LU101772B1 - Non-invasive biomarkers for identification/prewarning of dairy cows with fatty liver disease - Google Patents

Abstract

The present invention discloses a set of novel biomarkers for non-invasive identification and pre-warning of dairy cows with fatty liver diseases. The biomarkers are: L-a-aminobutyric acid and Behenic acid in feces, and 3-Nitrotyrosine in urine. After the diagnosis ability verification, the AUC value of each of the markers is higher than the traditional serum biochemical indicators, so the novel markers have higher clinical diagnostic application potential, especially for their non-invasiveness. Moreover, the combined diagnostic results of the three biomarkers show a higher diagnostic ability. It is not only economic in cost but also easy to operate by applying the non-invasive biomarkers of the present invention to diagnose, identify and monitor fatty liver cows detection method. This is in line with the concepts of animal welfare and healthy development of commerical farms. In the future, it can be widely applied for a large-scale detection and diagnosis process for cows with fatty liver disease in commerical dairy farms, benefiting for the sustainable development of dairy industry.

Description

TTS rae, BL-5141 ‘NON-INVASIVE BIOMARKERS FOR IDENTIFICATION/PREWARNING OF DAIRT lu101772

COWS WITH FATTY LIVER DISEASE BACKGROUND OF THE INVENTION |

[0001] Technical Field |

[0002] The present invention relates to the technical fields of analytical chemistry | and clinical medicine, in particular to a novel non-invasive biomarker for | identification/prewarning of dairy cows with fatty liver disease. |

[0003] Description of Related Art !

[0004] "The content of fat in normal liver is about 5% (calculated based on wet | weight). The process of fat metabolism in the liver may be affected for different reasons. | But, if the accumulation of fat in the liver exceeds the normal content, fatty liver disease | occurred. Cells in liver undergo steatosis, and histologically, the steatosis manifests as the | cytoplasm filled with fat droplets. The disease often occurs in postpartum cows, especially | for high-yielding dairy cows. The fatty liver disease in dairy cows is one of the metabolic | disorders that often occur in dairy cows during the perinatal period. Severe fatty liver |; disease may also cause ketosis and postpartum paralysis, which seriously limits milk | production performance, reproductive performance and shortens the service life of dairy cows. This disease is particularly prevalent in the perinatal period of dairy cows, and its | incidence is relatively high (5-10% of cows have severe fatty liver, and 30-40% have | moderate or mild fatty liver), causing high culling rate and therefore huge economic losses | to the dairy industry. The prevalent fatty liver disease in cattle production has been | developing into a bottleneck to be solved in the worldwide dairy industry. |

[0005] Fatty liver, as a common metabolic disorder, has existed for a long time and | caused considerable economic losses to the dairy industry. However, effective diagnostic | methods for this disease are still not available. At present, the only reliable diagnosis .

BL-5141 method is to measure the fat content in the liver fissues by liver biopsy. This method san 14101772 invasive method, which has a detrimental effect on the sick cows and is not conducive to animal welfare. Moreover, a poor prognosis may also cause complications such as | infections and other diseases. Therefore, the identification of non-invasive, | high-specificity, high-sensitivity and accurate diagnostic method that can meet the needs | of veterinary clinical and sustainable development of dairy industry. . |

[0006] In view of the prior art, the objective of the present invention is to provide | a metabolic biomarker for non-invasive identification or warning of fatty liver disease in | dairy cows. Using the biomarker of the present invention to diagnose and identify fatty | liver cows is not only low in cost and easy to operate, but also a non-invasive detection | method, which is in line with the concepts of animal welfare and healthy farming. In the | future, it can be widely used in large-scale breeding of dairy cows to promote the sound | and efficient development of the dairy industry.

