CN117949663A - Screening method and application of novel biomarker for diagnosis of preschool childhood asthma - Google Patents
Screening method and application of novel biomarker for diagnosis of preschool childhood asthma Download PDFInfo
- Publication number
- CN117949663A CN117949663A CN202310709824.5A CN202310709824A CN117949663A CN 117949663 A CN117949663 A CN 117949663A CN 202310709824 A CN202310709824 A CN 202310709824A CN 117949663 A CN117949663 A CN 117949663A
- Authority
- CN
- China
- Prior art keywords
- asthma
- preschool
- proteins
- serum
- children
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 208000029771 childhood onset asthma Diseases 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000003745 diagnosis Methods 0.000 title claims abstract description 17
- 238000012216 screening Methods 0.000 title claims abstract description 8
- 239000000101 novel biomarker Substances 0.000 title claims abstract description 7
- 239000000090 biomarker Substances 0.000 claims abstract description 23
- 101000693844 Homo sapiens Insulin-like growth factor-binding protein complex acid labile subunit Proteins 0.000 claims abstract description 20
- 102100025515 Insulin-like growth factor-binding protein complex acid labile subunit Human genes 0.000 claims abstract description 20
- 102100033715 Apolipoprotein A-I Human genes 0.000 claims abstract description 12
- 101000733802 Homo sapiens Apolipoprotein A-I Proteins 0.000 claims abstract description 12
- 101001054659 Homo sapiens Latent-transforming growth factor beta-binding protein 1 Proteins 0.000 claims abstract description 9
- 102100027000 Latent-transforming growth factor beta-binding protein 1 Human genes 0.000 claims abstract description 9
- 239000000203 mixture Substances 0.000 claims abstract description 8
- 239000003814 drug Substances 0.000 claims abstract description 6
- 208000006673 asthma Diseases 0.000 claims description 77
- 108090000623 proteins and genes Proteins 0.000 claims description 49
- 102000004169 proteins and genes Human genes 0.000 claims description 48
- WEVYAHXRMPXWCK-UHFFFAOYSA-N Acetonitrile Chemical compound CC#N WEVYAHXRMPXWCK-UHFFFAOYSA-N 0.000 claims description 33
- 210000002966 serum Anatomy 0.000 claims description 27
- BDAGIHXWWSANSR-UHFFFAOYSA-N methanoic acid Natural products OC=O BDAGIHXWWSANSR-UHFFFAOYSA-N 0.000 claims description 16
- 108010026552 Proteome Proteins 0.000 claims description 14
- 238000004458 analytical method Methods 0.000 claims description 13
- 230000029087 digestion Effects 0.000 claims description 11
- 108090000765 processed proteins & peptides Proteins 0.000 claims description 10
- 208000024716 acute asthma Diseases 0.000 claims description 9
- 239000000091 biomarker candidate Substances 0.000 claims description 9
- OSWFIVFLDKOXQC-UHFFFAOYSA-N 4-(3-methoxyphenyl)aniline Chemical compound COC1=CC=CC(C=2C=CC(N)=CC=2)=C1 OSWFIVFLDKOXQC-UHFFFAOYSA-N 0.000 claims description 8
- 102000004142 Trypsin Human genes 0.000 claims description 8
- 108090000631 Trypsin Proteins 0.000 claims description 8
- 235000019253 formic acid Nutrition 0.000 claims description 8
- 239000012588 trypsin Substances 0.000 claims description 8
- 102100022987 Angiogenin Human genes 0.000 claims description 6
- 102000004506 Blood Proteins Human genes 0.000 claims description 6
- 108010017384 Blood Proteins Proteins 0.000 claims description 6
- 101000757236 Homo sapiens Angiogenin Proteins 0.000 claims description 6
- 239000000243 solution Substances 0.000 claims description 6
- 101000677768 Homo sapiens Protein ABHD12B Proteins 0.000 claims description 5
- 102100021513 Protein ABHD12B Human genes 0.000 claims description 5
- 210000004369 blood Anatomy 0.000 claims description 4
- 239000008280 blood Substances 0.000 claims description 4
- 238000000751 protein extraction Methods 0.000 claims description 4
- HNSDLXPSAYFUHK-UHFFFAOYSA-N 1,4-bis(2-ethylhexyl) sulfosuccinate Chemical compound CCCCC(CC)COC(=O)CC(S(O)(=O)=O)C(=O)OCC(CC)CCCC HNSDLXPSAYFUHK-UHFFFAOYSA-N 0.000 claims description 3
- 239000005977 Ethylene Substances 0.000 claims description 3
- 101001011906 Homo sapiens Matrix metalloproteinase-14 Proteins 0.000 claims description 3
- -1 LTBP Proteins 0.000 claims description 3
- 102100030216 Matrix metalloproteinase-14 Human genes 0.000 claims description 3
- VZTDIZULWFCMLS-UHFFFAOYSA-N ammonium formate Chemical compound [NH4+].[O-]C=O VZTDIZULWFCMLS-UHFFFAOYSA-N 0.000 claims description 3
- 239000003153 chemical reaction reagent Substances 0.000 claims description 3
- VHJLVAABSRFDPM-QWWZWVQMSA-N dithiothreitol Chemical compound SC[C@@H](O)[C@H](O)CS VHJLVAABSRFDPM-QWWZWVQMSA-N 0.000 claims description 3
- 229940079593 drug Drugs 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000005194 fractionation Methods 0.000 claims description 3
- PGLTVOMIXTUURA-UHFFFAOYSA-N iodoacetamide Chemical compound NC(=O)CI PGLTVOMIXTUURA-UHFFFAOYSA-N 0.000 claims description 3
- 238000001819 mass spectrum Methods 0.000 claims description 3
- 238000005191 phase separation Methods 0.000 claims description 3
- 239000012460 protein solution Substances 0.000 claims description 3
- 238000011084 recovery Methods 0.000 claims description 3
- 230000000717 retained effect Effects 0.000 claims description 3
- 230000035945 sensitivity Effects 0.000 claims description 3
- 239000006228 supernatant Substances 0.000 claims description 3
- 238000001195 ultra high performance liquid chromatography Methods 0.000 claims description 3
- 239000000104 diagnostic biomarker Substances 0.000 claims description 2
- 230000003334 potential effect Effects 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 claims 1
- 230000006870 function Effects 0.000 abstract description 5
- 230000008569 process Effects 0.000 abstract description 2
- 235000018102 proteins Nutrition 0.000 description 38
- 238000012360 testing method Methods 0.000 description 8
- 238000010201 enrichment analysis Methods 0.000 description 6
- 208000034657 Convalescence Diseases 0.000 description 5
- 230000036541 health Effects 0.000 description 5
- 238000001294 liquid chromatography-tandem mass spectrometry Methods 0.000 description 5
- 238000010239 partial least squares discriminant analysis Methods 0.000 description 5
- 230000037361 pathway Effects 0.000 description 5
- 238000000513 principal component analysis Methods 0.000 description 5
