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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2020, Vol. 14 Issue (5) : 642-650    https://doi.org/10.1007/s11684-019-0719-3
RESEARCH ARTICLE
Correlation between serum miR-154-5p and urinary albumin excretion rates in patients with type 2 diabetes mellitus: a cross-sectional cohort study
Huiwen Ren1,2, Can Wu3, Ying Shao4, Shuang Liu5, Yang Zhou1, Qiuyue Wang1()
1. Department of Endocrinology, the First Hospital of China Medical University, Shenyang 110001, China
2. Advanced Institute for Medical Sciences, Dalian Medical University, Dalian 116044, China
3. Department of Gastroenterology and Endoscopy, the First Hospital of China Medical University, Shenyang 110001, China
4. Department of Endocrinology, the Second Hospital of China Medical University, Shenyang 110001, China
5. Severe Infection Intensive Care Unit, Affiliated Central Hospital of Shenyang Medical College, Shenyang 110001, China
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Abstract

This study aimed to investigate the correlation between serum miR-154-5p and urinary albumin to creatinine ratio (UACR) in patients with type 2 diabetes mellitus (T2DM) and the association with biomarkers of inflammation and fibrosis in diabetic kidney disease (DKD). A total of 390 patients with T2DM were divided into three groups: normal albuminuria (UACR<30 mg/g, n=136, NA), microalbuminuria (UACR at 30–300 mg/g, n=132, MA), and clinical albuminuria (UACR>300 mg/g, n=122, CA). Circulating miR-154-5p, inflammatory (C-reactive protein (CRP); erythrocyte sedimentation rate (ESR); and tumor necrosis factor-α (TNF-α) and fibrotic markers (vascular endothelial growth factor (VEGF); transforming growth factor-β1 (TGF-β1); and fibronectin (FN)), and other biochemical indicators were assessed via real-time PCR, enzyme-linked immunosorbent assay, and chemiluminescence assay in patients with T2DM and 138 control subjects (NC). UACR, miR-154-5p, glycated hemoglobin (HbA1c), serum creatinine (sCr), blood urea nitrogen (BUN), ESR, CRP, VEGF, TNF-α, TGF-β1, and FN were significantly higher and the estimated glomerular filtration rate (eGFR) was significantly lower in NA, MA, and CA groups than in NC subjects (P<0.05). Elevated levels of UACR and miR-154-5p were directly correlated with HbA1c, sCr, BUN, ESR, CRP, VEGF, TNF-α, TGF-β1, and FN and negatively correlated with eGFR (P<0.05). miR-154-5p, HbA1c, sCr, BUN, eGFR, ESR, CRP, VEGF, TNF-α, TGF-β1, and FN were important factors affecting UACR. These findings indicated that elevated serum miR-154-5p is significantly correlated with high UACR in patients with T2DM and may offer a novel reference for the early diagnosis of DKD.

Keywords type 2 diabetes mellitus      diabetic kidney disease      miR-154-5p      urinary albumin to creatinine ratio     
Corresponding Author(s): Qiuyue Wang   
Just Accepted Date: 30 December 2019   Online First Date: 17 January 2020    Issue Date: 12 October 2020
 Cite this article:   
Huiwen Ren,Can Wu,Ying Shao, et al. Correlation between serum miR-154-5p and urinary albumin excretion rates in patients with type 2 diabetes mellitus: a cross-sectional cohort study[J]. Front. Med., 2020, 14(5): 642-650.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0719-3
https://academic.hep.com.cn/fmd/EN/Y2020/V14/I5/642
Fig.1  Flow chart of the cross-sectional study.
