CN110178035A - Diabetes B marker and application thereof - Google Patents
Diabetes B marker and application thereof Download PDFInfo
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- G01N33/483—Physical analysis of biological material
- G01N33/487—Physical analysis of biological material of liquid biological material
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- 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
- G01N33/64—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving ketones
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- 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
- G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
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Abstract
One group of diabetes B marker, the diabetes B marker includes selected from least one of following: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24 : 1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.
Description
Priority information
Nothing
The present invention relates to field of biological detection, specifically, the present invention relates to diabetes B markers and application thereof, more specifically, the present invention relates to the purposes of diabetes B marker, the method for diagnosed type 2 diabetic, the system of diagnosed type 2 diabetic, kit and reagent in reagent preparation box, the kit is used for diagnosed type 2 diabetic marker.
Diabetes B (Type 2diabetes, T2D), is a kind of most common diabetes, accounts for about the 90% of diabetes sum.Diabetes B is the progressive metabolic disorder complex disease using hyperglycemia as main feature, especially shows glucose and disorders of lipid metabolism.Pathological characteristics are mainly shown as that insulin resistance causes insulin is opposite to reduce with islet beta cell function defect.The national epidemiological study of nearest two shows that China has become the most country of diabetic in the world.Data show, the illness rates of total diabetes of Chinese adult rises to 11.6% (American Diabetes Association (ADA) standard in 2010) in 2010 from 9.7% (World Health Organization (WHO) standard in 1999) in 2007.In addition, according to both different screening criterias, prediabetes adult ratio rises to 50.1% from 15.5%.
Mainly pass through Vein blood serum level for the diagnosis of diabetes at present to detect.Currently used diagnostic criteria is WHO (1999) standard and ADA (2003) standard.WHO standard mainly passes through fasting blood-glucose (Fastplasma glucose,) and 2 hours postprandial blood sugar (2-hour postprandial glucose FPG, 2h-PG, glycometabolism is divided into euglycemia, impaired fasting glucose (impaired fasting glucose, IFG), Impaired Glucose Tolerance Treated (impaired glucose tolerance, IGT) and diabetes.Impaired fasting glucose and Impaired Glucose Tolerance Treated are referred to as prediabetes (Prediabetes, Pre-DM).ADA standard in 2010 is by glycosylated hemoglobin (hemoglobin A1c, HbA1c) as one of diabetes diagnostic criterion.Existing diagnostic criteria cannot accomplish early warning just for established condition, cannot predict the trend of diabetes B morbidity and development；In addition disease pathology parting can be helped by developing the new diagnostic method of one kind, help Precise Diagnosis disease type, provide thinking for drug target research, accurate medication, pathogenetic research etc..
Therefore, the new diagnostic method of one kind is developed to assess, diagnosis, early diagnose, pathological staging for risk,
It is of great significance.
Summary of the invention
The application is to be made based on inventor to the discovery of following facts and problem and understanding:
The disadvantages of cannot accomplishing early warning for existing diabetes B diagnostic method, cannot predicting diabetes B morbidity and the trend of development, the present invention provides the biomarker combinations (i.e. biological marker composition) that can be used in diabetes B diagnosis and risk assessment, and the diagnosis and risk appraisal procedure of diabetes B, the trend that can predict diabetes B morbidity and development, is applied to disease pathology parting.
In the first aspect of the present invention, the invention proposes one group of diabetes B markers.Embodiment according to the present invention, the diabetes B marker includes selected from least one of following: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24 : 1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.Body lipid molecular is the basis of vital movement, the variation that the state of disease and the variation of body function will necessarily cause endogenous small molecule to be metabolized in vivo.For inventor by the comparison and analysis to diabetes B group and non-diabetic group lipid-metabolism object spectrum, finding the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group, there are apparent differences, and screen and obtain above-mentioned relevant biomarker.The lipid-metabolism object modal data of diabetes B marker combination diabetes B crowd and non-diabetic people biomarker accurately can carry out risk assessment and early diagnosis to diabetes B as training set.
According to an embodiment of the invention, above-mentioned diabetes B marker can further include at least one following additional technical feature:
According to an embodiment of the invention, the diabetes B marker further comprises at least one of the compound with following table parameter:
The parameter is obtained in the mass spectral analysis with the following conditions:
ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
In the second aspect of the present invention, the invention proposes a kind of methods of diagnosed type 2 diabetic.According to an embodiment of the invention, the described method includes: (1) determines the relative amount of above-mentioned marker in the sample of object to be diagnosed；(2) based on the obtained marker content in step (1), the diagnostic result of the object is determined.This method has the characteristics that noninvasive, convenient, fast, and high sensitivity, specificity are good compared with currently used diagnostic method.
In the third aspect of the present invention, the invention proposes a kind of systems for diagnosing 2- patients with type Ⅰ DM.According to an embodiment of the invention, include: measurement device, the relative amount of marker described in claim 1 in sample of the measurement device for determining object to be diagnosed；Determining device, the determining device are used for the relative amount based on the marker obtained in the measurement device, determine the diagnostic result of the object.The lipid-metabolism object modal data of diabetes B marker combination diabetes B crowd and non-diabetic people biomarker accurately can carry out risk assessment and early diagnosis to diabetes B as training set.The system has the characteristics that noninvasive, convenient, fast, and high sensitivity, specificity are good.
