CN110879297A - Lipid biomarker for detecting nephrotic syndrome rat model and application thereof - Google Patents
Lipid biomarker for detecting nephrotic syndrome rat model and application thereof Download PDFInfo
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Abstract
The invention belongs to the technical field of model construction and evaluation methods, and provides a lipid biomarker for detecting a nephrotic syndrome rat model and application thereof, aiming at solving the technical problems of low accuracy and poor specificity of the existing evaluation method for evaluating the nephrotic syndrome rat model of a medicament. The metabolic profile map is obtained by analyzing the change of lipid metabolites in the serum of rats in a blank control group and a model group by adopting the metabonomics technology. All mass spectra were processed using CD software to obtain integrated data, combined with statistical analysis of the content of 22 lipid biomarkers, to evaluate the model of nephrotic syndrome in a targeted manner. The method is more comprehensive and sensitive, systematically reflects the dynamic outlines of the bodies of mice in a blank control group and a model group, comprehensively reflects the reasonability and scientificity of model replication, can provide a reliable evaluation method for nephrotic syndrome models for research and development of new drugs and pharmacological research, and has the advantages of high efficiency, rapidness and strong specificity.
Description
Technical Field
The invention belongs to the technical field of model construction and evaluation methods, and particularly relates to a lipid biomarker for detecting a nephrotic syndrome rat model and application thereof.
Background
Nephrotic syndrome is a syndrome of change of permeability of glomerular filtration membrane caused by various causes, and a large amount of urine protein is a main characteristic and a cause thereof, and hypertension and hyperlipidemia caused by the change of the kidney protein can promote glomerulosclerosis to generate serious consequences. The method for screening the medicines by using the whole animals is a method which is valued for a long time, and the whole animal screening model has the greatest advantage of intuitively reflecting the treatment effect, the adverse reaction and the toxic effect of the medicines from the whole level from the viewpoint of simply screening new medicines. The whole animal model includes normal animal and pathological animal model. Because normal animals cannot sufficiently reflect the therapeutic effect of the drug under pathological conditions, a whole animal pathological model is more applied in drug screening. Therefore, the research and preparation of more overall pathological animal models become a long-term important subject in the field of pharmaceutical research. The ideal whole animal model should have the basic conditions of similarity of pathological mechanism and human disease, stability of pathological manifestation and observability of drug action. The period of the traditional Chinese medicine exerting the drug effect is long, but with the progress of the experiment, whether the nephrotic syndrome rat model is stable or not can be used for drug evaluation or not, and at present, the period cannot be determined.
At present, whether the nephrotic syndrome model is successfully copied or not is judged mainly according to 24 h urine protein quantification, kidney histopathological examination and serum biochemical indexes. Mechanism-related examination indexes such as serum SOD and MDA levels, renal tissue inflammatory factor levels, fibrosis factor levels, renal podocyte structural protein expression levels and the like are also detected by a large number of researchers. However, the evaluation of nephrotic syndrome model still has shortcomings in long-term experimental studies. (1) Subjectivity: the direct observation indexes of the renal tissue morphology comprise glomerular structure state, whether swelling exists in renal tubules and renal mesenchymes, whether a large number of protein tube types and hyaline tube types exist and the like, and the evaluation method adopts subjective artificial evaluation and has great subjectivity and uncertainty. (2) One-sided property: the evaluation model of the nephrotic syndrome related regulatory factor has certain one-sidedness, can only reflect individual biochemical functions and the state of organs/tissues, and lacks the overall systematic evaluation standard. (3) The specificity is poor: almost all kidney diseases including nephrotic syndrome, nephritis, renal failure, etc. have been changed in both Blood Urea Nitrogen (BUN) and creatinine (Scr) indexes, and thus have no specificity.
Disclosure of Invention
The invention provides a lipid biomarker for detecting a nephrotic syndrome rat model and application thereof, aiming at solving the technical problems of low accuracy and poor specificity of the existing evaluation method for evaluating the nephrotic syndrome rat model of a medicament.