- 238000007789 sealing Methods 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 238000002965 ELISA Methods 0.000 description 4
- 238000007619 statistical method Methods 0.000 description 4
- 210000004027 cell Anatomy 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 3
- 239000007788 liquid Substances 0.000 description 3
- 230000019491 signal transduction Effects 0.000 description 3
- 230000003595 spectral effect Effects 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 239000000758 substrate Substances 0.000 description 3
- 238000004885 tandem mass spectrometry Methods 0.000 description 3
- 238000005406 washing Methods 0.000 description 3
- 208000000884 Airway Obstruction Diseases 0.000 description 2
- 238000000729 Fisher's exact test Methods 0.000 description 2
- 108010001336 Horseradish Peroxidase Proteins 0.000 description 2
- 102000015696 Interleukins Human genes 0.000 description 2
- 108010063738 Interleukins Proteins 0.000 description 2
- 238000012313 Kruskal-Wallis test Methods 0.000 description 2
- 238000000585 Mann–Whitney U test Methods 0.000 description 2
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 208000037883 airway inflammation Diseases 0.000 description 2
- 238000010009 beating Methods 0.000 description 2
- 238000003766 bioinformatics method Methods 0.000 description 2
- 230000031018 biological processes and functions Effects 0.000 description 2
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 description 2
- 238000007621 cluster analysis Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 108010057085 cytokine receptors Proteins 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000012774 diagnostic algorithm Methods 0.000 description 2
- 210000003979 eosinophil Anatomy 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000012634 fragment Substances 0.000 description 2
- 229940047122 interleukins Drugs 0.000 description 2
- 150000002500 ions Chemical class 0.000 description 2
- 238000002955 isolation Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004879 molecular function Effects 0.000 description 2
- 210000000440 neutrophil Anatomy 0.000 description 2
- 238000001558 permutation test Methods 0.000 description 2
- 238000000575 proteomic method Methods 0.000 description 2
- 239000002904 solvent Substances 0.000 description 2
- 208000024891 symptom Diseases 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- BBABSCYTNHOKOG-UHFFFAOYSA-N 1,2,3,4,5-pentachloro-6-methoxybenzene Chemical compound COC1=C(Cl)C(Cl)=C(Cl)C(Cl)=C1Cl BBABSCYTNHOKOG-UHFFFAOYSA-N 0.000 description 1
- 208000036065 Airway Remodeling Diseases 0.000 description 1
- 102100031325 Anthrax toxin receptor 2 Human genes 0.000 description 1
- 102000004452 Arginase Human genes 0.000 description 1
- 108700024123 Arginases Proteins 0.000 description 1
- 208000037874 Asthma exacerbation Diseases 0.000 description 1
- 206010066091 Bronchial Hyperreactivity Diseases 0.000 description 1
- 102000019621 CXCR chemokine receptor binding proteins Human genes 0.000 description 1
- 108091016272 CXCR chemokine receptor binding proteins Proteins 0.000 description 1
- 102000019034 Chemokines Human genes 0.000 description 1
- 108010012236 Chemokines Proteins 0.000 description 1
- 208000017667 Chronic Disease Diseases 0.000 description 1
- 102100035324 Complement factor H-related protein 4 Human genes 0.000 description 1
- 102000004127 Cytokines Human genes 0.000 description 1
- 230000022963 DNA damage response, signal transduction by p53 class mediator Effects 0.000 description 1
- 101100407335 Dictyostelium discoideum pde7 gene Proteins 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 102000003688 G-Protein-Coupled Receptors Human genes 0.000 description 1
- 108090000045 G-Protein-Coupled Receptors Proteins 0.000 description 1
- 241000282414 Homo sapiens Species 0.000 description 1
- 101000796085 Homo sapiens Anthrax toxin receptor 2 Proteins 0.000 description 1
- 101000878133 Homo sapiens Complement factor H-related protein 4 Proteins 0.000 description 1
- 101000961149 Homo sapiens Immunoglobulin heavy constant gamma 4 Proteins 0.000 description 1
- 101000599951 Homo sapiens Insulin-like growth factor I Proteins 0.000 description 1
- 101001044927 Homo sapiens Insulin-like growth factor-binding protein 3 Proteins 0.000 description 1
- 101001059662 Homo sapiens Mucosal addressin cell adhesion molecule 1 Proteins 0.000 description 1
- 101001114673 Homo sapiens Multimerin-1 Proteins 0.000 description 1
- 101000693011 Homo sapiens Pancreatic alpha-amylase Proteins 0.000 description 1
- 101001130226 Homo sapiens Phosphatidylcholine-sterol acyltransferase Proteins 0.000 description 1
- 101001131840 Homo sapiens Pregnancy zone protein Proteins 0.000 description 1
- 101000612397 Homo sapiens Prenylcysteine oxidase 1 Proteins 0.000 description 1
- 101001091538 Homo sapiens Pyruvate kinase PKM Proteins 0.000 description 1
- 101000626163 Homo sapiens Tenascin-X Proteins 0.000 description 1
- 206010020751 Hypersensitivity Diseases 0.000 description 1
- 102100039347 Immunoglobulin heavy constant gamma 4 Human genes 0.000 description 1
- 206010061218 Inflammation Diseases 0.000 description 1
- 102100037852 Insulin-like growth factor I Human genes 0.000 description 1
- 102100022708 Insulin-like growth factor-binding protein 3 Human genes 0.000 description 1
- FFEARJCKVFRZRR-BYPYZUCNSA-N L-methionine Chemical compound CSCC[C@H](N)C(O)=O FFEARJCKVFRZRR-BYPYZUCNSA-N 0.000 description 1
- 101001066400 Mesocricetus auratus Homeodomain-interacting protein kinase 2 Proteins 0.000 description 1
- 102100028793 Mucosal addressin cell adhesion molecule 1 Human genes 0.000 description 1
- 102100023354 Multimerin-1 Human genes 0.000 description 1
- 102100026367 Pancreatic alpha-amylase Human genes 0.000 description 1
- 102000007079 Peptide Fragments Human genes 0.000 description 1
- 108010033276 Peptide Fragments Proteins 0.000 description 1
- 102100031538 Phosphatidylcholine-sterol acyltransferase Human genes 0.000 description 1
- 102000011420 Phospholipase D Human genes 0.000 description 1
- 108090000553 Phospholipase D Proteins 0.000 description 1
- 102100034569 Pregnancy zone protein Human genes 0.000 description 1
- 102100041004 Prenylcysteine oxidase 1 Human genes 0.000 description 1
- 206010036790 Productive cough Diseases 0.000 description 1
- 102000004005 Prostaglandin-endoperoxide synthases Human genes 0.000 description 1