In the fourth aspect of the present invention, the invention proposes a kind of kits.Embodiment according to the present invention, the kit includes reagent, the reagent includes selected from least one of following for detecting: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), L YsoPC (24:1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.As previously described, inventor passes through the comparison and analysis to diabetes B group and non-diabetic group lipid-metabolism object spectrum, it was found that the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group, there are apparent difference, there are apparent differences in the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group for above-mentioned associated biomarkers.Risk assessment, the early diagnosis that diabetes B can accurately be carried out to detection individual using kit according to an embodiment of the present invention, have the characteristics that noninvasive, convenient, fast, and kit high sensitivity, specific good.
In the fifth aspect of the invention, the invention proposes purposes of the reagent in reagent preparation box, the kit is used for diagnosed type 2 diabetic marker, and the reagent includes selected from least one of following for detecting: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2),
PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24:1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.As previously mentioned, inventor is by the comparison and analysis to diabetes B group and non-diabetic group metabolite profile, finding above-mentioned associated biomarkers, there are apparent differences in the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group.Risk assessment and early diagnosis accurately can be carried out to diabetes B using kit prepared by mentioned reagent, have the characteristics that noninvasive, convenient, fast, and kit high sensitivity, it is specific good.
Above-mentioned and/or additional aspect of the invention and advantage will be apparent and are readily appreciated that from the description of the embodiment in conjunction with the following figures, in which:
Fig. 1 is the system of diagnosed type 2 diabetic according to an embodiment of the present invention；
Fig. 2 is the system of diagnosed type 2 diabetic according to an embodiment of the present invention；
Fig. 3 is the structural schematic diagram of measurement device according to an embodiment of the present invention；
The Wei Entu that the significant metabolin that Fig. 4 is compared between showing utilization sugar tolerance normal group of (NGT), prediabetes group (Pre-DM), diabetes B group (T2D) two-by-two is drawn.The number for the significant metabolin that 3 groups compare two-by-two is described in figure, and shows their intersection (inspection of p < 0.05, Dunn ' s postposition)；
Fig. 5 shows the error rate distribution situation of 5 10 folding cross validations in random forest grader.Whole metabolin relative ion intensity that model training set sample (NGT=70, T2D=70) detects under zwitterion acquisition mode are trained.Solid black curve represents the average value of 5 tests (imaginary curve).Grey vertical line represents metabolin number in selected optimal combination；
Fig. 6, which is shown, differentiates T2D and NGT, the recipient's operating curve (ROC) and area under the curve (AUC) of training set based on Random Forest model (28 metabolite markers)；
Fig. 7 to Fig. 9 is shown based on Random Forest model (28 metabolite markers), verify the ROC and AUC of collection, Fig. 7 is NGT and T2D (n=21 and 36), Fig. 8 is Pre-DM and T2D (n=76 and 36), Fig. 9 are NGT and Pre-DM (n=21 and 76)；
Figure 10 is shown based on Random Forest model (28 metabolite markers), predicts prediabetes (Pre-DM) 3 sub- groupings, i.e. HbA1c5.7-6.4%Increment type, pure IGT and mating type IFG/IGT develop into the probability of illness of T2D；
Figure 11 shows the LC-MS/MS spectrogram of biomarker m/z 248.1511 and the chemical structure of supposition；
Figure 12 shows the appearance time and LC-MS/MS spectrogram of biomarker m/z 508.3406 (RT=1.83min) and standard items LysoPC (18:0)；
Figure 13 shows the LC-MS/MS spectrogram of biomarker m/z 506.3249 and the chemical structure of supposition；
Figure 14 shows the LC-MS/MS spectrogram of biomarker m/z 504.3093 and the chemical structure of supposition；
Figure 15 shows 4 metabolite markers (from Random Forest model) and differentiates T2D and NGT, recipient's operating curve (ROC) and area under the curve (AUC)；And
Figure 16 shows 4 metabolite markers (from Random Forest model) and differentiates T2D and non-T2D, recipient's operating curve (ROC) and area under the curve (AUC).
Detailed description of the Invention
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, and in which the same or similar labels are throughly indicated same or similar element or elements with the same or similar functions.The embodiments described below with reference to the accompanying drawings are exemplary, for explaining only the invention, and is not considered as limiting the invention.
It should be noted that term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance or implicitly indicate the quantity of indicated technical characteristic." first " is defined as a result, the feature of " second " can explicitly or implicitly include one or more of the features.Further, in the description of the present invention, unless otherwise indicated, the meaning of " plurality " is two or more.
Diabetes B marker
In the first aspect of the present invention, the invention proposes one group of diabetes B markers.Embodiment according to the present invention, the diabetes B marker includes selected from least one of following: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24 : 1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.Body lipid molecular is the basis of vital movement, the variation that the state of disease and the variation of body function will necessarily cause endogenous small molecule to be metabolized in vivo.For inventor by the comparison and analysis to diabetes B group and non-diabetic group lipid-metabolism object spectrum, finding the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group, there are apparent differences, and screen and obtain above-mentioned relevant biomarker.The lipid-metabolism object modal data of diabetes B marker combination diabetes B crowd and non-diabetic people biomarker accurately can carry out risk assessment and early diagnosis to diabetes B as training set.