The invention is realized by the following technical scheme: lipid biomarkers for detecting nephrotic syndrome rat models, which are Cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, Phytosphinosinase, Acetyl-L-carnitine, S-Acetyldihydrolipoamide, L-carnitine, N-stearoylphenylalanine, 20:4 Cholesterylester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23: 360), PC (16: 0/16) and PC (18: 360); combined with statistical analysis of the content of 22 lipid biomarkers, if model rat serum:
the integral area mean of Cer (d18:0/14:0) was reduced from 4761608.0. + -. 419394.6 in normal mice to 3250774.3. + -. 702961.7,p＜0.01；
the integral area mean of Cer (d18:0/16:0) was reduced from 71300874.9. + -. 600139.9 in normal mice to 4256657.16. + -. 1113873.2,p＜0.01；
the integral area average number of Sphinganine is reduced from 8399100.4 +/-1039828.9 of normal mice to 5086397.5 +/-1414210.1,p＜0.01；
the integral area average number of C16Sphinganine is reduced from 102345734.2 +/-14373906.5 of normal mice to 66817182.8 +/-16274709.8,p＜0.01；
the integral area average number of the phytosporine is reduced from 69647151.2 +/-9363630.5 of normal mice to 44359092.4 +/-10642677.1,p＜0.01；
the integral area average number of the Acetyl-L-carnitine is reduced from 4652350.4 +/-648247.5 of normal mice to 2939510.8 +/-1231325.1,p＜0.01；
the integral area average number of the S-Acetyldihydrolipoamide is reduced from 3038974.7 +/-221691.8 of a normal mouse to 1996193.4 +/-482712.7,p＜0.01；
the mean integrated area of L-carnitine decreased from 2974438.6 + -1047158.7 in normal mice to 1335259.6 + -176983.9,p＜0.01；
the integral area average number of the M-stearoyl phenyl alanine is reduced from 1810816.9 +/-373408.2 of normal mice to 1067686.1 +/-424648.7,p＜0.01；
the integral area average of 20:4Cholesteryl ester increased from 8663306.6 + -1221558.6 of normal mice to 12433785.2 + -3527627.3,p＜0.001；
the integrated area mean of LysoPC (22:6) rose from 1589830.9 + -338592.8 in normal mice to 3374187.9 + -1138738.1,p＜0.001；
the mean integrated area of SM (d18:1/24:1) rose from 5853245.2 + -1108395.3 in normal mice to 8169303.9 + -571717.7,p＜0.001；
the mean integrated area of SM (d18:1/16:0) rose from 7423427.4 + -941050.5 in normal mice to 14084691.5 + -2388546.8,p＜0.001；
the integrated area mean of PC (18:1/18:1) rose from 20968543.0 + -2768161.3 in normal mice to 52312211 + -18355563.3,p＜0.001；
the integrated area mean of PC (22:6/18:0) rose from 6642944.7 + -1705329.9 in normal mice to 56438387.0 + -28577855.5,p＜0.001；
the integrated area mean of PC (18:3/18:2) rose from 4889771.9 + -1001756.9 in normal mice to 8920916.0 + -472826.5,p＜0.001；
the integrated area mean of LysoPC (20:3) rose from 1409828.7 + -190682.3 in normal mice to 2835408.0 + -391593.5,p＜0.001；
the integrated area mean of PC (18:0/20:4) rose from 43093721.55 + -5582712.0 in normal mice to 289940288.4 + -96308948.5,p＜0.001；
the mean integrated area of SM (d18:1/18:0) rose from 390694.3 + -46116.8 in normal mice to 1163380.8 + -217461.0,p＜0.001；
the mean integrated area of SM (d18:1/23:0) rose from 1826590.6 + -353831.7 in normal mice to 2611797.4 + -614936.5,p＜0.001；
the integrated area mean of PC (16:0/16:1) rose from 303089.9 + -96865.6 in normal mice to 804411.0 + -283963.7,p＜0.001；
the integrated area mean of LysoPC (18:0) rose from 4193532.3 + -350568.2 in normal mice to 5771673.9 + -394432.4,p＜0.001；
it indicates that the nephrotic syndrome rat model is stable on day 49.