NC NA MA CA F/c2 P value
N (M/F) 138 (68/70) 136 (70/66) 132 (65/67) 122 (62/60) 2.165 0.539
Age (year) 56.20±11.01 55.96±10.83 54.98±10.00 55.77±10.39 0.330 0.804
Course (year) 0.00 (0.00–0.00) 0.00 (0.00–3.50)a 0.00 (0.00–6.25)a 0.00 (0.00–7.00)a 15.484 <0.001
SBP (mmHg) 114.87±8.41 115.42±8.59 115.61±8.79 114.19±8.58 0.700 0.554
DBP (mmHg) 68.48±5.83 70.59±5.73a 70.38±5.57a 69.77±5.84a 3.740 0.011
BMI (kg/m2) 25.97±3.24 25.80±2.91 26.50±3.35 25.38±3.19a 2.750 0.042
HOMA-IR 5.54 (2.55–8.51) 3.65 (1.99–6.10)a 3.67 (1.74–6.08)a 3.54 (1.27–6.52)a 16.340 <0.001
HbA1c (%) 5.12±1.13 8.17±2.25a 8.91±1.62ab 9.85±1.93abc 177.450 <0.001
HDL-C (mmol/L) 1.33±0.36 1.10±0.27a 1.07±0.41a 1.13±0.52a 11.890 <0.001
LDL-C (mmol/L) 2.72±0.81 3.10±1.09a 3.07±1.09a 3.19±1.03a 5.680 <0.001
TC (mmol/L) 4.34±1.16 4.81±1.24a 4.84±1.22a 5.05±1.51a 7.190 <0.001
TG (mmol/L) 1.13 (0.78–1.78) 1.46 (1.01–2.46)a 1.52 (1.08–2.41)a 1.47 (0.97–2.38)a 15.070 0.002
UA (mmol/L) 267.54±73.06 299.41±91.68a 300.11±89.31a 306.11±91.09a 5.470 0.001
sCr (mmol/L) 57.40±8.34 59.93±9.64a 62.53±10.60ab 68.21±9.17abc 30.620 <0.001
BUN (mmol/L) 4.81±1.03 4.94±0.91 5.92±0.84ab 6.33±1.05abc 78.560 <0.001
eGFR 125.24 (121.91–128.35) 117.72 (114.15–120.80)a 105.91 (102.44–108.31)ab 92.37 (89.53–94.18)abc 463.620 <0.001
UACR (mg/g) 9.66 (3.98–14.15) 11.05 (6.51–14.96) 95.63 (59.63–142.51)ab 579.05 (364.57–1473.33)abc 439.810 <0.001
*ESR (mmH2O) 6.00 (4.00–9.00) 9.00 (6.50–12.00)a 17.00 (13.00–22.00)ab 35.00 (26.00–44.00)abc 327.310 <0.001
CRP (mg/L) 3.76±1.30 5.41±1.32a 7.93±5.14ab 10.69±7.12abc 61.710 <0.001
miR-154-5p 0.47 (0.45–0.49) 0.64 (0.58–0.69)a 0.71 (0.66–0.75)ab 0.87 (0.82–0.96)abc 423.460 <0.001
VEGF (ng/L) 110.34±27.25 131.35±17.78a 146.55±22.03ab 182.76±20.76abc 241.150 <0.001
TNF-α (pg/mL) 28.36±0.97 44.34±2.12a 66.33±3.97ab 84.06±5.10abc 6849.150 <0.001
TGF-β1 (mg/L) 5.73±0.71 11.61±1.78a 13.52±3.24ab 18.98±1.95abc 871.830 <0.001
FN (ng/mL) 246.23±12.91 353.02±13.51a 481.90±14.60ab 610.05±19.96abc 13 682.520 <0.001
Tab.1  Levels of serum biomarkers and clinical characteristics in the studied groups
  Ln miR-154-5p
r P
HbA1c 0.204 <0.001
sCr 0.272 <0.001
BUN 0.345 <0.001
Ln eGFR −0.740 <0.001
Ln UACR 0.678 <0.001
Ln ESR 0.576 <0.001
CRP 0.291 <0.001
VEGF 0.567 <0.001
TNF-α 0.714 <0.001
TGF-β1 0.584 <0.001
FN 0.731 <0.001
Tab.2  Correlation between miR-154-5p and other clinical parameters in patients with T2DM
  Ln UACR
r P
Ln miR-154-5p 0.678 <0.001
HbA1c 0.304 <0.001
sCr 0.343 <0.001
BUN 0.477 <0.001
Ln eGFR −0.846 <0.001
Ln ESR 0.681 <0.001
CRP 0.399 <0.001
VEGF 0.638 <0.001
TNF-α 0.887 <0.001
TGF-β1 0.701 <0.001
FN 0.900 <0.001
Tab.3  Correlation between UACR and clinical parameters in patients with T2DM
Fig.2  Ridge trace curve of the association between the clinical parameters and Ln UACR. y= Ln UACR as dependent variables and x1−x11 referred to HbA1c, CRP, sCr, BUN, VEGF, TNF-α, TGF-β1, Ln miR-154-5p, Ln eGFR, Ln ESR, and FN as independent variables.
