DE102023110285B3 - NMR MEASUREMENT OF GLYCOPROTEINS - Google Patents
NMR MEASUREMENT OF GLYCOPROTEINS Download PDFInfo
- Publication number
- DE102023110285B3 DE102023110285B3 DE102023110285.0A DE102023110285A DE102023110285B3 DE 102023110285 B3 DE102023110285 B3 DE 102023110285B3 DE 102023110285 A DE102023110285 A DE 102023110285A DE 102023110285 B3 DE102023110285 B3 DE 102023110285B3
- Authority
- DE
- Germany
- Prior art keywords
- signal group
- ppm
- glycb
- glyca
- neu5ac
- 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.)
- Active
Links
- 102000003886 Glycoproteins Human genes 0.000 title claims abstract description 51
- 108090000288 Glycoproteins Proteins 0.000 title claims abstract description 51
- 238000005481 NMR spectroscopy Methods 0.000 title description 26
- 150000004676 glycans Chemical class 0.000 claims abstract description 42
- 239000000090 biomarker Substances 0.000 claims abstract description 41
- 210000002966 serum Anatomy 0.000 claims abstract description 40
- 238000009792 diffusion process Methods 0.000 claims abstract description 36
- 238000000655 nuclear magnetic resonance spectrum Methods 0.000 claims abstract description 34
- 210000002381 plasma Anatomy 0.000 claims abstract description 27
- 238000001228 spectrum Methods 0.000 claims abstract description 22
- OVRNDRQMDRJTHS-RTRLPJTCSA-N N-acetyl-D-glucosamine Chemical group CC(=O)N[C@H]1C(O)O[C@H](CO)[C@@H](O)[C@@H]1O OVRNDRQMDRJTHS-RTRLPJTCSA-N 0.000 claims abstract description 21
- SQVRNKJHWKZAKO-UHFFFAOYSA-N beta-N-Acetyl-D-neuraminic acid Natural products CC(=O)NC1C(O)CC(O)(C(O)=O)OC1C(O)C(O)CO SQVRNKJHWKZAKO-UHFFFAOYSA-N 0.000 claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000004458 analytical method Methods 0.000 claims abstract description 19
- 125000002496 methyl group Chemical group [H]C([H])([H])* 0.000 claims abstract description 19
- SQVRNKJHWKZAKO-LUWBGTNYSA-N N-acetylneuraminic acid Chemical compound CC(=O)N[C@@H]1[C@@H](O)CC(O)(C(O)=O)O[C@H]1[C@H](O)[C@H](O)CO SQVRNKJHWKZAKO-LUWBGTNYSA-N 0.000 claims abstract description 17
- 230000006978 adaptation Effects 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims abstract description 5
- 238000007620 mathematical function Methods 0.000 claims abstract description 5
- 101000981881 Brevibacillus parabrevis ATP-dependent glycine adenylase Proteins 0.000 claims abstract description 3
- 101000981889 Brevibacillus parabrevis Linear gramicidin-PCP reductase Proteins 0.000 claims abstract description 3
- 102000004169 proteins and genes Human genes 0.000 claims description 28
- 108090000623 proteins and genes Proteins 0.000 claims description 28
- 239000011159 matrix material Substances 0.000 claims description 13
- 208000025721 COVID-19 Diseases 0.000 claims description 12
- 201000010099 disease Diseases 0.000 claims description 10
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 10
- 238000004611 spectroscopical analysis Methods 0.000 claims description 9
- 206010007625 cardiogenic shock Diseases 0.000 claims description 7
- 208000008589 Obesity Diseases 0.000 claims description 5
- 206010012601 diabetes mellitus Diseases 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 5
- 235000020824 obesity Nutrition 0.000 claims description 5
- 206010019280 Heart failures Diseases 0.000 claims description 4
- 201000010065 polycystic ovary syndrome Diseases 0.000 claims description 4
- 206010039073 rheumatoid arthritis Diseases 0.000 claims description 4
- 201000000596 systemic lupus erythematosus Diseases 0.000 claims description 4
- 201000003883 Cystic fibrosis Diseases 0.000 claims description 3
- 208000022559 Inflammatory bowel disease Diseases 0.000 claims description 3
- 208000011200 Kawasaki disease Diseases 0.000 claims description 3
- 201000004681 Psoriasis Diseases 0.000 claims description 3
- 230000003920 cognitive function Effects 0.000 claims description 3
- 230000007423 decrease Effects 0.000 claims description 3
- 239000003814 drug Substances 0.000 claims description 3
- 230000036252 glycation Effects 0.000 claims description 3
- 238000012067 mathematical method Methods 0.000 claims description 3
- 208000001725 mucocutaneous lymph node syndrome Diseases 0.000 claims description 3
- 208000006545 Chronic Obstructive Pulmonary Disease Diseases 0.000 claims description 2
- 208000001145 Metabolic Syndrome Diseases 0.000 claims description 2
- 206010028980 Neoplasm Diseases 0.000 claims description 2
- 208000010067 Pituitary ACTH Hypersecretion Diseases 0.000 claims description 2
- 208000020627 Pituitary-dependent Cushing syndrome Diseases 0.000 claims description 2
- 206010057190 Respiratory tract infections Diseases 0.000 claims description 2
- 201000000690 abdominal obesity-metabolic syndrome Diseases 0.000 claims description 2
- 201000011510 cancer Diseases 0.000 claims description 2
- 239000002131 composite material Substances 0.000 claims description 2
- 238000010168 coupling process Methods 0.000 claims description 2
- 238000005859 coupling reaction Methods 0.000 claims description 2
- 238000000338 in vitro Methods 0.000 claims description 2
- 208000017169 kidney disease Diseases 0.000 claims 1
- OVRNDRQMDRJTHS-UHFFFAOYSA-N N-acelyl-D-glucosamine Natural products CC(=O)NC1C(O)OC(CO)C(O)C1O OVRNDRQMDRJTHS-UHFFFAOYSA-N 0.000 description 19
- MBLBDJOUHNCFQT-LXGUWJNJSA-N N-acetylglucosamine Natural products CC(=O)N[C@@H](C=O)[C@@H](O)[C@H](O)[C@H](O)CO MBLBDJOUHNCFQT-LXGUWJNJSA-N 0.000 description 19
- 102000011767 Acute-Phase Proteins Human genes 0.000 description 14
- 108010062271 Acute-Phase Proteins Proteins 0.000 description 14
- 238000001208 nuclear magnetic resonance pulse sequence Methods 0.000 description 12
- 102000004338 Transferrin Human genes 0.000 description 10
- 108090000901 Transferrin Proteins 0.000 description 10
- 239000000523 sample Substances 0.000 description 10
- 108090001030 Lipoproteins Proteins 0.000 description 9
- 102000004895 Lipoproteins Human genes 0.000 description 9
- 206010061218 Inflammation Diseases 0.000 description 8
- 210000004369 blood Anatomy 0.000 description 8
- 239000008280 blood Substances 0.000 description 8
- 230000004054 inflammatory process Effects 0.000 description 8
- 239000003550 marker Substances 0.000 description 7
- 230000003595 spectral effect Effects 0.000 description 7
- 238000005160 1H NMR spectroscopy Methods 0.000 description 6
- 230000002757 inflammatory effect Effects 0.000 description 6
- 238000000425 proton nuclear magnetic resonance spectrum Methods 0.000 description 6
- 229930182817 methionine Natural products 0.000 description 5
- 238000000685 Carr-Purcell-Meiboom-Gill pulse sequence Methods 0.000 description 4
