CN112697889B - Application of serum metabolism marker and detection kit - Google Patents
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Abstract
The invention relates to a new application of a micromolecular metabolite 12-hydroxy arachidonic acid (12-HETE) in a serum sample as a marker in preparing a kit for diagnosing a diabetic retinopathy patient in a subject. The invention also relates to a kit for detecting diabetic retinopathy in a subject, which is used for judging whether the subject suffers from diabetic retinopathy or not by detecting the relative concentration of 12-HETE in serum of the subject, calculating the variable Prob of the marker and a judgment cut-off value (cutoff) based on a binary logistic regression equation. The kit has low detection cost and good repeatability, and can efficiently detect the marker related to the invention. Meanwhile, the invention can be applied to the clinical diagnosis of the auxiliary diabetic retinopathy, has the characteristics of high diagnosis sensitivity and good specificity, and has higher development and application prospects.
Description
Technical Field
The invention relates to application of a micromolecular metabolite 12-HETE in a serum sample as a marker in preparing a kit for diagnosing a diabetic retinopathy patient in a subject. Belongs to the fields of analytical chemistry, biochemistry and clinical medicine.
Background
Diabetes is a common metabolic disorder characterized by abnormal insulin metabolism, often accompanied by hyperglycemia, hyperlipidemia, hypertension, and neurovascular injury. At present, the incidence of diabetes mellitus in China is the first to come across the world. Retinopathy is the most common complication of diabetes mellitus, and seriously harms the vision level and physical and psychological health of patients. Statistically, nearly 1.26 million people among 3.82 million diabetics worldwide currently suffer from retinopathy, and the risk of blindness of diabetics is 25 times that of normal people [ reference 1: Zheng Y, He M, concdon n. indian J ophthalmol.2012sep-Oct,60(5):428-31 ]. Diabetic retinopathy varies in stages depending on the absence or presence of clinical biomarkers of retinal vasculopathy, such as small aneurysms, bleeding, soft and hard exudates, edema, and neovascularization. The stages of diabetic retinopathy range from normal (or apparently normal) to background diabetic retinopathy ( stages 1, 2, 3) to Proliferative Diabetic Retinopathy (PDR). The existing diagnosis technology needs a patient to go to the ophthalmology regularly to carry out the examination of fundus fluorescence angiography and the like, has higher cost and fussy process, and is difficult to determine the early retinopathy. Therefore, development of a new clinical diagnostic method is imperative.
Lipids are important components of cell membranes and participate in important vital processes such as energy metabolism, membrane fixation and homeostasis, signal transduction, and autophagy. Lipidomics is a subject for large-scale qualitative and quantitative analysis of lipidosome in biological samples such as cells, body fluid, tissues and the like, mainly researches lipid metabolism, interaction of lipid and other molecules or a lipid-mediated signal communication process, and is an important component of system biology. Lipidomics, as a powerful analytical technique, play an irreplaceable role in the discovery of biomarkers and the study of disease mechanisms. Relevant studies indicate that various metabolic diseases such as diabetes, cancer, senile dementia, non-alcoholic fatty liver disease and the like are closely related to lipid metabolism disorder.
With the continuous development of mass spectrometry technology, lipidomics analysis methods based on mass spectrometry have been dominant. Mainly comprises analysis technologies such as direct sample injection (shotgun lipidomics), chromatography-mass spectrometry, mass spectrometry imaging and the like, and has advantages and disadvantages. The lipidomics analysis method based on the ultra-high performance liquid chromatography-mass spectrometry is one of the most common technologies due to the advantages of effectively reducing ion inhibition, being beneficial to isomer separation and the like. The invention utilizes ultra-high performance liquid chromatography-high resolution mass spectrometry to detect serum lipid mass spectrometry, and preferably selects a lipid metabolite 12-HETE with the largest change rate (about 7 times) as a metabolic marker for judging whether retinopathy exists in diabetic people. 12-HETE can regulate the expression of vascular endothelial growth factor and pigment epithelium derived factor, and is an important regulator of retinal neovascularization (Al-Shabraway M1, Mussell R, et Al diabetes, 2011). There is no report of the use of this metabolite for the diagnosis of diabetic retinopathy.