  Ln UACR
B Standard error Standard regression coefficient t P 95% CI
Constant 8.545 1.019 8.384 <0.001 (6.547, 10.543)
Ln miR-154-5p 0.873 0.180 0.074 4.856 <0.001 (0.521, 1.226)
HbA1c 0.034 0.015 0.034 2.214 0.027 (0.004, 0.064)
sCr 0.012 0.003 0.061 4.032 <0.001 (0.006, 0.018)
BUN 0.100 0.029 0.053 3.445 0.001 (0.043, 0.156)
Ln eGFR −2.277 0.190 −0.147 −11.985 <0.001 (−2.649, −1.904)
Ln ESR 0.254 0.043 0.091 5.949 <0.001 (0.171, 0.338)
CRP 0.020 0.006 0.054 3.531 <0.001 (0.009, 0.032)
VEGF 0.002 0.001 0.033 2.227 0.027 (0.000, 0.004)
TNF-α 0.023 0.001 0.189 20.317 <0.001 (0.021, 0.026)
TGF-β1 0.043 0.008 0.082 5.436 <0.001 (0.028, 0.059)
FN 0.004 0.000 0.201 19.859 <0.001 (0.004, 0.004)
Tab.4  Ridge regression analysis of UACR and clinical parameters among patients with T2DM
1 V Sandeep. Type 2 diabetes. Ann Intern Med 2015; 162(5): 231–242
2 B Quiroga, D Arroyo, G de Arriba. Present and future in the treatment of diabetic kidney disease. J Diabetes Res 2015; 2015: 801348
https://doi.org/10.1155/2015/801348 pmid: 25945357
3 S Toth-Manikowski, MG Atta. Diabetic kidney disease: pathophysiology and therapeutic targets. J Diabetes Res 2015; 2015: 697010
https://doi.org/10.1155/2015/697010 pmid: 26064987
4 JJ Chamberlain, WH Herman, S Leal, AS Rhinehart, JH Shubrook, N Skolnik, RR Kalyani. Pharmacologic therapy for type 2 diabetes: synopsis of the 2017 American Diabetes Association Standards of Medical Care in Diabetes. Ann Intern Med 2017; 166(8): 572–578
https://doi.org/10.7326/M16-2937 pmid: 28288484
5 M Brownlee, LP Aiello, ME Cooper, AI Vinik, J Plutzky, AJM Boulton. Chapter 33—Complications of Diabetes Mellitus. Elsevier Inc., 2016
6 S Bagga, J Bracht, S Hunter, K Massirer, J Holtz, R Eachus, AE Pasquinelli. Regulation by let-7 and lin-4 miRNAs results in target mRNA degradation. Cell 2005; 122(4): 553–563
https://doi.org/10.1016/j.cell.2005.07.031 pmid: 16122423
7 D Saito, Y Maeshima, T Nasu, H Yamasaki, K Tanabe, H Sugiyama, H Sonoda, Y Sato, H Makino. Amelioration of renal alterations in obese type 2 diabetic mice by vasohibin-1, a negative feedback regulator of angiogenesis. Am J Physiol Renal Physiol 2011; 300(4): F873–F886
https://doi.org/10.1152/ajprenal.00503.2010 pmid: 21228103
8 J Milosevic, K Pandit, M Magister, E Rabinovich, DC Ellwanger, G Yu, LJ Vuga, B Weksler, PV Benos, KF Gibson, M McMillan, M Kahn, N Kaminski. Profibrotic role of miR-154 in pulmonary fibrosis. Am J Respir Cell Mol Biol 2012; 47(6): 879–887
https://doi.org/10.1165/rcmb.2011-0377OC pmid: 23043088
9 American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care 2014; 37(Suppl 1): S14–S80
https://doi.org/10.2337/dc14-S014 pmid: 24357209
10 J Chalmers. The 1999 WHO-ISH Guidelines for the Management of Hypertension. Med J Aust 1999; 171(9): 458–459
https://doi.org/10.5694/j.1326-5377.1999.tb123747.x pmid: 10615337
11 M Affara, D Sanders, H Araki, Y Tamada, BJ Dunmore, S Humphreys, S Imoto, C Savoie, S Miyano, S Kuhara, D Jeffries, C Print, DS Charnock-Jones. Vasohibin-1 is identified as a master-regulator of endothelial cell apoptosis using gene network analysis. BMC Genomics 2013; 14(1): 23
https://doi.org/10.1186/1471-2164-14-23 pmid: 23324451