- 230000013595 glycosylation Effects 0.000 description 4
- 230000000770 proinflammatory effect Effects 0.000 description 4
- 238000001551 total correlation spectroscopy Methods 0.000 description 4
- 208000024172 Cardiovascular disease Diseases 0.000 description 3
- 102000014702 Haptoglobin Human genes 0.000 description 3
- 108050005077 Haptoglobin Proteins 0.000 description 3
- FFEARJCKVFRZRR-BYPYZUCNSA-N L-methionine Chemical compound CSCC[C@H](N)C(O)=O FFEARJCKVFRZRR-BYPYZUCNSA-N 0.000 description 3
- 238000005119 centrifugation Methods 0.000 description 3
- 230000009266 disease activity Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 239000002245 particle Substances 0.000 description 3
- 150000003904 phospholipids Chemical class 0.000 description 3
- 208000001072 type 2 diabetes mellitus Diseases 0.000 description 3
- CMEKTLLACGGQGP-UDWSHUFISA-N (4S,5R,6R)-5-acetyl-5-amino-2,4-dihydroxy-6-[(1R,2R)-1,2,3-trihydroxypropyl]oxane-2-carboxylic acid Chemical compound CC(=O)[C@@]1(N)[C@@H](O)CC(O)(C(O)=O)O[C@H]1[C@H](O)[C@H](O)CO CMEKTLLACGGQGP-UDWSHUFISA-N 0.000 description 2
- 108010074051 C-Reactive Protein Proteins 0.000 description 2
- 102100032752 C-reactive protein Human genes 0.000 description 2
- 101710088235 Envelope glycoprotein C homolog Proteins 0.000 description 2
- 206010022489 Insulin Resistance Diseases 0.000 description 2
- 102000007330 LDL Lipoproteins Human genes 0.000 description 2
- 108010007622 LDL Lipoproteins Proteins 0.000 description 2
- 230000001154 acute effect Effects 0.000 description 2
- 108010050122 alpha 1-Antitrypsin Proteins 0.000 description 2
- 102000015395 alpha 1-Antitrypsin Human genes 0.000 description 2
- 229940024142 alpha 1-antitrypsin Drugs 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 239000013060 biological fluid Substances 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
- 208000037976 chronic inflammation Diseases 0.000 description 2
- 230000006020 chronic inflammation Effects 0.000 description 2
- 208000029078 coronary artery disease Diseases 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 230000002526 effect on cardiovascular system Effects 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 208000015181 infectious disease Diseases 0.000 description 2
- 230000002503 metabolic effect Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 239000000101 novel biomarker Substances 0.000 description 2
- 238000001472 pulsed field gradient Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 102000016752 1-Alkyl-2-acetylglycerophosphocholine Esterase Human genes 0.000 description 1
- 238000004791 1D NOESY Methods 0.000 description 1
- 208000030507 AIDS Diseases 0.000 description 1
- 102000011690 Adiponectin Human genes 0.000 description 1
- 108010076365 Adiponectin Proteins 0.000 description 1
- 206010001580 Albuminuria Diseases 0.000 description 1
- 102100022524 Alpha-1-antichymotrypsin Human genes 0.000 description 1
- 206010003211 Arteriosclerosis coronary artery Diseases 0.000 description 1
- 108010024976 Asparaginase Proteins 0.000 description 1
- 201000001320 Atherosclerosis Diseases 0.000 description 1
- 108010075016 Ceruloplasmin Proteins 0.000 description 1
- 102100023321 Ceruloplasmin Human genes 0.000 description 1
- 208000016998 Conn syndrome Diseases 0.000 description 1
- 208000011231 Crohn disease Diseases 0.000 description 1
- 208000033054 Cushing disease Diseases 0.000 description 1
- 208000014311 Cushing syndrome Diseases 0.000 description 1
- WQZGKKKJIJFFOK-QTVWNMPRSA-N D-mannopyranose Chemical compound OC[C@H]1OC(O)[C@@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-QTVWNMPRSA-N 0.000 description 1
- KCXVZYZYPLLWCC-UHFFFAOYSA-N EDTA Chemical compound OC(=O)CN(CC(O)=O)CCN(CC(O)=O)CC(O)=O KCXVZYZYPLLWCC-UHFFFAOYSA-N 0.000 description 1
- 108010049003 Fibrinogen Proteins 0.000 description 1
- 102000008946 Fibrinogen Human genes 0.000 description 1
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 1
- HSRJKNPTNIJEKV-UHFFFAOYSA-N Guaifenesin Chemical compound COC1=CC=CC=C1OCC(O)CO HSRJKNPTNIJEKV-UHFFFAOYSA-N 0.000 description 1
- 102000015779 HDL Lipoproteins Human genes 0.000 description 1
- 108010010234 HDL Lipoproteins Proteins 0.000 description 1
- 208000031886 HIV Infections Diseases 0.000 description 1
- 208000037357 HIV infectious disease Diseases 0.000 description 1
- HTTJABKRGRZYRN-UHFFFAOYSA-N Heparin Chemical compound OC1C(NC(=O)C)C(O)OC(COS(O)(=O)=O)C1OC1C(OS(O)(=O)=O)C(O)C(OC2C(C(OS(O)(=O)=O)C(OC3C(C(O)C(O)C(O3)C(O)=O)OS(O)(=O)=O)C(CO)O2)NS(O)(=O)=O)C(C(O)=O)O1 HTTJABKRGRZYRN-UHFFFAOYSA-N 0.000 description 1
- 102000016267 Leptin Human genes 0.000 description 1
- 108010092277 Leptin Proteins 0.000 description 1
- 208000019693 Lung disease Diseases 0.000 description 1
- 208000005777 Lupus Nephritis Diseases 0.000 description 1
- 230000004988 N-glycosylation Effects 0.000 description 1
- 102000005348 Neuraminidase Human genes 0.000 description 1
- 108010006232 Neuraminidase Proteins 0.000 description 1
- 108010061952 Orosomucoid Proteins 0.000 description 1
- 102000012404 Orosomucoid Human genes 0.000 description 1
- 108010026552 Proteome Proteins 0.000 description 1
- 208000006265 Renal cell carcinoma Diseases 0.000 description 1
- 208000037847 SARS-CoV-2-infection Diseases 0.000 description 1
- 108700028909 Serum Amyloid A Proteins 0.000 description 1
- 102000054727 Serum Amyloid A Human genes 0.000 description 1
- 125000000218 acetic acid group Chemical group C(C)(=O)* 0.000 description 1
- OIPILFWXSMYKGL-UHFFFAOYSA-N acetylcholine Chemical compound CC(=O)OCC[N+](C)(C)C OIPILFWXSMYKGL-UHFFFAOYSA-N 0.000 description 1
- 229960004373 acetylcholine Drugs 0.000 description 1
- 208000038016 acute inflammation Diseases 0.000 description 1
- 230000006022 acute inflammation Effects 0.000 description 1
- 108010091628 alpha 1-Antichymotrypsin Proteins 0.000 description 1
- 238000002583 angiography Methods 0.000 description 1
- 206010003246 arthritis Diseases 0.000 description 1
- 238000007681 bariatric surgery Methods 0.000 description 1
- 108700000130 basal insulin peglispro Proteins 0.000 description 1
- 230000023555 blood coagulation Effects 0.000 description 1
- 230000036765 blood level Effects 0.000 description 1
- 108091006374 cAMP receptor proteins Proteins 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 235000012000 cholesterol Nutrition 0.000 description 1
- 230000001684 chronic effect Effects 0.000 description 1
- 238000003759 clinical diagnosis Methods 0.000 description 1
- 206010009887 colitis Diseases 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 208000026758 coronary atherosclerosis Diseases 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000003748 differential diagnosis Methods 0.000 description 1
