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Yıl 2023, Cilt: 13 Sayı: 1, 26 - 38, 11.05.2023

Mustafa Gani Sürmen Tijen Alkan Bozkaya Şanser Ateş Saime Sürmen Çağrı Çakıcı Sadrettin Pençe Neslin Emekli

https://doi.org/10.26650/experimed.1219362

Öz

Destekleyen Kurum

İstanbul Medipol Üniversitesi BAP

Proje Numarası

BAP 2019/16

Kaynakça

  • 1. Isabel Padrao A, Ferreira R, Vitorino R, Amado F. Proteome-base biomarkers in diabetes mellitus: Progress on biofluids’ protein profiling using mass spectrometry. Proteomics Clin Appl 2012; 6: 447-66. [CrossRef] google scholar
  • 2. Shao S, Guo T, Aebersold R. Mass spectrometry-based proteomic quest for diabetes biomarkers. Biochim Biophys Acta 2015; 1854(6): 519-27. [CrossRef] google scholar
  • 3. Abdulwahab RA, Alaiya A, Shinwari Z, Allaith AAA, Giha HA. LC-MS/MS proteomic analysis revealed novel associations of 37 proteins with T2DM and notable upregulation of immunoglobulins. Int J Mol Med 2019; 43(5): 2118-32. [CrossRef] google scholar
  • 4. Lepedda AJ, Lobina O, Rocchiccioli S, Nieddu G, Ucciferri N, De Muro P, et al. Identification of differentially expressed plasma proteins in atherosclerotic patients with type 2 diabetes. J Diabetes Complications 2016; 30(5): 880-6. [CrossRef] google scholar
  • 5. Zhao L, Zhang Y, Liu F, Yang H, Zhong Y, Wang Y, et al. Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy. J Endocrinol Invest 2021; 44(12): 2709-23. [CrossRef] google scholar
  • 6. Lee PY, Osman J, Low TY, Jamal R. Plasma/serum proteomics: depletion strategies for reducing high-abundance proteins for biomarker discovery. Bioanalysis 2019; 11(19): 1799-1812. [CrossRef] google scholar
  • 7. Ku EJ, Cho KC, Lim C, Kang JW, Oh JW, Choi YR, et al. Discovery of plasma biomarkers for predicting the severity of coronary artery atherosclerosis by quantitative proteomics. BMJ Open Diabetes Res Care 2020; 8(1): e001152. [CrossRef] google scholar
  • 8. Sürmen MG, Sürmen S, Cansız D, Ünal İ, Üstündağ ÜV, Alturfan AA, et al. Amelioration of rotenone-induced alterations in energy/ redox system, stress response and cytoskeleton proteins by octanoic acid in zebrafish: A proteomic study. J Biochem Mol Toxicol 2022; 36(5): e23024. [CrossRef] google scholar
  • 9. Fiorentino TV, Prioletta A, Zuo P, Folli F. Hyperglycemia-induced oxidative stress and its role in diabetesmellitus-related cardiovascular diseases. Curr Pharm Des 2013; 19(32): 5695-703. [CrossRef] google scholar
  • 10. Castro AR, Silva SO, Soares SC. The use of high sensitivity C-Reactive protein in cardiovascular disease detection. J Pharm Pharm Sci 2018; 21(1): 496-503. [CrossRef] google scholar
  • 11. Shimoda M, Kaneto H, Yoshioka H, Okauchi S, Hirukawa H, Kimura T, et al. Influence of atherosclerosis-related risk factors on serum high-sensitivity C-reactive protein levels in patients with type 2 diabetes: Comparison of their influence in obese and non-obese patients. J Diabetes Investig 2016; 7(2): 197-205. [CrossRef] google scholar
  • 12. Dullaart RP, de Vries R, Sluiter WJ, Voorbij HA. High plasma C-reactive protein (CRP) is related to low paraoxonase-I (PON-I) activity independently of high leptin and low adiponectin in type 2 diabetes mellitus. Clin Endocrinol (Oxf) 2009; 70(2): 221-6. [CrossRef] google scholar
  • 13. Crow JA, Meek EC, Wills RW, Chambers JE. A case-control study: The association of serum paraoxonase 1 activity and concentration with the development of type 2 diabetes mellitus. Diabetes Metab Res Rev 2018; 34(3). [CrossRef] google scholar
  • 14. Wang Y, Meng RW, Kunutsor SK, Chowdhury R, Yuan JM, Koh WP, et al. Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated metaanalysis. Sci Rep 2018; 8(1): 406. [CrossRef] google scholar