12 AV Chobanian, GL Bakris, HR Black, WC Cushman, LA Green, JL Izzo Jr, DW Jones, BJ Materson, S Oparil, JT Wright Jr, EJ Roccella; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003; 289(19): 2560–2572
https://doi.org/10.1001/jama.289.19.2560 pmid: 12748199
13 R Yu, Y Yang, Y Tian, Y Zhang, G Lyu, J Zhu, L Xiao, J. Zhu The mechanism played by 1,25-dihydroxyvitamin D3 in treating renal fibrosis in diabetic nephropathy. Chin J Endocrinol Metab (Zhonghua Nei Fen Mi Dai Xie Za Zhi) 2015; 9: 793–799 (in Chinese)
14 Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013; 3: 1–150
https://doi.org/10.1038/kisup.2012.73
15 YC Wang, Y Li, XY Wang, D Zhang, H Zhang, Q Wu, YQ He, JY Wang, L Zhang, H Xia, J Yan, X Li, H Ying. Circulating miR-130b mediates metabolic crosstalk between fat and muscle in overweight/obesity. Diabetologia 2013; 56(10): 2275–2285
https://doi.org/10.1007/s00125-013-2996-8 pmid: 23868745
16 EK Ng, WW Chong, H Jin, EK Lam, VY Shin, J Yu, TC Poon, SS Ng, JJ Sung. Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut 2009; 58(10): 1375–1381
https://doi.org/10.1136/gut.2008.167817 pmid: 19201770
17 FJ Ortega, JM Mercader, JM Moreno-Navarrete, O Rovira, E Guerra, E Esteve, G Xifra, C Martínez, W Ricart, J Rieusset, S Rome, M Karczewska-Kupczewska, M Straczkowski, JM Fernández-Real. Profiling of circulating microRNAs reveals common microRNAs linked to type 2 diabetes that change with insulin sensitization. Diabetes Care 2014; 37(5): 1375–1383
https://doi.org/10.2337/dc13-1847 pmid: 24478399
18 Y Shao, H Ren, C Lv, X Ma, C Wu, Q Wang. Changes of serum miR-217 and the correlation with the severity in type 2 diabetes patients with different stages of diabetic kidney disease. Endocrine 2017; 55(1): 130–138
https://doi.org/10.1007/s12020-016-1069-4 pmid: 27522360
19 X Ma, C Lu, C Lv, C Wu, Q. Wang The expression of miR-192 and its significance in diabetic nephropathy patients with different urine albumin creatinine ratio. J Diabetes Res 2016; 2016: 6789402
https://doi.org/10.1155/2016/6789402 pmid: 26881255
20 C Lv, YH Zhou, C Wu, Y Shao, CL Lu, QY Wang. The changes in miR-130b levels in human serum and the correlation with the severity of diabetic nephropathy. Diabetes Metab Res Rev 2015; 31(7): 717–724
https://doi.org/10.1002/dmrr.2659 pmid: 25952368
21 X Lin, Z Yang, P Zhang, Y Liu, G Shao. miR-154 inhibits migration and invasion of human non-small cell lung cancer by targeting ZEB2. Oncol Lett 2016; 12(1): 301–306
https://doi.org/10.3892/ol.2016.4577 pmid: 27347142
22 S Dambal, AA Giangreco, AM Acosta, A Fairchild, Z Richards, R Deaton, D Wagner, R Vieth, PH Gann, A Kajdacsy-Balla, T Van der Kwast, L Nonn. MicroRNAs and DICER1 are regulated by 1,25-dihydroxyvitamin D in prostate stroma. J Steroid Biochem Mol Biol 2017; 167: 192–202
https://doi.org/10.1016/j.jsbmb.2017.01.004 pmid: 28089917
23 JM Luk, J Burchard, C Zhang, AM Liu, KF Wong, FH Shek, NP Lee, ST Fan, RT Poon, I Ivanovska, U Philippar, MA Cleary, CA Buser, PM Shaw, CN Lee, DG Tenen, H Dai, M Mao. DLK1-DIO3 genomic imprinted microRNA cluster at 14q32.2 defines a stemlike subtype of hepatocellular carcinoma associated with poor survival. J Biol Chem 2011; 286(35): 30706–30713
https://doi.org/10.1074/jbc.M111.229831 pmid: 21737452