- 238000000914 diffusion-ordered spectroscopy Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 229940012952 fibrinogen Drugs 0.000 description 1
- 230000024924 glomerular filtration Effects 0.000 description 1
- 239000008103 glucose Substances 0.000 description 1
- 238000006206 glycosylation reaction Methods 0.000 description 1
- 229960002897 heparin Drugs 0.000 description 1
- 229920000669 heparin Polymers 0.000 description 1
- 238000003919 heteronuclear multiple bond coherence Methods 0.000 description 1
- 238000001052 heteronuclear multiple bond coherence spectrum Methods 0.000 description 1
- 238000005570 heteronuclear single quantum coherence Methods 0.000 description 1
- 238000000990 heteronuclear single quantum coherence spectrum Methods 0.000 description 1
- 208000033519 human immunodeficiency virus infectious disease Diseases 0.000 description 1
- 125000004435 hydrogen atom Chemical group [H]* 0.000 description 1
- 230000003907 kidney function Effects 0.000 description 1
- NRYBAZVQPHGZNS-ZSOCWYAHSA-N leptin Chemical compound O=C([C@H](CO)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(O)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CC=1C2=CC=CC=C2NC=1)NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](NC(=O)[C@H](CC(O)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](N)CC(C)C)CCSC)N1CCC[C@H]1C(=O)NCC(=O)N[C@@H](CS)C(O)=O NRYBAZVQPHGZNS-ZSOCWYAHSA-N 0.000 description 1
- 229940039781 leptin Drugs 0.000 description 1
- 230000004130 lipolysis Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 206010025135 lupus erythematosus Diseases 0.000 description 1
- 150000002704 mannoses Chemical class 0.000 description 1
- 239000002207 metabolite Substances 0.000 description 1
- 125000001360 methionine group Chemical group N[C@@H](CCSC)C(=O)* 0.000 description 1
- 125000000325 methylidene group Chemical group [H]C([H])=* 0.000 description 1
- 208000001022 morbid obesity Diseases 0.000 description 1
- 238000000491 multivariate analysis Methods 0.000 description 1
- 230000000414 obstructive effect Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 239000008363 phosphate buffer Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 208000013846 primary aldosteronism Diseases 0.000 description 1
- 201000009395 primary hyperaldosteronism Diseases 0.000 description 1
- 238000000358 protein NMR Methods 0.000 description 1
- 230000002685 pulmonary effect Effects 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 238000012502 risk assessment Methods 0.000 description 1
- 150000003384 small molecules Chemical class 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012421 spiking Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 239000002753 trypsin inhibitor Substances 0.000 description 1
- 210000002700 urine Anatomy 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
- G01N24/00—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects
- G01N24/08—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects by using nuclear magnetic resonance
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Immunology (AREA)
- Chemical & Material Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Pathology (AREA)
- Biochemistry (AREA)
- Analytical Chemistry (AREA)
- Bioinformatics & Computational Biology (AREA)
- High Energy & Nuclear Physics (AREA)
- Urology & Nephrology (AREA)
- General Physics & Mathematics (AREA)
- Hematology (AREA)
- Biophysics (AREA)
- Biotechnology (AREA)
- Cell Biology (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Microbiology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
Die Erfindung betrifft ein Verfahren zur Messung der Beiträge einzelner Glykoproteine und/oder Glykoylierungsmuster als Biomarker, abgeleitet aus einer Analyse von NMR-Spektren von Blutserum und/oder Blutplasma, umfassend die Schritte:i. Selektion von Glykoporoteinen aus einer Probe von Blutserum anhand ihrer spezifischen Diffusions- und/oder Relaxationseigenschaften und/oder Frequenzen und/oder J-Kopplungenii. Bestimmung der Glykan, GlycA- und GlycB-Signalgruppen in einem NMR-Spektrum wobei die GlyA-Signalgruppe von Methylgruppen von Neu5Ac gebildet ist und wobei die GlycB-Signalgruppe von Methylgruppen von GlcNAc-Einheiten gebildet ist und wobei die Glykan-Signalgruppe zwischen 3,5 und 5,5 ppm und die Neu5Ac-H3eq-Signalgruppe zwischen 2,6 und 2,9 ppm und die Neu5Ac-H3ax-Signalgruppe zwischen 1,6 und 1,88 ppm und die GycA-Signalgruppe zwischen 2,0 und 2,07 ppm und die GlycB-Signalgruppe zwischen 2,07 und 2,2 ppm liegt und wobei eine Zuordnung der Signale anhand des aus Abbildung 1 zu entnehmenden Schemas erfolgtiii. Anpassung von charakteristischen Frequenzmatrizen für einzelne oder zuvor zu Klassen zusammengestellte Glykoproteine an die bestimmten Signalgruppen mittels mathematischer Methodeniv. Ermittlung der Beiträge einzelner Glykoprotein-Biomarker durch Dekonvolution des Spektrums unter Verwendung der in Schritt iii angepassten Frequenzmatrizen und Addition einer zuvor zugeordneten Anzahl von mathematischen Funktionen.Ferner betrifft die Erfindung ein Computerprogrammprodukt und eine Verwendung.The invention relates to a method for measuring the contributions of individual glycoproteins and/or glycoylation patterns as biomarkers derived from an analysis of NMR spectra of blood serum and/or blood plasma, comprising the steps:i. Selection of glycoproteins from a sample of blood serum based on their specific diffusion and/or relaxation properties and/or frequencies and/or J-couplingsii. Determination of the glycan, GlycA and GlycB signal groups in an NMR spectrum, where the GlyA signal group is formed by methyl groups of Neu5Ac and where the GlycB signal group is formed by methyl groups of GlcNAc units and where the glycan signal group is between 3.5 and 5.5 ppm and the Neu5Ac-H3eq signal group is between 2.6 and 2.9 ppm and the Neu5Ac-H3ax signal group is between 1.6 and 1.88 ppm and the GycA signal group is between 2.0 and 2.07 ppm and the GlycB signal group is between 2.07 and 2.2 ppm and where the signals are assigned using the scheme shown in Figure 1iii. Adaptation of characteristic frequency matrices for individual glycoproteins or glycoproteins previously grouped into classes to the determined signal groups using mathematical methodsiv. Determining the contributions of individual glycoprotein biomarkers by deconvolution of the spectrum using the frequency matrices adjusted in step iii and adding a previously assigned number of mathematical functions.The invention further relates to a computer program product and a use.