[0007] To achieve the above objective, the present invention adopts the following | technical solutions: |

[0008] The first aspect of the present invention provides an application of the | substance described in at least one of the following 1) to 3) as a novel biomarker in the | preparation of a reagent or a kit for diagnosing fatty liver disease in cows: : [00091 DD L-o-aminobutyric acid; |

[0010] 2) Behenic acid; and |

[0011] 3) 3-nitrotyrosine. |

[0012] wherein L-o-aminobutyric acid and Behenic acid are small molecule | metabolic markers in feces, and 3-Nitrotyrosine is a small molecule metabolic marker in . urine. The above three biomarkers can accurately identify fatty liver disease in dairy cows. Ë

BL-5141 The AUC value of each biomarker is higher than the traditional clinical biochemical 1101772 indicator. Moreover, when more than one of the three biomarkers are used in combination, the AUC value is closer to 1 than that in the case of use of one of the three novel biomarkers, and the diagnosis effect is better. When the above three biomarkers are used | in combination, it has the best recognition effect on dairy liver fatty liver disease. |

[0013] Therefore, the present invention preferably sets forth the use of | L-o-aminobutyric acid, behenic acid, and 3-nitrotyrosine as a single biomarker and/or | combination biomarker in the preparation of a reagent or kit for identifying fatty liver | disease in dairy cows. |

[0014] The second aspect of the present invention provides an application of a | substance for detecting a content of a biomarker in a cow metabolite for preparing a | product for non-invasively identifying fatty liver disease in a cow. |

[0015] The cow metabolites include: feces and urine. |

[0016] The non-invasive biomarkers in the cow metabolites include: ; L-o-aminobutyric acid and Behenic acid in feces; and 3-Nitrotyrosine in urine.

[0017] À non-invasive method for identifying dairy fatty liver disease includes: |

[0018] (1) collecting metabolites from a cow to be tested; |

[0019] (2) detecting the content of biomarkers in cow metabolites; and !

[0020] (3) based on the detected relative content of the biomarkers, identifying whether the test cow has fatty liver disease. |

[0021] The third aspect of the present invention provides a method for obtaining | the biomarker for diagnosing fatty liver disease in a cow, comprising the following steps: :

[0022] (1) selecting 18 cows from 579 cows of two groups by 11 serum | biochemical indicator to form a Discovery set, dividing the cows into a normal group and | a fatty liver diseased group by liver biopsy, collecting feces and urine of the cows, : detecting the content of small molecule metabolites in feces and urine by mass |

BL-5141 ‘Spectrometry, carrying out multidimensional test and one-dimensional T et © 14101770 respectively screen significantly differential small molecule metabolites between normal and fatty liver diseased groups, and intersecting the small molecule metabolites screened by the two methods to obtain candidate differential markers for the Discovery set, wherein | the results show that the expression of the three markers is significantly different between | the disease group and the normal group; |

[0023] (2) Randomly selecting 16 cows to form a Test set to verify the expression | differences of the three markers, dividing the cows into a suspected normal group and a | suspected disease group according to the results of traditional clinical serum indicator, | B-ultrasound and veterinary comprehensive diagnosis, collecting feces and urine, | detecting the content of small molecular metabolites in feces and urine by mass | spectrometry, carrying out multidimensional test and one-dimensional T test to | respectively screen significantly differential small molecule metabolites between normal | and fatty liver diseased groups, and intersecting the small molecule metabolites screened by the two methods to obtain candidate differential markers for the Test set, wherein the | results show that the expression of the three markers is significantly different between the | suspected diseased group and the suspected normal group; and |

[0024] (3) Obtaining potential biomarkers by comparing the candidate differential | markers of the discovery set with the candidate differential markers of the test set and | intersecting the candidate differential markers of the Discovery set and the candidate | differential markers of the test set; and verifying the diagnostic ability of the potential ; biomarkers to obtain the biomarkers for the diagnosis of fatty liver disease in cows. ;

[0025] Preferably, in steps (1) and (2), the multidimensional test is based on VIP> | 1 and P <0.05; the one-dimensional T test is based on P <0.05. ,

[0026] Preferably, in step (3), a Violin plot and a ROC curve are used to verify the | diagnostic capability of the potential biomarkers. |

BL-5141 " [0027] The present invention has the following beneficial effects: ao

[0028] (1) Based on the metabolomics technology, the present invention provides for the first time three biomarkers that can be used for non-invasive identification of fatty liver diseased cows: L-a-aminobutyric acid and Behenic acid in feces, and 3-Nitrotyrosine in urine. After the diagnosis ability verification, the AUC value of each of the above | markers is higher than the traditional clinical biochemical indicator, so they have higher | clinical diagnostic application value; moreover, the combined diagnosis results of these | three biomarkers show a higher diagnostic application value. |

[0029] (2) Using the biomarker of the present invention to identify and monitor | fatty liver cows is not only low in cost and easy to operate, but also a non-invasive | detection method, which is in line with the concepts of animal welfare and healthy | farming. In the future, it can be widely used in large-scale breeding of dairy cows to | promote the sound and efficient development of the dairy industry. |

[0030] Figure 1 shows a flowchart of discovery of biomarkers of the present ‘ invention; !