- 108090000459 Prostaglandin-endoperoxide synthases Proteins 0.000 description 1
- 102100034911 Pyruvate kinase PKM Human genes 0.000 description 1
- 230000010799 Receptor Interactions Effects 0.000 description 1
- 208000002200 Respiratory Hypersensitivity Diseases 0.000 description 1
- 102100024549 Tenascin-X Human genes 0.000 description 1
- 108010067390 Viral Proteins Proteins 0.000 description 1
- 241001428384 Zamora Species 0.000 description 1
- 238000002835 absorbance Methods 0.000 description 1
- 230000010085 airway hyperresponsiveness Effects 0.000 description 1
- 201000009961 allergic asthma Diseases 0.000 description 1
- 208000026935 allergic disease Diseases 0.000 description 1
- 230000007815 allergy Effects 0.000 description 1
- 102000015395 alpha 1-Antitrypsin Human genes 0.000 description 1
- 108010050122 alpha 1-Antitrypsin Proteins 0.000 description 1
- 229940024142 alpha 1-antitrypsin Drugs 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- 125000004202 aminomethyl group Chemical group [H]N([H])C([H])([H])* 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 102000023732 binding proteins Human genes 0.000 description 1
- 108091008324 binding proteins Proteins 0.000 description 1
- 230000036427 bronchial hyperreactivity Effects 0.000 description 1
- 229940124630 bronchodilator Drugs 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 210000003850 cellular structure Anatomy 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 102000012594 chemokine activity proteins Human genes 0.000 description 1
- 108040003992 chemokine activity proteins Proteins 0.000 description 1
- 230000010252 chemokine signaling pathway Effects 0.000 description 1
- 230000001684 chronic effect Effects 0.000 description 1
- 208000020832 chronic kidney disease Diseases 0.000 description 1
- 238000003776 cleavage reaction Methods 0.000 description 1
- QZUDBNBUXVUHMW-UHFFFAOYSA-N clozapine Chemical compound C1CN(C)CCN1C1=NC2=CC(Cl)=CC=C2NC2=CC=CC=C12 QZUDBNBUXVUHMW-UHFFFAOYSA-N 0.000 description 1
- 238000013211 curve analysis Methods 0.000 description 1
- XUJNEKJLAYXESH-UHFFFAOYSA-N cysteine Natural products SCC(N)C(O)=O XUJNEKJLAYXESH-UHFFFAOYSA-N 0.000 description 1
- 235000018417 cysteine Nutrition 0.000 description 1
- 102000003675 cytokine receptors Human genes 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 229940074200 diamode Drugs 0.000 description 1
- 102000038379 digestive enzymes Human genes 0.000 description 1
- 108091007734 digestive enzymes Proteins 0.000 description 1
- 239000003085 diluting agent Substances 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000010494 dissociation reaction Methods 0.000 description 1
- 230000005593 dissociations Effects 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 238000011049 filling Methods 0.000 description 1
- 239000011888 foil Substances 0.000 description 1
- 238000013467 fragmentation Methods 0.000 description 1
- 238000006062 fragmentation reaction Methods 0.000 description 1
- 230000012010 growth Effects 0.000 description 1
- 210000000020 growth cone Anatomy 0.000 description 1
- 210000000987 immune system Anatomy 0.000 description 1
- 208000026278 immune system disease Diseases 0.000 description 1
- 230000004054 inflammatory process Effects 0.000 description 1
- 208000030603 inherited susceptibility to asthma Diseases 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 208000024710 intermittent asthma Diseases 0.000 description 1
- IXAQOQZEOGMIQS-SSQFXEBMSA-N lipoxin A4 Chemical compound CCCCC[C@H](O)\C=C\C=C/C=C/C=C/[C@@H](O)[C@@H](O)CCCC(O)=O IXAQOQZEOGMIQS-SSQFXEBMSA-N 0.000 description 1
- 238000004895 liquid chromatography mass spectrometry Methods 0.000 description 1
- 238000007477 logistic regression Methods 0.000 description 1
- PGYPOBZJRVSMDS-UHFFFAOYSA-N loperamide hydrochloride Chemical compound Cl.C=1C=CC=CC=1C(C=1C=CC=CC=1)(C(=O)N(C)C)CCN(CC1)CCC1(O)C1=CC=C(Cl)C=C1 PGYPOBZJRVSMDS-UHFFFAOYSA-N 0.000 description 1
- 210000004698 lymphocyte Anatomy 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 238000004949 mass spectrometry Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000001404 mediated effect Effects 0.000 description 1
- 230000004060 metabolic process Effects 0.000 description 1
- 229930182817 methionine Natural products 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 230000030503 positive regulation of chemotaxis Effects 0.000 description 1
- 230000013188 positive regulation of leukocyte chemotaxis Effects 0.000 description 1
- 230000008248 positive regulation of leukocyte migration Effects 0.000 description 1
- 239000002243 precursor Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 102000004196 processed proteins & peptides Human genes 0.000 description 1
- 230000006916 protein interaction Effects 0.000 description 1
- 230000009325 pulmonary function Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 230000018994 regulation of granulocyte chemotaxis Effects 0.000 description 1
- 230000008024 regulation of leukocyte chemotaxis Effects 0.000 description 1
- 230000024665 regulation of neutrophil chemotaxis Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 210000001908 sarcoplasmic reticulum Anatomy 0.000 description 1
- 230000007017 scission Effects 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 125000005630 sialyl group Chemical group 0.000 description 1
- 238000002791 soaking Methods 0.000 description 1
- 238000013125 spirometry Methods 0.000 description 1
- 208000024794 sputum Diseases 0.000 description 1
- 210000003802 sputum Anatomy 0.000 description 1
- 239000012089 stop solution Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000153 supplemental effect Effects 0.000 description 1
- 210000001519 tissue Anatomy 0.000 description 1
- 230000003827 upregulation Effects 0.000 description 1
- 239000011782 vitamin Substances 0.000 description 1
- 229940088594 vitamin Drugs 0.000 description 1
- 229930003231 vitamin Natural products 0.000 description 1
- 235000013343 vitamin Nutrition 0.000 description 1
- 150000003722 vitamin derivatives Chemical class 0.000 description 1
- 239000003643 water by type Substances 0.000 description 1
- 239000012224 working solution Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
- G01N33/6848—Methods of protein analysis involving mass spectrometry