Description
Die vorliegende Erfindung betrifft die NMR-Analyse von Proteinsignalen in Blutserum- oder Plasmaproben.The present invention relates to the NMR analysis of protein signals in blood serum or plasma samples.
Die Kernmagnetische Resonanz Spektroskopie wird zunehmend zur Bestimmung von Biomarkern eingesetzt, insbesondere von Lipoprotein-Biomarkern, die mit Cholesterin in Verbindung stehen. Siehe
Gruppen EG, Riphagen IJ, Connelly MA, Otvos JD, Bakker SJL, Dullaart RPF (2015) GlycA, a Pro-Inflammatory Glycoprotein Biomarker, and Incident Cardiovascular Disease: Relationship with C-Reactive Protein and renal Function. PLoS ONE 10 (9) schlagen GlycA als neuen NMRspektroskopischen Biomarker zur Erkennung von Entzündungen und kardiovaskulären Erkrankungen vor.Gruppen EG, Riphagen IJ, Connelly MA, Otvos JD, Bakker SJL, Dullaart RPF (2015) GlycA, a Pro-Inflammatory Glycoprotein Biomarker, and Incident Cardiovascular Disease: Relationship with C-Reactive Protein and renal Function. PLoS ONE 10 (9) propose GlycA as a new NMR spectroscopic biomarker for the detection of inflammation and cardiovascular disease.
NMR-Methoden, die zur Ableitung medizinischer Marker für die medizinische Risikobewertung Signale von Glykoproteinen (GlycA und GlycB) nutzen, sind aus der
Die Signale von GlycA und GlyB stammen von einer Reihe von Proteinen, die oft als Akut-Phase-Proteine bezeichnet werden und sich dadurch auszeichnen, dass sie stark auf Entzündungen reagieren, die zu einem erheblichen Anstieg oder Abfall im Blut führen. Zu den Akute-Phase-Proteinen gehören unter anderem CRP, Serum-Amyloid A, Haptoglobin, Fibrinogen, α-1-saures Glykoprotein, Haptoglobin, Serotransferrin, α-1-Antitrypsin und α-1-Antichymotrypsin. Es ist bekannt, dass sich die Konzentration von Akute-Phase-Proteinen nicht nur als Reaktion auf Entzündungsereignisse, sondern auch hinsichtlich ihres Glykosylierungsmusters krankheitsspezifisch verändert. Die GlycA und GlycB Signale in NMR Spektren beruhen auf Methylgruppen spezifischer Glykanreste, die Teil dieser Akut-Phase-Proteine sind und welche hervorragende Biomarker darstellen.The GlycA and GlyB signals originate from a group of proteins, often referred to as acute phase proteins, which are characterized by their strong response to inflammation, leading to a significant increase or decrease in blood levels. Acute phase proteins include CRP, serum amyloid A, haptoglobin, fibrinogen, α-1-acid glycoprotein, haptoglobin, serotransferrin, α-1-antitrypsin, and α-1-antichymotrypsin, among others. It is known that the concentration of acute phase proteins changes in a disease-specific manner not only in response to inflammatory events, but also in terms of their glycosylation pattern. The GlycA and GlycB signals in NMR spectra are based on methyl groups of specific glycan residues that are part of these acute phase proteins and which represent excellent biomarkers.
Die GlycA und GlycB NMR-Signale wurden Berichten zufolge mit klinisch-pathologischen Zuständen in Verbindung gebracht, wie z. B. einem erhöhten Sterberisiko [
Die von GlycA und GlycB abgeleiteten Ergebnisse sind allerdings bisweilen unspezifisch was die Natur der Proteine und der Art der Glykane betrifft. Es wäre eine detailliertere Analyse dieser und anderer Proteinsignale erforderlich, um den Beitrag spezifischer Akut-Phase-Proteine oder zumindest Gruppen von Proteinen zu ermitteln.However, the results derived from GlycA and GlycB are sometimes nonspecific with regard to the nature of the proteins and the type of glycans. A more detailed analysis of these and other protein signals would be required to determine the contribution of specific acute phase proteins or at least groups of proteins.
Eine weitere Patentanmeldung
Daher ist es Aufgabe der Erfindung ein Verfahren zur Messung der Beiträge einzelner Glykoproteine und/oder Glykoylierungsmuster als Biomarker, abgeleitet aus einer Analyse von NMR-Spektren von Blutserum und/oder Blutplasma zur Verfügung zu stellen.Therefore, it is an object of the invention to provide a method for measuring the contributions of individual glycoproteins and/or glycation patterns as biomarkers, derived from an analysis of NMR spectra of blood serum and/or blood plasma.
Die Aufgabe der Erfindung wird gelöst durch ein Verfahren zur Messung der Beiträge einzelner Glykoproteine und/oder Glykoylierungsmuster als Biomarker, abgeleitet aus einer Analyse von NMR-Spektren von Blutserum, umfassend die Schritte:
- Verfahren zur Messung der Beiträge einzelner Glykoproteine als Biomarker, abgeleitet aus einer Analyse von NMR-Spektren von Blutserum und/oder Blutplasma, umfassend die Schritte:
- i. Selektion von Glykoporoteinen in NMR Spektren aus einer Probe von Blutserum und/oder Blutplvasma anhand ihrer spezifischen Diffusions und/oder Relaxationseigenschaften und/oder ihrer spezifischen Frequenz und/oder Kopplungskonstanten im NMR Spektrum.
- ii. Bestimmung der Glykan, GlycA- und GlycB-Signalgruppen in einem NMR-Spektrum wobei die GlycA-Signalgruppe von Methylgruppen von Neu5Ac (5-AcetylNeuraminsäure) gebildet ist und wobei die GlycB-Signalgruppe von Methylgruppen von GlcNAc-Einheiten gebildet ist und wobei die Glykan-Signalgruppe zwischen 3,4 und 5,5 ppm und die Neu5Ac-H3eq-Signalgruppe zwischen 2,6 und 2,9 ppm und die Neu5Ac-H3ax-Signalgruppe zwischen 1,6 und 1,88 ppm und die GycA-Signalgruppe zwischen 2,0 und 2,07 ppm und die GlycB-Signalgruppe zwischen 2,07 und 2,2 ppm liegen und wobei eine Zuordnung der Signale anhand des aus
- iii. Anpassung von charakteristischen Frequenzmatrizen für einzelne oder zuvor zu Klassen zusammengestellten Glykoproteinen an die bestimmten Signalgruppen mittels mathematischer Methoden
- iv. Ermittlung der Beiträge einzelner Glykoprotein-Biomarker durch Dekonvolution des Spektrums unter Verwendung der in Schritt iii angepassten Frequenzmatrizen und Addition einer zuvor zugeordneten Anzahl von mathematischen Funktionen.
- A method for measuring the contributions of individual glycoproteins as biomarkers derived from an analysis of NMR spectra of blood serum and/or blood plasma, comprising the steps:
- i. Selection of glycoporoteins in NMR spectra from a sample of blood serum and/or blood plasma based on their specific diffusion and/or relaxation properties and/or their specific frequency and/or coupling constants in the NMR spectrum.