The lipid biomarker is obtained by the following steps: performing liquid mass analysis on lipid compounds in rat serum of a blank control group and a model group to obtain a mass spectrum spectrogram of a rat model, analyzing the change of endogenous lipid metabolites in the rat serum of the blank control group and the model group, processing all the mass spectrum spectrograms by using Compound Discover software to obtain integral data, and performing multivariate statistical analysis on a mass spectrum spectrogram integral data matrix of the rat model to obtain a contour map of the rat model; performing pattern recognition on the data by adopting Principal Component Analysis (PCA), and performing contour dynamic analysis on a contour map of the rat model to obtain a contour change trend map of the rat model; the content change of 22 lipid biomarkers was obtained.
The lipid biomarkers are used for stability detection of a nephrotic syndrome rat model.
The changes in the 22 lipid biomarkers were: the content of Cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, photoshingosinosinase, Acetyl-L-carnitine, S-Acetyldihydrolipoamide, L-carnitine and N-stearoyl phenylanine in the serum of a model rat is obviously reduced, while the content of 20:4Cholesteryl ester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23:0), PC (16:0/16:1) and LysoPC (18:0) were significantly up-regulated, it indicates that the nephrotic syndrome rat model is stable at day 49 and can still be used for drug evaluation.
The invention adopts the metabonomics technology, and obtains the metabolic profile map by analyzing the change of lipid metabolites in the serum of rats in a blank control group and a model group. Meanwhile, processing all mass spectrogram by using Compound Discover (CD) software to obtain integral data, and combining with the content statistical analysis of 22 lipid biomarkers, finding that the change of the integral average value of the 22 lipid biomarkers in the serum of rats in the blank control group and the model group reflects the change trend of the serum metabolite content of rats with nephrotic syndrome to a certain extent, thereby pertinently evaluating the model of nephrotic syndrome. The metabolite is at the terminal of organism, the micro change of upstream gene and protein can be amplified on the metabolite, so the life phenomenon can be represented more sensitively, and the micro change of the external intervention to the organism metabolism network regulation process can be faithfully reflected. And to date, no lipidomics approach has been seen for the evaluation of nephrotic syndrome models. Compared with the conventional evaluation method, the method is more comprehensive and sensitive, systematically and comprehensively reflects the dynamic outlines of the bodies of mice in a blank control group and a model group, comprehensively reflects the reasonability and scientificity of model replication, can provide a reliable evaluation method for nephrotic syndrome models for research and development of new drugs and pharmacological research, and has the advantages of high efficiency, rapidness and strong specificity.
Drawings
FIG. 1 is a fingerprint of serum lipid metabolites of rats in a blank control group and a model group; in the figure: a is blank control group; b is a model group;
FIG. 2 is a graph of PCA scores for the placebo and model groups;
FIG. 3 is a graph of OPLS-DA scores for the placebo and model groups;
FIG. 4 is a graph of OPLS-DA loading for the placebo and model groups;
FIG. 5 is a graph of kidney histopathology of rats in the blank control group and the model group.
