Abstract
Type 2 diabetes mellitus (T2DM) is the most frequent form of diabetes, characterized by insulin resistance and impaired insulin release. Its prevalence has shown remarkable expansion worldwide, particularly in low- and middle-income countries. Diabetic complications comprise kidney disease, retinopathy, and neuropathy. Moreover, metabolic, cardiovascular, and neurologic diseases have shared common pathways with T2DM. Proteomics is a technology involved in the quantification of overall proteins present in biological samples, as well as the study of their structures, functions, and interactions. Consequently, proteomics could be considered as the most relevant information to characterize a biological system and to propose new candidate biomarkers. This chapter goes on to discuss proteomic studies in order to characterize the T2DM profile, as well as the proteins commonly observed in T2DM, its complications, and other diseases.
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Abbreviations
- 2D PAGE:
-
Two-dimensional polyacrylamide gel electrophoresis
- AD:
-
Alzheimer’s disease
- AGEs:
-
Advanced glycation end products
- Apo:
-
Apolipoprotein
- CD163:
-
Scavenger receptor cysteine-rich type 1 protein M130
- CFAH :
-
Complement factor H
- CILP2:
-
Cartilage intermediate layer protein 2
- CKD:
-
Chronic kidney disease
- CTSD:
-
Cathepsin D
- CVDs:
-
Cardiovascular diseases
- DAF:
-
Decay-accelerating factor
- DKD:
-
Diabetic kidney disease
- DM:
-
Diabetes mellitus
- eGFR:
-
Estimated glomerular filtration rate
- eGPx:
-
Extracellular glutathione peroxidase
- ELISA:
-
Enzyme-linked immunosorbent assays
- GAL4:
-
Galectin-4
- Hb1Ac:
-
Glycated hemoglobin A1c
- HFpEF:
-
Heart failure with preserved ejection fraction
- HOMA-IR:
-
Homeostatic model assessment of insulin resistance
- IGFB2:
-
Insulin-like growth factor-binding protein 2
- InR:
-
Insulin-like receptor
- L1CAM:
-
L1 cell adhesion molecule
- LC:
-
Liquid chromatography
- MCI:
-
Mild cognitive impairment
- MetS:
-
Metabolic syndrome
- MMPs:
-
Matrix metalloproteinases
- MS:
-
Mass spectrometry
- mRNA:
-
Messenger ribonucleic acid
- NAFLD:
-
Non-alcoholic fatty liver disease
- NGAL:
-
Neutrophil gelatinase-associated lipocalin
- OR:
-
Odds ratio
- PAD:
-
Peripheral artery disease
- PIP:
-
Prolactin-induced protein
- PMCA:
-
Plasma membrane Ca + 2 ATPase
- RLS:
-
Restless leg syndrome
- STAT:
-
Signal transducer and activator of transcription
- T2DM:
-
Type 2 diabetes mellitus
- THBS2:
-
Thrombospondin-2
References
Abdulwahab RA, Alaiya A, Shinwari Z, et al. 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.
Ahn J, Kim B, Yu M, et al. Identification of diabetic nephropathy-selective proteins in human plasma by multi-lectin affinity chromatography and LC-MS/MS. Proteomics Clin Appl. 2010;4(6–7):644–53.
Alfadda A, Benabdelkamel H, Masood A, et al. Proteomic analysis of mature adipocytes from obese patients in relation to aging. Exp Gerontol. 2013;48:1196–203.
Alkhalaf A, Zürbig P, Bakker S, et al. Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy. PLoS One. 2010;5(10):e13421.
Aslam B, Basit M, Nisar M, et al. Proteomics: technologies and their applications. J Chromatogr Sci. 2017;55(2):182–96.
Avila-Vazquez M, Altamirano-Bustamante N, Altamirano-Bustamante M. Amyloid biomarkers in conformational diseases at face value: a systematic review. Molecules. 2017;23(1):79.
Basso D, Greco E, Fogar P, et al. Pancreatic cancer-associated diabetes mellitus: an open field for proteomic applications. Clin Chim Acta. 2005;357(2):184–9.
Bellei E, Rossi E, Lucchi L, et al. Proteomic analysis of early urinary biomarkers of renal changes in type 2 diabetic patients. Proteomics Clin Appl. 2008;2(4):478–91.
Chee C, Chang K, Loke M, et al. Association of potential salivary biomarkers with diabetic retinopathy and its severity in type-2 diabetes mellitus: a proteomic analysis by mass spectrometry. Peer J. 2016;4:e2022.
Cheema A, Kaur P, Fadel A, et al. Integrated datasets of proteomic and metabolomic biomarkers to predict its impacts on comorbidities of Type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2020;13:2409–31.
Chen Z, Gerszten R. Metabolomics and proteomics in type 2 diabetes. Circ Res. 2020;126(11):1613–27.
Conserva F, Pontrelli P, Accetturo M, et al. The pathogenesis of diabetic nephropathy: focus on microRNAs and proteomics. J Nephrol. 2013;26(5):811–20.