- ii. Determination of the glycan, GlycA and GlycB signal groups in an NMR spectrum, wherein the GlycA signal group is formed by methyl groups of Neu5Ac (5-acetyl neuraminic acid) and wherein the GlycB signal group is formed by methyl groups of GlcNAc units and wherein the glycan signal group is between 3.4 and 5.5 ppm and the Neu5Ac-H3eq signal group is between 2.6 and 2.9 ppm and the Neu5Ac-H3ax signal group is between 1.6 and 1.88 ppm and the GycA signal group is between 2.0 and 2.07 ppm and the GlycB signal group is between 2.07 and 2.2 ppm and wherein an assignment of the signals is made based on the
- iii. Adaptation of characteristic frequency matrices for individual or previously classified glycoproteins to the specific signal groups using mathematical methods
- iv. Determine the contributions of individual glycoprotein biomarkers by deconvolution of the spectrum using the frequency matrices fitted in step iii and adding a pre-assigned number of mathematical functions.
In einer bevorzugten Ausführungsform der Erfindung erfolgt die Selektion von Glykoporoteinen aus einer Probe von Blutserum und/oder Blutplasma anhand ihrer spezifischen Diffusions- und/oder Relaxationseigenschaften (Schritt i) mittels der Diffusionsdifferenzspektroskopie (DDS), wobei Differenzen von Diffusionsspektren mit unterschiedlichen Diffusionsparametern zur Selektion von Proteinen unterschiedlicher Größe und Diffusionseigenschaften verwendet werden.In a preferred embodiment of the invention, the selection of glycoporoteins from a sample of blood serum and/or blood plasma based on their specific diffusion and/or relaxation properties (step i) is carried out by means of diffusion difference spectroscopy (DDS), whereby differences of diffusion spectra with different diffusion parameters are used to select proteins of different sizes and diffusion properties.
In einer weiteren bevorzugten Ausführungsform der Erfindung erfolgt die Ermittlung der Beiträge einzelner Glykoprotein-Biomarker unter Verwendung von Differenzen der Beiträge einzelner Frequenzmatrix-Komponenten.In a further preferred embodiment of the invention, the contributions of individual glycoprotein biomarkers are determined using differences in the contributions of individual frequency matrix components.
In einer weiteren bevorzugten Ausführungsform erfolgt eine Multiplikation mit einem durch eine Referenzmessung ermittelten Skalierungsfaktor zur Angabe von Konzentrationen in mg/ml, wobei die Multiplikation vor der Dekonvolution der Spektren oder nach Schritt iv erfolgen kann.In a further preferred embodiment, a multiplication by a scaling factor determined by a reference measurement is carried out to indicate concentrations in mg/ml, wherein the multiplication can be carried out before the deconvolution of the spectra or after step iv.
In einem weiteren Aspekt wird die Aufgabe der Erfindung durch ein Computerprogrammprodukt zum Evaluieren von biologischen in-vitro-Blutplasma- oder-Serumproben enthaltend ein nichtflüchtiges computerlesbares Speichermedium mit computerlesbarem Programmcode, der in dem Speichermedium verkörpert ist, wobei der computerlesbare Programmcode folgendes beinhaltet: computerlesbaren Programmcode, der ein NMR-Spektrum einer Anpassungsregion einer Blutplasma- oder Serumprobe eines Individuums entfaltet, wobei der computerlesbare Programmcode das zusammengesetzte NMR-Spektrum unter Verwendung einer charakteristischen Frequenzmatrix, welche Entfaltungsmodelle für verschiedene Proteine beinhaltet, auf Signale mit Komponenten von (a) GlycA, (b) GlycB, (c) Glykan-Protonen und (d) Methyl-gruppen-Protonen angewendet und wobei der Programmcode eine Definition der Frequenzbereiche zur Ermittlung der Glykan, GlycA- und GlycB-Signalgruppen, wobei Glykan-Signalgruppe zwischen 3,4 und 5,5 ppm und die Neu5Ac-H3eq-Signalgruppe zwischen 2,6 und 2,9 ppm und die Neu5Ac-H3ax-Signalgruppe zwischen 1,6 und 1,88 ppm und die GycA-Signalgruppe zwischen 2,0 und 2,07 ppm und die GlycB-Signalgruppe zwischen 2,07 und 2,2 pm liegen und ein Schema zur Zuordnung der Signale entsprechend
Die Selektion von Glykoporoteinen aus einer Probe von Blutserum anhand ihrer spezifischen Diffusions- und/oder Relaxationseigenschaften (Schritt i) erfolgt durch Editierung des NMR-Spektrums. Erfindungsgemäß werden zur Editierung des NMR-Spektrums J-, T2-Relaxation- und Diffusions-Editierte-Spektren oder deren Differenz verwendet, was hier als Diffusionsdifferenzspektroskopie bezeichnet wird (DDS).The selection of glycoporoteins from a sample of blood serum based on their specific diffusion and/or relaxation properties (step i) is carried out by editing the NMR spectrum. According to the invention, J-, T 2 -relaxation and diffusion-edited spectra or their difference are used to edit the NMR spectrum, which is referred to here as diffusion difference spectroscopy (DDS).
Die Editierung nach Methode der T2-Relaxation kann von dem Fachmann aus [
Es kann ebenfalls die dem Fachmann aus [
Ebenfalls möglich ist die Editierung der NMR-Spektren entsprechend des DIRE-Ansatzes, der auf der Vereinfachung von 1 H-NMR-Spektren durch die Nutzung von Unterschieden in den Moleküldiffusionskoeffizienten allein und Kombinationen von Relaxations- und Diffusionsparametern beruht und dem Fachmann aus [
Die Diffusionsdifferenzspektroskopie (DDS) wird hier definiert als die Verwendung einer NMR-Pulssequenz, die ein Element der Diffusionsbearbeitung enthält, von Fachleuten als DOSY (Diffusion Editing Spectroscopy) [
Die DDS ermöglicht eine Editierung von NMR Spektren zur Selektion von Proteinen unterschiedlicher Diffusionseigenschaften, die sich zum Beispiel aus der Proteingröße ergeben. Mittels DDS können zusätzlich die Signale von kleinen Molekülen (<1000 Da) und von Lipoproteinen in NMR-Spektren unterdrückt werden.DDS enables editing of NMR spectra to select proteins with different diffusion properties, which result, for example, from protein size. DDS can also be used to suppress the signals of small molecules (<1000 Da) and lipoproteins in NMR spectra.
Alternativ können im Schritt i auch NMR-Verfahren eingesetzt werden, welche bestimmte Frequenzen selektieren und mittels, dem Fachmann als TOCSY (Total Correlation SpectroscopY) bekannten Verfahren, aus der initialen Selektion auf andere Frequenzbereiche übertragen. Auf diese Weise können Glycan und/oder GlycA und/oder GlycB Signale selektiert werden. [TOCSY: Kapitel 6 in J. Cavanagh, W. J. Fairbrother, A. G. Palmer .III, M. Rance and N. J. Skelton, Protein NMR Spectroscopy (2nd edition, Academic Press, 2007)].Alternatively, NMR methods can be used in step i, which select certain frequencies and transfer them from the initial selection to other frequency ranges using methods known to those skilled in the art as TOCSY (Total Correlation SpectroscopY). In this way, glycan and/or GlycA and/or GlycB signals can be selected. [TOCSY: Chapter 6 in J. Cavanagh, W. J. Fairbrother, A. G. Palmer .III, M. Rance and N. J. Skelton, Protein NMR Spectroscopy (2nd edition, Academic Press, 2007)].