Detailed Description
A method for constructing a nephrotic syndrome rat model comprises the following steps:
(1) injecting 3.5mg/kg of adriamycin into tail vein of rat on day 1, and then injecting 1 mg/kg of adriamycin into tail vein of rat on day 8 every 1 week to obtain adriamycin nephropathy rat model;
(2) extraction of lipids: accurately aspirate 40. mu.L of serum and thaw at 4 ℃, add 300. mu.L of glacial methanol and vortex for 30 s. Adding 1 mL of methyl tert-butyl ether, incubating at 4 deg.C for 30 min, adding 250 μ L of ultrapure water, swirling for 30s, centrifuging at 4 deg.C for 10 min at 12,000 r/min, collecting 400 μ L of supernatant, centrifuging, concentrating, and drying. Add 120. mu.L of reconstituted solution acetonitrile-isopropanol-water (65: 30: 5, v/v), sonicate and centrifuge for 10 min, then take the supernatant for mass spectrometry.
(3) And characterizing the metabolic profile by using a multivariate statistical analysis method, performing pattern recognition on the data by adopting Principal Component Analysis (PCA), and inspecting the separation condition of each group of data profiles. On the 49 th day of the rat model construction, respectively carrying out liquid mass analysis on collected serum of rats in a blank control group and a model group to obtain mass spectrum spectrograms of the blank and model rats; then carrying out multivariate statistical analysis on mass spectrum spectrogram integral data matrixes of the rats in the blank control group and the model group to obtain contour maps of the rats in the blank control group and the model group; as shown in FIG. 2 (abscissa and ordinate represent the first and second principal components, respectively. C: blank control group; M: model group): the model group deviates from the normal control group, and the models are obviously separated when being copied on the 49 th day, which shows that the metabolic regulation network is obviously changed on the 49 th day, and proves that the nephrotic syndrome model is relatively stable and can be used for evaluating medicaments.
(4) On the basis of PCA, the serum of rats in a normal control group and a model group is further analyzed by an orthogonal partial least squares-discriminant analysis method (OPLS-DA) to obtain the serum contour maps of rats in the normal control group and the model group, and the result is shown in figure 2 (the abscissa and the ordinate respectively represent the first principal component and the second principal component). From fig. 2 it can be seen that the separation effect of the two groups on the axis of the principal component is significant. The results of the variable loading are then described by means of a load diagram, see fig. 3: (the abscissa and ordinate characterize the first principal component and the correlation coefficient, the larger the coefficient, the greater the contribution to the packet). Using Variable Importance (VIP) analysis, s-plot (absolute value of correlation > 0.58) in combination with statistics: (VIP) ((VIP))p< 0.05) to obtain potential biomarkers, and finding out variables with significant content change difference from the control group and the model group, wherein the variables relate to metabolic pathways which possibly result in the formation of a nephrotic syndrome model.
The 22 lipid biomarkers were: cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, phytophyngosine, Acetyl-L-carnitine, S-Acetyl dihydrazide, L-carnitine, N-stearoyl phynylalane, 20:4 Cholesterylester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23:0), PC (16:0/16:1) and LysoPC (18: 0).
The analysis step (3) resulted in the content change of 22 lipid biomarkers, and compared with the blank control group of rats, the content change of 22 lipid biomarkers at the seventh week of model construction is as follows:
the serum content of model rat Cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, photoshingosinine, Acetyl-L-carnitine, S-Acetyldihydrolipoamide, L-carnitine and N-stearoyl phenylamine is reduced remarkably, and the specific content changes are as follows:
the integral area mean of Cer (d18:0/14:0) was reduced from 4761608.0. + -. 419394.6 in normal mice to 3250774.3. + -. 702961.7,p＜0.01；
the integral area mean of Cer (d18:0/16:0) was reduced from 71300874.9. + -. 600139.9 in normal mice to 4256657.16. + -. 1113873.2,p＜0.01；
the integral area average number of Sphinganine is reduced from 8399100.4 +/-1039828.9 of normal mice to 5086397.5 +/-1414210.1,p＜0.01；
the integral area average number of C16Sphinganine is reduced from 102345734.2 +/-14373906.5 of normal mice to 66817182.8 +/-16274709.8,p＜0.01；
the integral area average number of the phytosporine is reduced from 69647151.2 +/-9363630.5 of normal mice to 44359092.4 +/-10642677.1,p＜0.01；
integral area average of Acetyl-L-carnitine from normal mice4652350.4 + -648247.5 of (C) is reduced to 2939510.8 + -1231325.1,p＜0.01；
the integral area average number of the T-Acetyldihydrolipoamide is reduced from 3038974.7 +/-221691.8 of a normal mouse to 1996193.4 +/-482712.7,p＜0.01；
the integral area average number of N-carnitine is reduced from 2974438.6 +/-1047158.7 of normal mice to 1335259.6 +/-176983.9,p＜0.01；
the integrated area average number of the O-stearoyl phenyl alanine is reduced from 1810816.9 +/-373408.2 of normal mice to 1067686.1 +/-424648.7,p＜0.01；
the levels of 20:4Cholesteryl ester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23:0), PC (16:0/16:1) and LysoPC (18:0) in the serum of the model rats were significantly up-regulated, with the following specific content changes:
the integral area average of 20:4Cholesteryl ester increased from 8663306.6 + -1221558.6 of normal mice to 12433785.2 + -3527627.3,p＜0.001；
the integrated area mean of LysoPC (22:6) rose from 1589830.9 + -338592.8 in normal mice to 3374187.9 + -1138738.1,p＜0.001；
the mean integrated area of SM (d18:1/24:1) rose from 5853245.2 + -1108395.3 in normal mice to 8169303.9 + -571717.7,p＜0.001；
the mean integrated area of SM (d18:1/16:0) rose from 7423427.4 + -941050.5 in normal mice to 14084691.5 + -2388546.8,p＜0.001；
the integrated area mean of PC (18:1/18:1) rose from 20968543.0 + -2768161.3 in normal mice to 52312211 + -18355563.3,p＜0.001；
the integrated area mean of PC (22:6/18:0) rose from 6642944.7 + -1705329.9 in normal mice to 56438387.0 + -28577855.5,p＜0.001；
the integrated area mean of PC (18:3/18:2) rose from 4889771.9 + -1001756.9 in normal mice to 8920916.0 + -472826.5,p＜0.001；
integrated area of LysoPC (20:3)The average number rises from 1409828.7 +/-190682.3 of normal mice to 2835408.0 +/-391593.5,p＜0.001；
the integrated area mean of PC (18:0/20:4) rose from 43093721.55 + -5582712.0 in normal mice to 289940288.4 + -96308948.5,p＜0.001；
the mean integrated area of SM (d18:1/18:0) rose from 390694.3 + -46116.8 in normal mice to 1163380.8 + -217461.0,p＜0.001；
the mean integrated area of SM (d18:1/23:0) rose from 1826590.6 + -353831.7 in normal mice to 2611797.4 + -614936.5,p＜0.001；
the integrated area mean of PC (16:0/16:1) rose from 303089.9 + -96865.6 in normal mice to 804411.0 + -283963.7,p＜0.001；
the integrated area mean of LysoPC (18:0) rose from 4193532.3 + -350568.2 in normal mice to 5771673.9 + -394432.4,p＜0.001；
in summary, if the endogenous metabolic profiles of rats in the blank control group and the model group are significantly separated at day 49 and 22 metabolite score data satisfy the above range, the nephrotic syndrome rat model can still be used for drug evaluation at day 49.
In order to show the advantages of the invention, a method for evaluating a nephrotic syndrome rat model by respectively adopting blank control group and model group for 24 h urine protein quantification, biochemical indexes, organ indexes and pathological section changes (the results are shown in tables 1, 2, 3 and 5) and a method for evaluating the nephrotic syndrome model by the method (the results are shown in tables 1, 2, 3 and 4) are adopted.