Elhadad M, Wilson R, Zaghlool S, et al. Metabolic syndrome and the plasma proteome: from association to causation. Cardiovasc Diabetol. 2021;20(1):111.
Fang L, Kojima K, Zhou L, et al. Analysis of the human proteome in subcutaneous and visceral fat depots in diabetic and non-diabetic patients with morbid obesity. J Proteomics Bioinform. 2015;8(6):133–41.
Fogar P, Pasquali C, Basso D, et al. Diabetes mellitus in pancreatic cancer follow-up. Anticancer Res. 1994;14:2827–30.
García-Fontana B, Morales-Santana S, Longobardo V, et al. Relationship between proinflammatory and antioxidant proteins with the severity of cardiovascular disease in Type 2 diabetes mellitus. Int J Mol Sci. 2015;16(5):9469–83.
Gholizadeh E, Khaleghian A, Najafgholi Seyfi D, et al. Showing NAFLD, as a key connector disease between Alzheimer’s disease and diabetes via analysis of systems biology. Gastroenterol Hepatol Bed Bench. 2020;13(Suppl1):S89–97.
Golea-Secara A, Munteanu C, Sarbu M, et al. Urinary proteins detected using modern proteomics intervene in early type 2 diabetic kidney disease – a pilot study. Biomark Med. 2020;14(16):1521–36.
Hanff T, Cohen J, Zhao L, et al. Quantitative proteomic analysis of diabetes mellitus in heart failure with preserved ejection fraction. JACC Basic Transl Sci. 2021;6(2):89–99.
Ising E, Åhrman E, Thomsen N, et al. Quantitative proteomic analysis of human peripheral nerves from subjects with type 2 diabetes. Diabet Med. 2021;26:e14658.
Jim B, Ghanta M, Qipo A, et al. Dysregulated nephrin in diabetic nephropathy of type 2 diabetes: a cross sectional study. PLoS One. 2012;7(5):e36041.
Jin J, Ku Y, Kim Y, et al. Differential proteome profiling using iTRAQ in microalbuminuric and normoalbuminuric type 2 diabetic patients. Exp Diabetes Res. 2012;2012:168602.
Jin J, Min H, Kim S, et al. Development of diagnostic biomarkers for detecting diabetic retinopathy at early stages using quantitative proteomics. J Diabetes Res. 2016;2016:6571976.
Kienhorst L, van Lochem E, Kievit W, et al. Gout is a chronic inflammatory disease in which high levels of Interleukin-8 (CXCL8), myeloid-related protein 8/myeloid-related protein 14 complex, and an altered proteome are associated with diabetes mellitus and cardiovascular disease. Arthritis Rheum. 2015;67(12):3303–13.
Kim H, Cho E, Yoo J, et al. Proteome analysis of serum from type 2 diabetics with nephropathy. J Proteome Res. 2007;6(2):735–43.
Kim S, Choi J, Yun J, et al. Proteomics approach to identify serum biomarkers associated with the pro-gression of diabetes in Korean patients with abdominal obesity. PLoS One. 2019;14:e0222032.
Kr€uger M, Kratchmarova I, Blagoev B, et al. Dissection of the insulin signaling pathway via quantitative phosphoproteomics. Proc Natl Acad Sci U S A. 2008;105:2451–6.
Kraniotou C, Karadima V, Bellos G, et al. Predictive biomarkers for type 2 of diabetes mellitus: Bridging the gap between systems research and personalized medicine. J Proteome. 2018;188:59–62.
Krisp C, Jacobsen F, McKay M, et al. Proteome analysis reveals antiangiogenic environments in chronic wounds of diabetes mellitus type 2 patients. Proteomics. 2013;13(17):2670–81.
Liu Y, Hu S, Wu Z, et al. Proteomic analysis of human serum from diabetic retinopathy. Int J Ophthalmol. 2011;4(6):616–22.
López-Villar E, Martos-Moreno G, Chowen J, et al. A proteomic approach to obesity and type 2 diabetes. J Cell Mol Med. 2015;19(7):1455–70.
Maahs D, Siwy J, Argilés A, et al. Urinary collagen fragments are significantly altered in diabetes: a link to pathophysiology. PLoS One. 2010;5(9):e13051.
McCarthy C, Shrestha S, Ibrahim N, et al. Performance of a clinical/proteomic panel to predict obstructive peripheral artery disease in patients with and without diabetes mellitus. Open Heart. 2019;6(1):e000955.
Meng Q, Ge S, Yan W, et al. Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS. Proteomics Clin Appl. 2017;11(3–4):1–34
Merchant M, Klein J. Proteomics and diabetic nephropathy. Curr Diab Rep. 2005;5(6):464–9.
Midena E, Frizziero L, Midena G, et al. Intraocular fluid biomarkers (liquid biopsy) in human diabetic retinopathy. Graefes Arch Clin Exp Ophthalmol. 2021;259:3549–356.