Im Folgenden wird der erfindungsgemäße Schritt iii, die Anpassung von charakteristischen Frequenzmatrizen für einzelne oder zuvor zu Klassen zusammengestellten Glykoproteinen an die bestimmten Signalgruppen mittels mathematischer Methoden eingehender erläutert, ohne dabei die Allgemeinheit der Lehre einzuschränken.In the following, step iii according to the invention, the adaptation of characteristic frequency matrices for individual glycoproteins or glycoproteins previously grouped into classes to the specific signal groups by means of mathematical methods, is explained in more detail without restricting the generality of the teaching.
Die Auswertung der Impulsfolgen für die Analyse von Glykoproteinen folgt [
In
Im Folgenden wird exemplarisch die Analyse von Proben gesunder Kontrollen im Vergleich zu Proben von Patienten mit kardiogenem Schock und COVID-19 im Vergleich zu konventionell ermittelten Werten gezeigt.The following shows an example of the analysis of samples from healthy controls compared to samples from patients with cardiogenic shock and COVID-19 in comparison to conventionally determined values.
Es wird in
Das erfindungsgemäße Verfahren geht über bisherige Analysen von Glykoproteinen hinaus, indem die Beiträge einzelner Glykoproteine oder Proteinklassen (z. B. im Fall von IgG) oder Glykoylierungsmuster detailliert aufzeigt werden können. Dies wird durch die Bestimmung einer charakteristischen Frequenzmatrix für jedes Glykoprotein erreicht, welche dann an die Spektren von Blutserum oder -plasma angepasst wird. Die Erfindung hat erkannt, dass auch der Glykanbereich von NMR-Spektren als weiteres Merkmal des Glykoproteintyps und der Glykanstruktur verwendet werden sollte.The method according to the invention goes beyond previous analyses of glycoproteins in that the contributions of individual glycoproteins or protein classes (e.g. in the case of IgG) or glycoylation patterns can be shown in detail. This is achieved by determining a characteristic frequency matrix for each glycoprotein, which is then adapted to the spectra of blood serum or plasma. The invention has recognized that the glycan range of NMR spectra should also be used as a further feature of the glycoprotein type and glycan structure.
Erfindungsgemäß werden 1H-NMR-NMR-Spektren von Blutserum oder-plasma verwendet, um Biomarker für die Risikobewertung oder klinische Diagnose von Krankheiten abzuleiten. Spezifische Proteine oder Klassen von Proteinen, die im Blut sehr häufig vorkommen und als Akute-Phase-Proteine bezeichnet werden, werden anhand einer Matrix von für jedes Protein charakteristischen chemischen Verschiebungen identifiziert und/oder quantifiziert. Die Biomarker werden durch elektronische Entfaltung charakteristischer Proteinsignale unter Verwendung einer Matrix charakteristischer chemischer Verschiebungen für einzelne Signalkomponenten abgeleitet. Die Signalkomponenten stellen einzelne Akutphasenproteine oder Klassen von glykosylierten Akutphasenproteinen dar. Die Messungen von Akute-Phase-Proteinen können als klinische Biomarker für klinische Krankheitszustände verwendet werden.According to the invention, 1H NMR spectra of blood serum or plasma are used to derive biomarkers for risk assessment or clinical diagnosis of disease. Specific proteins or classes of proteins that are highly abundant in blood, referred to as acute phase proteins, are identified and/or quantified using a matrix of chemical shifts characteristic of each protein. The biomarkers are derived by electronic deconvolution of characteristic protein signals using a matrix of characteristic chemical shifts for individual signal components. The signal components represent individual acute phase proteins or classes of glycosylated acute phase proteins. The measurements of acute phase proteins can be used as clinical biomarkers for clinical disease states.
Die Analyse kann für medizinische Diagnosezwecke eingesetzt werden, wie in beispielhaften Fällen mit Proben von gesunden Kontrollen, kardiogenem Schock und COVID-19-Patienten gezeigt wurde. Die detaillierteren Glykoproteinparameter können die medizinische Diagnose oder die Differenzierung zwischen Patienten unterstützen.The analysis can be used for medical diagnostic purposes, as demonstrated in exemplary cases with samples from healthy controls, cardiogenic shock and COVID-19 patients. The more detailed glycoprotein parameters can support medical diagnosis or differentiation between patients.
Im Folgenden wird die Allgemeinheit der Lehre nicht einschränkend das Vorgehen bei der Durchführung des erfindungsgemäßen Verfahrens aufgezeigt.In the following, the generality of the teaching is shown in a non-limiting manner and the procedure for carrying out the method according to the invention is shown.
Zur Präparation der Blutproben wurde Serum oder Plasma nach in der Klinik etablierten Methoden präpariert, für Serum durch Zentrifugation nach einer Periode der Blutgerinnung und anschließender Zentrifugation, bei Plasma (EDTA oder Heparin-Plasma) Zentrifugation der Proben, nach Protokollen in klinischen Laboren.For the preparation of blood samples, serum or plasma was prepared according to methods established in the clinic, for serum by centrifugation after a period of blood coagulation and subsequent centrifugation, for plasma (EDTA or heparin plasma) by centrifugation of the samples, according to protocols in clinical laboratories.
Die gefrorenen Serum oder Plasma Proben wurde aufgetaut und anschließend 1/1 mit einem 75mM Phosphatpuffer versetzt, dann für eine Minute geschüttelt. 600µL Probe wurde dann in ein 5 mm NMR-Röhrchen transferiert. Die NMR Analyse wurde anschließend mit einem 600 MHz NMR Spektrometer (Bruker Avance III HD Spektrometer mit einem Raum-Temperatur für 1H optimierten Probenkopf) gemessen. Das Spektrometer wurde für diese Untersuchungen kalibiriert wie in Dona et al beschrieben.Frozen serum or plasma samples were thawed and then mixed 1/1 with a 75 mM phosphate buffer and shaken for one minute. 600 µL of sample was then transferred to a 5 mm NMR tube. NMR analysis was then performed using a 600 MHz NMR spectrometer (Bruker Avance III HD spectrometer with a room temperature probe head optimized for 1H). The spectrometer was calibrated for these studies as described in Dona et al.