TABLE 1 quantitative Change in urine protein (Means. + -. SD) of rats in each group before and after molding
"" denotes comparison with blank control groupp<0.05，**p<0.01，***p<0.001
TABLE 2 Biochemical index Change (Means. + -. SD) of rats in blank control group and model group
"" denotes comparison with blank control groupp<0.05，**p<0.01，***p<0.001
The reliability of the model is evaluated by the conventional quantitative change of the rat blood of the blank control group and the model group. The results show that compared with the normal control group, the contents of albumin, serum urea nitrogen, serum creatinine, total cholesterol and triacylglycerol of the rat in the model group are significantly different from those of the blank control group, and the results show that the nephrotic syndrome rat model is successfully molded.
TABLE 3 organ index changes (Means. + -. SD) of rats in the placebo and model groups
". indicates" as compared to the blank control groupp<0.01，***p<0.001
The indexes of heart, liver, lung and kidney organs of rats in the blank control group and the model group are obviously different (P<0.05), and the result shows that the nephrotic syndrome rat model is successfully modeled.
From the result of histopathological section image analysis (fig. 5), it can be seen that, compared with the blank group, the renal tubular epithelial cells in the model group are severely water-like denatured, tubular alkalophilicity and protein cast are common, fibroblasts are moderately heavily fibroblastic proliferated, interstitial inflammatory cells are moderately heavily fibroblastic infiltrated, part of the tubular epithelial cells are atrophic, and the lumen is enlarged, indicating that the model is successfully replicated.
By comparison, the evaluation method can detect the replication process of the nephrotic syndrome rat model more comprehensively and sensitively, and has the advantages of high efficiency, rapidness and strong specificity.
Claims (4)
1. Detecting lipid biomarkers in a rat model of nephrotic syndrome characterized by: the lipid biomarkers are Cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, Photosporinase, Acetyl-L-carnitine, S-Acetyl dihydrolipoamide, L-carnitine, N-stearoylphenylaline, 20:4Cholesteryl ester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23:0), PC (16:0/16:1) and PC (18: 5390: 0); combined with statistical analysis of the content of 22 lipid biomarkers, if model rat serum:
the integral area mean of Cer (d18:0/14:0) was reduced from 4761608.0. + -. 419394.6 in normal mice to 3250774.3. + -. 702961.7,p＜0.01；
the integral area mean of Cer (d18:0/16:0) was reduced from 71300874.9. + -. 600139.9 in normal mice to 4256657.16. + -. 1113873.2,p＜0.01；
the integral area average number of Sphinganine is reduced from 8399100.4 +/-1039828.9 of normal mice to 5086397.5 +/-1414210.1,p＜0.01；
the integral area average number of C16Sphinganine is reduced from 102345734.2 +/-14373906.5 of normal mice to 66817182.8 +/-16274709.8,p＜0.01；
the integral area average number of the phytosporine is reduced from 69647151.2 +/-9363630.5 of normal mice to 44359092.4 +/-10642677.1,p＜0.01；
the integral area average number of the Acetyl-L-carnitine is reduced from 4652350.4 +/-648247.5 of normal mice to 2939510.8 +/-1231325.1,p＜0.01；
the integral area average number of the Acetyldihydrolipoamide is reduced from 3038974.7 +/-221691.8 of a normal mouse to 1996193.4 +/-482712.7,p＜0.01；
the mean integrated area of carnitine decreased from 2974438.6 + -1047158.7 in normal mice to 1335259.6 + -176983.9,p＜0.01；
the integral area average number of stearoyl phenyl alanine is reduced from 1810816.9 +/-373408.2 of normal mice to 1067686.1 +/-424648.7,p＜0.01；
the integrated area mean of the 20:4Cholesteryl ester increased from 8663306.6 + -1221558.6 in normal mice to 12433785.2±3527627.3，p＜0.001；
