Background The initiation and progression of diabetic nephropathy (DN) is complex. Quantification of mRNA expression in urinary sediment has emerged as a novel strategy for studying renal diseases. Considering the numerous molecules involved in DN development, a high-throughput platform with parallel detection of multiple mRNAs is needed. In this study, we constructed a self-assembling mRNA array to analyze urinary mRNAs in DN patients with aims to reveal its potential in searching novel biomarkers. Methods mRNA array containing 88 genes were fabricated and its performance was evaluated. A pilot study with 9 subjects including 6 DN patients and 3 normal controls were studied with the array. DN patients were assigned into two groups according to their estimate glomerular rate (eGFR): DNI group (eGFR>60 ml/min/1.73 m2, n = 3) and DNII group (eGFR<60 ml/min/1.73 m2, n = 3). Urinary cell pellet was collected from each study participant. Relative abundance of these target mRNAs from urinary pellet was quantified with the array. Results The array we fabricated displayed high sensitivity and specificity. Moreover, the Cts of Positive PCR Controls in our experiments were 24±0.5 which indicated high repeatability of the array. A total of 29 mRNAs were significantly increased in DN patients compared with controls (p<0.05). Among these genes, α-actinin4, CDH2, ACE, FAT1, synaptopodin, COL4α, twist, NOTCH3 mRNA expression were 15-fold higher than those in normal controls. In contrast, urinary TIMP-1 mRNA was significantly decreased in DN patients (p<0.05). It was shown that CTGF, MCP-1, PAI-1, ACE, CDH1, CDH2 mRNA varied significantly among the 3 study groups, and their mRNA levels increased with DN progression (p<0.05). Conclusion Our pilot study demonstrated that mRNA array might serve as a high-throughput and sensitive tool for detecting mRNA expression in urinary sediment. Thus, this primary study indicated that mRNA array probably could be a useful tool for searching new biomarkers for DN.
References
[1]
Atkins RC, Zimmet P (2010) World Kidney Day 2010: diabetic kidney disease–act now or pay later. Am J Kidney Dis 55: 205–8.
[2]
Chang SS (2008) Albuminuria and diabetic nephropathy. Pediatr Endocrinol Rev 5: Suppl 4974–9.
[3]
Macisaac RJ, Jerums G (2011) Diabetic kidney disease with and without albuminuria. Curr Opin Nephrol Hypertens 20: 246–57.
[4]
Navarro-Gonzalez JF, Mora-Fernandez C, Muros de Fuentes M, Garcia-Perez J (2011) Inflammatory molecules and pathways in the pathogenesis of diabetic nephropathy. Nat Rev Nephrol 7: 327–40.
[5]
Li MX, Liu BC (2007) Epithelial to mesenchymal transition in the progression of tubulointerstitial fibrosis. Chin Med J (Engl) 120: 1925–30.
[6]
Tesch GH, Lim AK (2011) Recent insights into diabetic renal injury from the db/db mouse model of type 2 diabetic nephropathy. Am J Physiol Renal Physiol 300: F301–10.
[7]
Menzel S, Moeller MJ (2011) Role of the podocyte in proteinuria. Pediatr Nephrol 26: 1775–80.
[8]
Muthukumar T, Dadhania D, Ding R, Snopkowski C, Naqvi R, et al. (2005) Messenger RNA for FOXP3 in the urine of renal-allograft recipients. N Engl J Med 353: 2342–51.
[9]
Wang G, Lai FM, Lai KB, Chow KM, Kwan CH, et al. (2008) Urinary mRNA expression of ACE and ACE2 in human type 2 diabetic nephropathy. Diabetologia 51: 1062–7.
[10]
Zheng M, Lv LL, Ni J, Ni HF, Li Q, et al. (2011) Urinary podocyte-associated mRNA profile in various stages of diabetic nephropathy. PLoS One 6: e20431.
[11]
Zheng M, Lv LL, Cao YH, Zhang JD, Wu M, et al. (2011) Urinary mRNA markers of epithelial-mesenchymal transition correlate with progression of diabetic nephropathy. Clin Endocrinol (Oxf). [Epub ahead of print].
[12]
Roepman P (2010) The future of diagnostic gene-expression microarrays: bridging the gap between bench and bedside. Bioanalysis 2: 249–62.
[13]
Svensson K, Granberg M, Karlsson L, Neubauerova V, Forsman M, et al. (2009) A real-time PCR array for hierarchical identification of Francisella isolates. PLoS One 4: e8360.
[14]
Munshi R, Johnson A, Siew ED, Ikizler TA, Ware LB, et al. (2011) MCP-1 gene activation marks acute kidney injury. J Am Soc Nephrol 22: 165–75.
[15]
Rodder S, Scherer A, Korner M, Marti HP (2011) A subset of metzincins and related genes constitutes a marker of human solid organ fibrosis. Virchows Arch 458: 487–96.
[16]
Wu CC, Chen JS, Huang CF, Chen CC, Lu KC, et al. (2011) Approaching biomarkers of membranous nephropathy from a murine model to human disease. J Biomed Biotechnol 581928:
[17]
Petermann AT, Krofft R, Blonski M, Hiromura K, Vaughn M, et al. (2003) Podocytes that detach in experimental membranous nephropathy are viable. Kidney Int 64: 1222–31.
[18]
Vogelmann SU, Nelson WJ, Myers BD, Lemley KV (2003) Urinary excretion of viable podocytes in health and renal disease. Am J Physiol Renal Physiol 285: F40–8.
[19]
Tam FW, Riser BL, Meeran K, Rambow J, Pusey CD, et al. (2009) Urinary monocyte chemoattractant protein-1 (MCP-1) and connective tissue growth factor (CCN2) as prognostic markers for progression of diabetic nephropathy. Cytokine 47: 37–42.
[20]
Huang Y, Border WA, Yu L, Zhang J, Lawrence DA, et al. (2008) A PAI-1 mutant, PAI-1R, slows progression of diabetic nephropathy. J Am Soc Nephrol 19: 329–38.
[21]
Chawla T, Sharma D, Singh A (2010) Role of the renin angiotensin system in diabetic nephropathy. World J Diabetes 1: 141–5.
[22]
Liu Y (2010) New insights into epithelial-mesenchymal transition in kidney fibrosis. J Am Soc Nephrol 21: 212–22.
[23]
National Kidney Foundation (2007) KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 49: S12–154.
[24]
Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, et al. (2006) Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol 17: 2937–44.