According to a particular embodiment of the invention, the diabetes B marker further comprises at least one of the compound with following table parameter:
The parameter is obtained in the mass spectral analysis with the following conditions:
ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
Inventor is by the comparison and analysis to diabetes B group and non-diabetic group lipid-metabolism object spectrum, and finding the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group, there are apparent differences, and further screening obtains above-mentioned relevant biomarker.The lipid-metabolism object modal data of above-mentioned 28 kinds of diabetes Bs marker combination diabetes B crowd and non-diabetic people biomarker that inventor screens further accurately can carry out risk assessment and early diagnosis to diabetes B as training set.
The method of diagnosed type 2 diabetic
In the second aspect of the present invention, the invention proposes a kind of methods of diagnosed type 2 diabetic.According to an embodiment of the invention, the described method includes: (1) determines the relative amount (relative ion intensity) of above-mentioned marker in the sample of object to be diagnosed；(2) relative amount based on the obtained marker in step (1), determines the diagnostic result of the object.This method has the characteristics that noninvasive, convenient, fast, and high sensitivity, specificity are good compared with currently used diagnostic method.
According to a particular embodiment of the invention, relative amount based on the obtained marker in step (1), determine that the diagnostic result of the object is realized in the following way: the disease risks value of marker model is higher than predetermined threshold, is the instruction that the object suffers from 2- patients with type Ⅰ DM.According to a particular embodiment of the invention, the predetermined threshold is 0.5.Specific example according to the present invention calculates risk based on the model that 28 characteristic metabolic objects that random forest screens calculate jointly, and risk is higher than 0.5, that is, is determined as the instruction with diabetes B.Specifically, according to Random Forest model, the risk probability of Pre-DM group different pathological phase patient, the incremental trend of different pathological phase prediction probability, in HbA1c raised type are examined5.6-6.4%In minimum (median of probability of illness be 0.298), slightly elevated in pure IGT (iIGT) (median of probability of illness is 0.398), highest (median of probability of illness is 0.494), the RF in associativity IFG/IGT
Model can be used to react the molecule parting feature of different prediabetes pathological stages.
According to a particular embodiment of the invention, the sample includes at least one of blood, skin, hair, saliva and muscle.Specifically, the sample is blood plasma lipide extract.
According to a particular embodiment of the invention, in step (1), the content of the marker is determined by the method for liquid chromatography-mass spectrometry.
Specifically, the liquid-phase chromatographic analysis carries out under the following conditions:
Ultra Performance Liquid Chromatography instrument ACQUITY UPLC (Waters, Manchester, USA),
Chromatographic column: Waters CSH C18 column (100mm × 2.1mm, 1.7 μm)；
Mobile phase A: acetonitrile: H2O=60:40,0.1% formic acid, 10mM ammonium formate；
Mobile phase B: isopropanol: ACN=90:10,0.1% formic acid, 10mM ammonium formate；
Gradient elution program: 2min, 40%B linear gradient increase to 43%B；0.1min increases to 50%B；3.9min increases to 54%B；0.1min increases to 70%B；1.9min, gradient increase to 99%B；0.1min, is restored to 40%B, to chromatography column equilibration 1.9min before each sample introduction；
Flow velocity: 0.4mL/min；10 μ L of sampling volume.
Specifically, the mass spectral analysis carries out under the following conditions:
ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
The present invention uses analysis method associated with liquid chromatography mass, analyze the lipid-metabolism object spectrum of plasma sample, based on 28 metabolite markers, diabetes B group and non-diabetic group (including prediabetes and normal group of sugar tolerance) are differentiated with random forest discrimination model, obtain probability of illness, for risk assessment, diagnosis, the early diagnosis of diabetes B, potential drug target spot is found.
In the specific embodiment of the present invention, metabolite profile obtains initial data by processing, and the initial data is preferably the peak height or peak area and the data such as mass number and retention time at each peak.
In the specific embodiment of the present invention, blob detection and peak match are carried out to initial data, the blob detection and peak match are preferably carried out using Progenesis QI software.
Mass spectral analysis type is roughly divided into ion trap, level four bars, electrostatic field orbit ion trap, four class of flight time mass spectrum, and the mass deviation of these four types of analyzers is respectively 0.2amu, 0.4amu, 3ppm, 5ppm.The experimental result that the present invention obtains is flying time mass spectrum analysis, so being suitable for all using flight time mass spectrum as the mass spectrometer of mass analyzer, TQS, TQD etc. including Waters.
In embodiments of the invention, indicate that the opposite of biomarker contains with mass spectrographic peak area (peak intensity)
Amount.
In the present invention, the mass-to-charge ratio and retention time have meaning well known in the art.
Well known to those skilled in the art, when using different liquid chromatography mass combination equipment and different detection methods, the atomic mass unit of each biomarker and retention time can fluctuate in a certain range in biological marker composition of the invention；Wherein, the atomic mass unit can be fluctuated in ± 10ppm, such as in the range of ± 5ppm, such as ± 3ppm, and the retention time can be fluctuated in ± 60s, such as in the range of ± 45s, such as ± 30s, such as ± 15s.