Disclosure of Invention
The invention aims to solve the clinical practical problems that the diagnosis of retinopathy in a diabetic patient group is difficult, particularly that the diagnosis of retinopathy in an early stage is difficult, and provides a metabolic marker for diagnosing retinopathy in a diabetic patient group, wherein the characteristics and the detection method of the metabolite are as follows:
the metabolic markers are lipid metabolites: 12-HETE, in electrospray ion source negative ion mode (ESI)-) And (6) detecting.
The detection kit for the metabolic markers comprises the following components:
and (3) standard substance: deuterated 12-hydroxyarachidonic acid (12-HETE d8), and the standard is used for the characterization of 12-hydroxyarachidonic acid (12-HETE) in the corresponding serum.
Extracting solvent: extractants used to pre-treat serum samples from subjects include methanol solution containing an internal standard (12-HETE d8), methyl tert-butyl ether, and ultrapure water. The metabolite is in the upper organic phase of a two-phase extraction system, so that the upper solution is taken for freeze-drying and re-dissolving, and is used for the analysis of ultra-high performance liquid chromatography-mass spectrometry. Elution solution: mobile phase a, acetonitrile/water ═ 6:4 (v/v); mobile phase B, 9:1(v/v) isopropanol/water, mobile phase A, B all contained 10mM ammonium acetate.
Separation detection system: separating and detecting the metabolic markers by using ultra-performance liquid chromatography (Waters) -high resolution mass spectrometry (AB SCIEX 5600 plus). The liquid chromatography column adopts Waters BEH C8 column (2.1 × 100mm,1.7 μm), column temperature 60 deg.C, column flow rate 0.3ml/min, ESI-And detecting the mode.
Pretreatment of serum samples of subjects: taking 20-40 ul of serum, sequentially adding 150-300 ul of methanol solution containing internal standard 12-HETE d8 and 500-1000 ul of methyl tert-butyl ether, and performing vortex oscillation for 10 min; adding 150-300 ul of ultrapure water, swirling for 30sec, and standing for 10 min; centrifugation (14000rpm 10min at4 deg.C), freeze-drying the upper layer solution, and finally re-dissolving with acetonitrile/isopropanol/water (65/30/5, v/v/v) containing 5mM ammonium acetate for ultra performance liquid chromatography-mass spectrometry.
And (5) determining 12-HETE in the serum sample according to the retention time of the standard substance and the secondary fragment information, and extracting the chromatographic peak intensity of the serum sample. The relative concentration of 12-HETE can be obtained by comparing the intensity of the chromatographic peak of 12-HETE with the intensity of the chromatographic peak of the internal standard 12-HETE d8 in the sample. The concentration of the internal standard in the extractant was 0.67. mu.g/ml.
The SPSS software was further used to perform a binary logistic regression analysis on the relative concentration data of 12-hydroxyarachidonic acid, and of the two types of samples, 2/3 was randomly selected for each type of sample to be used as a discovery set and the other 1/3 was used as a validation set. The binary logistic regression equation is as follows:
Prob(retinopathy among people with diabetes)＝1/(1+e-(0.016a-0.233))
Prob(diabetic patients early retinopathy, stage 1)＝1/(1+e-(0.012a-1.220))
Wherein a is the relative concentration of 12-hydroxyarachidonic acid, Prob(retinopathy among people with diabetes)Is the probability of retinopathy among people with diabetes. The resulting variable Prob, which is elevated in diabetic individuals with retinopathy, can be used to assist in the determination of retinopathy in diabetic individuals. The optimal cut-off value (cut-off value) for the metabolic markers determined by the present invention for the presence of retinopathy in diabetic populations is set to 0.57. For the diabetic population, if the Prob value is higher than the cut-off value, it is judged that diabetic retinopathy may occur, and if the Prob value is lower than the cut-off value, it indicates that there is no retinopathy at present. Prob(diabetic patients early retinopathy, stage 1)Is the probability of having retinopathy in the early stages of the diabetic population. The resulting variable Prob, which is elevated in diabetic populations with early retinopathy, can be used to assist in the determination of early retinopathy in diabetic populations. The optimal cut-off value (cut-off value) for the metabolic markers determined by the present invention for the presence of early retinopathy in diabetic populations is set to 0.31. For the diabetic population, if the Prob value is above the cut-off value, it is judged that there is a possibility of early diabetic retinopathy, and if it is below the cut-off value, it indicates that there is no retinopathy at present. Or obtaining the new compound by binary logistic regression according to the experimental result of the subjectAnd defining the optimal cut-off value for the laboratory. The cut-off value was determined based on the receiver operating curve (ROC curve) based on the values of the marker variables Prob. And (3) calculating to obtain a point with the maximum sum of the sensitivity and the specificity on the curve by taking the ordinate of the ROC curve as the sensitivity and the abscissa as the (1-specificity), wherein the Prob value corresponding to the point is the optimal cut-off value, and the sensitivity and the specificity corresponding to the point are the sensitivity and the specificity of the marker for disease discrimination.