[0031] Figure 2 shows a VIP volcano map of feces samples, VIP > 1; |

[0032] Figure 3 shows a one-dimensional T test chart of feces samples, P <0.05; |

[0033] Figure 4 shows a single multidimensional intersection Venn diagram of ; feces samples, where there are 23 candidate differential metabolites in the intersection; |

[0034] Figure 5 shows a VIP volcano map of urine sample, VIP> 1; .

[0035] Figure 6 shows a one-dimensional T test chart of urine samples, P <0.05; |

[0036] Figure 7 shows a single multidimensional intersection Venn diagram of ; urine samples, where there are 7 candidate differential metabolites in the intersection; '

[0037] Figure 8 shows a Violin plot of differential biomarkers, where A. Fecal |

BL-5141 marker L-a-aminobutyric acid in the diseased group is significantly lower than Tal Te. 10101770 control group, and fecal marker Behenic acid in the diseased group is significantly higher than that in the control group; Urine marker 3-Nitrotyrosine in the diseased group is significantly lower than that in the control group; |

[0038] Figure 9 shows a ROC curve of the biomarker L-a-aminobutyric acid, | where the area under the L-a-aminobutyric acid curve (AUC) is 0.863; |

[0039] Figure 10 shows a ROC curve of the biomarker Behenic acid, where the | area under the Behenic acid curve is 0.794; and |

[0040] Figure 11 shows a ROC curve of the biomarker 3-Nitrotyrosine, where the | area under the 3-Nitrotyrosine curve is 0.802. |

[0041] It should be noted that the following detailed descriptions are all exemplary ; and are intended to provide a further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning | as those commonly understood by any skilled in the art to which the present application | belongs. |

[0042] As explained in the “Background” section, the fatty liver disease in dairy | cows is one of the metabolic disorders that prevantly occur in dairy cows during their perinatal period. Severe fatty liver disease may also cause ketosis and postpartum | paralysis, which seriously limits milk production performance, reproductive performance | and shortens the service life of dairy cows. It causes huge economic losses to the dairy | industry. If the fatty liver disease in dairy cows can be identified and/or early warned in ; advance, these losses can be effectively avoided. At present, however, the only reliable . diagnosis method is liver biopsy, which is to measure the fat content in the liver tissue. , This method is an invasive method, which has a detrimental effect on the sick cows and is .

BL-5141 not conducive to animal welfare. Moreover, a poor prognosis may also cause concurrent 41177 infections and diseases. Therefore, the non-invasive method is of great significance and value for the early diagnosis of dairy cows with fatty liver disease.

[0043] Metabonomics and other new technologies, which involve the study of the entire metabolome, have been identified as promising for detecting the progress of a disease, elucidating its pathology, and assessing the effects of drugs on certain | pathological conditions. The metabolomics technology offers a lot of opportunities for the | development of new biomarkers which are important tools for identifying and analyzing | diseases, predicting disease progression, and determining the effectiveness and safety of | therapeutic interventions. |

[0044] The present invention is intended to study non-invasive biomarkers for | early diagnosis and warning of fatty liver disease in dairy cows. The present invention | uses XploreMET TM technology to determine metabolic markers. This technology uses | time-of-flight mass spectrometers, gas chromatography, and robotic online derivation Ë stations to determine major functional metabolites (such as amino acids and amines, | organic acids, carbohydrates, fatty acids and lipids, nucleotides, sugars, vitamins and | cofactors). XploreMETTM software integrates the most comprehensive mammalian | metabolite library (JiaLibTM), data processing, metabolite annotation, statistical analysis, | metabolic pathway enrichment analysis, and project reports in the metabolomics | community and streamline. The discovery process of the biomarker of the present ; invention is supported by scientific technologies and scientific methods, and has : undergone a rigorous screening process and a rigorous group verification process. This is | due to one-by-one research and breakthroughs in the following five areas: :

[0045] (1) The present invention uses the GC-MS technology for metabolomics ; analysis of feces and urine. The advantage of metabolomics lies in that it is closer to the ! phenotype of animals, can sensitively indicate phenotype and has been widely explored l

BL-5141 for disease identification. lu101772

[0046] (2) Metabolomics data are first subjected to QC (quality control) to reject or remove unreasonable data; principal component analysis (PCA) and OPLS-DA methods are used to verify the reliability of the screening model, and then candidate differential markers are screened by VIP volcano map and independent sample T test.