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6884—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids from lung
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2570/00—Omics, e.g. proteomics, glycomics or lipidomics; Methods of analysis focusing on the entire complement of classes of biological molecules or subsets thereof, i.e. focusing on proteomes, glycomes or lipidomes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/12—Pulmonary diseases
- G01N2800/122—Chronic or obstructive airway disorders, e.g. asthma COPD
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Physics & Mathematics (AREA)
- Biomedical Technology (AREA)
- Chemical & Material Sciences (AREA)
- Hematology (AREA)
- Immunology (AREA)
- Urology & Nephrology (AREA)
- Cell Biology (AREA)
- Biochemistry (AREA)
- Biotechnology (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Analytical Chemistry (AREA)
- Microbiology (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Biophysics (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention provides a novel biomarker screening method for preschool childhood asthma diagnosis and application thereof, belongs to the field of biological medicine, screens LTBP1, APOA1 and IGFALS proteins as biomarkers for preschool childhood asthma diagnosis, and takes an expression level index of a composition as a basis for judging preschool childhood asthma, so that the accuracy of preschool childhood asthma diagnosis can be improved, the diagnosis process is simplified, and important functions are played in childhood asthma diagnosis and treatment.
Description
Technical Field
The invention belongs to the technical field of biology, and particularly relates to a novel biomarker screening method for preschool childhood asthma diagnosis and application thereof.
Background
Asthma is the most common chronic disease in children and is characterized by airway hyperresponsiveness, reversible airway obstruction and chronic airway inflammation, with the incidence of asthma and hospitalization being higher in preschool children than in the elderly. The pulmonary function track is established in childhood and airway remodeling associated with asthma occurs 3 years ago, therefore preschool children are a critical period for asthma intervention, and accurate identification and diagnosis of preschool children's asthma may help to understand asthma symptoms and improve treatment compliance. Because asthma symptoms are recurrent and fluctuating, their diagnosis in children remains challenging and few effective independent diagnostic tests are available. Recently, the national institute of health and care and Asthma-12 global initiative have proposed diagnostic algorithms that combine available tests such as spirometry, bronchodilator reversibility tests, bronchial excitation tests to measure bronchial hyperreactivity, exhaled nitric oxide fraction (Feno) and allergy tests. However, the diagnostic accuracy of these algorithms for preschool childhood asthma is not yet established.
Thus, there is an urgent need for better methods of diagnosing asthma. To achieve this goal, new studies are needed to identify biomarkers that can distinguish between asthma and healthy preschool children, which can then be incorporated into diagnostic algorithms. In asthma, certain proteins associated with airway obstruction and inflammation are produced in tissue cells and secreted into the circulatory system. Proteomics is therefore a promising approach to identify potential diagnostic biomarkers for preschool childhood asthma. While proteomics has been used in previous studies to analyze blood samples from asthmatic patients, most use Data Dependent Acquisition (DDA) -Mass Spectrometry (MS) and focus on elderly children or adults. The Data Independent Acquisition (DIA) -MS is a time parallel acquisition method, has better consistency and reproducibility than DDA, and is particularly suitable for proteomics research of large sample groups.
Previous studies have identified several asthma protein biomarkers. For example, nieto-Fontarigo et al found serum IGFALS to be a biomarker of allergic asthma in adults. Zamora et al determined that sialyl Interleukins (IL) -8 and IL-10 are biomarkers of childhood asthma. Another study showed that sputum LXA4 could differentiate between children with severe asthma and children with intermittent asthma. Furthermore, by proteomic analysis, C7, C3, C4, α -1-antitrypsin, PDE7, arginase, UK 16-binding protein, phospholipase D and cyclooxygenase were found to accumulate to varying degrees in serum of bronchial asthma patients and healthy individuals. However, few studies have focused on biomarkers of preschool childhood asthma, although diagnosis of asthma is more difficult in this population.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a novel biomarker screening method for diagnosing asthma of preschool children, and the Orbitrap Exploris platform is used for carrying out serum proteome analysis based on DIA-MS on the preschool children. Key signaling pathways and biomarker proteins associated with preschool childhood asthma were determined in combination with bioinformatics and statistical analysis.
Based on the technical thought, the technical scheme adopted by the invention is as follows:
the invention provides a novel biomarker screening method for preschool childhood asthma diagnosis, which comprises the following steps:
step 1: analyzing serum proteome characteristics of a subject by adopting independent data acquisition mass spectrum, and determining differential expression proteins between an acute asthma group and a healthy control group after data filtering;
Step 3: a total of 50 differential expression proteins exist between the acute asthma group and the healthy control group, the potential actions of the differential expression proteins on asthmatic individuals and healthy children are analyzed by adopting a supervised orthogonal partial least squares discriminant analysis model, and MMP14, ABHD12B, LTBP1, APOA1, ANG and IGFALS proteins are screened out to be used as biomarkers for distinguishing asthmatic children and healthy children;
Step 4: six biomarkers were mapped using TBtools and subject operating profile analysis was performed on six differentially expressed proteins to assess sensitivity and specificity of the six biomarkers in distinguishing asthmatic individuals from healthy children.