The application of the metabolic marker comprises the following steps: can be well distinguished for diabetic retinopathy patients, diabetic retinopathy patients at early stage (stage 1) and diabetic retinopathy-free patients.
The established model has good discrimination ability on diabetic retinopathy and diabetic retinopathy, and a discovery set (shown in figure 1) and a verification set (shown in figure 2). The established model has good discrimination capability on diabetic retinopathy and diabetic retinopathy at early stage (stage 1), and a discovery set (see figure 3) and a verification set (see figure 4) are provided.
For diabetic retinopathy and diabetic retinopathy, the area under the AUC curve of the metabolic marker is 0.890, the sensitivity is 0.863, and the specificity is 0.878 (see table 2). Meanwhile, in the discovery set, the accuracy of judgment of the diabetic retinopathy-free and diabetic retinopathy is 0.878 and 0.863, respectively, and the verification set is 0.865 and 0.819, respectively.
For diabetic non-retinopathy and diabetic early retinopathy (stage 1), the area under the AUC curve of the metabolic marker is 0.910, the sensitivity is 0.879, and the specificity is 0.878 (see table 2). Meanwhile, in the discovery set, the accuracy of judging the diabetic retinopathy-free and diabetic retinopathy at an early stage is respectively 0.878 and 0.879, and the verification set is respectively 0.865 and 0.818. The excellent ROC curve result, the discovery set and the verification set have good diagnosis accuracy, so that the marker has the diagnosis potential of retinopathy in a diabetic patient group.
The invention has the following effects:
the 12-HETE in the serum sample can be used for judging whether retinopathy exists in the diabetic population or not, and can also be used for judging early retinopathy in the diabetic population. The kit has the characteristics of low detection cost, good repeatability, good specificity and high sensitivity. The metabolic markers can assist in diagnosing retinopathy in diabetic people, and have the same good effect in early diagnosis of diabetic retinopathy.
Drawings
FIG. 1 shows the ROC curve and the diagnosis result of retinopathy in the population with diabetes mellitus. 0 is diabetic non-ocular control group, 1 is mild diabetic retinopathy, 2 is moderate diabetic retinopathy, and 3 is severe diabetic retinopathy. 4 proliferative diabetic retinopathy.
FIG. 2 is a graph showing the ROC curve and the diagnosis results of the patients with localized diabetes. 0 is diabetic non-ocular control group, 1 is mild diabetic retinopathy, 2 is moderate diabetic retinopathy, and 3 is severe diabetic retinopathy. 4 proliferative diabetic retinopathy.
FIG. 3, ROC curve and diagnostic result graph for early retinopathy found in the diabetes-concentrated population. 0 is diabetic non-ocular disease control group, 1 is mild diabetic retinopathy.
FIG. 4 is a graph demonstrating the ROC curve for early retinopathy in a population with pooled diabetes and a diagnostic result. 0 is diabetic non-ocular disease control group, 1 is mild diabetic retinopathy.