[0047] (3) The biomarkers in the present invention have undergone a rigorous screening process, and are not only significantly differentially expressed in the groups diagnosed by liver biopsy, but also verified in the groups diagnosed as suspected by serum | biochemical indicator, and the three biomarkers are thus provided with "double | insurance”! |

[0048] (4) Metabolic markers have variability among different individuals, which | is also the difficulty in screening metabolic markers with diagnostic value. In order to | overcome this technical difficulty, during the discovery process, the present invention | undergoes marker detection and screening of a large number of samples (579 heads in two | groups), and multiple samples are repeatedly taken to intersect to eliminate variation. | Compared with the traditional methods of identifying fatty liver individuals based on | serum biochemical indicator, the present invention has obvious advantages in | identification accuracy (Table 2). |

[0049] The marker of the present invention has undergone accuracy verification by / the independent sample set, which is a breakthrough rarely involved in the previous | studies (Fig. 8 and Fig. 9). |

[0050] The present invention finally found three biomarkers with diagnostic value: | L-a-aminobutyric acid and Behenic acid in feces, and 3-Nitrotyrosine in urine, as ; non-invasive small molecule metabolic markers for identifying cows with fatty liver ; disease. |

[0051] Among them: L-o-aminobutyric acid, having a molecular formula of |

BL-5141 CHINO; and a molecular weight of103.1198, can be synthesized from raw materials 1401772 L-threonine and DL-2-aminobutyric acid. It exists in the fecal metabolites of perinatal cows through multi-dimensional VIP and single-dimensional T test and shows significant difference between the control group and the diseased group.

[0052] Behenic acid, with a molecular formula of C»,H440,, is a solid with a soft odor. It is used in the manufacture of behenyl alcohol, behenic acid ester and behenic acid amide. It can be widely used in textiles, petroleum, detergent, cosmetics and other industries. Through multi-dimensional VIP and single-dimensional T test, it was found that there were significant differences in fecal metabolites between the control group and the diseased group.

[0053] 3-Nitrotyrosine, with a molecular formula of CsHoN,Os and a molecular | weight of 225.1787, was screened by multi-dimensional VIP and single-dimensional T test | techniques and found to be significantly different in dairy cow control and diseased groups / among urine metabolites of dairy cows during the perinatal period. |

[0054] The three biomarkers of diagnostic value are from feces and urine. Identification using cow's normal metabolites is time-saving and convenient and saves | diagnostic costs. No traditional blood sample collection or surgical puncture is required | for diagnosis. It is a painless identification marker and is of great significance to the health | and safety of cows and animal welfare. Using the marker of the present invention to | identify and diagnose fatty liver disease in dairy cows will not affect dairy cow production, | and will not have negative effects such as the decrease of production of dairy cattle, health | stress and even concurrent infection caused by blood sample collection, surgical puncture, | etc. It can save diagnosis and treatment costs and promote high production and efficiency. |

[0055] The biomarker used in the present invention is derived from feces/urine and | is a metabolite of dairy cows, which can well indicate the metabolism of dairy cows. For | fatty liver of dairy cows, the change to the content of biomarkers in the metabolites can be |

BL-5141 sed to acourately indicate that metabolie Status. Tot

[0056] The present invention utilizes the metabolomics technology, which has the advantage of the sensitivity to the correlation between the content of the markers and the occurrence of disease. The use of metabolic markers can find phenotypic metabolites that are not detected by proteins and genes, can realize the direct link to the disease itself, and can find upstream target genes and target proteins through the metabolic pathways of the metabolites, which is favorable to tracing the source of the disease based on characterization and enhanceing diagnostic accuracy. Before conducting metabolomics research, we performed biochemical indicator testing and screening on a large number of serum samples (579 heads in two groups), laying a solid foundation for the discovery of biomarkers in the invention.