Preferably, in step 1 the subject comprises an acute asthma group, an asthma recovery phase group and a healthy control group, and the serum proteome of the subject is extracted as follows:
(1) The subjects were not treated with the drug, collected blood samples, placed in the dark at room temperature for 1 hour, centrifuged at 3000rpm for 15 minutes at 4 ℃ to separate serum, and finally the serum was aliquoted and stored in a refrigerator at 80 ℃;
(2) Protein extraction and trypsin digestion
First, a serum sample was centrifuged at 12000g for 10 minutes at 4℃to remove cell debris, then the supernatant was retained, the protein concentration of serum was measured using the BCA kit, then a serum protein solution was reduced with 5mM dithiothreitol at 56℃for 30 minutes, and alkylated with 11mM iodoacetamide at dark room temperature for 15 minutes, the first overnight digestion added trypsin at a 1:5 ratio, the second 4 hour digestion added at a 1:100 ratio, the digested peptide was desalted using C18 Ziptips, eluted with 0.1% TFA in 50-70% acetonitrile, then lyophilized and redissolved in 1% formic acid 5% acetonitrile;
(3) High pH-reverse phase fractionation
The treated peptide solutions were combined in equal amounts and further separated by high pH-reverse phase separation using a Dionex UHPLC and ethylene bridge hybrid C18 column at 40 ℃ with a flow rate of 0.2 ml/min and ACN gradient of 60 min in 5mM ammonium formate; fractions were collected at 1 minute intervals and pooled into 12 fractions, and then each fraction was lyophilized and redissolved in 1% formic acid 5% acetonitrile.
It is another object of the present invention to provide a biomarker composition for diagnosing preschool childhood asthma, the composition comprising LTBP1, APOA1 and IGFALS proteins.
It is a further object of the present invention to provide the use of a novel marker composition for diagnosing pre-school-age childhood asthma in the preparation of a reagent for serodiagnosing asthma in a subject.
The invention has the beneficial effects that:
The invention adopts data independent acquisition mass spectrum (DIA-MS) to analyze the serum proteome characteristics of children suffering from acute asthma and children suffering from convalescence, identifies 50 differentially expressed proteins in 46 serum, distinguishes children suffering from asthma and healthy children, confirms the central function of an inflammation-immune mechanism in asthma attack by carrying out function enrichment analysis on the differentially expressed proteins, establishes a supervision orthogonal partial least squares discriminant analysis (OPLS-DA) model, and after 200 permutation tests, R2 and Q2 of the OPLS-DA asthma model and healthy control are respectively 0.53 and 0.45, and R2 and Q2 of the OPLS-DA asthma model and healthy control are respectively 0.766 and 0.491. The model is well fitted and has reliable prediction capability. Thereby, MP14, ABHD12B, LTBP1, APOA1, ANG and IGFALS proteins are screened out as biomarkers by using the model.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a summary of the proteomic analysis of pediatric asthma serum DIA-MS; (A) An unsupervised model of pentachloroanisole in healthy subjects of asthma, convalescence group.
(B) A disturbed graph of differential protein between asthma, convalescent group and healthy control group. (C) Volcanic plot of 37 altered proteins between asthma and healthy subjects. (unsupervised clustered heatmap of 20 common different altered proteins for convalescent group asthma group versus healthy group.
FIG. 2 is a GO and KEGG enrichment analysis of differentially expressed proteins. (a) biological processes; (B) molecular function; (C) a cellular component; (D) KEGG pathway enrichment.
Figure 3 is a statistical analysis of stable candidate biomarkers. (A) Multivariate principal component analysis score plots of all differential proteins between asthma and healthy subjects; (B) A supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model of differential proteins between preschool asthma and healthy subjects, asthma and health representing asthma and healthy subjects under 5 years of age, respectively; (C) the relative expression level of the candidate biomarker.
FIG. 4 is a prognostic model evaluation of preschool childhood asthma based on protein biomarkers; (A) Abundance heatmaps of 6 candidate biomarkers in preschool asthma and health cohorts; (B) ROC analysis of IGFALS in asthma and health cohorts at all ages; (C) ROC analysis of IGFALS in pre-school-age asthma and health cohorts.
FIG. 5 shows the results of the serum proteome OPLS-DA and substitution test; (A) Proteomic OPLS-DA results for all asthmatic patients with healthy controls; (B) Replacement test results for proteome OPLS-DA for all asthmatic patients with healthy controls; (C) Proteomic OPLS-DA results for preschool childhood asthma patients with healthy controls; (D) Replacement test results for proteomic OPLS-DA of preschool childhood asthma patients with healthy controls.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The embodiment provides a method for establishing a preschool childhood asthma diagnosis model, which comprises the following steps:
1. Study of clinical characteristics of patients
A total of 46 children were divided into three groups, asthma exacerbation (n=17), convalescent asthma (n=19), and healthy controls (n=10). To determine asthma biomarkers for preschool children, 7, 10, and 7 preschool children (age <5 years) were included in the asthma group, recovery group, and healthy control three groups, respectively. The clinical characteristics of each group are shown in tables 1 and S1. As shown, children with acute asthma had a one second forced expiratory volume (FEV 1%) lower than those of the convalescence and healthy control groups. However, children with acute asthma had higher Fe v 1/forced vital capacity (FEV/FVC) than children in the convalescent and healthy control group (table 1). Compared to the convalescent group and the healthy control group, the neutrophil and eosinophil counts were higher and the lymphocyte counts were lower in the asthmatic group (table 1). Eosinophil counts, feNO and IgE were significantly higher in children of the asthma and convalescent groups than in the healthy group (table 1).
TABLE 1
a Kruskal-Wallis test p-value
Table S1
2. Proteomic findings associated with asthma
To analyze the serum proteome of asthmatic children, a total of 747 proteins were identified in 46 serum samples using DIA-MS proteome sequencing. Principal Component Analysis (PCA) showed that the serum proteome can differentiate between the three study groups (fig. 1A). To determine asthma biomarkers in children, 50 significantly altered proteins were determined between asthma and healthy controls after data filtration (fold change [ FC ] >1.5, mann-Whitney U test p value < 0.05) (fig. 1B and C; table 2), such as IGFALS, TNXB, LCAT, MMRN1, IGFBP3, APOA1, MADCAM1, PKM, AMY2A, PZP, IGHV-38, ABHD12B, ANTXR2, IGF1 and AGT. At the same time, 63 proteins were significantly differentially expressed between the convalescent group and the healthy control group (fig. 1C and table S3). Interestingly, there were 20 common differentially expressed proteins between the convalescent group and the asthmatic group compared to the healthy group (fig. 1C). Cluster analysis showed that these 20 common differential proteins in asthma, convalescent group and healthy control group could be distinguished in unsupervised cluster analysis (fig. 1D).