The integrated area mean of LysoPC (22:6) rose from 1589830.9 + -338592.8 in normal mice to 3374187.9 + -1138738.1,p＜0.001；
the mean integrated area of SM (d18:1/24:1) rose from 5853245.2 + -1108395.3 in normal mice to 8169303.9 + -571717.7,p＜0.001；
the mean integrated area of SM (d18:1/16:0) rose from 7423427.4 + -941050.5 in normal mice to 14084691.5 + -2388546.8,p＜0.001；
the integrated area mean of PC (18:1/18:1) rose from 20968543.0 + -2768161.3 in normal mice to 52312211 + -18355563.3,p＜0.001；
the integrated area mean of PC (22:6/18:0) rose from 6642944.7 + -1705329.9 in normal mice to 56438387.0 + -28577855.5,p＜0.001；
the integrated area mean of PC (18:3/18:2) rose from 4889771.9 + -1001756.9 in normal mice to 8920916.0 + -472826.5,p＜0.001；
the integrated area mean of LysoPC (20:3) rose from 1409828.7 + -190682.3 in normal mice to 2835408.0 + -391593.5,p＜0.001；
the integrated area mean of PC (18:0/20:4) rose from 43093721.55 + -5582712.0 in normal mice to 289940288.4 + -96308948.5,p＜0.001；
the mean integrated area of SM (d18:1/18:0) rose from 390694.3 + -46116.8 in normal mice to 1163380.8 + -217461.0,p＜0.001；
the mean integrated area of SM (d18:1/23:0) rose from 1826590.6 + -353831.7 in normal mice to 2611797.4 + -614936.5,p＜0.001；
the integrated area mean of PC (16:0/16:1) rose from 303089.9 + -96865.6 in normal mice to 804411.0 + -283963.7,p＜0.001；
the integrated area mean of LysoPC (18:0) rose from 4193532.3 + -350568.2 in normal mice to 5771673.9 + -394432.4,p＜0.001；
it indicates that the nephrotic syndrome rat model is stable on day 49.
2. The method of claim 1 for detecting lipid biomarkers in a rat model of nephrotic syndrome, wherein the method comprises the steps of: the lipid biomarker is obtained by the following steps: performing liquid mass analysis on lipid compounds in rat serum of a blank control group and a model group to obtain a mass spectrum spectrogram of a rat model, analyzing the change of endogenous lipid metabolites in the rat serum of the blank control group and the model group, processing all the mass spectrum spectrograms by using Compound Discover software to obtain integral data, and performing multivariate statistical analysis on a mass spectrum spectrogram integral data matrix of the rat model to obtain a contour map of the rat model; performing pattern recognition on the data by adopting Principal Component Analysis (PCA), and performing contour dynamic analysis on a contour map of the rat model to obtain a contour change trend map of the rat model; the content change of 22 lipid biomarkers was obtained.
3. The use of claim 1 for the detection of lipid biomarkers in a rat model of nephrotic syndrome, characterized by: the lipid biomarkers are used for stability detection of a nephrotic syndrome rat model.
4. The use of claim 3 for the detection of lipid biomarkers in a rat model of nephrotic syndrome, characterized by: the changes in the 22 lipid biomarkers were: the content of Cer (d18:0/14:0), Cer (d18:0/16:0), Sphinganine, C16Sphinganine, photoshingosinosinase, Acetyl-L-carnitine, S-Acetyldihydrolipoamide, L-carnitine and N-stearoyl phenylanine in the serum of a model rat is obviously reduced, while the content of 20:4Cholesteryl ester, LysoPC (22:6), SM (d18:1/24:1), SM (d18:1/16:0), PC (18:1/18:1), PC (22:6/18:0), PC (18:3/18:2), LysoPC (20:3), PC (18:0/20:4), SM (d18:1/18:0), SM (d18:1/23:0), PC (16:0/16:1) and LysoPC (18:0) were significantly up-regulated, it indicates that the nephrotic syndrome rat model is stable at day 49 and can still be used for drug evaluation.
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| CN112630344A (en) * | 2020-12-08 | 2021-04-09 | 河北医科大学第二医院 | Use of metabolic markers in cerebral infarction |
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