Screening Of Silica-exposed Population Serum Biomarkers And Studying Of The Related Functions Of The Biomarkers

Slilicosis, with the characteristics of pulmonary interstitial fibrosis, is caused by long-term inhalation of a large number of free slilica dust .It is one of the most serious occupational diseases in China.The average annual economic losses of each pneumoconiosis case was about 34.1 thousand yuan and the direct economic losses caused by silicosis alone were more than 140 billion yuan each year.An annual increase of cases of pneumoconiosis could cause economic losses of 600 million yuan.In recent years,the prevalence of silicosis showing new features of group incidence, lower-aged tendency and high-disabled rate,which brings new chanllenges for prevetion and treatment of silicosis.Recently,many of the valuable serum biomarkers have been found for the diagnosis of silicosis, such as the lung-specific Clara cell protein(CC16) and pulmonary surfactant D(SP-D).As the diagnostic indicators, they still exist disadvantages of sentisitivity and specificity and different types of interstitial lung disease exist large overlap of these indicators.However,bronchoalveolar lavage fluid chemistry and cytology can only add or exclude from imaging diagnosis.The use of new technology to screen high specific and sensitive biomarkers will play an important force in prevention and treatment of silicosis.Liquid-chip time of flight mass spectrometry is one of the protein identification techniques that bases on magnetic beads separation combined with matrix-assisted laser desorption ionization time of flight mass spectrometry(MALDI-TOF-MS).It can directly detect clinical specimens without special treatment,such as serum,urine fluid,cerebrospinal fluid, serous effusion or others but with high sensitivity and specificity for diagnosis.The aim of this study is to screen serum biomarkers of silica-exposed population by Liquid-chip time of flight mass spectrometry,then estabilish an artifical neural network model for early diagnosis and identify some associated functions of the markers which may contribute to a further study of the pathogenesis of silicosis mechanisms.ObjectivesTo screen serum biomarkers of silica-exposed population for early diagnosis by liquid-chip time of flight mass spectrometry,and identify some associated functions of the markers.MethodsEighty-five workers were selected from refractory plant of YangQuan City,ShanXi Province. All the silica-exposed population were diagnosed as having phase 0,phase 0+,or phase I of silicosis using radiograph(120-150KV, 100mA, 0.03-0.05s), following the national diagnostic standard(GBZ70-2002) of China for pneumoconsis.Thirty healthy people without silica exposure history were chosen as the control population.Serum proteins(peptides) from silica-exposed population and control population was separated by a kind of magnetic beads produced by Invitrogen Company called Dynabeads RPC18, using MALDI-TOF-MS and an analysis software called ClinProTools to screen differences in protein peaks.Then,Matlab analysis software was applied to estabilish an artificial neural network diagnosis model.Finally, the amino acid sequences of the selected protein peaks were identified by MALDI-TOF-TOF-MS.According to the amino acid sequence identified by MALDI-TOF-TOF-MS to synthesize the selected protein. Using different concentrations of protein solutions as stimulus to observe the effects of the target cells in the formation of silicosis called human embryo lung fibroblast(MRC-5) cells.Results1. Differentially expressed protein peaks found by MALDI-TOF-MSUsing neural network algorithm(SNN) to build pairwise comparison between each two groups, we found that the recognition rates between phase 0 and 0+, phase 0 and I , phase 0+ and I were respectively 64.35%,84.38% and 73.49%, similarly the cross-validations were 63.14%,52.82% and 69.07%; while between control group and phase 0, control group and phase 0+, control group and phase I, the recognition rates were 89.23%,98.52% and 98.96% respectively, similarly the cross-validations were 87.66%,94.20% and 85.53%.Clear from the foregoing, the recognition rates and cross-validation capabilities between phase 0 and 0+, phase 0 and I, phase 0+ and I are all poor; while between control group and phase 0, control group and phase 0+, control group and phase I are all better. Thus, we just study differentially expressed protein peaks between control group and phase 0, control group and phase 0+, control group and phase I. A total of 5 peaks (P<0.01)have been found, in which the expressions of 5081Da and 5066Da are up-regulated while the expressions of 3954Da, 2021Da and 1777Da are down-regulated.2. Amino acid sequence identified by MALDI-TOF-TOF-MS2021Da and 1777Da peaks with molecular weight <3KD are selected for MALDI-TOF-TOF-MS. The amino acid sequences of the two peaks identified are both a fragment of complement C3 called complement C3f.3. the correlation between the exprosure dose of dust and the intensitiy of peaks in silica-exposed populationThe correlation coefficient is respectively r5081=0.039(P=0.614), r5066=0.104(P=0.180),r3954=-0.047(P=0.543),r2021=-0.028(P=0.714),r1777=-0.016(P=0.853),and there were no correlation between each group.4.Establishment of artificial neural network diagnosis model of silica-exposed populationPeaks of 2021Da, 2554Da, 5066Da, 8600Da(P<0.01) are chosen to estabilish the diagnosis model. The specificity, sensitivity and accuracy rate of the model to distinguish between silica-exposed population and control group are 100%, 90% and 92.3%. While the recognition rates of phase 0,phase 0+ and phase I are respectively 100%,93% and 96%.5.Expression differences of typeâ… ,â… collagen and TGF-β₁in the supernatant of MRC-5 stimulated by C3f with different concentrationsWith the increasing concentrations of C3f, the expressions of typeâ… ,â… collagen and TGF-β₁ show progressive reductions.Compared with control group, any concentration points are significantly different(P<0.05). 6.Expression differences of TGF-β₁ in the cytoplasm of MRC-5 stimulated by C3f with different concentrationsWith the increasing concentrations of C3f, the expressions of TGF-β₁ show progressive reductions.Compared with control group, any concentration points are significantly different(P<0.05).Conclusions1.Using MALDI-TOF-MS of liquid-chip time of flight mass spectrometry to search differentially expressed protein peaks and successfully estabilish artificial neural network diagnosis model of silica-exposed population. 2.Using MALDI-TOF-TOF-MS of liquid-chip time of flight mass spectrometry to identify the peaks of 1777Da and 2021Da are both complement C3f. The following functional studies have show that C3f can reduce the formation of typeâ… ,â… collagen and TGF-β₁of MRC-5.In summary, this study successfully estabilishs artificial neural network diagnosis model of silica-exposed population which can offer a new and effective way for the early diagnosis of silica-exposed population,while the following functional study of C3f provides a clue for further study of the immune mechanisms in the pathogenesis of silicosis.