TABLE 2
Table S3
3. GO and KEGG enrichment analysis of altered proteins
Based on the results of gene theory (GO) annotation, functional enrichment analysis was performed on the differential protein between asthma and healthy controls. Fisher' S exact test p-value was used to determine significance (Table S4). GO terminology with p value <0.05 is considered significantly rich (fig. 2). As shown, the differential proteins are significantly enriched in immune system-related biological processes such as chemokine-mediated signaling pathways, positive regulation of leukocyte chemotaxis, regulation of granulocyte chemotaxis, positive regulation of leukocyte migration, positive regulation of neutrophil migration, regulation of neutrophil chemotaxis, regulation of leukocyte chemotaxis, and positive regulation of chemotaxis (fig. 2A). In terms of molecular function, differential proteins are significantly enriched in immune related functions such as CXCR chemokine receptor binding, chemokine activity and G protein-coupled receptor binding (fig. 2C). In sarcoplasmic reticulum, growth cone, polarized growth sites and sarcoplasmic cell component entries, differential proteins were significantly enriched (fig. 2B). Next, a KEGG pathway enrichment analysis was performed (Table S5). As expected, the differential proteins are significantly enriched in immune-related pathways such as chemokine signaling pathways, viral protein interactions with cytokines and cytokine receptors, cytokine-cytokine receptor interactions, p53 signaling pathways, and TGF- β signaling pathways. In addition, fat digestion and absorption, cholesterol metabolism, vitamin digestion and absorption pathways are also enriched (fig. 2D).
Table S4
Table S5
4. Biomarkers for preschool children with asthma
A total of 50 differential proteins were found between asthma and healthy controls. Multivariate PCA showed that differential proteins can differentiate between asthma and healthy subjects (fig. 3A and supplemental fig. 5C). To examine the potential role of these proteins in distinguishing asthma from healthy controls, a supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model was constructed (fig. 3B-5A). After 200 permutation tests, R2 and Q2 of the OPLS-DA asthma model and healthy controls were 0.53 and 0.45 respectively fig. 5B), and R2 and Q2 of the OPLS-DA asthma model and healthy controls were 0.766 and 0.491 respectively (fig. 5D), indicating that these models fit well with reliable predictive power. MMP14, ABHD12B, PCYOX1, LTBP1, CFHR4, APOA1, IGHG4, ANG, and IGFALS proteins significantly help differentiate asthmatic children from healthy children (predictive variable importance [ VIP pred ] >1; table 3) and are considered biomarker candidates. The relative expression levels of these candidate biomarkers are shown in the box plot in fig. 3C. Interestingly, these candidates exhibited significantly higher relative abundance in the asthma and convalescence cohorts compared to the healthy cohorts (fig. 3C). In particular, ANG, APOA1, IGFALS, and LTBP1 levels showed a gradual decrease trend from asthma to convalescence to healthy cohorts (fig. 3C).
TABLE 3 Table 3
a The relative abundance is the LC-MS/MS intensity value
b The P-value is that of the Kruskal Wallis test
5. Biomarker-based development and evaluation of preschool childhood asthma diagnostic models
To better present the differences in abundance of candidate biomarkers in pre-school-age asthmatic patients, a heat map of six candidate biomarkers was plotted using TBtools (fig. 5A). As shown, all protein abundance was significantly higher in asthmatic preschool children than in healthy preschool children, especially ANG, APOA1 and IGFALS (fig. 5A). Next, subject work character (ROC) curve analysis was performed on 6 candidate proteins to assess their sensitivity and specificity to distinguish asthmatic individuals from healthy children (table 4). Part of the candidate proteins had an area under the curve (AUC) of greater than 0.8 for diagnosis of asthma in whole-age and preschool children. These proteins, including IGFALS, APOA1 and LTBP1, showed good diagnostic value (table 4). To construct a diagnostic model of asthma, we performed a double logistic regression analysis and ROC analysis on 6 protein biomarkers. Thus, IGFALS was suggested as a biomarker for childhood asthma (table 4). For diagnosis of asthma in children (preschool and school-age children), the AUC of the IGFALS model was 0.882, the asymptotic meaning was 0.004 (table 4), and the AUC of the IGFALS model was 0.959 (asymptotic significance: 0.004) for preschool asthma prediction (fig. 5C and table 4). To verify the reliability of the biomarkers, we measured the content of IGFALS, LTBP1 and APOA1 in the samples of the verification set using ELISA. And ROC analysis was performed. As a result, the AUC of the IGFALS model in ELISA data was 0.897, indicating that the IGFALS-based diagnostic model is useful for our cohort and may have significant diagnostic potential for the diagnosis of preschool childhood asthma.
TABLE 4 Table 4
6. Serum protein extraction and treatment
6.1 Subject and serum sample collection during the period 2020 to 2021, a group of 46 children was recruited from the second affiliated hospital of the university of chinese medicine, shanxi. These children were divided into three study groups, asthma attacks (n=17), convalescent asthma (n=19), and healthy controls [ ]
N=10). Children with immune diseases, chronic kidney disease or other diseases affecting serum proteins are excluded. All clinical diagnoses followed the global asthma initiative guidelines in 2019 [10]. On the following morning after the child was admitted without medication, blood samples (4 mL) were collected, left in the dark at room temperature (22-25 ℃) for 1 hour, and then centrifuged at 3,000rpm for 15 minutes at 4℃to isolate serum. Finally, serum was aliquoted and stored in a refrigerator at 80 ℃. The second affiliated hospital ethics committee of the university of shanxi chinese medicine approves the study protocol (ChiCTR 2000033383). All participants provided written informed consent.
