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Differential urinary proteomics analysis of myocardial infarction using iTRAQ quantification.

ABSTRACT: Myocardial infarction (MI) is a disease characterized by high morbidity and mortality rates. MI biomarkers are frequently used in clinical diagnosis; however, their specificity and sensitivity remain unsatisfactory. Urinary proteome is an easy, efficient and noninvasive source to examine biomarkers associated with various diseases. The present study, to the best of the authors' knowledge, is the first to examine the urinary proteome using the isobaric tags for relative and absolute quantitation (iTRAQ) technology to identify potential diagnostic biomarkers of MI. The urinary proteome was analyzed within 12 h following the first symptoms of early?onset MI and at day 7 following percutaneous coronary intervention via iTRAQ labeling and two?dimensional liquid chromatography?tandem mass spectrometry. Candidate biomarkers were validated by multiple reaction monitoring (MRM) analysis. A total of 233 urinary proteins were differentially expressed. Gene enrichment analysis identified that the urinary proteome in patients with MI was associated with atherosclerosis, abnormal coagulation and abnormal cell metabolism. In total, 12 differentially expressed urinary proteins were validated by MRM analysis, five of which were associated with MI for the first time in the present study. Binary logistic regression analysis suggested that the combination of five urinary proteins (antithrombin?III, complement C3, ??1?acid glycoprotein 1, serotransferrin and cathepsin Z) may be used to diagnose MI with 94% sensitivity and 93% specificity. In addition, the protein expression levels of three proteins were significantly restored to normal levels following surgical treatment. The verified candidate biomarkers may be used for the diagnosis of MI, and for monitoring the disease status and the effects of treatments for MI. The present results may facilitate future clinical applications of the urinary proteome to diagnose MI.

SUBMITTER: Zou L

PROVIDER: S-EPMC6471447 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Differential urinary proteomics analysis of myocardial infarction using iTRAQ quantification.

Zou Lili L Wang Xubo X Guo Zhengguang Z Sun Haidan H Shao Chen C Yang Yehong Y Sun Wei W

Molecular medicine reports 20190326 5

Myocardial infarction (MI) is a disease characterized by high morbidity and mortality rates. MI biomarkers are frequently used in clinical diagnosis; however, their specificity and sensitivity remain unsatisfactory. Urinary proteome is an easy, efficient and noninvasive source to examine biomarkers associated with various diseases. The present study, to the best of the authors' knowledge, is the first to examine the urinary proteome using the isobaric tags for relative and absolute quantitation ...[more]

PMID: 30942401

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Project description:BackgroundDiabetic nephropathy (DN) is the leading cause of chronic kidney failure and end-stage kidney disease. More accurate and non-invasive test for the diagnosis and monitoring the progression of DN is urgently needed for the better care of such patients.MethodsIn this study we utilized urinary glycoproteome to discover the differential proteins during the course of type 2 DN. The urinary glycoproteins from normal controls, normalbuminuira, microalbuminura, and macroalbuminuria patients were enriched by concanavalin A (ConA) and analyzed by 2DLC/MS/MS and isobaric tags for relative and absolute quantitation quantification.ResultsA total of 478 proteins were identified and 408 were annotated as N-linked glycoproteins. A total of 72, 107 and 123 differential proteins were identified in normalbuminuria, microalbuminuria and macroalbuminuria, respectively. By bioinformatics analysis, in normalbuminruia state, cell proliferation and cell movement were activated, which might reflect the compensatory phase during the disease development. In micro- and macro-albuminuria, cell death and apoptosis was activated, which might reflect the de-compensatory phase. Pathway analysis showed acute phase proteins, the member of high density lipoprotein and low density lipoprotein proteins were changed, indicating the role of the inflammatory response and lipid metabolism abnormality in the pathogenesis of DN. Six selected differential proteins were validated by Western Blot. Alpha-1-antitrypsin (SERPINA1) and Ceruloplasmin are the two markers with excellent area under curve values (0.929 and 1.000 respectively) to distinguish the microalbuminuria and normalbuminuria. For the first time, we found pro-epidermal growth factor and prolactin-inducible protein were decreased in macroalbuminuria stage, which might reflect the inhibition of cell viability and the activation of cell death in kidney.ConclusionsAbove data indicated that urinary glycoproteome could be useful to distinguish the differences in protein profiles in different stages in DN, which will help better individualized care of patients in DN.

