. 2018;9(1):3404. doi: 10.1038/s41467-018-05721-4 30143610
41. Dayeh T, Tuomi T, Almgren P, Perfilyev A, Jansson PA, de Mello VD, et al. DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk. Epigenetics. 2016;11(7):482–8. doi: 10.1080/15592294.2016.1178418 27148772
42. Cameron AR, Morrison VL, Levin D, Mohan M, Forteath C, Beall C, et al. Anti-Inflammatory Effects of Metformin Irrespective of Diabetes Status. Circ Res. 2016;119(5):652–65. doi: 10.1161/CIRCRESAHA.116.308445 27418629
43. Bruno S, Ledda B, Tenca C, Ravera S, Orengo AM, Mazzarello AN, et al. Metformin inhibits cell cycle progression of B-cell chronic lymphocytic leukemia cells. Oncotarget. 2015;6(26):22624–40. doi: 10.18632/oncotarget.4168 26265439
44. Xiao Z, Wu W, Poltoratsky V. Metformin Suppressed CXCL8 Expression and Cell Migration in HEK293/TLR4 Cell Line. Mediators Inflamm. 2017;2017:6589423. doi: 10.1155/2017/6589423 29147073
45. Gutzeit C, Magri G, Cerutti A. Intestinal IgA production and its role in host-microbe interaction. Immunol Rev. 2014;260(1):76–85. doi: 10.1111/imr.12189 24942683
46. Fadlallah J, El Kafsi H, Sterlin D, Juste C, Parizot C, Dorgham K, et al. Microbial ecology perturbation in human IgA deficiency. Sci Transl Med. 2018;10(439).
47. Elbere I, Kalnina I, Silamikelis I, Konrade I, Zaharenko L, Sekace K, et al. Association of metformin administration with gut microbiome dysbiosis in healthy volunteers. PLoS One. 2018;13(9):e0204317. doi: 10.1371/journal.pone.0204317 30261008
48. Malinska H, Oliyarnyk O, Skop V, Silhavy J, Landa V, Zidek V, et al. Effects of Metformin on Tissue Oxidative and Dicarbonyl Stress in Transgenic Spontaneously Hypertensive Rats Expressing Human C-Reactive Protein. PLoS One. 2016;11(3):e0150924. doi: 10.1371/journal.pone.0150924 26963617
49. Radovica-Spalvina I, Latkovskis G, Silamikelis I, Fridmanis D, Elbere I, Ventins K, et al. Next-generation-sequencing-based identification of familial hypercholesterolemia-related mutations in subjects with increased LDL-C levels in a latvian population. BMC Med Genet. 2015;16:86. doi: 10.1186/s12881-015-0230-x 26415676
50. Dixon JL, Ginsberg HN. Regulation of hepatic secretion of apolipoprotein B-containing lipoproteins: information obtained from cultured liver cells. J Lipid Res. 1993;34(2):167–79. 8381452
51. Trapani L, Segatto M, Pallottini V. Regulation and deregulation of cholesterol homeostasis: The liver as a metabolic "power station". World J Hepatol. 2012;4(6):184–90. doi: 10.4254/wjh.v4.i6.184 22761969
52. Wulffele MG, Kooy A, de Zeeuw D, Stehouwer CD, Gansevoort RT. The effect of metformin on blood pressure, plasma cholesterol and triglycerides in type 2 diabetes mellitus: a systematic review. J Intern Med. 2004;256(1):1–14. doi: 10.1111/j.1365-2796.2004.01328.x 15189360
53. Pentikainen PJ, Voutilainen E, Aro A, Uusitupa M, Penttila I, Vapaatalo H. Cholesterol lowering effect of metformin in combined hyperlipidemia: placebo controlled double blind trial. Ann Med. 1990;22(5):307–12. doi: 10.3109/07853899009147912 2291838
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