[0057] In order to enable those skilled in the art to understand the technical solution of the present application more clearly, the technical solution of the present application will be described in detail below with reference to specific embodiments.

[0058] The test materials that are not specifically described in the embodiments of the present invention are all conventional test materials in the art, and can be purchased through commercial channels.

[0059] Example 1: Screening and Discovery of Candidate Markers-Screening and Discovery of Differential Markers for Metabolites in the Liver Biopsy Diagnosis groups

[0060] Firstly, 18 cows were selected as a Discovery set, and were divided into normal group (n = 8) and diseased group (n = 10) by liver biopsy. The feces and urine of cows were collected, and the differential distribution of small molecular metabolites in the normal group and diseased group was detected by mass spectrometry. Model testing of | metabolites showed a significant difference in distribution between the two groups and the | model was reliable. The differential markers were screened by the following two statistical | analysis methods: VIP (Variable importance in projection) multi-dimensional test, with 10 |

BL-5141 VIP> 1 and P <0.05 as the standard, to screen out small molecules with distribution 10177 differences in the two groups (Figure 2); single-dimensional T test, with P <0.05 as the standard, to screen out small molecules with significant distribution differences in the two groups (Figure 3); the candidate markers screened by the two methods were intersected | 5 (Figure 4), thus finally obtaining the candidate differential markers of the Discovery set.

[0061] Example 2: Screening of potential biomarkers Verification of differential expression of candidate biomarkers in other groups

[0062] Sixteen cows were selected as the test set for the purpose of verifying the candidate differential markers of the Discovery set through an independent sample group. The traditional clinical serum indicator, B-ultrasound and the results of veterinary comprehensive diagnosis were used to divide the sixteen cows into suspected normal | group (n = 7) and suspected diseased group (n = 9). Feces and urine were collected and detected according to the same method as in Example 1: VIP (Variable importance in projection) multidimensional test (Figure 5) and one-dimensional T test (Figure 6). The candidate markers screened by the two methods were intersected (Figure 7) for small molecule metabolite mass spectrometry detection and statistical analysis, and finally the candidate differential markers of the Test set were screened.

[0063] The candidate differential markers of Discovery set and Test set were compared, and the two are intersected. Finally, potential biomarkers were obtained: two in feces, i.e., L-a-aminobutyric acid and Behenic acid, and one in urine, i.e., 3 -Nitrotyrosine.

[0064] The information of the above three biomarkers is shown in Table 1:

[0065] Table 1: Basic information of three metabolic biomarkers (FL/Normal) acid acid 52 11

BL-5141 om] TT] woe acid 04

[0066] The table details the source, class, HMDB number, KEGG channel number, and T-test P value of the three markers, all of which are less than 0.05, as well as the Fold change (FL / Normal) value. The FC value shows that the fecal marker L-0-aminobutyric acid and the urine marker 3-Nitrotyrosine are down-regulated in the diseased group, and the fecal marker Behenic acid is up-regulated in the diseased group.

[0067] Example 3: Verification of the identification ability of 3 potential biomarkers-Violin plot and ROC curve.

[0068] The Violin plot shows (Figure 8) that compared with normal cows, the diseased group has L-a-aminobutyric acid in the feces of cows and 3-Nitrotyrosine in urine significantly down-regulated, and has Behenic acid in the feces significantly up-regulated. It can be known from the ROC curve analysis (Figure 9-11) that the AUC | value of each marker is higher than the traditional clinical biochemical indicator, thus | achieving higher clinical diagnostic application value. Moreover, the combined diagnostic | results of the three fecal and urine biomarkers show a higher diagnostic value (AUC value [ can reach 0.988, Table 2). ß

[0069] In dairy farming applications, by detecting the relative contents of these | three biomarkers in cow feces or urine, potentially fatty liver diseased cows can be | detected. The biomarker provides new technologies and methods for non-invasive | detection and diagnosis of fatty liver disease in dairy cows in the future. |

[0070] Example 4: The recognition ability of three metabolic biomarkers for fatty | liver cows is much higher than that of the traditional serum biochemical indicator. |