Project description:BackgroundMass spectrometry based quantification of peptides can be performed using the iTRAQ reagent in conjunction with mass spectrometry. This technology yields information about the relative abundance of single peptides. A method for the calculation of reliable quantification information is required in order to obtain biologically relevant data at the protein expression level.ResultsA method comprising sound error estimation and statistical methods is presented that allows precise abundance analysis plus error calculation at the peptide as well as at the protein level. This yields the relevant information that is required for quantitative proteomics. Comparing the performance of our method named Quant with existing approaches the error estimation is reliable and offers information for precise bioinformatic models. Quant is shown to generate results that are consistent with those produced by ProQuant, thus validating both systems. Moreover, the results are consistent with that of Mascot 2.2. The MATLAB scripts of Quant are freely available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/, each under the GNU Lesser General Public License.ConclusionThe software Quant demonstrates improvements in protein quantification using iTRAQ. Precise quantification data can be obtained at the protein level when using error propagation and adequate visualization. Quant integrates both and additionally provides the possibility to obtain more reliable results by calculation of wise quality measures. Peak area integration has been replaced by sum of intensities, yielding more reliable quantification results. Additionally, Quant allows the combination of quantitative information obtained by iTRAQ with peptide and protein identifications from popular tandem MS identification tools. Hence Quant is a useful tool for the proteomics community and may help improving analysis of proteomic experimental data. In addition, we have shown that a lognormal distribution fits the data of mass spectrometry based relative peptide quantification.

Project description:ObjectiveThe isobaric tags for relative and absolute quantification (iTRAQ) technique for proteomic analysis was employed to identify diagnostic markers and therapeutic targets of Shenkangling intervention or prednisone tablets in rats with adriamycin nephropathy (AN).MethodsFifty healthy, clean-grade Sprague-Dawley rats were selected, with 10 rats in the normal group and the remaining 40 rats receiving a tail vein injection of 5.5 mg/kg of adriamycin (ADR) to induce AN. Treatment began 1 week later. The normal group received gastric administration of normal saline. Forty rats with induced AN were further randomly divided into the AN modeling group (n = 10), AN modeling + prednisone treatment group (n = 10), AN modeling + Shenkangling intervention group (n = 10), and AN modeling + prednisone + Shenkangling intervention group (n = 10). iTRAQ was employed in combination with mass spectrometry to analyze the differentially expressed proteins in the urine after 3 weeks of treatment (in the fourth week of the experiment).ResultsCompared with normal rats, AN rats had 6 down-regulated proteins and 1 upregulated protein. Compared with AN rats, prednisone rats had 2 down-regulated and 6 upregulated proteins. Compared with AN rats, combined treatment rats had 2 down-regulated and 8 upregulated proteins. Compared with the AN model group, the Shenkangling treatment group had 3 down-regulated and 9 upregulated proteins. Gro, Afamin, Cystatin-related protein 2, Afamin, and isoform CRA_a were considered diagnostic markers of primary nephrotic syndrome (PNS). Telomerase was considered the therapeutic target of prednisone. Urinary protein 2, Apolipoprotein A-II, 45 kDa calcium-binding protein, Vitronectin, and Osteopontin were the therapeutic targets of the Shenkangling intervention. Afamin, isoform CRA_a, Apolipoprotein A-IV, Coagulation factor XII, Prolactin-induced protein, and Coagulation factor XII were the therapeutic targets of the Shenkangling intervention combined with prednisone.ConclusionThe feasibility of urinary proteomics analysis in rats using a large number of proteins with finite molecular weights is controversial. The markers screened in this study may be of clinical value for the diagnosis and treatment of nephropathy. However, these findings should be confirmed in future cohort studies.

Dataset Information

Differential urinary proteomics analysis of myocardial infarction using iTRAQ quantification.

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Differential urinary proteomics analysis of myocardial infarction using iTRAQ quantification.

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