24 C Xin, H Zhang, Z Liu. miR-154 suppresses colorectal cancer cell growth and motility by targeting TLR2. Mol Cell Biochem 2014; 387(1-2): 271–277
https://doi.org/10.1007/s11010-013-1892-3 pmid: 24242044
25 E Gardiner, NJ Beveridge, JQ Wu, V Carr, RJ Scott, PA Tooney, MJ Cairns. Imprinted DLK1-DIO3 region of 14q32 defines a schizophrenia-associated miRNA signature in peripheral blood mononuclear cells. Mol Psychiatry 2012; 17(8): 827–840
https://doi.org/10.1038/mp.2011.78 pmid: 21727898
26 A Formosa, EK Markert, AM Lena, D Italiano, E Finazzi-Agro’, AJ Levine, S Bernardini, AV Garabadgiu, G Melino, E Candi. MicroRNAs, miR-154, miR-299-5p, miR-376a, miR-376c, miR-377, miR-381, miR-487b, miR-485-3p, miR-495 and miR-654-3p, mapped to the 14q32.31 locus, regulate proliferation, apoptosis, migration and invasion in metastatic prostate cancer cells. Oncogene 2014; 33(44): 5173–5182
https://doi.org/10.1038/onc.2013.451 pmid: 24166498
27 H Seitz, H Royo, ML Bortolin, SP Lin, AC Ferguson-Smith, J Cavaillé. A large imprinted microRNA gene cluster at the mouse Dlk1-Gtl2 domain. Genome Res 2004; 14(9): 1741–1748
https://doi.org/10.1101/gr.2743304 pmid: 15310658
28 A Dixon-McIver, P East, CA Mein, JB Cazier, G Molloy, T Chaplin, T Andrew Lister, BD Young, S Debernardi. Distinctive patterns of microRNA expression associated with karyotype in acute myeloid leukaemia. PLoS One 2008; 3(5): e2141
https://doi.org/10.1371/journal.pone.0002141 pmid: 18478077
29 Y Altuvia, P Landgraf, G Lithwick, N Elefant, S Pfeffer, A Aravin, MJ Brownstein, T Tuschl, H Margalit. Clustering and conservation patterns of human microRNAs. Nucleic Acids Res 2005; 33(8): 2697–2706
https://doi.org/10.1093/nar/gki567 pmid: 15891114
30 N Kaminski, P Benos, D Corcoran, KV Pandit, J Milosevic, H Yousef. MicroRNAs In Idiopathic Pulmonary Fibrosis. Mosby, Inc., 2012. 191–199
31 H Yang, L Wang, J Zhao, Y Chen, Z Lei, X Liu, W Xia, L Guo, HT Zhang. TGF-b-activated SMAD3/4 complex transcriptionally upregulates N-cadherin expression in non-small cell lung cancer. Lung Cancer 2015; 87(3): 249–257
https://doi.org/10.1016/j.lungcan.2014.12.015 pmid: 25595426
32 Y Li, F Hu, M Xue, YJ Jia, ZJ Zheng, L Wang, MP Guan, YM Xue. Klotho down-regulates Egr-1 by inhibiting TGF-b1/Smad3 signaling in high glucose treated human mesangial cells. Biochem Biophys Res Commun 2017; 487(2): 216–222
https://doi.org/10.1016/j.bbrc.2017.04.036 pmid: 28411025
33 J Huang, J Wu, Y Li, X Li, T Yang, Q Yang, Y Jiang. Deregulation of serum microRNA expression is associated with cigarette smoking and lung cancer. BioMed Res Int 2014; 2014: 364316
https://doi.org/10.1155/2014/364316 pmid: 25386559
34 Y Zheng, C Zhu, L Ma, P Shao, C Qin, P Li, Q Cao, X Ju, G Cheng, Q Zhu, X Gu, L Hua. miRNA-154-5p inhibits proliferation, migration and invasion by targeting E2F5 in prostate cancer cell lines. Urol Int 2017; 98(1): 102–110
https://doi.org/10.1159/000445252 pmid: 27074041
35 J Ding, JL Li, MK Yu. Expression of miRNA-154 in astrocytomas and its clinical significance. Chin Clin Oncol (Lin Chuang Zhong Liu Xue Za Zhi) 2017; 22(4): 314–318 (in Chinese)
36 HY Liu, CH Zhang. China’s urban and rural public health resources insufficiency input or unbalanced allocation. Chin Health Econ (Zhongguo Wei Sheng Jing Ji) 2012; 31(8): 12–15 (in Chinese)