6.2 Protein extraction and trypsin digestion first, serum samples were centrifuged at 12,000 g for 10 min at 4 ℃ to remove cell debris. The supernatant was then retained and the protein concentration of the serum was determined using BCA kit (ThermoFisher Scientific, waltham, MA, USA) according to the manufacturer's instructions. The serum protein solution was then reduced with 5mM dithiothreitol at 56℃for 30 minutes and alkylated with 11mM iodoacetamide at dark room temperature for 15 minutes. Trypsin was added in a 1:50 (trypsin/protein mass ratio) ratio for the first overnight digestion and in a 1:100 ratio for the second 4 hours digestion. The digested peptides were desalted using C18Ziptips (Millipore), eluted with 0.1% TFA in 50-70% acetonitrile, then lyophilized and redissolved in 1% formic acid 5% acetonitrile. The iRT peptide (Biognosys, schlieren, switzerland) was added to the samples prior to LC-MS/MS analysis according to the manufacturer's instructions.
6.3 High pH-reverse phase fractionation the treated peptide solutions of subjects were combined in equal amounts and further separated by high pH-reverse phase separation using Dionex UHPLC (ThermoFisher Scientific) and ethylene bridge hybrid C18 column (Waters) at 40℃with a flow rate of 0.2 ml/min and an ACN gradient of 60 min (5-30%) in 5mM ammonium formate (pH 10). Fractions were collected at 1 minute intervals and pooled into 12 fractions. Each component was then lyophilized and redissolved in 1% formic acid 5% acetonitrile.
6.4 Data Dependent Acquisition (DDA) LC-MS/MS analysis and spectral library Generation to generate the spectral library, DDA-MS analysis was used and performed in tandem with Orbitrap Exploris 480 mass spectrometer (ThermoFisher Scientific) on an Easy-nLC 1200UPLC system. First, each peptide fragment was loaded onto Easy-nLC 1200UPLC system and separated from 95% solvent A (0.1% formic acid/2% acetonitrile/98% water) to 28% solvent B (0.1% formic acid/80% acetonitrile) at 50deg.C in a linear gradient of 120 minutes at a flow rate of 250 nL/min. The mass spectrometer operates in a data dependent mode. A full MS scan of 350 to 1500m/z is acquired at high resolution r=120,000 (defined as m/z=400); the resolution of the MS/MS scan was 30,000, the isolation window was 4Da, and the collision energy was 30+ -5% high energy collision dissociation (HCD) fragmentation. Dynamic exclusion was set to 30 seconds using the Pulsar search engine in Spectronaut X (Biognosys, schlieren, switzerland) to process raw data and search the UniProt homo sapiens proteome database within default parameters to generate a spectral library. The digestive enzyme is a specific trypsin with two missing specific cleavage, the fixed modification is an aminomethyl group of cysteine, and the variable modification is the oxidation of methionine. iRT is calculated from the iRT median of all DDA runs. The fragment ions used for target data analysis were selected from 300 to 1800m/z, the minimum relative intensity was set to >5%, and the number of fragment ions >3. The False Discovery Rate (FDR) of protein and peptide profile matches was set to 1%. Protein inference was performed using the ID Picker algorithm in Spectronaut software.
6.5 Data Independent Acquisition (DIA) LC-MS/MS analysis DIA-MS was performed using the same LC-MS system and LC linear gradient method as DDA-MS. For MS/MS acquisition, the DIA mode was set for 50 variable isolation windows according to FWTH (full width at half maximum) and a specific window list was constructed according to the corresponding DDA data of the pooled samples. In the range of m/z from 350 to 1500, the full scan is set to 1200,000 followed by a diameter scan with a resolution of 30,000; 30.5% of administrative officials; AGC target 1e6, maximum injection time 54ms. DIA raw files were processed using Spectronaut X (Biognosys, schlieren, switzerland) and default parameters. The retention time prediction type is dynamic iRT, the correction factor is window 1, and interference correction at the MS2 level is enabled. The system variance is normalized by a local normalization strategy. FDR of peptide precursors and proteins was evaluated at 1% threshold using mProphet method. The total peak area of the peptide MS2 fragment ions was calculated as protein intensity. All results were filtered using Q value and FDR threshold of 1%.
7. Tool for cutting tools
Bioinformatics and statistical analysis all identified serum proteins were annotated using GO (http:// david. Abcc. Ncifcrf. Gov/home. Jsp) and KEGG databases (http:// www.genome.jp/KEGG /). The obtained proteome data were subjected to unsupervised PCA and supervised orthogonal partial least squares discriminant analysis (OPLS-DA) using SIMCA14 software (Umetrics AB in sweden). The standard of FC >1.5 and Mann-Whitney U test p-value <0.05 was used to identify significantly different proteins. Thermal mapping analysis was performed using TB tools (https:// gitsub. Com/CJ-Chen/TB tools). r (version 4.0.3) and SPSS (version 28) are used for functional enrichment and statistical analysis, such as AUC. Fisher's exact test p-value <0.05 was used to test significantly enriched GO functions and KEGG pathways. Availability of data and materials raw data for LC-MS/MS proteomes has been saved to iProX database (https:// www.iprox.cn /), item ID is IPX0004341000.
8. ELISA (enzyme-linked immunosorbent assay) verification
All reagents and components were first returned to room temperature, standards, quality controls and samples, and duplicate wells were recommended. Working solutions of various components of the kit are prepared according to the method described in the specification of the kit. The required strips are taken out of the aluminum foil bags, and the rest strips are put back into the refrigerator by sealing with the self-sealing bags. Setting a standard substance hole, a 0-value hole, a blank hole and a sample hole, wherein 50 mu L of standard substances with different concentrations are respectively added into the standard substance hole, 50 mu L of sample diluent is added into the 0-value hole, 50 mu L of sample to be detected is added into the sample hole without adding the blank hole. In addition to the blank wells, standard wells, 0-value wells, and sample wells, 100 μl of horseradish peroxidase (HRP) -labeled detection antibody was added. The reaction plate is covered by a sealing plate film, and incubated for 60min in a water bath kettle or an incubator at 37 ℃ in a dark place. Uncovering the sealing plate film, discarding the liquid, beating the water absorbing paper, filling the washing liquid in each hole, standing for 20S, throwing the washing liquid, beating the water absorbing paper, and repeating the steps for 5 times. If an automatic plate washer is used, the plate washer is required to be washed according to the operation procedure of the plate washer, and a procedure of soaking for 30s is added, so that the detection precision can be improved. And after the plate washing is finished, before the substrate is added, the reaction plate is fully patted on clean paper without scraps. Substrates A and B were thoroughly mixed in a 1:1 volume, and 100. Mu.L of the substrate mixture was added to all wells. The reaction plate is covered by a sealing plate film, and incubated for 15min in a water bath kettle or an incubator at 37 ℃ in a dark place. And adding 50 mu L of stop solution into all the wells, reading the absorbance (OD value) of each well on an enzyme-labeled instrument, and drawing a standard curve to calculate the content of the molecules to be detected.