[
Verzeichnis der AbbildungenList of illustrations
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Claims (7)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102023110285.0A DE102023110285B3 (en) | 2023-04-21 | 2023-04-21 | NMR MEASUREMENT OF GLYCOPROTEINS |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102023110285.0A DE102023110285B3 (en) | 2023-04-21 | 2023-04-21 | NMR MEASUREMENT OF GLYCOPROTEINS |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| DE102023110285B3 true DE102023110285B3 (en) | 2024-05-08 |
Family
ID=90732456
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| DE102023110285.0A Active DE102023110285B3 (en) | 2023-04-21 | 2023-04-21 | NMR MEASUREMENT OF GLYCOPROTEINS |
Country Status (1)
| Country | Link |
|---|---|
| DE (1) | DE102023110285B3 (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4933844A (en) | 1988-09-26 | 1990-06-12 | Otvos James D | Measurement of blood lipoprotein constituents by analysis of data acquired from an NMR spectrometer |
| US6617167B2 (en) | 2001-08-01 | 2003-09-09 | Liposcience, Inc. | Method of determining presence and concentration of lipoprotein X in blood plasma and serum |
| US9470771B2 (en) | 2012-06-08 | 2016-10-18 | Liposcience, Inc. | NMR measurements of NMR biomarker GlycA |
| EP3588120B1 (en) | 2018-06-26 | 2021-02-24 | Bruker BioSpin GmbH | System and method for improved signal detection in nmr spectroscopy |
| WO2022157729A1 (en) | 2021-01-22 | 2022-07-28 | Bruker Biospin Gmbh | Infection diagnosis and characterization using diffusion and relaxation edited proton nmr spectroscopy |
-
2023
- 2023-04-21 DE DE102023110285.0A patent/DE102023110285B3/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4933844A (en) | 1988-09-26 | 1990-06-12 | Otvos James D | Measurement of blood lipoprotein constituents by analysis of data acquired from an NMR spectrometer |
| US6617167B2 (en) | 2001-08-01 | 2003-09-09 | Liposcience, Inc. | Method of determining presence and concentration of lipoprotein X in blood plasma and serum |
| US9470771B2 (en) | 2012-06-08 | 2016-10-18 | Liposcience, Inc. | NMR measurements of NMR biomarker GlycA |
| EP2859339B1 (en) | 2012-06-08 | 2020-10-28 | Liposcience, Inc. | Nmr measurements of glyca |
| EP3588120B1 (en) | 2018-06-26 | 2021-02-24 | Bruker BioSpin GmbH | System and method for improved signal detection in nmr spectroscopy |
| WO2022157729A1 (en) | 2021-01-22 | 2022-07-28 | Bruker Biospin Gmbh | Infection diagnosis and characterization using diffusion and relaxation edited proton nmr spectroscopy |
Non-Patent Citations (36)
| Title |
|---|
| Berends AMA, Buitenwerf E, Gruppen EG, et al. Primary aldosteronism is associated with decreased lowdensity and high-density lipoprotein particle concentrations and increased GlycA, a pro-inflammatory glycoprotein biomarker. Clin Endocrinol. 2019;90:79-87 |
| Carr HY, Purcell EM. Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments. Phys Rev. 1954;94:630-638 |
| Chung CP, Ormseth MJ, Connelly MA, et al. GlycA, a novel marker of inflammation, is elevated in systemic lupus erythematosus. Lupus. 2016;25:296-300 |
| Cohen-Manheim I, Doniger GM, Sinnreich R, et al. Increase in the Inflammatory Marker GlycA over 13 Years in Young Adults Is Associated with Poorer Cognitive Function in Midlife. Wylie GR, ed. PLoS ONE. 2015;10:e0138036 |
| Connelly MA, Otvos JD, Zhang Q, et al. Effects of hepato-preferential basal insulin peglispro on nuclear magnetic resonance biomarkers lipoprotein insulin resistance index and GlycA in patients with diabetes. Biomarkers in Medicine. 2017;11:991-1001 |
| Connelly MA, Shimizu C, Winegar DA, et al. Differences in GlycA and lipoprotein particle parameters may help distinguish acute kawasaki disease from other febrile illnesses in children. BMC Pediatr. 2016;16:151 |
| Dierckx T, Chiche L, Daniel L, Lauwerys B, Van Weyenbergh J, Jourde-Chiche N. Serum GlycA Level Is Elevated in Active Systemic Lupus Erythematosus and Correlates to Disease Activity and Lupus Nephritis Severity. JCM. 2020;9:970 |
| Dierckx T, Verstockt B, Vermeire S, van Weyenbergh J. GlycA, a Nuclear Magnetic Resonance Spectroscopy Measure for Protein Glycosylation, is a Viable Biomarker for Disease Activity in IBD. Journal of Crohn's and Colitis. 2019;13:389-394,31 |
| Dona, A. C., Jimenez, B., Schäfer, H., Humpfer, E., Spraul, M., Lewis, M. R., et al. (2014). Precision High-Throughput Proton NMR Spectroscopy of Human Urine, Serum, and Plasma for Large-Scale Metabolic Phenotyping. Anal. Chem. 86, 9887-9894. doi:10.1021/ac5025039 |
| Dullaart RPF, Gruppen EG, Connelly MA, Otvos JD, Lefrandt JD. GlycA, a biomarker of inflammatory glycoproteins, is more closely related to the leptin/adiponectin ratio than to glucose tolerance status, Akinkuolie AO, Pradhan AD, Buring JE, Ridker PM, Mora S. Novel Protein Glycan Side-Chain Biomarker and Risk of Incident Type 2 Diabetes Mellitus. ATVB. 2015;35:1544-1550 |
| Fuertes-Martin R, Moncayo S, Insenser M, et al. Glycoprotein A and B Height-to-Width Ratios as Obesity-Independent Novel Biomarkers of Low-Grade Chronic Inflammation in Women with Polycystic Ovary Syndrome (PCOS). J Proteome Res. 2019;18:4038-4045 |
| Gao H, Dong B, Liu X, Xuan H, Huang Y, Lin D. Metabonomic profiling of renal cell carcinoma: High-resolution proton nuclear magnetic resonance spectroscopy of human serum with multivariate data analysis. Analytica Chimica Acta. 2008;624:269-277 |
| Gruppen EG, Connelly MA, Sluiter WJ, Bakker SJL, Dullaart RPF. Higher plasma GlycA, a novel pro-inflammatory glycoprotein biomarker, is associated with reduced life expectancy: The PREVEND study. Clinica Chimica Acta. 2019;488:7-12 |
| Gruppen EG, Riphagen IJ, Connelly MA, Otvos JD, Bakker SJL, Dullaart RPF. GlycA, a Pro-Inflammatory Glycoprotein Biomarker, and Incident Cardiovascular Disease: Relationship with C-Reactive Protein and Renal Function. Shimosawa T, ed. PLoS ONE. 2015;10:e0139057 |
| Jago R, Drews KL, Otvos JD, Willi SM, Buse JB, for the HEALTHY Study Group. Novel measures of inflammation and insulin resistance are related to obesity and fitness in a diverse sample of 11-14 year olds: The HEALTHY Study. Int J Obes. 2016;40:1157-1163 |
| Jang S, Ogunmoroti O, Ndumele CE, et al. Association of the Novel Inflammatory Marker GlycA and Incident Heart Failure and Its Subtypes of Preserved and Reduced Ejection Fraction: The Multi-Ethnic Study of Atherosclerosis. Circ: Heart Failure. 2020;13:e007067 |
| Joshi AA, Lerman JB, Aberra TM, et al. GlycA Is a Novel Biomarker of Inflammation and Subclinical Cardiovascular Disease in Psoriasis. Circ Res. 2016;119:1242-1253 |