  • 15. Katsiki N, Mantzoros C, Mikhailidis DP. Adiponectin, lipids, and atherosclerosis. Curr Opin Lipidol 2017; 28(4): 347-54. [CrossRef] google scholar
  • 16. Ferrannini G, Manca ML, Magnoni M, Andreotti F, Andreini D, Latini R, et al. Coronary artery disease and type 2 diabetes: A proteomic study. Diabetes Care 2020; 43(4): 843-51. [CrossRef] google scholar
  • 17. Lindberg S, Jensen JS, Bjerre M, Pedersen SH, Frystyk J, Flyvbjerg A, et al. Adiponectin, type 2 diabetes,s and cardiovascular risk. Eur J Prev Cardiol 2015; 22(3): 276-83. [CrossRef] google scholar
  • 18. Li S, Shin HJ, Ding EL, van Dam RM. Adiponectin levels and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 2009; 302(2): 179-88. [CrossRef] google scholar
  • 19. Efrat M, Aviram M. Paraoxonase 1 interactions with HDL, antioxidants, and macrophages regulate atherogenesis - a protective role for HDL phospholipids. Adv Exp Med Biol 2010; 660: 153-66. [CrossRef] google scholar
  • 20. Viktorinova A, Jurkovicova I, Fabryova L, Kinova S, Koren M, Stecova A, et al. Abnormalities in the relationship of paraoxonase 1 with HDL and apolipoprotein A1 and their possible connection to HDL dysfunctionality in type 2 diabetes. Diabetes Res Clin Pract 2018; 140: 174-82. [CrossRef] google scholar
  • 21. Pérez-Méndez O, Pacheco HG, Martinez-Sanchez C, Franco M. HDL-cholesterol in coronary artery disease risk: function or structure? Clin Chim Acta 2014; 429: 111-22. [CrossRef] google scholar
  • 22. Bhale AS, Venkataraman K. Leveraging knowledge of HDLs major protein ApoA1: Structure, function, mutations, and potential therapeutics. Biomed Pharmacother 2022; 154: 113634. [CrossRef] google scholar
  • 23. Sun T, Hu J, Yin Z, Xu Z, Zhang L, Fan L, et al. Low serum paraoxonase1 activity levels predict coronary artery disease severity. Oncotarget 2017; 8(12):19443-54. [CrossRef] google scholar
  • 24. Shabalala SC, Johnson R, Basson AK, Ziqubu K, Hlengwa N, Mthembu SXH, et al. Detrimental effects of lipid peroxidation in type 2 diabetes: Exploring the neutralizing influence of antioxidants. Antioxidants (Basel) 2022; 11(10): 2071. [CrossRef] google scholar
  • 25. Kesavulu MM, Kameswararao B, Apparao Ch, Kumar EG, Harinarayan CV. Effect of omega-3 fatty acids on lipid peroxidation and antioxidant enzyme status in type 2 diabetic patients. Diabetes Metab 2002; 28(1): 20-6. [CrossRef] google scholar
  • 26. Ramakrishna V, Jailkhani R. Oxidative stress in non-insulindependent diabetes mellitus (NIDDM) patients. Acta Diabetol 2008; 45(1): 41-6. [CrossRef] google scholar
  • 27. Aouacheri O, Saka S, Krim M, Messaadia A, Maidi I. The investigation of the oxidative stress-related parameters in type 2 diabetes mellitus. Can J Diabetes 2015; 39(1): 44-9. [CrossRef] google scholar
  • 28. Zarei M, Farahnak Z, Hosseinzadeh-Attar MJ, Javanbakht MH, Hosseinzadeh P, Derakhshanian H, et al. Lipid peroxidation and antioxidant enzymes activity in controlled and uncontrolled Type 2 diabetic patients. ARYA Atheroscler 2016; 12(3): 118-23. google scholar
  • 29. Kumawat M, Sharma TK, Singh I, Singh N, Ghalaut VS, Vardey SK, et al. Antioxidant enzymes and lipid peroxidation in type 2 diabetes mellitus patients with and without nephropathy. N Am J Med Sci 2013; 5(3): 213-9. [CrossRef] google scholar
  • 30. Gunawardena HP, Silva R, Sivakanesan R, Ranasinghe P, Katulanda P. Poor glycaemic control is associated with increased lipid peroxidation and glutathione peroxidase activity in type 2 diabetes patients. Oxid Med Cell Longev 2019; 2019: 9471697. [CrossRef] google scholar
  • 31. Tavares AM, Silva JH, Bensusan CO, Ferreira ACF, Matos LPL, E Souza KLA, et al. Altered superoxide dismutase-1 activity and intercellular adhesion molecule 1 (ICAM-1) levels in patients with type 2 diabetes mellitus. PLoS One 2019; 14(5): e0216256. [CrossRef] google scholar