Claims (4)
1. A method for screening novel biomarkers for diagnosis of preschool childhood asthma, comprising the steps of:
step 1: analyzing serum proteome characteristics of a subject by adopting independent data acquisition mass spectrum, and determining differential expression proteins between an acute asthma group and a healthy control group after data filtering;
Step 3: a total of 50 differential expression proteins exist between the acute asthma group and the healthy control group, the potential actions of the differential expression proteins on asthmatic individuals and healthy children are analyzed by adopting a supervised orthorhombic least squares discriminant analysis model, and MMP14, ABHD12B, LTBP, APOA1, ANG and IGFALS proteins are screened out as biomarker candidates for distinguishing asthmatic children from healthy children;
Step 4: the six biomarkers were mapped using TBtools and subject operating profile analysis was performed on the six differentially expressed proteins to assess the sensitivity and specificity of the six biomarker candidates in distinguishing asthmatic individuals from healthy children, screening for preschool childhood asthma diagnostic biomarkers.
2. The method of claim 1, wherein in step 1, the subject comprises an acute asthma group, an asthma recovery phase group and a healthy control group, and the serum proteome extraction process of the subject is as follows:
(1) The subjects were not treated with the drug, collected blood samples, placed in the dark at room temperature for 1 hour, centrifuged at 3000rpm for 15 minutes at 4 ℃ to separate serum, and finally the serum was aliquoted and stored in a refrigerator at 80 ℃;
(2) Protein extraction and trypsin digestion
First, a serum sample was centrifuged at 12000g for 10 minutes at 4℃to remove cell debris, then the supernatant was retained, the protein concentration of serum was measured using the BCA kit, then a serum protein solution was reduced with 5mM dithiothreitol at 56℃for 30 minutes, and alkylated with 11mM iodoacetamide at dark room temperature for 15 minutes, the first overnight digestion added trypsin at a 1:5 ratio, the second 4 hour digestion added at a 1:100 ratio, the digested peptide was desalted using C18 Ziptips, eluted with 0.1% TFA in 50-70% acetonitrile, then lyophilized and redissolved in 1% formic acid 5% acetonitrile;
(3) High pH-reverse phase fractionation
The treated peptide solutions were combined in equal amounts and further separated by high pH-reverse phase separation using a Dionex UHPLC and ethylene bridge hybrid C18 column at 40 ℃ with a flow rate of 0.2 ml/min and ACN gradient of 60 min in 5mM ammonium formate; fractions were collected at 1 minute intervals and pooled into 12 fractions, and then each fraction was lyophilized and redissolved in 1% formic acid 5% acetonitrile.
3. A biomarker composition for diagnosing preschool childhood asthma, the composition comprising LTBP1, APOA1, and IGFALS proteins.
4. Use of a biomarker composition for diagnosing preschool childhood asthma in the manufacture of a reagent for serodiagnosing asthma patients in a subject.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310709824.5A CN117949663A (en) | 2023-06-15 | 2023-06-15 | Screening method and application of novel biomarker for diagnosis of preschool childhood asthma |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310709824.5A CN117949663A (en) | 2023-06-15 | 2023-06-15 | Screening method and application of novel biomarker for diagnosis of preschool childhood asthma |
Publications (1)
Publication Number | Publication Date |
---|---|
CN117949663A true CN117949663A (en) | 2024-04-30 |
Family
ID=90802391
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202310709824.5A Pending CN117949663A (en) | 2023-06-15 | 2023-06-15 | Screening method and application of novel biomarker for diagnosis of preschool childhood asthma |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117949663A (en) |
-
2023
- 2023-06-15 CN CN202310709824.5A patent/CN117949663A/en active Pending
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP2023178345A (en) | Method and system for determining autism spectrum disorder risk | |
Wang et al. | Emerging salivary biomarkers by mass spectrometry | |
CN111289736A (en) | Slow obstructive pulmonary early diagnosis marker based on metabonomics and application thereof | |
US8541183B2 (en) | Methods of identification, assessment, prevention and therapy of lung diseases and kits thereof | |
US9945872B2 (en) | Biomarkers of lung function | |
JP2024024128A (en) | Methods and kits for identification, assessment, prevention and therapy of lung diseases, including sexuality-based identification, assessment, prevention and therapy of diseases | |
JP7179356B2 (en) | Diagnosis of Behçet's disease using metabolite analysis | |
US20160123997A1 (en) | Materials and methods relating to alzheimer's disease | |
Byerley et al. | Development of a serum profile for healthy aging | |
CN111279193A (en) | Method for diagnosing Behcet's disease using urine metabolome analysis | |
AU2011217734B2 (en) | Protein biomarkers for obstructive airways diseases | |
US20060029980A1 (en) | Method for diagnosing obstructive sleep apnea | |
Liang et al. | Novel liquid chromatography-mass spectrometry for metabolite biomarkers of acute lung injury disease | |
WO2014138583A1 (en) | Compositions and methods related to obstructive sleep apnea | |
US20160018413A1 (en) | Methods of Prognosing Preeclampsia | |
CN113358881B (en) | Biomarker for NMOSD prediction or recurrence monitoring and application thereof | |
CN117949663A (en) | Screening method and application of novel biomarker for diagnosis of preschool childhood asthma | |
Song et al. | The proteomic analysis of human neonatal umbilical cord serum by mass spectrometry | |
CN114674969A (en) | Application of urine biomarker detection reagent in preparation of neocoronary pneumonia diagnostic kit | |
CN116718783A (en) | Biomarker for diagnosis of infant asthma, screening method and application thereof | |
WO2007139777A2 (en) | Methods for the diagnosis and prognosis of alzheimer's disease using csf protein profiling | |
US20240241139A1 (en) | Diagnosis of autism spectrum disorder by multiomics platform | |
Liu et al. | Identification of urinary peptides associated with allergic rhinitis | |
CN117110617A (en) | Group of markers related to chronic obstructive pulmonary frequent acute exacerbation phenotype and application thereof | |
CN118311262A (en) | Biomarker for diagnosing beta-thalassemia and subtype and application thereof |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |