CN115326958A - Marker composition for assisting in predicting or diagnosing children with obesity and hyperlipidemia - Google Patents
Marker composition for assisting in predicting or diagnosing children with obesity and hyperlipidemia Download PDFInfo
- Publication number
- CN115326958A CN115326958A CN202210962076.7A CN202210962076A CN115326958A CN 115326958 A CN115326958 A CN 115326958A CN 202210962076 A CN202210962076 A CN 202210962076A CN 115326958 A CN115326958 A CN 115326958A
- Authority
- CN
- China
- Prior art keywords
- marker composition
- children
- composition according
- hyperlipidemia
- obesity
- 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.)
- Granted
Links
- 239000003550 marker Substances 0.000 title claims abstract description 38
- 239000000203 mixture Substances 0.000 title claims abstract description 38
- 208000008589 Obesity Diseases 0.000 title claims abstract description 27
- 235000020824 obesity Nutrition 0.000 title claims abstract description 23
- 208000031226 Hyperlipidaemia Diseases 0.000 title claims abstract description 17
- 239000002207 metabolite Substances 0.000 claims abstract description 28
- 238000001514 detection method Methods 0.000 claims abstract description 16
- 150000001335 aliphatic alkanes Chemical class 0.000 claims abstract description 13
- 229920006395 saturated elastomer Polymers 0.000 claims abstract description 13
- 150000004945 aromatic hydrocarbons Chemical class 0.000 claims abstract description 12
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 claims abstract description 6
- 208000031288 Combined hyperlipidaemia Diseases 0.000 claims abstract description 3
- UFWIBTONFRDIAS-UHFFFAOYSA-N Naphthalene Chemical compound C1=CC=CC2=CC=CC=C21 UFWIBTONFRDIAS-UHFFFAOYSA-N 0.000 claims description 16
- NDJKXXJCMXVBJW-UHFFFAOYSA-N heptadecane Chemical compound CCCCCCCCCCCCCCCCC NDJKXXJCMXVBJW-UHFFFAOYSA-N 0.000 claims description 16
- 206010033307 Overweight Diseases 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 12
- 238000004817 gas chromatography Methods 0.000 claims description 12
- 238000001819 mass spectrum Methods 0.000 claims description 10
- 238000005070 sampling Methods 0.000 claims description 9
- 238000002414 normal-phase solid-phase extraction Methods 0.000 claims description 8
- XJHRZBIBSSVCEL-ARJAWSKDSA-N (Z)-non-6-en-1-ol Chemical compound CC\C=C/CCCCCO XJHRZBIBSSVCEL-ARJAWSKDSA-N 0.000 claims description 6
- XJHRZBIBSSVCEL-UHFFFAOYSA-N Z-Non-6-en-1-ol Natural products CCC=CCCCCCO XJHRZBIBSSVCEL-UHFFFAOYSA-N 0.000 claims description 6
- 238000003745 diagnosis Methods 0.000 claims description 6
- 238000002470 solid-phase micro-extraction Methods 0.000 claims description 6
- 239000004809 Teflon Substances 0.000 claims description 4
- 229920006362 Teflon® Polymers 0.000 claims description 4
- 150000001299 aldehydes Chemical class 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000007664 blowing Methods 0.000 claims description 4
- 235000021152 breakfast Nutrition 0.000 claims description 4
- 238000011534 incubation Methods 0.000 claims description 4
- 150000002576 ketones Chemical class 0.000 claims description 4
- 238000012805 post-processing Methods 0.000 claims description 3
- -1 aldehyde ketone Chemical class 0.000 abstract description 8
- 239000000126 substance Substances 0.000 abstract description 8
- 238000000034 method Methods 0.000 abstract description 7
- 238000011160 research Methods 0.000 abstract description 4
- 230000004907 flux Effects 0.000 abstract 1
- 230000035945 sensitivity Effects 0.000 abstract 1
- 208000032928 Dyslipidaemia Diseases 0.000 description 11
- 208000017170 Lipid metabolism disease Diseases 0.000 description 11
- 239000012855 volatile organic compound Substances 0.000 description 10
- 201000010099 disease Diseases 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
- 150000001875 compounds Chemical class 0.000 description 4
- 238000007619 statistical method Methods 0.000 description 4
- 108010023302 HDL Cholesterol Proteins 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 150000002500 ions Chemical class 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- XMGQYMWWDOXHJM-JTQLQIEISA-N (+)-α-limonene Chemical compound CC(=C)[C@@H]1CCC(C)=CC1 XMGQYMWWDOXHJM-JTQLQIEISA-N 0.000 description 2
- QPUYECUOLPXSFR-UHFFFAOYSA-N 1-methylnaphthalene Chemical compound C1=CC=C2C(C)=CC=CC2=C1 QPUYECUOLPXSFR-UHFFFAOYSA-N 0.000 description 2
- YNQLUTRBYVCPMQ-UHFFFAOYSA-N Ethylbenzene Chemical compound CCC1=CC=CC=C1 YNQLUTRBYVCPMQ-UHFFFAOYSA-N 0.000 description 2
- 206010020772 Hypertension Diseases 0.000 description 2
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 description 2
- 208000007683 Pediatric Obesity Diseases 0.000 description 2
- ISWSIDIOOBJBQZ-UHFFFAOYSA-N Phenol Chemical compound OC1=CC=CC=C1 ISWSIDIOOBJBQZ-UHFFFAOYSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 239000004205 dimethyl polysiloxane Substances 0.000 description 2
- 235000013870 dimethyl polysiloxane Nutrition 0.000 description 2
- SNRUBQQJIBEYMU-UHFFFAOYSA-N dodecane Chemical compound CCCCCCCCCCCC SNRUBQQJIBEYMU-UHFFFAOYSA-N 0.000 description 2
- 230000002526 effect on cardiovascular system Effects 0.000 description 2
- 230000000366 juvenile effect Effects 0.000 description 2
- 150000002632 lipids Chemical class 0.000 description 2
- CXQXSVUQTKDNFP-UHFFFAOYSA-N octamethyltrisiloxane Chemical compound C[Si](C)(C)O[Si](C)(C)O[Si](C)(C)C CXQXSVUQTKDNFP-UHFFFAOYSA-N 0.000 description 2
- 230000001575 pathological effect Effects 0.000 description 2
- YCOZIPAWZNQLMR-UHFFFAOYSA-N pentadecane Chemical compound CCCCCCCCCCCCCCC YCOZIPAWZNQLMR-UHFFFAOYSA-N 0.000 description 2
- 238000004987 plasma desorption mass spectroscopy Methods 0.000 description 2
- 229920000435 poly(dimethylsiloxane) Polymers 0.000 description 2
- UOHMMEJUHBCKEE-UHFFFAOYSA-N prehnitene Chemical compound CC1=CC=C(C)C(C)=C1C UOHMMEJUHBCKEE-UHFFFAOYSA-N 0.000 description 2
- 238000012552 review Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- BGHCVCJVXZWKCC-UHFFFAOYSA-N tetradecane Chemical compound CCCCCCCCCCCCCC BGHCVCJVXZWKCC-UHFFFAOYSA-N 0.000 description 2
- 150000003626 triacylglycerols Chemical class 0.000 description 2
- IIYFAKIEWZDVMP-UHFFFAOYSA-N tridecane Chemical compound CCCCCCCCCCCCC IIYFAKIEWZDVMP-UHFFFAOYSA-N 0.000 description 2
- UFTFJSFQGQCHQW-UHFFFAOYSA-N triformin Chemical compound O=COCC(OC=O)COC=O UFTFJSFQGQCHQW-UHFFFAOYSA-N 0.000 description 2
- RSJKGSCJYJTIGS-UHFFFAOYSA-N undecane Chemical compound CCCCCCCCCCC RSJKGSCJYJTIGS-UHFFFAOYSA-N 0.000 description 2
- LVBXEMGDVWVTGY-SREVYHEPSA-N 2-octenal Chemical compound CCCCC\C=C/C=O LVBXEMGDVWVTGY-SREVYHEPSA-N 0.000 description 1
- 206010002383 Angina Pectoris Diseases 0.000 description 1
- 208000019838 Blood disease Diseases 0.000 description 1
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 208000017667 Chronic Disease Diseases 0.000 description 1
- 208000006545 Chronic Obstructive Pulmonary Disease Diseases 0.000 description 1
- 206010058467 Lung neoplasm malignant Diseases 0.000 description 1
- 208000001145 Metabolic Syndrome Diseases 0.000 description 1
- 201000000690 abdominal obesity-metabolic syndrome Diseases 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 206010003246 arthritis Diseases 0.000 description 1
- 208000006673 asthma Diseases 0.000 description 1
- 238000011953 bioanalysis Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 239000013256 coordination polymer Substances 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 125000000524 functional group Chemical group 0.000 description 1
- 208000014951 hematologic disease Diseases 0.000 description 1
- 208000018706 hematopoietic system disease Diseases 0.000 description 1
- 229930182851 human metabolite Natural products 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000002458 infectious effect Effects 0.000 description 1
- 238000009533 lab test Methods 0.000 description 1
- 201000005202 lung cancer Diseases 0.000 description 1
- 208000020816 lung neoplasm Diseases 0.000 description 1
- 238000004949 mass spectrometry Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010197 meta-analysis Methods 0.000 description 1
- 208000030159 metabolic disease Diseases 0.000 description 1
- 230000002503 metabolic effect Effects 0.000 description 1
- 244000005700 microbiome Species 0.000 description 1
- CCCMONHAUSKTEQ-UHFFFAOYSA-N octadecene Natural products CCCCCCCCCCCCCCCCC=C CCCMONHAUSKTEQ-UHFFFAOYSA-N 0.000 description 1
- 108010071584 oxidized low density lipoprotein Proteins 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 238000004393 prognosis Methods 0.000 description 1
- 230000005180 public health Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- LVBXEMGDVWVTGY-UHFFFAOYSA-N trans-2-octenal Natural products CCCCCC=CC=O LVBXEMGDVWVTGY-UHFFFAOYSA-N 0.000 description 1
- 238000007492 two-way ANOVA Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/62—Detectors specially adapted therefor
- G01N30/72—Mass spectrometers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N2030/022—Column chromatography characterised by the kind of separation mechanism
- G01N2030/025—Gas chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
- G01N2030/062—Preparation extracting sample from raw material
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention belongs to the technical field of biomedicine, and particularly relates to a marker composition for assisting in predicting or diagnosing children with obesity-combined hyperlipidemia, wherein the marker composition comprises saturated alkanes, aromatic hydrocarbons and unsaturated aldehyde ketone substances, and is used for detecting a sample through gas chromatography-mass spectrometry, and the sample is an expired gas volatile metabolite. The marker composition containing the saturated alkane, the aromatic hydrocarbon and the unsaturated aldehyde ketone substances is used for assisting in predicting or diagnosing the children with obesity and hyperlipidemia for the first time, and the marker composition is detected by gas chromatography-mass spectrometry on the volatile metabolites of exhaled breath, so that the method has the advantages of simple detection method, high detection flux, high sensitivity, high specificity and the like, and has important scientific research and clinical application values.
Description
Technical Field
The invention belongs to the technical field of biological medicines, and particularly relates to a marker composition for assisting in predicting or diagnosing children with obesity and hyperlipidemia.
Background
Obesity has become an increasingly global public health problem over the past few decades. Obesity is associated with hypertension, angina pectoris, hypertension, diabetes and arthritis, and also causes a variety of other diseases. The increasing prevalence of childhood and adolescent obesity presents an increasing problem, as a large proportion of overweight children tend to become obese adults. Obesity, especially dyslipidemia from early years, can significantly increase cardiovascular risk in later years. That is, obesity in juvenile life is closely related to the occurrence of various cardiovascular and metabolic diseases after adulthood, so that accurate classification of juvenile obesity may be of great significance for the prediction of future combined diseases.
Obese children with combined hyperlipidemia may have some differences in metabolic characteristics compared to other obese or overweight children. Previous studies have revealed that both Triglycerides (TG) and non-HDL-cholesterol are high in obese children with dyslipidemia (see, e.g., calcaterra V, de Giuseppe R, biino G, mantelli M, marchini S, bendotti G, mad. Sub.A, avanzini MA, montalbono C, cossellu G et al: relationship between circulating oxidized-LDL and metabolic syndrome in childrenn with ease of evaluation: the role of triglyceride in obesity. J. Pet Endocrinol Met8978 zft 8978 (12): 1257-1263). However, previous studies have also shown that obese children may not always be complicated by dyslipidemia, and vice versa. This different dyslipidemia or obesity phenotype may contain different internal mechanisms and future risks. Therefore, developing a method to differentiate between types of obesity with or without dyslipidemia would be beneficial for the understanding and treatment of certain complications. However, the conventional method including the laboratory test has a limitation in diagnostic efficiency. It follows that innovative methods for non-invasive detection of breath-volatizable metabolites may offer opportunities for intensive research.