Mirza Z, Ali A, Ashraf G. Proteomics approaches to understand linkage between Alzheimer’s disease and type 2 diabetes mellitus. CNS Neurol Disord Drug Targets. 2014;13(2):213–25.
Moin A, Kahal H, Al-Qaissi A, et al. Amyloid-related protein changes associated with dementia differ according to severity of hypoglycemia. BMJ Open Diabetes Res Care. 2021;9(1):e002211.
Molvin J, Jujić A, Melander O, et al. Proteomic exploration of common pathophysiological pathways in diabetes and cardiovascular disease. ESC Heart Fail. 2020;7(6):4151–8.
Mondello S, Kobeissy F, Mechref Y, et al. Searching for novel candidate biomarkers of RLS in blood by proteomic analysis. Nat Sci Sleep. 2021;13:873–83.
Nicolls M, D’Antonio J, Hutton J. Proteomics as a tool for discovery: proteins implicated in Alzheimer’s disease are highly expressed in normal pancreatic islets. J Proteome Res. 2003;2(2):199–205.
Noordam R, van Heemst D, Suhre K, et al. Proteome-wide assessment of diabetes mellitus in Qatari identifies IGFBP-2 as a risk factor already with early glycaemic disturbances. Arch Biochem Biophys. 2020;689:108476.
Nowak C, Sundström J, Gustafsson S, et al. Protein biomarkers for insulin resistance and type 2 diabetes risk in two large community cohorts. Diabetes. 2016;65:276–84.
Organization – Global report on Diabetes 2021. https://www.who.int/news-room/fact-sheets/detail/diabetes. Accessed on August 6, 2021.
Papale M, Di Paolo S, Magistroni R, et al. Urine proteome analysis may allow noninvasive differential diagnosis of diabetic nephropathy. Diabetes Care. 2010;33(11):2409–15.
Pereira J, Fraga V, Santos A, et al. Alzheimer’s disease and type 2 diabetes mellitus: a systematic review of proteomic studies. J Neurochem. 2021;156(6):753–76.
Preil S, Kristensen L, Beck H, et al. Quantitative proteome analysis reveals increased content of basement membrane proteins in arteries from patients with Type 2 diabetes mellitus and lower levels among metformin users. Circ Cardiovasc Genet. 2015;8(5):727–35.
Riaz S, Alam S, Akhtar M. Proteomic identification of human serum biomarkers in diabetes mellitus type 2. J Pharm Biomed Anal. 2010a;51(5):1103–7.
Riaz S, Alam S, Srai S, et al. Proteomic identification of human urinary biomarkers in diabetes mellitus type 2. Diabetes Technol Ther. 2010b;12(12):979–88.
Santos A, Fraga V, Magalhães C, et al. Doença de Alzheimer e diabetes mellitus tipo 2: qual a relação? Rev Bras Neurol. 2017;53(4):17–26.
Sohail W, Majeed F, Afroz A. Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications. Diabetes Metab Syndr. 2018;12(6):1125–31.
Szerlip H, Edwards M, Williams B. Association between cognitive impairment and chronic kidney disease in Mexican Americans. J Am Geriatr Soc. 2015;63(10):2023–8.
Tans R, Verschuren L, Wessels H, et al. The future of protein biomarker research in type 2 diabetes mellitus. Expert Rev Proteomics. 2019;16(2):105–15.
Valle A, Catalán V, Rodríguez A, et al. Identification of liver proteins altered by type 2 diabetes mellitus in obese subjects. Liver Int. 2012;32(6):951–61.
Wang W, Liu X, Liu L, et al. Identification of proteins implicated in the development of pancreatic cancer-associated diabetes mellitus by iTRAQ-based quantitative proteomics. J Proteome. 2013;12(84):52–60.
Xiao H, Xin W, Sun L, et al. Comprehensive proteomic profiling of aqueous humor proteins in proliferative diabetic retinopathy. Transl Vis Sci Technol. 2021;10(6):3.
Yeh S, Chang W, Chuang H, et al. Differentiation of type 2 diabetes mellitus with different complications by proteomic analysis of plasma low abundance proteins. J Diabetes Metab Disord. 2016;15:24.
Zarch S, Tezerjani M, Talebi M, et al. Molecular biomarkers in diabetes mellitus (DM). Med J Islam Repub Iran. 2020;34:28.
Zhang Z, Wu S, Stenoien D, et al. High-throughput proteomics. Annu Rev Anal Chem (Palo Alto, Calif). 2014;7:427–54.
Zhao L, Zhang Y, Liu F 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 Investig. 2021;44:2709–2723.
Zürbig P, Jerums G, Hovind P, et al. Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes. 2012;61(12):3304–3313.58.
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Gomes, K.B. (2023). Proteomic Biomarkers: What They Are and How Type 2 Diabetes Mellitus Has Similarities with Other Diseases. In: Patel, V.B., Preedy, V.R. (eds) Biomarkers in Diabetes. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-08014-2_16
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DOI: https://doi.org/10.1007/978-3-031-08014-2_16
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