| Kevat AC, Carzino R, Vidmar S, Ranganathan S. Glycoprotein A as a biomarker of pulmonary infection and inflammation in children with cystic fibrosis. Pediatr Pulmonol. 2020;55:401-406 |
| Levine JA, Han JM, Wolska A, et al. Associations of GlycA and high-sensitivity C-reactive protein with measures of lipolysis in adults with obesity. Journal of Clinical Lipidology. 2020;14:667-674 |
| Liu M, Nicholson JK, Lindon JC. High-Resolution Diffusion and Relaxation Edited One- and Two-Dimensional 1 H NMR Spectroscopy of Biological Fluids. Anal Chem. 1996; 68:3370-3376 |
| Liu M, Nicholson JK, Lindon JC. High-Resolution Diffusion and Relaxation Edited One- and Two-Dimensional1 H NMR Spectroscopy of Biological Fluids. Anal Chem. 1996; 68:3370-3376 |
| Lodge S, Nitschke P, Kimhofer T, et al. Diffusion and Relaxation Edited Proton NMR Spectroscopy of Plasma Reveals a High-Fidelity Supramolecular Biomarker Signature of SARS-CoV-2 Infection. Anal Chem. 2021;93:3976-3986 |
| Makri A, Cheung A, Sinaii N, et al. Lipoprotein particles in patients with pediatric Cushing disease and possible cardiovascular risks. Pediatr Res. 2019;86:375-381 |
| Malo A-I, Rull A, Girona J, et al. Glycoprotein Profile Assessed by 1 H-NMR as a Global Inflammation Marker in Patients with HIV Infection. A Prospective Study. JCM. 2020;9:1344 |
| Manmadhan A, Lin B-X, Zhong J, et al. Elevated GlycA in severe obesity is normalized by bariatric surgery. Diabetes Obes Metab. 2019;21:178-182 |
| Meiboom S, Gill D. Modified Spin-Echo Method for Measuring Nuclear Relaxation Times. Review of Scientific Instruments. 1958;29:688-691 |
| Nitschke P, Lodge S, Kimhofer T, et al. J-Edited Dlffusional (JEDI) Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum. :24 |
| Nitschke P, Lodge S, Kimhofer T, et al. J-Edited Dlffusional (JEDI) Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum. :24] HIV |
| Ormseth MJ, Chung CP, Oeser AM, et al. Utility of a novel inflammatory marker, GlycA, for assessment of rheumatoid arthritis disease activity and coronary atherosclerosis. Arthritis Res Ther. 2015;17:117 |
| Prokic I, Lahousse L, de Vries M, et al. A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease. BMC Pulm Med. 2020;20:193 |
| Ritchie SC, Kettunen J, Brozynska M, et al. Elevated serum alpha-1 antitrypsin is a major component of GlycAassociated risk for future morbidity and mortality. Feng Y-M, ed. PLoS ONE und Kettunen J, Ritchie SC, Anufrieva O, et al. Biomarker Glycoprotein Acetyls Is Associated With the Risk of a Wide Spectrum of Incident Diseases and Stratifies Mortality Risk in Angiography Patients. Circ: Genomic and Precision Medicine. 2018;11:e002234 |
| Ritchie SC, Würtz P, Nath AP, et al. The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection. Cell Systems. 2015;1:293-301 |
| Rodriguez-Carrio J, Alperi-Löpez M, Löpez P, et al. GlycA Levels during the Earliest Stages of Rheumatoid Arthritis: Potential Use as a Biomarker of Subclinical Cardiovascular Disease. JCM. 2020;9:2472 |
| subjects but not in diabetic or metabolic syndrome subjects. Journal of Clinical Lipidology. 2016;10:512-518 |
| Tibuakuu M, Fashanu OE, Zhao D, et al. GlycA, a novel inflammatory marker, is associated with subclinical coronary disease. AIDS. 2019;33:547-557 |
| Titan SM, Pecoits-Filho R, Barreto SM, Lopes AA, Bensenor IJ, Lotufo PA. GlycA, a marker of protein glycosylation, is related to albuminuria and estimated glomerular filtration rate: the ELSA-Brasil study. BMC Nephrol. 2017;18:367 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guleria et al. | NMR based serum metabolomics reveals a distinctive signature in patients with Lupus Nephritis | |
| DE60026287T2 (en) | NMR METHOD FOR DETERMINING THE RISK FOR DEVELOPING DIABETES TYPE 2 | |
| Mallol et al. | Human serum/plasma lipoprotein analysis by NMR: application to the study of diabetic dyslipidemia | |
| Brindle et al. | Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics | |
| Yu et al. | More accurate 1JCH coupling measurement in the presence of 3JHH strong coupling in natural abundance | |
| US7373256B2 (en) | Method for the identification of molecules and biomarkers using chemical, biochemical and biological data | |
| Robosky et al. | In vivo toxicity screening programs using metabonomics | |
| EP0361214A1 (en) | NMR lipoprotein analysis of blood | |
| Martineau et al. | Fast quantitative 2D NMR for metabolomics and lipidomics: A tutorial | |
| DE102010038014B4 (en) | Use of specific substances as markers to determine the risk of kidney rejection | |
| Wang et al. | Coefficient of variation, signal-to-noise ratio, and effects of normalization in validation of biomarkers from NMR-based metabonomics studies | |
| Sandusky et al. | Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids | |
| EP3159681B1 (en) | Method and device for automatable determination of the detection threshold and the relative error in the quantification of the concentration of a substance to be tested in a measuring probe | |
| DE10392707T5 (en) | Method of using data binning in the analysis of chromatography / spectrometry data | |
| Bervoets et al. | Influence of preanalytical sampling conditions on the 1 H NMR metabolic profile of human blood plasma and introduction of the Standard PREanalytical Code used in biobanking | |
| AU2004286629A2 (en) | Methods, systems and computer programs for assessing CHD risk using mathematical models that consider in vivo concentration gradients of LDL particle subclasses of discrete size | |
| Bathen et al. | Quantification of plasma lipids and apolipoproteins by use of proton NMR spectroscopy, multivariate and neural network analysis | |
| US10613169B2 (en) | Methods for monitoring changes in the core of lipoprotein particles in metabolism and disease | |
| Shaykhutdinov et al. | Quantitative analysis of metabolite concentrations in human urine samples using 13 C {1 H} NMR spectroscopy | |
| DE102004026903B4 (en) | Determination of lipoprotein classes in body fluids comprises analyzing NMR spectra of a plasma or serum sample and measuring under different measuring conditions; and determining the different effects of these measuring conditions | |
| DE102012214660B4 (en) | Automated spectral fat saturation | |
| DE102023110285B3 (en) | NMR MEASUREMENT OF GLYCOPROTEINS | |
| EP0422170B1 (en) | A process for recording spin resonance spectra | |
| McKenzie et al. | Peak fitting in 2D 1 H–13 C HSQC NMR spectra for metabolomic studies | |
| Stolzenburg et al. | Improved quality of 1 H NMR spectroscopic data for enhanced metabolic profiling of low molecular weight metabolites in human serum |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| R012 | Request for examination validly filed | ||
| R018 | Grant decision by examination section/examining division |