Human exhaled breath provides several benefits for diagnostic applications in children, including ease of access and non-invasive collection. Exhaled breath is a rich source of clinically relevant biological information. The evaluation of volatile organic compounds for the diagnosis or prognosis of diseases is an area of ongoing research. Several investigators have demonstrated that Breath testing can significantly improve the early detection of lung cancer or non-infectious chronic diseases (see, e.g., issitt T, wiggins L, veysey M, sweeney ST, brackenbury WJ, redeker K: volatile compounds in human Breath: clinical review and meta-analysis. J Breath Res 2022,16 (2)). Previous studies have found that a group of volatile metabolites, such as ethylbenzene, 2-octenal or octadecene, can be used to distinguish asthmatic children from healthy children (see, e.g., gahleittner F, guar-hoya C, beardsmore CS, pandya HC, thomas CP: microorganisms pillow to identify volatile organic compounds markers of childhood ash in exposed branched biology 3242. Bioanalysis 2013,5 (18): 2239-2247). In addition, volatile organic compounds (e.g. nitric oxide concentrates) exhaled by chronic obstructive pulmonary disease patients have the ability to distinguish between unstable patients and stable patients. Thus, in principle, it is entirely possible to provide clues to the classification of obesity or the prediction of risk in children by the evaluation of exhaled volatile metabolites or their relative concentrations.
Disclosure of Invention
In order to solve the technical problems, the inventor adopts a gas chromatography-mass spectrometry method to respectively investigate the difference situation of various volatile metabolites in children with obesity and hyperlipidemia, overweight blood disease, overweight blood lipid abnormality and obesity blood lipid, and discovers that the content of saturated alkane, aromatic hydrocarbon and unsaturated aldehyde ketone substances in different children is remarkably different for the first time, thereby providing a new auxiliary prediction and diagnosis method for children with obesity and hyperlipidemia, and laying a foundation for further clarifying the pathological mechanism of the diseases.
Specifically, the invention is realized by the following technical schemes:
the invention provides a marker composition for assisting in predicting or diagnosing children with obesity and hyperlipidemia, which comprises saturated alkanes, aromatic hydrocarbons and unsaturated aldehyde ketones.
Alternatively, in the marker composition described above, the marker composition comprises heptadecane, naphthalene, and cis-6-nonenol.
Alternatively, in the above marker composition, the marker composition consists of heptadecane, naphthalene, and cis-6-nonenol.
Alternatively, in the above marker composition, the marker composition is used for detecting a sample by gas chromatography-mass spectrometry.
Alternatively, in the marker composition described above, the sample is an exhaled breath volatizable metabolite.
Alternatively, in the marker composition described above, the child is in the age range of 9-11 years.
Alternatively, in the above marker composition, the detection method for aiding in the prediction or diagnosis of obesity-complicated hyperlipidemia children comprises the steps of:
step 1: collecting the exhaled air;
and 2, step: solid-phase extraction of metabolites;
and step 3: detecting a metabolite; and
and 4, step 4: and (4) analyzing mass spectrum data.
Alternatively, in the marker composition, the step 1 specifically includes the following steps: before breakfast in the morning, the expired air of the tested child is collected, the tested child is ordered to deeply inhale, then the expired air is slowly inhaled into the air bag, the expired air is collected by using the disposable Teflon gas sampling bag until the air bag is full, the one-way valve is closed, and the air bag needs to be subsequently detected within 6 hours.
Alternatively, in the marker composition, the step 2 specifically includes the following steps: and (3) removing a blowing nozzle of the exhaled air bag collected in the step (1), screwing a sampling cap, carrying out solid-phase extraction on metabolites in the exhaled air, inserting an extraction needle in a solid-phase microextraction assembly into the air bag, extending out the extraction needle, and placing in an incubator at 37 ℃ for incubation for 30 minutes.
Alternatively, in the marker composition, the step 3 specifically includes the following steps: the extraction needle is retracted, taken out of the air bag, immediately inserted into a Gas Chromatography (GC) sampling hole, and after 30 seconds of release, the collection is started, wherein the GC temperature gradient is as follows: 40 ℃ for 1 minute, from 40 ℃ to 180 ℃,5 ℃/minute, 180 ℃ for 2 minutes, total 31 minutes; the mass spectrum detection source temperature is 250 ℃, the ion source temperature is 200 ℃, the scanning range of the mass-to-nuclear ratio (m/z) is 30-550, the scanning speed is 2.8 times of scanning/second, and the ionization energy is 70eV.
Alternatively, in the marker composition, the step 4 specifically includes the following steps: performing post-processing on mass spectrum data by using TraceFinder 5.0 software (Thermo), performing deconvolution analysis, subtracting an air blank background, performing peak alignment comparison on a sample, and if the abundance of saturated alkane, aromatic hydrocarbon and unsaturated aldehyde ketone substances in the sample is remarkably high, determining that the child is high in possibility of being obese and combined with hyperlipidemia.
Preferably, as an alternative, in the above marker composition, the detection method for aiding in the prediction or diagnosis of obesity-complicated hyperlipidemia children comprises the steps of:
step 1: collecting exhaled air: before breakfast in the morning, collecting expired air of a tested child, ordering the tested child to deeply inhale, slowly inhaling the air bag, collecting the expired air by using a disposable Teflon gas sampling bag (2L), closing a one-way valve until the air bag is full, and carrying out subsequent detection on the air bag within 6 hours;
step 2: solid-phase extraction of metabolites: removing a blowing nozzle of the exhaled air bag collected in the step 1, screwing a sampling cap, performing solid phase extraction on metabolites in the exhaled air, inserting an extraction needle (50/30 mu m DVB/CARBOXEN/PDMS) in a Solid Phase Microextraction (SPME) component into the air bag, extending out the extraction needle, and placing in an incubator at 37 ℃ for incubation for 30 minutes.
And step 3: and (3) metabolite detection: the extraction needle was retracted, removed from the air pocket, immediately inserted into a Gas Chromatography (GC) access port (200 ℃) and 30 seconds after release the collection commenced with a GC temperature gradient: 40 ℃ for 1 minute, from 40 ℃ to 180 ℃,5 ℃/minute, 180 ℃ for 2 minutes, for a total of 31 minutes; the mass spectrum detection source temperature is 250 ℃, the ion source temperature is 200 ℃, the scanning range of the mass-to-nuclear ratio (m/z) is 30-550, the scanning speed is 2.8 times of scanning/second, and the ionization energy is 70eV; and
and 4, step 4: mass spectrometry data analysis: mass spectral data were post-processed using TraceFinder 5.0 software (Thermo), deconvoluted, the air blank background was subtracted, samples were compared for peak alignment, and children were considered to be more likely to be obese combined with hyperlipidemia if the abundance of saturated alkanes, aromatics and unsaturated aldehydes and ketones in the samples was significantly higher compared to the historical average abundance of obese but uncomplexed hyperlipidemic children or overweight children.
Compared with the prior art, the invention has the following beneficial effects:
the marker composition containing saturated alkane, aromatic hydrocarbon and unsaturated aldehyde ketone substances (especially heptadecane, naphthalene and cis-6-nonenol) is firstly used for assisting in predicting or diagnosing children with obesity and hyperlipidemia, and the marker composition is detected by gas chromatography-mass spectrometry on volatile metabolites of exhaled breath.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1: and (4) analyzing the main component of the exhaled volatile metabolites.
FIG. 2: statistical analysis of volatile metabolites of expired gas from saturated alkanes.
FIG. 3: statistical analysis of volatile metabolites of exhaled aromatic hydrocarbons.
FIG. 4: statistical analysis of volatile metabolites of aldehyde ketone exhaled breath.
FIG. 5: representative profiles of exhaled breath volatile metabolites with significant differences between the obesity-associated dyslipidemia group samples and the other group samples.
Detailed Description
The invention is further illustrated with reference to specific examples. It should be understood that the specific embodiments described herein are illustrative only and are not limiting upon the scope of the invention.
The examples do not specify particular techniques or conditions, and are to be construed in accordance with the description of the art in the literature or with the specification of the product. The reagents or instruments used are conventional products which are not known to manufacturers and are available from normal sources.
The experimental procedures in the following examples are conventional unless otherwise specified. The test materials used in the following examples are all commercially available products unless otherwise specified.
The embodiment is as follows:
1. collecting exhaled air
Before breakfast in the morning, a child subject is enabled to carry out the detection, the subject is ordered to inhale deeply, then the air bag is slowly inhaled, a disposable Teflon gas sampling bag (2L) is used for collecting exhaled air, and the one-way valve is closed until the air bag is full; the air bag is subjected to subsequent detection within 6 hours; the study collected the exhaled breath of 25 overweight (10 of these) and 57 obese (17 of these) children.