  • 32. Andújar-Vera F, García-Fontana C, Lozano-Alonso S, González-Salvatierra S, Iglesias-Baena I, Muñoz-Torres M, et al. Association between oxidative-stress-related markers and calcified femoral artery in type 2 diabetes patients. J Pharm Biomed Anal 2020; 190: 113535. [CrossRef] google scholar
  • 33. Kadoglou NP, Daskalopoulou SS, Perrea D, Liapis CD. Matrix metalloproteinases and diabetic vascular complications. Angiology 2005; 56(2): 173-89. [CrossRef] google scholar
  • 34. Chen Y, Peng W, Raffetto JD, Khalil RA. Matrix Metalloproteinases in remodeling of lower extremity veins and chronic venous disease. Prog Mol Biol Transl Sci 2017; 147: 267-99. [CrossRef] google scholar
  • 35. Uemura S, Matsushita H, Li W, Glassford AJ, Asagami T, Lee KH, et al. Diabetes mellitus enhances vascular matrix metalloproteinase activity: Role of oxidative stress. Circ Res 2001; 88(12): 1291-8. [CrossRef] google scholar
  • 36. Death AK, Fisher EJ, McGrath KC, Yue DK. High glucose alters matrix metalloproteinase expression in two key vascular cells: potential impact on atherosclerosis in diabetes. Atherosclerosis 2003; 168(2): 263-9. [CrossRef] google scholar
  • 37. Derosa G, D’Angelo A, Tinelli C, Devangelio E, Consoli A, Miccoli R, et al. Evaluation of metalloproteinase 2 and 9 levels and their inhibitors in diabetic and healthy subjects. Diabetes Metab 2007; 33(2): 129-34. [CrossRef] google scholar
  • 38. Li T, Li X, Feng Y, Dong G, Wang Y, Yang J. The role of matrix metalloproteinase-9 in atherosclerotic plaque instability. Mediators Inflamm 2020; 2020: 3872367. [CrossRef] google scholar
  • 39. Moradipoor S, Ismail P, Etemad A, Wan Sulaiman WA, Ahmadloo S. Expression profiling of genes related to endothelial cells biology in patients with type 2 diabetes and patients with prediabetes. Biomed Res Int 2016; 2016: 1845638. [CrossRef] google scholar
  • 40. Moore R, Hawley A, Sigler R, Farris D, Wrobleski S, Ramacciotti E, et al. Tissue inhibitor of metalloproteinase-1 is an early marker of acute endothelial dysfunction in a rodent model of venous oxidative injury. Ann Vasc Surg 2009; 23(4): 498-505. [CrossRef] google scholar
  • 41. Inokubo Y, Hanada H, Ishizaka H, Fukushi T, Kamada T, Okumura K. Plasma levels of matrix metalloproteinase-9 and tissue inhibitor of metalloproteinase-1 are increased in the coronary circulation in patients with the acute coronary syndrome. Am Heart J 2001; 141(2): 211-7. [CrossRef] google scholar
  • 42. Liu F, Cai Z, Yang Y, Plasko G, Zhao P, Wu X, et al. The adipocyte-enriched secretory protein tetranectin exacerbates type 2 diabetes by inhibiting insulin secretion from ß cells. Sci Adv 2022; 8(38): eabq1799. [CrossRef] google scholar
  • 43. Ding Y, Ge Q, Qu H, Feng Z, Long J, Wei Q, et al. Increased serum periostin concentrations are associated with the presence of diabetic retinopathy in patients with type 2 diabetes mellitus. J Endocrinol Invest 2018; 41(8): 937-45. [CrossRef] google scholar
  • 44. Milek M, Moulla Y, Kern M, Stroh C, Dietrich A, Schön MR, et al. Adipsin serum concentrations and adipose tissue expression in people with obesity and type 2 diabetes. Int J Mol Sci 2022; 23(4): 2222. [CrossRef] google scholar
  • 45. Zhang Q, Fillmore TL, Schepmoes AA, Clauss TR, Gritsenko MA, Mueller PW, et al. Serum proteomics reveals systemic dysregulation of innate immunity in type 1 diabetes. J Exp Med 2013; 210(1): 191-203. [CrossRef] google scholar
  • 46. Cangemi C, Skov V, Poulsen MK, Funder J, Twal WO, Gall MA, et al. Fibulin-1 is a marker for arterial extracellular matrix alterations in type 2 diabetes. Clin Chem 2011; 57(11): 1556-65. [CrossRef] google scholar