In the present invention, the application method of Random Forest model and ROC curve (Drogan D, Dunn WB well known in the art, Lin W, Buijsse B, Schulze MB, Langenberg C, Brown M, Floegel a., Dietrich S, Rolandsson O, Wedge DC, Goodacre R, Forouhi NG, Sharp SJ, Spranger J, Wareham NJ, Boeing H:Untargeted Metabolic Profiling Identifies Altered Seru M Metabolites of Type 2Diabetes Mellitus in a Prospective, Nested Case Control Study.Clin Chem 2015,61:487-497.；Mihalik SJ, Michaliszyn SF, de las Heras J, Bacha F, Lee S, Chace DH, DeJesus VR, Vockley J, Arslanian SA:Metabolomic profiling of fatty acid and amino acid metabolism in youth with obesity and type 2diabetes:evidence for enhanced mitochondrial oxidation.Diabetes Care 2012,35:605-611. is incorporated to herein by reference of text), those skilled in the art can carry out parameter setting and adjustment as the case may be.
In the present invention, the training set and verifying collection have meaning well known in the art.In embodiments of the invention, the training set refers to the data acquisition system of the content of the diabetes B subject comprising certain sample number and each biomarker in non-diabetic subject's sample to be tested.The verifying collection is the independent data set for testing training set performance.
In the present invention, the training set of the biomarker of diabetes B subject and non-diabetic subject is constructed, and as benchmark, the biomarker content value of sample to be tested is assessed.
In the present invention, the data of the training set are as shown in table 1.
In the present invention, non-diabetic subject is sugar tolerance normal subjects and/or prediabetes subject.
In the present invention, the subject can be people.
In the present invention, the unit of mass-to-charge ratio is amu, and it is the unit for measuring atom or molecular mass that amu, which refers to atomic mass unit, also referred to as dalton (Dalton, Da, D), it is defined as the 1/12 of 12 atomic mass of carbon.Permission mass resolution (error) when the present invention identifies metabolin is 10ppm, ppm i.e. hundred a ten thousandths.For example, certain metabolin A isotope exact mass=118Da, quality=118.001Da of apparatus measures；Deviation=0.001amu；Error [deviation/exact mass × 106]=8.47ppm.
As known to those skilled in the art, when further expansion sample size, pattern detection well known in the art and calculation method are utilized, it can be deduced that the normal contents value section (absolute figure) of every kind of biomarker in the sample.In this way when using except mass spectrum
When other methods in addition detect the content of biomarker (such as utilizing antibody and ELISA method etc.), the absolute value for the biomarker content that can be will test is compared with normal contents value, optionally, it can be combined with statistical method, with risk evaluation, the diagnosis etc. for obtaining diabetes B.
It does not wish to be bound by any theory restrictions, inventor points out that these biomarkers are the endogenous compound being present in human body and/or food-borne compound.The method analyzes the metabolite profile of subject's blood plasma through the invention, preferably, the lipid-metabolism object of blood plasma is analyzed, the mass figures and retention time in metabolite profile indicate the presence of corresponding biomarker and the corresponding position in metabolite profile.Meanwhile the biomarker of diabetes B group shows certain content range value in its metabolite profile.
The system of diagnosed type 2 diabetic
In the third aspect of the present invention, the invention proposes a kind of systems for diagnosing 2- patients with type Ⅰ DM.According to an embodiment of the invention, with reference to Fig. 1, comprising: measurement device 100, content of the measurement device 100 for above-mentioned marker in the sample of determining object to be diagnosed；Determining device 200, the determining device 200 are used to determine the diagnostic result of the object based on the obtained marker content in the measurement device.The metabolite profile data of diabetes B marker combination diabetes B crowd and non-diabetic people biomarker accurately can carry out risk assessment, early diagnosis to diabetes B as training set.The system has the characteristics that noninvasive, convenient, fast, and high sensitivity, specificity are good.
According to a particular embodiment of the invention, the sample is blood plasma lipide extract.Specifically, with reference to Fig. 2, the system further comprises: extraction element 300, the extraction element 300 is connected with the measurement device 100, for extracting the blood plasma lipide of object to be diagnosed.
Still another embodiment according to the present invention, with reference to Fig. 3, the measurement device 100 includes liquid-phase chromatographic analysis unit 110 and mass spectrometry unit 120.
Kit
In the fourth aspect of the present invention, the invention proposes a kind of kits.Embodiment according to the present invention, the kit includes reagent, the reagent includes selected from least one of following for detecting: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), L YsoPC (24:1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.As previously described, inventor passes through the comparison and analysis to diabetes B group and non-diabetic group metabolite profile, it was found that the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group, there are apparent difference, there are apparent differences in the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group for above-mentioned associated biomarkers.Risk assessment and early diagnosis accurately can be carried out to diabetes B using kit according to an embodiment of the present invention, have the characteristics that noninvasive, convenient, fast, and kit high sensitivity, it is specific good.
Purposes of the reagent in reagent preparation box
In the fifth aspect of the invention, the invention proposes purposes of the reagent in reagent preparation box, the kit is used for diagnosed type 2 diabetic marker, the reagent includes selected from least one of following for detecting: LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38 : 2), LysoPC (18:1), PS (38:1), LysoPC (24:1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acid.As previously mentioned, inventor is by comparison and analysis to diabetes B group and non-diabetic group lipid-metabolism object spectrum, finding above-mentioned associated biomarkers, there are apparent differences in the blood plasma lipide metabolite profile of diabetes B group and non-diabetic group.Risk assessment, early diagnosis accurately can be carried out to diabetes B using kit prepared by mentioned reagent, have the characteristics that noninvasive, convenient, fast, and kit high sensitivity, it is specific good.