The study was designed and conducted according to the declaration of helsinki and was approved by the institutional review board of third hospital, beijing university (LM 2021316). Written informed consent has been obtained from participants and their parents.
Diagnostic criteria for overweight and obesity: after correcting age and sex, overweight means BMI more than or equal to 85 percent, and obesity means BMI more than or equal to 95 percent.
Confirmation criteria for dyslipidemia: (1) HDL-cholesterol <1.03mmol/L (40 mg/dl); (2) non-HDL-cholesterol is more than or equal to 3.76mmol/L (145 mg/dl); (3) triglyceride is more than or equal to 1.47mmol/L (130 mg/dl).
2. Solid phase extraction of metabolites
Removing the blowing nozzle of the air bag, screwing a sampling cap, performing solid phase extraction on metabolites in the exhaled breath, inserting an extraction needle (50/30 mu mDVB/CARBOXEN/PDMS) in a Solid Phase Microextraction (SPME) component into the air bag, extending out the extraction needle, and placing in an incubator at 37 ℃ for incubation for 30 minutes.
3. Metabolite detection
The extraction needle was retracted, removed from the air pocket, immediately inserted into a Gas Chromatography (GC) access port (200 ℃) and 30 seconds after release the collection commenced with a GC temperature gradient: 40 ℃ for 1 minute, from 40 ℃ to 180 ℃,5 ℃/minute, 180 ℃ for 2 minutes, for a total of 31 minutes; the mass spectrum detection source temperature is 250 ℃, the ion source temperature is 200 ℃, the scanning range mass-to-nuclear ratio (m/z) is 30-550, the scanning speed is 2.8 times of scanning/s, and the ionization energy is 70eV.
4. Mass spectrometric data analysis
Post-processing mass spectrum data by using TraceFinder 5.0 software (Thermo), performing deconvolution analysis, deducting air blank background, performing peak alignment comparison on samples, and finding 138 Volatile Organic Compounds (VOC) in total; comparing the substances with a Human Metabolite Database (HMDB), and confirming that 56 metabolites belong to the human body; on the basis, the obtained product is compared with a mass spectrum compound database, and 13 metabolites with the score higher than 80 are taken for differential analysis.
5. Results of the study
Performing principal component analysis on the determined VOC, observing the capability of the VOC for distinguishing obese children with hyperlipidemia from other obese or overweight children, and finding that the VOC has better distinguishing effect after further classification, including saturated alkanes, aromatic hydrocarbons and unsaturated aldehydes and ketones (figure 1); further, 13 VOCs were analyzed individually, their relative abundances were compared differently between different groups, and statistical analysis of data was performed using GraphPad Prism 8, and differences between different modules of each compound were analyzed using two-way ANOVA, and as a result, 6 saturated alkanes (heptadecane, undecane, dodecane, tridecane, tetradecane, and pentadecane), 4 aromatic hydrocarbons (naphthalene, methylnaphthalene, 1,2,3,4-tetramethylbenzene, and phenol), and 3 unsaturated aldones (cis-6-nonel, octenal, and D-limonene) were found to be more abundant in the obese combined dyslipidemia group than the overweight normoglycemia group, the overweight dyslipidemia group, and the obese normoglycemia group, in which heptadecane, naphthalene, and cis-6-nonel were significant (fig. 2-5).
6. Conclusion of the study
The research separates a group of volatile organic compounds from three chemical functional groups, namely saturated alkane, aromatic hydrocarbon and unsaturated aldehyde ketone substances in obese children with dyslipidemia. Furthermore, heptadecane, naphthalene and cis-6-nonenol belonging to the three compounds are further found to be remarkably increased in obese children suffering from dyslipidemia, so that a novel auxiliary prediction and diagnosis method is provided for children suffering from obesity and hyperlipidemia, and a foundation is laid for further clarifying the pathological mechanism of the diseases.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A marker composition for aiding in the prediction or diagnosis of obesity-complicated hyperlipidemia in children, comprising: the marker compositions comprise saturated alkanes, aromatic hydrocarbons, and unsaturated aldehydes and ketones.
2. Marker composition according to claim 1, characterized in that: the marker composition comprises heptadecane, naphthalene, and cis-6-nonenol.
3. Marker composition according to claim 1, characterized in that: the marker composition consists of heptadecane, naphthalene and cis-6-nonenol.
4. Marker composition according to any one of claims 1 to 3, characterized in that: the marker compositions are useful for detecting a sample by gas chromatography-mass spectrometry.