Large-Scale Proteomic Analysis of Patients with Type 2 Diabetes Mellitus and Atherosclerosis Using a Label-Free LC-MS/MS Approach

Yıl 2023, Cilt: 13 Sayı: 1, 26 - 38, 11.05.2023

Mustafa Gani Sürmen Tijen Alkan Bozkaya Şanser Ateş Saime Sürmen Çağrı Çakıcı Sadrettin Pençe Neslin Emekli

https://doi.org/10.26650/experimed.1219362

Öz

Objective: Type 2 diabetes mellitus (T2D) is a metabolic disease whose molecular events have not yet been fully clarified. However, next-generation powerful molecular approaches such as mass spectrometry (MS)-based proteomics holds promise. In this study, we aimed to reveal the protein profile of serum samples obtained from patients with T2D and atherosclerotic cardiovascular disease using the high-resolution liquid chromatography (LC)-MS/MS system.
Materials and Methods: Immune depletion was performed for the top 12 abundant proteins in 10 μl serum samples taken from individuals. Then, tryptic peptides were obtained from total proteins by applying a digestion protocol. Accordingly, reduction, alkylation, and digestion with trypsin enzyme were carried out, respectively. Tryptic peptides were analyzed in an ultra-high-pressure LC-MS/MS system with a label-free proteomic approach. The raw data were processed using the software program.
Results: LC-MS/MS analyses revealed 120 proteins with significant expression changes. Some of these proteins were associated with inflammation, lipid transport, and oxidative stress, which are known to play an important role in T2D and its complications.
Conclusion: As a result, LC-MS/MS analyses highlighted the proteins that will provide predictions in the treatment and course of T2D. We believe that validation of these proteins with targeted proteomic approaches in a larger sample in further studies will contribute to the development of clinically usable panels.