Embodiment of the present invention is described in detail below in conjunction with embodiment, it will be appreciated by those skilled in the art that the following example is merely to illustrate the present invention, and should not be taken as limiting the scope of the invention.The person that is not specified actual conditions in embodiment, carries out according to conventional conditions or manufacturer's recommended conditions.Reagents or instruments used without specified manufacturer, being can be with conventional products that are commercially available.
The plasma sample of diabetes B and non-diabetic subject of the invention comes from Suzhou City's disease prevention and control center.
Embodiment 1
1.1 sample collections: the empty stomach morning blood blood plasma of volunteer is collected, is immediately placed in -80 DEG C of low temperature refrigerators and stores.Sugar is resistant to normal group (NGT) and collects 98 parts of plasma samples altogether, and prediabetes group (Pre-DM) collects 81 parts of plasma samples altogether, and diabetes B group (T2D) collects 114 parts of plasma samples altogether.Wherein, Pre-DM group can further be divided into four subgroups: a) HbA1c increment type5.7-6.4%(WHO-2011 diagnostic criteria, HbA1c is between 5.7-6.4% and FPG < 6.1mmol/L and 2h-PG < 7.8mmol/L, n=15)；B) pure IFG (FPG is between 6.1-7.0mmol/L and 2h-PG < 7.8mmol/L, n=7)；C) pure IGT (abbreviation iIGT, FPG < 6.1mmol/L and 2h-PG is between 7.8~11.0mmol/L, n=35)；D) associativity IFG/IGT (FPG is between 6.1-7.0mmol/l and 2h-PG is between 7.8~11.0mmol/L, n=24).
1.2 lipids extractions: plasma sample is placed on ice to melt, and extracts lipid using isopropanol (IPA).In simple terms, 40 μ L blood plasma are taken to be extracted using the IPA that 120 μ L are pre-chilled, vortex 1min is incubated at room temperature 10min, and extraction mixture is then placed in -20 DEG C overnight.4000g is centrifuged 20min, supernatant is transferred in 96 new orifice plates, with IPA/ acetonitrile (ACN)
/ H2O (2:1:1, V:V:V) presses 1:10 dilution proportion, marks sample names and negative ions with marking pen, before liquid chromatograph-mass spectrometer analysis, is placed in -80 DEG C and saves backup.In addition, taking 10ul mixing as QC Quality Control sample in each sample to be detected.
1.3 liquid chromatography mass combination analysis
Instrument and equipment
Ultra Performance Liquid Chromatography instrument ACQUITY UPLC (Waters, Manchester, USA), mass spectrograph Waters XevoTMG2-XS Qtof (Waters, USA)
Chromatographic condition
Chromatographic column: Waters CSH C18 column (100mm × 2.1mm, 1.7 μm)；Mobile phase A: ACN (acetonitrile): H2O=60:40, v/v, 0.1% formic acid (FA), 10mM ammonium formate；Mobile phase B: IPA (isopropanol): ACN=90:10, v/v, 0.1%FA, 10mM ammonium formate.
Gradient elution program: 2min, 40%B linear gradient increase to 43%B；0.1min increases to 50%B；3.9min increases to 54%B；0.1min increases to 70%B；1.9min, gradient increase to 99%B；0.1min, is restored to 40%B, to chromatography column equilibration 1.9min before each sample introduction.Flow velocity: 0.4mL/min；10 μ L of sampling volume.
Mass Spectrometry Conditions
ESI ion source, positive/negative ion mode acquisition data ,-mass range m/z 50~2000, (s) per second/time.Ion source temperature is 120 DEG C, and desolvation (desolvation) temperature is 600 DEG C, and mobile phase gas is nitrogen, and throughput 800L/h, pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V.Using leucine enkephalin (molecular weight (MW)=555.62；200pg/ μ L, is dissolved in the ACN:H2O of 1:1) it is used as lock mass, it is calibrated using the sodium formate solution of 0.5mM.All samples are ordered randomly, and inject 10 QC samples first to adjust chromatographic column, 10 samples of every injection just inject 1-2 QC sample later, with the repeatability of survey data.