5. Marker composition according to claim 4, characterized in that: the sample is an exhaled breath volatile metabolite.
6. Marker composition according to any one of claims 1 to 5, characterized in that: the detection method for assisting in predicting or diagnosing children with obesity and hyperlipidemia comprises the following steps:
step 1: collecting the exhaled air;
step 2: solid-phase extraction of metabolites;
and step 3: detecting a metabolite; and
and 4, step 4: and (4) analyzing mass spectrum data.
7. Marker composition according to claim 6, characterized in that: the step 1 specifically comprises the following steps: before breakfast in the morning, the expired air of the tested child is collected, the tested child is ordered to deeply inhale, then the expired air is slowly inhaled into the air bag, the expired air is collected by using the disposable Teflon gas sampling bag until the air bag is full, the one-way valve is closed, and the air bag needs to be subsequently detected within 6 hours.
8. Marker composition according to claim 6, characterized in that: the step 2 specifically comprises the following steps: and (3) removing a blowing nozzle of the exhaled air bag collected in the step (1), screwing a sampling cap, carrying out solid-phase extraction on metabolites in the exhaled air, inserting an extraction needle in a solid-phase microextraction assembly into the air bag, extending out the extraction needle, and placing in an incubator at 37 ℃ for incubation for 30 minutes.
9. Marker composition according to claim 6, characterized in that: the step 3 specifically comprises the following steps: the extraction needle was retracted, removed from the air pocket, immediately inserted into a Gas Chromatography (GC) inlet, and collection commenced 30 seconds after release, with a GC temperature gradient: 40 ℃ for 1 minute, from 40 ℃ to 180 ℃,5 ℃/minute, 180 ℃ for 2 minutes, total 31 minutes; the mass spectrum detection source temperature is 250 ℃, the ion source temperature is 200 ℃, the scanning range mass-to-nuclear ratio (m/z) is 30-550, the scanning speed is 2.8 times of scanning/second, and the ionization energy is 70eV.
10. Marker composition according to claim 6, characterized in that: the step 4 specifically comprises the following steps: post-processing mass spectrum data using TraceFinder 5.0 software, performing deconvolution analysis, subtracting an air blank background, performing peak alignment comparison on samples, and considering that children are more likely to be obese and have combined hyperlipidemia if the abundance of saturated alkanes, aromatic hydrocarbons and unsaturated aldehydes and ketones in the samples is significantly higher than the historical average abundance of obese but uncomplexed hyperlipidemia children or overweight children.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210962076.7A CN115326958B (en) | 2022-08-11 | 2022-08-11 | Marker composition for assisting in predicting or diagnosing obesity-associated hyperlipidemia children |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210962076.7A CN115326958B (en) | 2022-08-11 | 2022-08-11 | Marker composition for assisting in predicting or diagnosing obesity-associated hyperlipidemia children |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115326958A true CN115326958A (en) | 2022-11-11 |
| CN115326958B CN115326958B (en) | 2023-11-24 |
Family
ID=83921644
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210962076.7A Active CN115326958B (en) | 2022-08-11 | 2022-08-11 | Marker composition for assisting in predicting or diagnosing obesity-associated hyperlipidemia children |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115326958B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015183985A2 (en) * | 2014-05-28 | 2015-12-03 | Stealth Peptides International, Inc. | Therapeutic compositions including naphthoquinones and uses thereof |
| CN106011303A (en) * | 2016-08-08 | 2016-10-12 | 南京市妇幼保健院 | Childhood obesity-related serum or plasma miRNA markers and use thereof |
| CN108362754A (en) * | 2018-01-19 | 2018-08-03 | 北京大学 | Biomarker on-line detecting system and method in a kind of expiratory air |
| US20190264262A1 (en) * | 2016-07-25 | 2019-08-29 | Kobiolabs, Inc. | Composition for diagnosing or predicting risk of metabolic syndrome or metabolic syndrome-related diseases using human oral microbiome |
| CN113164446A (en) * | 2018-10-15 | 2021-07-23 | Ck生物技术股份有限公司 | Compositions and methods for inhibiting and/or treating metabolic disorders and/or clinical conditions thereof |