[0071] The three biomarkers of the present invention were compared with the { traditional serum biochemical indicator in the identification ability for fatty liver diseased ‘ cows. The results are shown in Table 2. It can be seen from Table 2 that the AUC value |

BL-5141 (0.794 -0.863) of each of the three biomarkers of the present invention is higher than the lu101772 traditional serum biochemical indicator (0.112 - 0.756). The combined diagnostic ability of the two markers in feces (AUC = 0.975) is higher than that of single fecal markers (AUC 0.863 and 0.794, respectively). In addition, feces and urine metabolites and three markers have the highest combined diagnostic ability (AUC = 0.988). The present invention uses three biomarkers from feces and urine as a combined diagnostic marker combination, which can significantly improve the ability to diagnose and identify fatty liver cows.

[0072] Table 2: Comparison in diagnostic ability for fatty liver diseased cows AUC in AUC in Test uma [os | os || Traditional serum biochemical indicator 038 | — | L-Alpha-aminobutyric 0. 863 0. 825 Biomarker in Feces acid Feces Combined biomarkers in

[0073] The above description is merely used to explain preferred embodiments of the present application and is not intended to limit the present application, and various changes and modifications of the present application may be made by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc, made within the spirit 13

BL-5141 and principle of the present application, should also fall within the scope of the present lu101772 application. 14

Claims (9)

1. : 1. An application of a substance described in at least one of the following 1) to 3), as a biomarker, for preparing a reagent or a kit for diagnosing fatty liver disease in cows: | 1) L-o-aminobutyric acid; | 5 2) Behenic acid; | 3) 3-nitrotyrosine. | 2. The application according to claim 1, wherein the L-&-aminobutyric acid, the | Behenic acid, and the 3-nitrotyrosine are combined as a biomarker combination. | 3. An application of a substance for detecting a content of a biomarker in a cow | 10 metabolite for preparing a product for non-invasively identifying fatty liver disease in | COWS. | 4. The application according to claim 3, wherein the cow metabolite includes feces | and urine. | 5. The application according to claim 4, wherein the biomarker in the cow | 15 metabolite includes L-a-aminobutyric acid and Behenic acid in the feces and | 3-Nitrotyrosine in the urine. | 6. The application according to claim 3, wherein a method for non-invasively | identifying fatty liver disease in the cow comprises: | (1) collecting metabolites from a cow to be tested; | 20 (2) detecting the content of the biomarkers in the metabolites of the cow; and | (3) based on the detected content of the biomarker, identifying or warning whether | the tested cow has fatty liver disease. | 7. A method for obtaining the biomarker for diagnosing fatty liver disease in cows | according to claim 1, comprising the following steps: | 25 (1) selecting cows to form a Discovery set, dividing the cows into a normal group ] and a fatty liver disease group by liver biopsy, collecting feces and urine of the cows,

   BL-5141 détecting the content of small molecule metabolites in the feces and urlne by mas quo spectrometry, carrying out a multidimensional test and a one-dimensional T test to respectively screen out significantly differential small molecule metabolites between normal and fatty liver disease groups, and intersecting the small molecule metabolites screened out by the two methods to obtain candidate differential markers for the Discovery set; (2) selecting cows to form a Test set, dividing the cows into a suspected normal group and a suspected disease group according to results of traditional clinical serum indicators, B-ultrasound and veterinary comprehensive diagnosis, collecting feces and urine, detecting the content of small molecular metabolites in the feces and urine by mass spectrometry, carrying out a multidimensional test and a one-dimensional T test to | respectively screen out significantly differential small molecule metabolites between normal and fatty liver disease groups, and intersecting the small molecule metabolites screened out by the two methods to obtain candidate differential markers for the Test set; and (3) comparing the candidate differential markers for the Discovery set with the | candidate differential markers for the test set to obtain potential biomarkers, and verifying the diagnostic ability of the potential biomarkers to obtain the biomarker for diagnosing the fatty liver disease in the cows. |

   8. The method for obtaining the biomarker according to claim 7, wherein in steps / (1) and (2), the multidimensional test is based on VIP> 1 and P <0.05, the one-dimensional T test is based on P <0.05. |

   9. The method for obtaining the biomarker according to claim 7, in step (3), a violin diagram and a ROC curve are used to verify the diagnostic ability of the potential biomarkers.