Proteomic analysis of peritoneal dialysate fluid in patients with different types of peritoneal membranes

Efficacy of peritoneal dialysis is determined by solute transport through peritoneal membranes. With the use of the peritoneal equilibration test (PET), peritoneal membranes can be classified as high (H), high average (HA), low average (LA), and low (L) transporters, based on the removal or transport rate of solutes, which are small molecules. Whether there is any difference in macromolecules (i.e., proteins) removed by different types of peritoneal membranes remains unclear. We performed a gel-based differential proteomics study of peritoneal dialysate effluents (PDE) obtained from chronic peritoneal dialysis (CPD) patients with H, HA, LA, and L transport rates (n=5 for each group; total n=20). Quantitative analysis and ANOVA with Tukey's posthoc multiple comparisons revealed five proteins whose abundance in PDE significantly differed among groups. These proteins were successfully identified by matrix-assisted laser desorption ionization quadrupole time-of-flight (MALDI-Q-TOF) mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analyses, including serum albumin in a complex with myristic acid and triiodobenzoic acid, alpha1-antitrypsin, complement component C4A, immunoglobulin kappa light chain, and apolipoprotein A-I. The differences among groups in PDE levels of C4A and immunoglobulin kappa were clearly confirmed in a validation set of the other 24 patients (n=6 for each group) using ELISA. These data may lead to better understanding of the physiology of peritoneal membrane transport in CPD patients. Extending the study to a larger number of patients with subgroup analyses may yield additional information of the peritoneal dialysate proteins in association with dialysis adequacy, residual renal function, nutritional status, and risk of peritoneal infection.     

Association between Human Prothrombin Variant (T165M) and Kidney Stone Disease

We previously reported the association between prothrombin (F2), encoding a stone inhibitor protein - urinary prothrombin fragment 1 (UPTF1), and the risk of kidney stone disease in Northeastern Thai patients. To identify specific F2 variation responsible for the kidney stone risk, we conducted sequencing analysis of this gene in a group of the patients with kidney stone disease. Five intronic SNPs (rs2070850, rs2070852, rs1799867, rs2282687, and rs3136516) and one exonic non-synonymous single nucleotide polymorphism (nsSNP; rs5896) were found. The five intronic SNPs have no functional change as predicted by computer programs while the nsSNP rs5896 (c.494 C>T) located in exon 6 results in a substitution of threonine (T) by methionine (M) at the position 165 (T165M). The nsSNP rs5896 was subsequently genotyped in 209 patients and 216 control subjects. Genotypic and allelic frequencies of this nsSNP were analyzed for their association with kidney stone disease. The frequency of CC genotype of rs5896 was significantly lower in the patient group (13.4%) than that in the control group (22.2%) (P = 0.017, OR 0.54, 95% CI 0.32–0.90), and the frequency of C allele was significantly lower in the patient group (36.1%) than that in the control group (45.6%) (P = 0.005, OR 0.68, 95% CI 0.51–0.89). The significant differences of genotype and allele frequencies were maintained only in the female group (P = 0.033 and 0.003, respectively). The effect of amino-acid change on UPTF1 structure was also examined by homologous modeling and in silico mutagenesis. T165 is conserved and T165M substitution will affect hydrogen bond formation with E180. In conclusion, our results indicate that prothrombin variant (T165M) is associated with kidney stone risk in the Northeastern Thai female patients.     

Urinary proteome profiling using microfluidic technology on a chip

Clinical diagnostics and biomarker discovery are the major focuses of current clinical proteomics. In the present study, we applied microfluidic technology on a chip for proteome profiling of human urine from 31 normal healthy individuals (15 males and 16 females), 6 patients with diabetic nephropathy (DN), and 4 patients with IgA nephropathy (IgAN). Using only 4 microL of untreated urine, automated separation of proteins/peptides was achieved, and 1-7 (3.8 +/- 0.3) spectra/bands of urinary proteins/peptides were observed in the normal urine, whereas 8-16 (11.3 +/- 1.2) and 9-14 (10.8 +/- 1.2) spectra were observed in urine samples of DN and IgAN, respectively. Coefficient of variations of amplitudes of lower marker (1.2 kDa), system spectra (6-8 kDa), and upper marker (260.0 kDa) were 22.84, 24.92, and 32.65%, respectively. ANOVA with Tukey post-hoc multiple comparisons revealed 9 spectra of which amplitudes significantly differed between normal and DN urine (DN/normal amplitude ratios ranged from 2.9 to 3102.7). Moreover, the results also showed that 3 spectra (with molecular masses of 12-15, 27-28, and 34-35 kDa) were significantly different between DN and IgAN urine (DN/IgAN amplitude ratios ranged from 3.9 to 7.4). In addition to the spectral amplitudes, frequencies of some spectra could differentiate the normal from the diseased urine but could not distinguish between DN and IgAN. There was no significant difference, regarding the spectral amplitude or frequency, observed between males and females. These data indicate that the microfluidic chip technology is applicable for urinary proteome profiling with potential uses in clinical diagnostics and biomarker discovery.