Anahtar Kelimeler

Diabetes Proteomics Serum Mass spectrometry Atherosclerosis

Proje Numarası

BAP 2019/16

Kaynakça

  • 1. Isabel Padrao A, Ferreira R, Vitorino R, Amado F. Proteome-base biomarkers in diabetes mellitus: Progress on biofluids’ protein profiling using mass spectrometry. Proteomics Clin Appl 2012; 6: 447-66. [CrossRef] google scholar
  • 2. Shao S, Guo T, Aebersold R. Mass spectrometry-based proteomic quest for diabetes biomarkers. Biochim Biophys Acta 2015; 1854(6): 519-27. [CrossRef] google scholar
  • 3. Abdulwahab RA, Alaiya A, Shinwari Z, Allaith AAA, Giha HA. LC-MS/MS proteomic analysis revealed novel associations of 37 proteins with T2DM and notable upregulation of immunoglobulins. Int J Mol Med 2019; 43(5): 2118-32. [CrossRef] google scholar
  • 4. Lepedda AJ, Lobina O, Rocchiccioli S, Nieddu G, Ucciferri N, De Muro P, et al. Identification of differentially expressed plasma proteins in atherosclerotic patients with type 2 diabetes. J Diabetes Complications 2016; 30(5): 880-6. [CrossRef] google scholar
  • 5. Zhao L, Zhang Y, Liu F, Yang H, Zhong Y, Wang Y, et al. Urinary complement proteins and risk of end-stage renal disease: quantitative urinary proteomics in patients with type 2 diabetes and biopsy-proven diabetic nephropathy. J Endocrinol Invest 2021; 44(12): 2709-23. [CrossRef] google scholar
  • 6. Lee PY, Osman J, Low TY, Jamal R. Plasma/serum proteomics: depletion strategies for reducing high-abundance proteins for biomarker discovery. Bioanalysis 2019; 11(19): 1799-1812. [CrossRef] google scholar
  • 7. Ku EJ, Cho KC, Lim C, Kang JW, Oh JW, Choi YR, et al. Discovery of plasma biomarkers for predicting the severity of coronary artery atherosclerosis by quantitative proteomics. BMJ Open Diabetes Res Care 2020; 8(1): e001152. [CrossRef] google scholar
  • 8. Sürmen MG, Sürmen S, Cansız D, Ünal İ, Üstündağ ÜV, Alturfan AA, et al. Amelioration of rotenone-induced alterations in energy/ redox system, stress response and cytoskeleton proteins by octanoic acid in zebrafish: A proteomic study. J Biochem Mol Toxicol 2022; 36(5): e23024. [CrossRef] google scholar
  • 9. Fiorentino TV, Prioletta A, Zuo P, Folli F. Hyperglycemia-induced oxidative stress and its role in diabetesmellitus-related cardiovascular diseases. Curr Pharm Des 2013; 19(32): 5695-703. [CrossRef] google scholar
  • 10. Castro AR, Silva SO, Soares SC. The use of high sensitivity C-Reactive protein in cardiovascular disease detection. J Pharm Pharm Sci 2018; 21(1): 496-503. [CrossRef] google scholar
  • 11. Shimoda M, Kaneto H, Yoshioka H, Okauchi S, Hirukawa H, Kimura T, et al. Influence of atherosclerosis-related risk factors on serum high-sensitivity C-reactive protein levels in patients with type 2 diabetes: Comparison of their influence in obese and non-obese patients. J Diabetes Investig 2016; 7(2): 197-205. [CrossRef] google scholar
  • 12. Dullaart RP, de Vries R, Sluiter WJ, Voorbij HA. High plasma C-reactive protein (CRP) is related to low paraoxonase-I (PON-I) activity independently of high leptin and low adiponectin in type 2 diabetes mellitus. Clin Endocrinol (Oxf) 2009; 70(2): 221-6. [CrossRef] google scholar
  • 13. Crow JA, Meek EC, Wills RW, Chambers JE. A case-control study: The association of serum paraoxonase 1 activity and concentration with the development of type 2 diabetes mellitus. Diabetes Metab Res Rev 2018; 34(3). [CrossRef] google scholar
  • 14. Wang Y, Meng RW, Kunutsor SK, Chowdhury R, Yuan JM, Koh WP, et al. Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated metaanalysis. Sci Rep 2018; 8(1): 406. [CrossRef] google scholar
  • 15. Katsiki N, Mantzoros C, Mikhailidis DP. Adiponectin, lipids, and atherosclerosis. Curr Opin Lipidol 2017; 28(4): 347-54. [CrossRef] google scholar
  • 16. Ferrannini G, Manca ML, Magnoni M, Andreotti F, Andreini D, Latini R, et al. Coronary artery disease and type 2 diabetes: A proteomic study. Diabetes Care 2020; 43(4): 843-51. [CrossRef] google scholar