FIG. 5, finding set on the left and validation set on the right, the change in relative concentration of 12-HETE in serum samples at various stages of diabetic retinopathy (mean. + -. standard error). 0 is diabetic non-ocular control group, 1 is mild diabetic retinopathy, 2 is moderate diabetic retinopathy, and 3 is severe diabetic retinopathy. 4 proliferative diabetic retinopathy.
Detailed Description
Example 1
1. Collecting a serum sample: all volunteers enrolled in the study signed an informed consent prior to blood collection. Serum samples of subjects were collected under the same conditions as a finding group, 74 diabetic patients without eyes were used as a control group, 234 diabetic patients with eyes (66 cases at stage 1, 60 cases at stage 2, 57 cases at stage 3, 51 cases at proliferation stage) were used as a disease group, and these serum samples were placed in a refrigerator at-80 ℃ for examination.
2. Analytical method
2.1 serum sample pretreatment
Thawing the serum sample at4 deg.C, taking 40 μ l serum into 2ml EP tube, adding 300 μ l methanol solution containing internal standard 12-HETE d8, vortexing, adding 1ml MTBE, vortexing and shaking for 10min, adding 300 μ l ultrapure water, vortexing, standing, centrifuging (14000rpm x 10min at4 deg.C), taking 400 μ l supernatant, lyophilizing, storing in-80 deg.C refrigerator, and waiting for mass spectrometry.
2.2 ultra high performance liquid chromatography Mass Spectrometry
(1) Liquid phase conditions: the chromatograph was a WatersACQUITY ultra high performance liquid system (Milford, U.S. A.) and the column was a Waters UPLCBEH C8 column (2.1 mm. times.100 mm,1.7 μm). Mobile phase a was ACN/H2O ═ 6:4(v/v) and mobile phase B was IPA/ACN ═ 9:1(v/v) (isopropanol/acetonitrile), each containing 10mM ammonium acetate. The column temperature was 60 ℃, the flow rate was 0.3ml/min, the sample size was 5. mu.l, and the elution gradient is shown in Table 1:
TABLE 1
| Time | A | B％ | |
| 0 | 50 | 50 | |
| 1.5 | 50 | 50 | |
| 9 | 15 | 85 | |
| 9.1 | 0 | 100 | |
| 11 | 0 | 100 | |
| 11.1 | 50 | 50 | |
| 13 | 50 | 50 |
At 0 to 1.5min, mobile phase B was held at a 50% ratio, 1.5 to 9min, mobile phase B increased linearly to 85%, 9 to 9.1min, mobile phase B rose to 100%, at 9.1 to 11min, mobile phase B was held at 100% for column elution, at 11 to 11.1min, mobile phase B dropped to 50%, at 11.1 to 13min, mobile phase B was held at 50% for equilibrium, and the total analysis time was 13 min.
(2) Conditions of Mass Spectrometry
The mass spectrometer is AB SCIEX Triple Q-TOF 5600+In the system (Concord, Canada), negative ion mode analysis is adopted, the voltage of an ion source is 4500 volts, the surface heating temperature is 550 ℃, the gas 1 and the gas 2 of the ion source are both 55psi, and the gas of a curtain is 35 psi. The mass spectrometry scan range 150-.
3. Standard analysis A standard of deuterated 12-hydroxyarachidonic acid was placed in a mixed solution of 1:4(v/v) methanol and water at a concentration of 10 ug/mL. And (4) carrying out chromatographic mass spectrometry on the standard solution, wherein the detection conditions are the same as those of the serum sample. The retention time of deuterated 12-hydroxyarachidonic acid and the corresponding secondary information are confirmed according to the mass-to-charge ratio (319.2273, 5ppm) of the deuterated 12-hydroxyarachidonic acid extract.
4. Serum test results and auxiliary diagnostic methods
And (3) performing assisted qualitative determination on 12-hydroxy arachidonic acid (the retention time is 0.98min, the mass-to-charge ratio is 319.2273, 5ppm in a mass spectrum negative ion detection mode) in the serum sample according to the retention time, the extracted mass-to-charge ratio and the secondary information of the standard sample, and extracting the chromatographic peak intensity of the serum sample.