1.4 data processing
Liquid chromatography mass combination initial data is handled using 2.0 software of business software Progenesis QI (Newcastle UK Nonlinear Dynamics company), successively includes initial data input, the selection of adduct ion, peak is compared, detected, deconvoluting, low quality peak filters, the normalization relative quantification of noise data correction, peak identification and peak intensity.Make a concrete analysis of parameter are as follows: 1) select [M+H]+,[M+H-H2O]+,[M+Na]+[M+K]+Cation electrodeposition is from mode adduct；It selects [M-H]-It is anionic electrodeposition from mode adduct；2) quasi-molecular ions retention time is 0.5-9min；3) peak width is 1-30s；4) the parent ion mass number margin of error is 10ppm；5) the parent ion theory fragment ion mass number margin of error is
10ppm, by above-mentioned strict parameter, to improve the accuracy of metabolin identification.Identification peak intensity is normalized using MetaX software.It will be less than 50%QC sample or be considered as low quality peak lower than the peak occurred in 80% blood plasma detection sample, and remove；Above-mentioned missing values are filled in the sample using nearest neighboring rule.After above-mentioned analysis, common property goes out 12,000 high quality metabolin, wherein 923 are identified for ion mode, 11,077 are identified for cation mode.It detects the low quality outliers under zwitterion mode respectively using PCA (Principal components analysis) analysis, and removes, which removes 20 parts of outliers (including 7 NGT, 8 T2D and 5 Pre-DM) altogether.To quality data collection after above-mentioned multiple stringent filtering, using QC-RLSC (locally weighted regression smoothing method, quality control-based robust LOESS signal correction), correct difference caused by signal fluctuation between batch.After correction, the characteristic peak of relative standard deviation still > 30% is removed.Using Progenesis Metascope through HMDB 3.6 (http://www.hmdb.ca/), three database comparisons of LIPID MAPS (http://www.lipidmaps.org/) and LipidBlast (http://fiehnlab.ucdavis.edu/projects/LipidBlast) annotate metabolin, and the margin of error of parent ion mass number and theoretical fragment ion mass number is 10ppm.The metabolin of above-mentioned matching condition will be met according to the CSHC used by Waters company to this experiment18The operating guidance that UPLC system provides, the retention time characteristic based on different lipids are filtered above-mentioned matching result.Wherein, cation electrodeposition is under mode: 1) lysophospholipids retention time range is 0.5-4 minutes, including lysophosphatidyl choline (lysophosphatidylethanolamine, LysoPC)；Lysophosphatidyl ethanolamine (lysophosphatidylethanolamine, LysoPE)；Lysophosphatidyl glycerol (lysophosphatidylglycerol, LysoPG)；Hemolytic phosphatidylserine (lysophosphatidylserine, LysoPS)；Lysophosphatidic acid (lysophosphatidic acid, LysoPA) and lysophosphatidylinositol (lysophosphatidylinositol, LysoPI)；2) sphingomyelins is retention time 3-8.1 minutes, including sphingomyelin (sphingomyelin, SM), ceramide (ceramide, Cer), galactosylceramide (lactosylceramide, LacCer), glucose ceramide (glucosylceramide, GluCer) and galactosyl ceramide (galactosylceramide, GalCer)；3) retention time 4-7.8 minutes are phosphatidyl choline, phosphatidyl-ethanolamine, phosphatidyl glycerol, phosphatidylserine, phosphatidic acid, phosphatidylinositols；4) it is diglyceride (Diacylglycerol, DG), triglycerides (Triacylglycerol, TG), cholesteryl ester (cholesterol ester, ChE) that long-chain esters retention time range, which is 7.8-9.5min,；Anionic electrodeposition is under mode: 1) lysophospholipids and free acid kind retention time are 0.5-4 minutes；2) phospholipid is 4-9 minutes.After being reserved time screening, it is matched to that LIPID MAPS, the metabolin of aliphatic compound is classified as lipid or lipid analog in LipidBlast database or HMDB database molecular framework level.The target metabolite selected in subsequent analysis will carry out secondary identification using data dependence type tandem mass spectrometry (DDA) combination with standard product, and carry out classification report to metabolin according to metabolism group program of standards development (MSI) standard.
1.5 being metabolized spectrum analysis and potential biomarker
1.5.1 monotropic amount comparing analysis
Examining screening to obtain 1590 metabolins in three groups of samples by Kruskal-Wallis first, there were significant differences (p < 0.05, district's groups Kruskal-Wallis examine) for relative intensity.Further compare group difference metabolite analysis (p < 0.05 two-by-two on the basis of to difference metabolin, Dunn ' s postposition is examined) such as Wei Entu (Fig. 4) display, the quantity of different group difference metabolins and classification (p < 0.05, postposition is examined) different: the difference metabolin quantity wherein between NGT group and T2D group is maximum, it secondly is NGT group and Pre-DM group, the difference metabolin between Pre-DM group and T2D group is relatively minimal.
1.5.2 the potential source biomolecule marker of random forest (ROC/AUC) screening T2D occurrence and development is utilized
Further to screen the blood plasma lipide metabolin closely related with disease, the present invention uses random forest grader, and screening biomarker carries out disease risks prediction modeling to NGT and T2D crowd, and crowd is not trained to complete the verifying to the prediction model using independent.Specific practice is as follows: (91 NGT, 106 T2D) randomly select 140 samples (70 NGT and 70 T2D) as training set from whole NGT and T2D crowds, and remaining sample is as verifying collection.By all 12,000 metabolin inputs random forest grader, 5 10 folding cross validations are carried out to test set, 10 repetitions, its T2D risk is calculated to each individual using the metabolin relative intensity of RF model discrimination, and receiver operating characteristic (receiver operation characteristic, ROC) curve is drawn, and calculate area under the curve (AUC) as discrimination model efficiency evaluation parameter.It chooses in 10 reproducible results, marker number of combinations < 30, and differentiates optimal group of efficiency and be combined into combination of the present invention.The selection frequency of each metabolin is exported in a model, and frequency is higher, represents the metabolin and is used to differentiate that the importance of T2D and NGT are higher.
