Screening Of Serum Markers For Early Diagnosis Of Osteoporosis In Elderly Men

Objective: Using proteomics to compare the differences in serum proteins between elderly men with osteoporosis(Osteoporosis,OP)and normal people,to screen out potential serum markers that can be used for early diagnosis of elderly men with osteoporosis.Methods: Select elderly male osteoporosis patients who were admitted to Subei People’s Hospital from June 2018 to March 2019 and ensure that the information is complete.Select 24 serum samples from the normal population and the elderly male osteoporosis population that meet the criteria for inclusion,and perform isobaric tags for relative and absolute quantification(iTRAQ)peptide labeling,grading,mass spectrometry,and mass spectrometry analysis on the samples.Database comparison,bioinformatics analysis,comparing the differences between the proteins in each group of samples,screening out the proteins with obvious differences(Fold change>1.20 or <0.84,P<0.05),which is defined as the difference protein in the experiment,find recent relevant literature to select and preliminary analysis of the obtained differential proteins.By analyzing the characteristics of differential proteins and their association with osteoporosis,the potential serum markers for the early diagnosis of osteoporosis in elderly men were initially screened.Results: 1、Differential protein identification and quantitative result evaluation In this experiment,mass spectrometry data was obtained by the Q Exactive Plus high-resolution mass spectrometer,which can export high-quality mass spectroscopy(MS)spectra,including MS1 spectra and MS2 spectra.Use Mascot(Mascot daemon)software for data analysis of the MS spectrum obtained above.We usually use Mascot software as a standard tool for MS spectrum analysis,and finally output the score of each MS2 spectrum.In the protein qualitative experiment,the results of each group of iTRAQ used FDR <0.01 as the selection criterion,combined with the results output by the Mascot software,which proved the dispersion trend of high-quality peptide scores,indicating that the MS experimental data obtained was of high quality.In this experiment,the peptide ion score scatter diagram obtained by Mascot shows that more than 70% of the peptide scores are greater than 20,and the median is 20.Therefore,the score of MS2 passing Mascot in this experiment is in line with the expected result.2、Differential protein quantitative results This experiment is based on the quantitative proteomics experiment results of iTRAQ.A total of 227,876 secondary mass spectra were obtained.A total of 47,491 matched peptide spectra were obtained through the software database.The results showed a total of 11,063 peptides.The total number of unique peptides is 4713.In the end,a total of 932 proteins were identified for further research.3、Differential protein screening results Among the 932 proteins identified by the data center,the expression of the protein in the "osteoporosis group" has a significant change(increased or decreased)(Fold change>1.20 or<0.84,P<0.05);and there is no significant change in the expression in the "normal group"(Fold change<1.20 or<0.84 or P>0.05)as the screening condition,and the protein that meets the screening criteria is determined to be the differential protein studied in this experiment.Total screening have 31 different protein,containing eight higher protein and 23 protein.4、Bioinformatics analysis Based on Ingenuity Pathway Analysis(IPA),we analyze the upstream regulatory factors of genes and explore the degree of association between upstream regulatory factors and proteins,which shows that we explore the upstream regulatory factors of all differential genes.As a gene upstream regulatory factor,it can be any molecule that can interfere with gene expression,including transcription factors Micro RNA(mi RNA),receptors,and kinases.In this investigation,using algorithm tools based on the inhibition of KRT6 B,DDT,IGFBP3,HBA1/A2 genes,it can be predicted that the upstream regulator trichostatin A will also be inhibited,further proving that they have potential interactions and can carry out these related proteins.In-depth research and analysis.Interaction network analysis using IPA.This experiment further analyzed the interaction network of 31 differential proteins,and showed that of the 31 proteins identified in this study,13 proteins are connected to each other in the protein protein interaction(PPI)network.In addition,we found that KRT is located in the center of the network and has a complex relationship with other proteins.EPHA4 is significantly up-regulated and the bioinformatics function is in line with expectations,while OSTF1 has a positive correlation with osteoporosis,which is the same as the conclusions of recent domestic and foreign literature.The results show that the EPHA4,KRT,and OSTF1 that we have screened are valuable as potential biomarkers for elderly men with osteoporosis.Conclusion: There are significant differences in serum protein expression between elderly men with osteoporosis and normal people.31 differential proteins were initially screened through iTRAQ technology,of which 8 proteins were up-regulated in the osteoporosis group and 23 proteins were down-regulated.According to bioinformatics analysis and related literature,comparing the effects and connections of different proteins in the organism,this experiment selected EPHA4,KRT,OSTF1 as potential candidate biomarkers for the early diagnosis of osteoporosis in elderly men,which is more in-depth One step to explore its pathogenesis,early diagnosis and treatment provide new research directions.