For the findings, 12-hydroxyarachidonic acid was significantly elevated in diabetic retinopathy (see left side of fig. 5). Substituting the relative concentration of the metabolic marker into SPSS software to perform a binary logistic regression equation, Prob(retinopathy among people with diabetes)＝1/(1+e-(0.016a-0.233)) And calculating the probability value, setting the cutoff value to be 0.57, namely, the probability of the metabolic marker is more than 0.57, and determining that the diabetic retinopathy exists. The metabolic marker has AUC 0.890 (see fig. 1), the sensitivity and specificity are also higher, 0.863 and 0.878 (see table 2), respectively, the metabolic marker 12-HETE has better diagnostic potency in diabetic retinopathy compared to lysophosphatidylcholine LPC16:0(AUC 0.853), the AUC indicates the area under the ROC curve, which is a value between 0 and 1. The larger the area under the curve, the greater the diagnostic efficacy of the test.
For the findings, 12-hydroxyarachidonic acid was also significantly elevated in diabetic early retinopathy (see left side of fig. 5). Substituting the relative concentration of the metabolic marker into a binary logistic regression equation, Prob(diabetic patients early retinopathy, stage 1)＝1/(1+e-(0.012a-1.220)) And calculating the probability value, setting the cutoff value to be 0.31, namely, the probability of the metabolic marker is more than 0.31, and determining that the diabetic early retinopathy exists. The AUC of the metabolic marker was 0.910 (see fig. 3), and the sensitivity and specificity were also higher, 0.879 and 0.878, respectively (see table 2). The metabolic marker 12-HETE has better diagnostic efficacy in early diabetic retinopathy compared to lysophosphatidylcholine LPC16:0(AUC ═ 0.888), which represents the area under the ROC curve, which isThe value is between 0 and 1. The larger the area under the curve, the greater the diagnostic efficacy of the test.
TABLE 2
Example 2
1. Collecting a serum sample: all volunteers enrolled in the study signed an informed consent prior to blood collection. Serum samples of subjects were collected under the same conditions as a validation set, 37 diabetic patients without eyes were used as a control group, 116 diabetic patients with eyes (33 cases at stage 1, 30 cases at stage 2, 28 cases at stage 3, and 25 cases at proliferation stage) were used as a disease study group, and the serum samples were placed in a refrigerator at-80 ℃ for examination.
2. Analytical method
The analytical method was the same as in example 1
3. Serum test results and auxiliary diagnostic methods
Example 2 the test results of the validation set substantially match those of example 1.
And (3) performing assisted qualitative determination on the 12-hydroxy arachidonic acid in the sample according to the retention time, the extracted mass-to-charge ratio and the secondary information of the standard product (the retention time is 0.98min under the mass spectrum negative ion detection mode, the mass-to-charge ratio is 319.2273, 5ppm), extracting the chromatographic peak intensity, and comparing the chromatographic peak intensity with the intensity of an internal standard peak in the sample to obtain the relative concentration of the chromatographic peak.
In the diabetic retinopathy group of the validation set, 12-hydroxyarachidonic acid was significantly elevated (see right side of fig. 5). Substituting the relative concentration of the metabolic marker into a binary logistic regression equation, Prob(retinopathy among people with diabetes)＝1/(1+e-(0.016a-0.233) Calculating the probability value, setting the cutoff value to be 0.57, namely the probability of the metabolic marker to be more than 0.57, and then the diabetic retinopathy is detected (see figure 2). The accuracy of the concentrated diabetic retinopathy-free judgment and the diabetic retinopathy-containing judgment is respectively 0.865 and 0.819.
In the validated group of diabetic early retinopathy, 12-hydroxyarachidonic acidSignificantly increased (see right side of fig. 5). Substituting the relative concentration of the metabolic marker into a binary logistic regression equation, Prob(diabetic patients early retinopathy, stage 1)＝1/(1+e-(0.012a-1.220)) And calculating a probability value, setting the cutoff value to be 0.31, namely, the probability of the metabolic marker to be more than 0.31, and determining that the diabetic retinopathy at the early stage is suffered (see figure 4). The accuracy of the judgment of concentrated diabetic retinopathy and diabetic retinopathy at the early stage is respectively 0.865 and 0.818.
The excellent ROC curve result, the discovery set and the verification set have good diagnosis accuracy, so that the marker has the diagnosis potential of retinopathy and early retinopathy in a diabetic patient group. The kit has the characteristics of low detection cost, good repeatability, good specificity and high sensitivity. The metabolic markers can assist in diagnosing retinopathy in diabetic people, and have the same good effect in early diagnosis of diabetic retinopathy.
Claims (4)
1. Use of a serum metabolism marker for the manufacture of a kit for diagnosing diabetic retinopathy in a subject, characterized in that: the metabolic marker is 12-hydroxy arachidonic acid; the kit comprises:
(1) and (3) standard substance: deuterated 12-hydroxyarachidonic acid, the standard being used to characterize 12-hydroxyarachidonic acid (12-HETE) in the corresponding serum; deuterated 12-hydroxyarachidonic acid is 12-HETE d 8;
(2) an extracting agent: the extracting agent comprises a methanol solution containing 0.3-0.7 mu g/ml internal standard 12-HETE d8, methyl tert-butyl ether and ultrapure water;
(3) eluting the solution;
elution solution: acetonitrile/water =4: 6-6: 4(v/v), isopropanol/acetonitrile =5: 5-9: 1(v/v), and both eluents contain a final concentration of 10mM ammonium acetate.
2. Use according to claim 1, characterized in that:
(1) firstly, treating a serum sample from a subject by using methanol containing an internal standard, precipitating serum protein, sequentially adding methyl tert-butyl ether and ultrapure water, carrying out vortex centrifugation to form a two-phase distribution system, then taking supernatant, carrying out vacuum centrifugation and freeze-drying, then carrying out concentration and redissolution, and finally carrying out ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS);
elution solution: acetonitrile/water =6: 4(v/v), isopropanol/acetonitrile =9: 1(v/v), eluent contains 10mM ammonium acetate;
liquid chromatography column: waters BEH C8 column, 2.1mm by 100mm,1.7 μm;
(2) comparing the chromatographic peak area of each subject serum sample after standard sample qualification with the corresponding internal standard substance peak area in the extracting agent respectively, and calculating the relative concentration of 12-hydroxy arachidonic acid;
(3) and calculating the variable Prob value of the marker by using a binary logistic regression equation according to the relative concentration value of the 12-hydroxy arachidonic acid.
3. Use according to claim 2, characterized in that: the optimal cut-off value (cut-off value) for the determined metabolic marker for the presence of retinopathy in the diabetic population is set to 0.57; for the diabetic population, if the Prob value is higher than the cut-off value, the diabetic retinopathy is judged to be possible to suffer, and if the Prob value is lower than the cut-off value, the diabetic retinopathy is not existed at present;
the optimal cut-off value (cut-off value) for the metabolic marker for the presence of early retinopathy in the diabetic population is set to 0.31; for the diabetic population, if the Prob value is higher than the cut-off value, the diabetic population is judged to possibly suffer from early diabetic retinopathy, and if the Prob value is lower than the cut-off value, the diabetic population is judged to have no retinopathy at present; or, a new equation can be obtained by binary logistic regression according to the experimental result of the subject, and the optimal cut-off value of the experiment is defined; confirming the intercept point value according to the ROC curve made by the Prob value of the marker variable; and (3) calculating to obtain a point with the maximum sum of the sensitivity and the specificity on the curve by taking the ordinate of the ROC curve as the sensitivity and the abscissa as the (1-specificity), wherein the Prob value corresponding to the point is the optimal cut-off value, and the sensitivity and the specificity corresponding to the point are the sensitivity and the specificity of the marker for disease discrimination.
4. The use of claim 2, wherein the subject comprises one or more of stage 1, 2, 3, proliferative stage of diabetic retinopathy patients, and non-retinopathy diabetic patients as controls thereof.
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