As the result is shown, gained RF classifier of the invention contains 28 metabolin (Fig. 5, table 1-1,1-2,1-3, metabolin is numbered with table 3), to the differentiation efficiency of above-mentioned training set sample are as follows: AUC=90.23%, 95% confidence interval CI=84.95-95.52% (Fig. 6), the results showed that the model, which obtains metabolin combination, can be used as the potential source biomolecule marker for distinguishing T2D and NGT.
1.5.3 the biomarker screened using verifying collection data verification
The present invention immediately verifies the model using independent crowd, and probability of illness (RP) >=0.5 prediction individual, which has, suffers from diabetes B risk or with diabetes B.
Based on this model:
To individual authentication collection 1 (T2D=36 and NGT=21), the differentiation AUC=86.24% (95%CI=76.05-96.43%) of model；Accuracy=80.70% (Fig. 7, table 2)；
To individual authentication collection 2 (T2D=36 and Pre-DM=76), the differentiation AUC=71.77% (95%CI=of model
61.95-81.58%)；Accuracy=66.07% (Fig. 8, table 2)；
To individual authentication collection 3 (Pre-DM=76 and NGT=21), the differentiation AUC=68.08% (95%CI=54.87-81.28%) of model, accuracy=63.91% (Fig. 9), table 2.
3 validation batches are the result shows that the high-effect differentiation diabetes of the model and normal glucose tolerance people；It simultaneously can be to diabetes and prediabetes；Prediabetes and normal glucose tolerance people have the differentiation efficiency centainly distinguished.
According to Random Forest model, inventor further examines the risk probability (Fig. 7) of Pre-DM group different pathological phase patient, as a result the incremental trend of different pathological phase prediction probability is also showed that, minimum in HbA1c raised type 5.6-6.4% (median of probability of illness is 0.298), slightly elevated in pure IGT (iIGT) (median of probability of illness is 0.398), highest in associativity IFG/IGT (median of probability of illness is 0.494), show that the RF model can also be used to react the molecule parting feature of different prediabetes pathological stages.
The RF classifier includes 28 potential source biomolecule markers altogether, as shown in table 3.The details (based on above-mentioned 273 population sample) of above-mentioned 28 potential source biomolecule markers, including retention time (RT), parent ion (m/z), best match compound, P value, change multiple, VIP value are listed in table 3.Table 4 lists the AUC value that 28 metabolins individually identify T2D and NGT, T2D and non-T2D (including Pre-DM and NGT), T2D and Pre-DM and Pre-DM and NGT respectively (based on above-mentioned 273 population sample).Table 5 lists 28 biomarkers and compares details two-by-two at tri- groups of T2D, NGT, Pre-DM (based on above-mentioned 273 population sample).
The potential source biomolecule marker of 28 random forests is identified through further data dependence type mass spectral analysis (DDA), at 2 grades of MSI, identification obtains 4 kinds of compounds (Figure 11-Figure 14) altogether, that is maloyl group carnitine (hydroxybutyrylcarnitine) (marker 3, m/z 248.1511), LysoPC (18:0) (marker 2 and 7, m/z 508.3406 and m/z 508.3404), LysoPC (18:1) (marker 19, m/z 506.3249), LysoPC (18:2) (marker 17, m/z 504.3093) (table 3).Wherein, blood plasma relative amount of the maloyl group carnitine (hydroxybutyrylcarnitine) in crowd develops with disease and significant be incremented by is presented, it is in particular in that NGT group is minimum, is significantly higher than NGT in Pre-DM group, in T2D group highest and is significantly higher than Pre-DM group (table 5).And LysoPC (18:0), LysoPC (18:1), LysoPC (18:2) three classes lysophospholipids compound, quite without significant difference, but are all remarkably higher than T2D group (table 5) in NGT group and Pre-DM group content.Further, it (is bought from Avanti Polar Lipids Inc (Alabaster by standard items LysoPC (18:0), AL), article No. are as follows: 855775P) map and retention time and plasma sample comparison, marker 2 and 7 (m/z 508.3406 and m/z 508.3404) is accredited as LysoPC (18:0).4 kinds of potential source biomolecule markers, which combine, can significantly identify T2D and NGT and T2D and non-T2D (based on above-mentioned verifying collection population sample), distinguishing ability (AUC) respectively reaches 0.784 (95%CI=0.703-0.849) (Figure 15, table 6) and 0.723 (95%CI=0.654-0.771) (Figure 16, table 6) (note: represent marker 2 using only m/z 508.3406 and modeled).
Table 6 is based on 4 metabolite markers prediction T2D and NGT and T2D and non-T2D sample suffers from diabetes B risk or with diabetes B probability
The above result shows that, biomarker disclosed by the invention accuracy with higher and specificity, it is the prospect of diagnostic method with good exploitation, to find potential drug target spot for risk assessment, diagnosis, the early diagnosis of diabetes B and provide foundation.
In the description of this specification, the description of reference term " one embodiment ", " some embodiments ", " example ", " specific example " or " some examples " etc. means that particular features, structures, materials, or characteristics described in conjunction with this embodiment or example are included at least one embodiment or example of the invention.In the present specification, the schematic representation of the above terms does not necessarily have to refer to the same embodiment or example.Moreover, particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more of the embodiments or examples.In addition, without conflicting with each other, the feature of different embodiments or examples described in this specification and different embodiments or examples can be combined by those skilled in the art.