  • 17. Lindberg S, Jensen JS, Bjerre M, Pedersen SH, Frystyk J, Flyvbjerg A, et al. Adiponectin, type 2 diabetes,s and cardiovascular risk. Eur J Prev Cardiol 2015; 22(3): 276-83. [CrossRef] google scholar
  • 18. Li S, Shin HJ, Ding EL, van Dam RM. Adiponectin levels and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 2009; 302(2): 179-88. [CrossRef] google scholar
  • 19. Efrat M, Aviram M. Paraoxonase 1 interactions with HDL, antioxidants, and macrophages regulate atherogenesis - a protective role for HDL phospholipids. Adv Exp Med Biol 2010; 660: 153-66. [CrossRef] google scholar
  • 20. Viktorinova A, Jurkovicova I, Fabryova L, Kinova S, Koren M, Stecova A, et al. Abnormalities in the relationship of paraoxonase 1 with HDL and apolipoprotein A1 and their possible connection to HDL dysfunctionality in type 2 diabetes. Diabetes Res Clin Pract 2018; 140: 174-82. [CrossRef] google scholar
  • 21. Pérez-Méndez O, Pacheco HG, Martinez-Sanchez C, Franco M. HDL-cholesterol in coronary artery disease risk: function or structure? Clin Chim Acta 2014; 429: 111-22. [CrossRef] google scholar
  • 22. Bhale AS, Venkataraman K. Leveraging knowledge of HDLs major protein ApoA1: Structure, function, mutations, and potential therapeutics. Biomed Pharmacother 2022; 154: 113634. [CrossRef] google scholar
  • 23. Sun T, Hu J, Yin Z, Xu Z, Zhang L, Fan L, et al. Low serum paraoxonase1 activity levels predict coronary artery disease severity. Oncotarget 2017; 8(12):19443-54. [CrossRef] google scholar
  • 24. Shabalala SC, Johnson R, Basson AK, Ziqubu K, Hlengwa N, Mthembu SXH, et al. Detrimental effects of lipid peroxidation in type 2 diabetes: Exploring the neutralizing influence of antioxidants. Antioxidants (Basel) 2022; 11(10): 2071. [CrossRef] google scholar
  • 25. Kesavulu MM, Kameswararao B, Apparao Ch, Kumar EG, Harinarayan CV. Effect of omega-3 fatty acids on lipid peroxidation and antioxidant enzyme status in type 2 diabetic patients. Diabetes Metab 2002; 28(1): 20-6. [CrossRef] google scholar
  • 26. Ramakrishna V, Jailkhani R. Oxidative stress in non-insulindependent diabetes mellitus (NIDDM) patients. Acta Diabetol 2008; 45(1): 41-6. [CrossRef] google scholar
  • 27. Aouacheri O, Saka S, Krim M, Messaadia A, Maidi I. The investigation of the oxidative stress-related parameters in type 2 diabetes mellitus. Can J Diabetes 2015; 39(1): 44-9. [CrossRef] google scholar
  • 28. Zarei M, Farahnak Z, Hosseinzadeh-Attar MJ, Javanbakht MH, Hosseinzadeh P, Derakhshanian H, et al. Lipid peroxidation and antioxidant enzymes activity in controlled and uncontrolled Type 2 diabetic patients. ARYA Atheroscler 2016; 12(3): 118-23. google scholar
  • 29. Kumawat M, Sharma TK, Singh I, Singh N, Ghalaut VS, Vardey SK, et al. Antioxidant enzymes and lipid peroxidation in type 2 diabetes mellitus patients with and without nephropathy. N Am J Med Sci 2013; 5(3): 213-9. [CrossRef] google scholar
  • 30. Gunawardena HP, Silva R, Sivakanesan R, Ranasinghe P, Katulanda P. Poor glycaemic control is associated with increased lipid peroxidation and glutathione peroxidase activity in type 2 diabetes patients. Oxid Med Cell Longev 2019; 2019: 9471697. [CrossRef] google scholar
  • 31. Tavares AM, Silva JH, Bensusan CO, Ferreira ACF, Matos LPL, E Souza KLA, et al. Altered superoxide dismutase-1 activity and intercellular adhesion molecule 1 (ICAM-1) levels in patients with type 2 diabetes mellitus. PLoS One 2019; 14(5): e0216256. [CrossRef] google scholar
  • 32. Andújar-Vera F, García-Fontana C, Lozano-Alonso S, González-Salvatierra S, Iglesias-Baena I, Muñoz-Torres M, et al. Association between oxidative-stress-related markers and calcified femoral artery in type 2 diabetes patients. J Pharm Biomed Anal 2020; 190: 113535. [CrossRef] google scholar
  • 33. Kadoglou NP, Daskalopoulou SS, Perrea D, Liapis CD. Matrix metalloproteinases and diabetic vascular complications. Angiology 2005; 56(2): 173-89. [CrossRef] google scholar