37 Z Feng. Chinese health care in rural areas. BMJ 2010; 341: c5254
https://doi.org/10.1136/bmj.c5254 pmid: 20966007
38 KDOQI. KDOQI clinical practice guidelines and clinical practice recommendations for diabetes and chronic disease. Am J Kidney Dis 2007; 49(2 Suppl 2): S12–S154
https://doi.org/10.1053/j.ajkd.2006.12.005 pmid: 17276798
39 KR Tuttle, GL Bakris, RW Bilous, JL Chiang, IH de Boer, J Goldstein-Fuchs, IB Hirsch, K Kalantar-Zadeh, AS Narva, SD Navaneethan, JJ Neumiller, UD Patel, RE Ratner, AT Whaley-Connell, ME Molitch. Diabetic kidney disease: a report from an ADA Consensus Conference. Am J Kidney Dis 2014; 64(4): 510–533
https://doi.org/10.1053/j.ajkd.2014.08.001 pmid: 25257325
40 National Clinical Guideline Centre (UK). Chronic Kidney Disease (Partial Update): Early Identification and Management of Chronic Kidney Disease in Adults in Primary and Secondary Care. London: National Institute for Health and Care Excellence (UK). 2014
pmid: 25340245
41 BS Zitkus. Update on the American Diabetes Association Standards of Medical Care. Nurse Pract 2014; 39(8): 22–32
https://doi.org/10.1146/annurev.pathol.4.110807.092150 pmid: 24979246
42 YS Kanwar, L Sun, P Xie, FY Liu, S Chen. A glimpse of various pathogenetic mechanisms of diabetic nephropathy. Annu Rev Pathol 2011; 6(1): 395–423
https://doi.org/10.1097/01.NPR.0000451880.48790.50 pmid: 21261520
43 HY Lan, ACK Chung. Transforming growth factor-b and Smads. Contrib Nephrol 2011; 170: 75–82
https://doi.org/10.1159/000324949 pmid: 21659760
44 Y Sato. The vasohibin family: a novel family for angiogenesis regulation. J Biochem 2013; 153(1): 5–11
https://doi.org/10.1093/jb/mvs128 pmid: 23100270
45 XF Yao, D Cai, JJ Quan. Levels and clinical significances of IGF-1, TGF-β and VEGF in patients with type 2 diabetic nephropathy. Med Pharm J Chin PLA (Jie Fang Jun Yi Yao Za Zhi) 2017; 29(6): 78–81 (in Chinese)
46 SA Fathy, MR Mohamed, M A M Ali, AE El-Helaly, AT Alattar. Influence of IL-6, IL-10, IFN-γ and TNF-α genetic variants on susceptibility to diabetic kidney disease in type 2 diabetes mellitus patients. Biomarkers 2019; 24(1): 43–55
pmid: 30015512
47 C Lu, HD Han, LS Mangala, R Ali-Fehmi, CS Newton, L Ozbun, GN Armaiz-Pena, W Hu, RL Stone, A Munkarah, MK Ravoori, MM Shahzad, JW Lee, E Mora, RR Langley, AR Carroll, K Matsuo, WA Spannuth, R Schmandt, NB Jennings, BW Goodman, RB Jaffe, AM Nick, HS Kim, EO Guven, YH Chen, LY Li, MC Hsu, RL Coleman, GA Calin, EB Denkbas, JY Lim, JS Lee, V Kundra, MJ Birrer, MC Hung, G Lopez-Berestein, AK Sood. Regulation of tumor angiogenesis by EZH2. Cancer Cell 2010; 18(2): 185–197
https://doi.org/10.1016/j.ccr.2010.06.016 pmid: 20708159
48 ES Yeo, JY Hwang, JE Park, YJ Choi, KB Huh, WY Kim. Tumor necrosis factor (TNF-α) and C-reactive protein (CRP) are positively associated with the risk of chronic kidney disease in patients with type 2 diabetes. Yonsei Med J 2010; 51(4): 519–525
https://doi.org/10.3349/ymj.2010.51.4.519 pmid: 20499416
49 CJ Magri, N Calleja, G Buhagiar, S Fava, J Vassallo. Factors associated with diabetic nephropathy in subjects with proliferative retinopathy. Int Urol Nephrol 2012; 44(1): 197–206
https://doi.org/10.1007/s11255-011-9958-1 pmid: 21516475
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