Although the embodiments of the present invention has been shown and described above, it can be understood that, above-described embodiment is exemplary, and is not considered as limiting the invention, and those skilled in the art can make changes, modifications, alterations, and variations to the above described embodiments within the scope of the invention.
Claims (16)
- One group of diabetes B marker, which is characterized in that including selected from least one of following:LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24:1 (15Z)), Carotenes and 5,6-dichloro - tetradecanoic acid.
- Diabetes B marker according to claim 1, which is characterized in that further comprise at least one of the compound with following table parameter:The parameter is obtained in the mass spectral analysis with the following conditions:ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
- A method of diagnosis 2- patients with type Ⅰ DM characterized by comprising(1) relative amount of marker as claimed in claim 1 or 2 in the sample of object to be diagnosed is determined；(2) relative amount based on the obtained marker in step (1), determines the diagnostic result of the object.
- According to the method described in claim 2, it is characterized in that, the relative amount based on the obtained marker in step (1), determines that the diagnostic result of the object is realized in the following way:The disease risks value of marker model is higher than predetermined threshold, is the instruction that the object suffers from 2- patients with type Ⅰ DM.
- According to the method described in claim 3, it is characterized in that, the predetermined threshold is 0.5.
- According to the method described in claim 4, it is characterized in that, the sample includes at least one of blood, skin, hair, saliva and muscle.
- According to the method described in claim 6, it is characterized in that, the sample is blood plasma lipide extract.
- According to the method described in claim 3, it is characterized in that, the relative amount of the marker is determined by the method for liquid chromatography-mass spectrometry in step (1).
- According to the method described in claim 8, it is characterized in that, the liquid-phase chromatographic analysis carries out under the following conditions:Ultra Performance Liquid Chromatography instrument ACQUITY UPLC (Waters, Manchester, USA),Chromatographic column: Waters CSH C18 column (100mm × 2.1mm, 1.7 μm)；Mobile phase A: acetonitrile: H2O=60:40,0.1% formic acid, 10mM ammonium formate；Mobile phase B: isopropanol: ACN=90:10,0.1% formic acid, 10mM ammonium formate；Gradient elution program: 2min, 40%B linear gradient increase to 43%B；0.1min increases to 50%B；3.9min increases to 54%B；0.1min increases to 70%B；1.9min, gradient increase to 99%B；0.1min, is restored to 40%B, to chromatography column equilibration 1.9min before each sample introduction；Flow velocity: 0.4mL/min；10 μ L of sampling volume.
- According to the method described in claim 8, it is characterized in that, the mass spectral analysis carries out under the following conditions:ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
- A kind of system diagnosing 2- patients with type Ⅰ DM characterized by comprisingMeasurement device, relative amount of the measurement device for marker described in claim 1 in the sample of determining object to be diagnosed；Determining device, the determining device are used to determine the diagnostic result of the object based on the obtained marker relative amount in the measurement device.
- System according to claim 11, which is characterized in that the sample is blood plasma lipide extract.
- System according to claim 12, which is characterized in that further comprise: extraction element, the extraction dress It sets and is connected with the measurement device, for extracting the blood plasma lipide of object to be diagnosed.
- According to the method for claim 11, which is characterized in that the measurement device includes liquid-phase chromatographic analysis unit and mass spectrometry unit.
- A kind of kit, which is characterized in that including reagent, the reagent includes selected from least one of following for detecting:LysoPC (18:0), Hydroxybutyrylcarnitine, 3-oxo-4-pentenoic acid, Ajoene, Hydroxybutyric acid, N- (3-oxo-octanoyl)-homoserine lactone, PC (42:8), TG (62:9), LysoPC (P-16:0), LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24:1 (15Z)), Carotenes and 5,6-dichloro - tetradecanoic acid,Optionally, the reagent further comprises for detecting at least one of the compound with following table parameter:The parameter is obtained in the mass spectral analysis with the following conditions:ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
- Purposes of the reagent in reagent preparation box, the kit are used for diagnosed type 2 diabetic marker, and the reagent includes selected from least one of following for detecting:LysoPC(18:0)、Hydroxybutyrylcarnitine、3-oxo-4-pentenoic acid、Ajoene、Hydroxybutyric acid、N-(3-oxo-octanoyl)-homoserine lactone、PC(42:8)、TG(62:9)、LysoPC(P-16:0)、 LysoPC (18:2), PI (P-38:1), PI (O-38:2), LysoPC (18:1), PS (38:1), LysoPC (24:1 (15Z)), Carotenes and 5,6-dichloro-tetradecanoic acidOptionally, the reagent further comprises for detecting at least one of the compound with following table parameter:The parameter is obtained in the mass spectral analysis with the following conditions:ESI ion source, positive/negative ion mode acquires data, mass range m/z 50~2000, s/ times per second, ion source temperature is 120 DEG C, and desolvation temperature is 600 DEG C, mobile phase gas is nitrogen, throughput is 800L/h, and pore voltage and orifice potential are respectively 2.0KV (+)/1.5KV (-) and 30V, using leucine enkephalin as lock mass.
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