  • 34. Chen Y, Peng W, Raffetto JD, Khalil RA. Matrix Metalloproteinases in remodeling of lower extremity veins and chronic venous disease. Prog Mol Biol Transl Sci 2017; 147: 267-99. [CrossRef] google scholar
  • 35. Uemura S, Matsushita H, Li W, Glassford AJ, Asagami T, Lee KH, et al. Diabetes mellitus enhances vascular matrix metalloproteinase activity: Role of oxidative stress. Circ Res 2001; 88(12): 1291-8. [CrossRef] google scholar
  • 36. Death AK, Fisher EJ, McGrath KC, Yue DK. High glucose alters matrix metalloproteinase expression in two key vascular cells: potential impact on atherosclerosis in diabetes. Atherosclerosis 2003; 168(2): 263-9. [CrossRef] google scholar
  • 37. Derosa G, D’Angelo A, Tinelli C, Devangelio E, Consoli A, Miccoli R, et al. Evaluation of metalloproteinase 2 and 9 levels and their inhibitors in diabetic and healthy subjects. Diabetes Metab 2007; 33(2): 129-34. [CrossRef] google scholar
  • 38. Li T, Li X, Feng Y, Dong G, Wang Y, Yang J. The role of matrix metalloproteinase-9 in atherosclerotic plaque instability. Mediators Inflamm 2020; 2020: 3872367. [CrossRef] google scholar
  • 39. Moradipoor S, Ismail P, Etemad A, Wan Sulaiman WA, Ahmadloo S. Expression profiling of genes related to endothelial cells biology in patients with type 2 diabetes and patients with prediabetes. Biomed Res Int 2016; 2016: 1845638. [CrossRef] google scholar
  • 40. Moore R, Hawley A, Sigler R, Farris D, Wrobleski S, Ramacciotti E, et al. Tissue inhibitor of metalloproteinase-1 is an early marker of acute endothelial dysfunction in a rodent model of venous oxidative injury. Ann Vasc Surg 2009; 23(4): 498-505. [CrossRef] google scholar
  • 41. Inokubo Y, Hanada H, Ishizaka H, Fukushi T, Kamada T, Okumura K. Plasma levels of matrix metalloproteinase-9 and tissue inhibitor of metalloproteinase-1 are increased in the coronary circulation in patients with the acute coronary syndrome. Am Heart J 2001; 141(2): 211-7. [CrossRef] google scholar
  • 42. Liu F, Cai Z, Yang Y, Plasko G, Zhao P, Wu X, et al. The adipocyte-enriched secretory protein tetranectin exacerbates type 2 diabetes by inhibiting insulin secretion from ß cells. Sci Adv 2022; 8(38): eabq1799. [CrossRef] google scholar
  • 43. Ding Y, Ge Q, Qu H, Feng Z, Long J, Wei Q, et al. Increased serum periostin concentrations are associated with the presence of diabetic retinopathy in patients with type 2 diabetes mellitus. J Endocrinol Invest 2018; 41(8): 937-45. [CrossRef] google scholar
  • 44. Milek M, Moulla Y, Kern M, Stroh C, Dietrich A, Schön MR, et al. Adipsin serum concentrations and adipose tissue expression in people with obesity and type 2 diabetes. Int J Mol Sci 2022; 23(4): 2222. [CrossRef] google scholar
  • 45. Zhang Q, Fillmore TL, Schepmoes AA, Clauss TR, Gritsenko MA, Mueller PW, et al. Serum proteomics reveals systemic dysregulation of innate immunity in type 1 diabetes. J Exp Med 2013; 210(1): 191-203. [CrossRef] google scholar
  • 46. Cangemi C, Skov V, Poulsen MK, Funder J, Twal WO, Gall MA, et al. Fibulin-1 is a marker for arterial extracellular matrix alterations in type 2 diabetes. Clin Chem 2011; 57(11): 1556-65. [CrossRef] google scholar
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Klinik Tıp Bilimleri
Bölüm Araştırma Makalesi
Yazarlar

Mustafa Gani Sürmen 0000-0001-9084-7528

Tijen Alkan Bozkaya 0000-0002-4728-1079

Şanser Ateş 0000-0002-4502-9670

Saime Sürmen 0000-0002-7748-0757

Çağrı Çakıcı 0000-0002-8662-5284

Sadrettin Pençe 0000-0001-9453-4166

Neslin Emekli 0000-0002-0109-5086

Proje Numarası BAP 2019/16
Yayımlanma Tarihi 11 Mayıs 2023
Gönderilme Tarihi 15 Aralık 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 13 Sayı: 1

Kaynak Göster

Vancouver Sürmen MG, Alkan Bozkaya T, Ateş Ş, Sürmen S, Çakıcı Ç, Pençe S, Emekli N. Large-Scale Proteomic Analysis of Patients with Type 2 Diabetes Mellitus and Atherosclerosis Using a Label-Free LC-MS/MS Approach. Experimed. 2023;13(1):26-38.
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