| US20210227864A1 (en) * | 2018-06-04 | 2021-07-29 | Takasago International Corporation | Fragrance and flavor materials |
-
2022
- 2022-08-11 CN CN202210962076.7A patent/CN115326958B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015183985A2 (en) * | 2014-05-28 | 2015-12-03 | Stealth Peptides International, Inc. | Therapeutic compositions including naphthoquinones and uses thereof |
| US20190264262A1 (en) * | 2016-07-25 | 2019-08-29 | Kobiolabs, Inc. | Composition for diagnosing or predicting risk of metabolic syndrome or metabolic syndrome-related diseases using human oral microbiome |
| CN106011303A (en) * | 2016-08-08 | 2016-10-12 | 南京市妇幼保健院 | Childhood obesity-related serum or plasma miRNA markers and use thereof |
| CN108362754A (en) * | 2018-01-19 | 2018-08-03 | 北京大学 | Biomarker on-line detecting system and method in a kind of expiratory air |
| US20210227864A1 (en) * | 2018-06-04 | 2021-07-29 | Takasago International Corporation | Fragrance and flavor materials |
| CN113164446A (en) * | 2018-10-15 | 2021-07-23 | Ck生物技术股份有限公司 | Compositions and methods for inhibiting and/or treating metabolic disorders and/or clinical conditions thereof |
Non-Patent Citations (3)
| Title |
|---|
| ANTHONY L. ROBINSON等: "Development of a sensitive non-targeted method for characterizing the wine volatile profile using headspace solid-phase microextraction comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry", JOURNAL OF CHROMATOGRAPHY A, vol. 1218, pages 3 * |
| LIU MIAO等: "Circulating miR‑3659 may be a potential biomarker of dyslipidemia in patients with obesity", JOURNAL OF TRANSLATIONAL MEDICINE, pages 1 - 10 * |
| 于慧子 等: "中华绒螯蟹蟹肉和蟹黄中挥发性风味物质组成", 食品科学, vol. 32, no. 8, pages 1 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115326958B (en) | 2023-11-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Chen et al. | Metabolome analysis for investigating host-gut microbiota interactions | |
| CN105209909B (en) | Biomarker relevant to renal function and its application method | |
| CA3030255C (en) | Methods and systems for determining autism spectrum disorder risk | |
| US20240230622A9 (en) | Methods and Systems for Determining Autism Spectrum Disorder Risk | |
| CN111289736A (en) | Slow obstructive pulmonary early diagnosis marker based on metabonomics and application thereof | |
| CN104777242B (en) | Associating mark, test kit and system for diagnosis of polycystic ovary syndrome | |
| JP7018605B2 (en) | Colorectal cancer test method | |
| CN111983083B (en) | Application of metabolite marker detection in preparation of multiple myeloma diagnosis tool | |
| CN112630311A (en) | Metabolic markers and kits for detecting affective disorders and methods of use | |
| CN113008972A (en) | Serum metabolic marker for gestational diabetes diagnosis and application thereof | |
| CN106716127A (en) | Methods for detecting ovarian cancer | |
| JP5636567B2 (en) | Biomarker for diagnosing fatty liver disease, measuring method thereof, computer program, and storage medium | |
| CN110749732B (en) | Blood metabolite marker for diagnosing multiple myeloma and application thereof | |
| WO2018117064A1 (en) | Method for testing for disease presenting depressive state | |
| Liu et al. | An integrating strategy for serum metabolomics and microarray analysis to expand the understanding of diet-induced obesity | |
| CN115326958A (en) | Marker composition for assisting in predicting or diagnosing children with obesity and hyperlipidemia | |
| CN114026427A (en) | Marker for diagnosing renal disease and diagnostic method | |
| WO2022255774A1 (en) | Biomarker composition containing acyl carnitine metabolite for diagnosis of oral cancer | |
| CN114758719B (en) | Colorectal cancer prediction system and application thereof | |
| Poujois et al. | Biochemical markers | |
| CN114755422A (en) | Biomarker for colorectal cancer detection and application thereof | |
| Yang et al. | Quantitation of sibutramine in human hair using gas chromatography–isotope dilution tandem mass spectrometry | |
| CN115616227B (en) | Use of indole-3-acryloylglycine detection reagent, and kit and system for diagnosis or auxiliary diagnosis of chronic obstructive disease | |
| CN111830169B (en) | Compound for diagnosing polycystic ovarian syndrome and application thereof | |
| TW202024636A (en) | Method for detecting non-alcoholic fatty liver disease, kit for detecting non-alcoholic fatty liver disease, and biomarker for use in detection of non-alcoholic fatty liver disease |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |