Multiple organ dysfunction syndrome monitoring system and use thereof

Abstract

The application provides a multiple organ dysfunction syndrome monitoring system and application thereof. The multiple organ dysfunction syndrome monitoring system is used for monitoring tissue-specific methylation genes related to damage of six kinds of tissue organs, i.e. heart, liver, lung, kidney, intestine and pancreas. The bisDNA sequence of each gene and the bisDNA sequence of the internal reference ACTB gene are simultaneously detected, and finally, a multiple combined qMS-PCR method of 6 genes is screened out, which is used for high-sensitivity and high-specificity detection of the methylation sites.

Description

Technical Field

[0001] This invention relates to the field of medical technology, and in particular to a monitoring system for multiple organ dysfunction syndrome and its application. Background Technology

[0002] Patients in the Intensive Care Unit (ICU) are in an extremely vulnerable state, and multiple organ dysfunction syndrome (MODS) or even multiple organ failure (MOF) are the leading causes of death. Patients in hospital ICUs are prone to death from multiple organ damage and failure; therefore, early and accurate detection of multi-organ damage is crucial for developing clinical treatment plans. Early and accurate identification of early multi-organ damage is a key prerequisite for breaking the vicious cycle of "damage-failure-death" and optimizing treatment strategies.

[0003] Currently, clinical assessment of organ and tissue damage primarily relies on various protein markers in the blood. For example, troponin, natriuretic peptide, and myoglobin (Myo) generally reflect cardiomyocyte damage; while alanine aminotransferase (ALT) and aspartate aminotransferase (AST) generally reflect hepatocyte damage. However, these protein markers are not highly specific. For instance, troponin levels are generally elevated in patients with kidney disease and cannot reflect cardiac damage. Furthermore, ALT and AST are not unique to liver cells; AST is expressed in the heart, muscles, kidneys, brain, pancreas, lungs, leukocytes, and erythrocytes. ALT is mainly expressed in the liver and kidneys, but also shows low-level expression in the heart and skeletal muscle. Moreover, because these plasma protein markers have long half-lives, they are difficult to promptly indicate whether an organ is in the recovery phase after injury. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a monitoring system for multiple organ dysfunction syndrome (MODS). This system is used to monitor tissue-specific methylated genes associated with damage to six organs: heart, liver, lungs, kidneys, intestines, and pancreas. Specifically, the methylated gene for monitoring heart tissue is the genomic DNA sequence of the RFLNA gene promoter region >hg38 range=chr12:124294884-124295760 strand=+; the methylated gene for monitoring liver tissue is the genomic DNA sequence of the F12 gene hg38 range=chr5:177403275-177404638 strand=+; and the methylated gene for monitoring lung tissue is the ACOXL gene promoter region >hg38. The methylation gene used for kidney organ tissue monitoring is the PAX2 gene promoter region. The genomic DNA sequence is range=chr2:110732401-110733307strand=+. The methylation gene used for kidney organ tissue monitoring is the MUC12 gene. The methylation gene used for intestinal organ tissue monitoring is the MUC12 gene. The methylation gene used for pancreatic organ tissue monitoring is the CH5 gene. The genomic DNA sequence is range=chr7:100965212-1009664555'pad=500 3'pad=500strand=+. The methylation gene used for pancreatic organ tissue monitoring is the CH5 gene. The genomic DNA sequence is range=chr5:1701671-1702963strand=+.

[0005] In one embodiment, the reagent used for monitoring cardiac tissue and organs is a triple-linked quantitative real-time PCR detection reagent, which is used to simultaneously detect three fragments in a genomic DNA sequence. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 1, SEQ ID No. 2, and SEQ ID No. 3, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 4, SEQ ID No. 5, and SEQ ID No. 6, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 7, SEQ ID No. 8, and SEQ ID No. 9, respectively.

[0006] In one embodiment, the reagent used for monitoring liver tissue is a quadruple combined real-time PCR detection reagent, which is used to simultaneously detect four fragments in the hg38 range=chr5:177403275-177404638 strand=+ genomic DNA sequence. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 16, SEQ ID No. 17, and SEQ ID No. 18, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 19, SEQ ID No. 20, and SEQ ID No. 21, respectively; the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 22, SEQ ID No. 23, and SEQ ID No. 24, respectively; and the upstream and downstream primers and probes for detecting the fourth fragment are SEQ ID No. 28, SEQ ID No. 29, and SEQ ID No. 30, respectively.

[0007] In one embodiment, the reagent used for monitoring lung organ tissue is a triple-linked quantitative real-time PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence >hg38 range=chr2:110732401-110733307 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 37, SEQ ID No. 38, and SEQ ID No. 39, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 40, SEQ ID No. 41, and SEQ ID No. 42, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 43, SEQ ID No. 44, and SEQ ID No. 45, respectively.

[0008] In one embodiment, the reagent used for monitoring lung organ tissue is a dual-linked quantitative real-time PCR detection reagent, which is used to simultaneously detect two fragments in the genomic DNA sequence >hg38 range=chr10:100744157-100746389 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 52, SEQ ID No. 53, and SEQ ID No. 54, respectively, and the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 58, SEQ ID No. 59, and SEQ ID No. 60, respectively.

[0009] In one embodiment, the reagent used for monitoring intestinal organ tissue is a triple-linked quantitative PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence >hg38_cpgIslandExt_CpG: 23 range=chr7:100965212-100966455 5'pad=500 3'pad=500 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 67, SEQ ID No. 68, and SEQ ID No. 69, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 73, SEQ ID No. 74, and SEQ ID No. 75, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 76, SEQ ID No. 77, and SEQ ID No. 78, respectively.

[0010] In one embodiment, the reagent used for monitoring pancreatic organ tissue is a triple-linked quantitative real-time PCR detection reagent, which is used to simultaneously detect three fragments in the hg38 range=chr5:1701671-1702963 strand=+ genomic DNA sequence. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 82, SEQ ID No. 83, and SEQ ID No. 84, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 85, SEQ ID No. 86, and SEQ ID No. 87, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 88, SEQ ID No. 89, and SEQ ID No. 90, respectively.

[0011] In one embodiment, the present invention provides the application of the above-described monitoring system in the preparation of reagents for detecting multiple organ dysfunction syndrome.

[0012] Studies have shown that each tissue and organ produces a tissue-specific gene methylation state during development and differentiation. These tissue-specific methylated genes have high specificity and short half-life in peripheral blood, which can reflect the condition of tissue and organ damage in a timely manner.

[0013] This invention utilizes bioinformatics analysis of public databases for methylation sequencing or methylation microarray testing of various tissues and organs. Through experimental verification, it identified methylation sites of genes representing six tissue cell types: heart, liver, lung, kidney, intestine, and pancreas. A quantitative real-time PCR kit was designed for highly sensitive and specific detection of these methylation sites. Specific primers and probes were designed for the methylated CpG island DNA sequence of each gene. Circulating cfDNA from plasma was then used for testing. Samples were obtained from whole blood samples of patients clinically diagnosed with diseases related to tissue or organ damage and patients with normal corresponding organ function. The bisDNA sequences of each gene and the internal reference ACTB gene were simultaneously detected. Finally, a multiplexed qMS-PCR method was selected for the six genes to achieve highly sensitive and specific detection of these methylation sites. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of a genomic DNA sequence containing 108 CpGs in the promoter region of the RFLNA gene;

[0016] Figure 2 yes Figure 1 A schematic diagram of the DNA sequence after sulfite treatment;

[0017] Figure 3 It is a genomic DNA sequence containing 147 CpGs within the F12 gene;

[0018] Figure 4 yes Figure 3 A schematic diagram of the DNA sequence after sulfite treatment;

[0019] Figure 5 The ACOXL gene contains a genomic DNA sequence of 94 CpGs.

[0020] Figure 6 yes Figure 5 A schematic diagram of the DNA sequence after sulfite treatment;

[0021] Figure 7 The PAX2 gene contains a genomic DNA sequence of 188 CpGs.

[0022] Figure 8 yes Figure 7A schematic diagram of the DNA sequence after sulfite treatment;

[0023] Figure 9 MUC12 contains a genomic DNA sequence with 23 CpGs.

[0024] Figure 10 yes Figure 9 A schematic diagram of the DNA sequence after sulfite treatment;

[0025] Figure 11 It is the genomic DNA sequence of CpG within the CH5 gene;

[0026] Figure 12 yes Figure 11 A schematic diagram of the DNA sequence after sulfite treatment. Detailed Implementation

[0027] Example 1

[0028] The most efficient methylation sites of the RFLNA gene, representing cardiomyocyte-specific methylation, were screened. The RFLNA gene promoter region contains 108 CpG genomic DNA sequences; see details below. Figure 1 .

[0029] After sulfite treatment, methylated CG sequences in the aforementioned genomic reference sequence are expected to remain CG sequences, while unmethylated CG sequences are converted to TG sequences, with all individual C bases converting to T bases. This creates the conditions for distinguishing between methylated and unmethylated sequences using qPCR primers and probes. The sequence of this segment becomes... Figure 2 , Figure 2 The fused base Y represents the base C / T; 3-digit numbers of 100 and above are partially abbreviated, and the underlined numbers should actually be followed by 100.

[0030] Five sequences of the RFLNA gene after sulfite treatment were selected to design primers and probes for methylation quantitative real-time PCR (qMS-PCR). The boxes represent the positions of the upstream and downstream primers; the gray areas represent the positions of the probes. The primer and probe sequences are shown in Table 1. Table 1 shows the five sets of qMS-PCR primers and probes designed from the RFLNA gene sequence containing 108 CpGs.

[0031] Table 1

[0032]

[0033] qMS-PCR was designed targeting the five fragments of the above RFLNA gene and tested using plasma samples from 116 patients with different disease types, including 56 negative samples and 60 positive samples. The negative samples came from patients with normal cardiac function, while the positive samples came from patients with different types of impaired cardiac function, including coronary heart disease, myocardial infarction or occlusion, diffuse myocarditis, and viral myocarditis.

[0034] From primers and probes designed for multiple sequence segments, one or more sequence segments were randomly selected and mixed with primers and probes for the internal control gene ACTB in a single tube for multiplex qPCR. The reaction system components were obtained from Promega, and the specific reaction system is shown in Table 2.

[0035] Table 2

[0036]

[0037] Add water to 30μL.

[0038] The reaction conditions are the same for all systems, and the specific reaction conditions are shown in Table 3:

[0039] Table 3

[0040]

[0041] Fluorescence was collected at 65℃.

[0042] Methylation result interpretation: The internal reference gene ACTB showed S-type amplification with a Ct value ≤ 36. Based on the Ct values ​​of the target gene and the ACTB gene, the expression value of the target gene relative to ACTB was 2. （ACTB的Ct-靶基因的Ct） *100 If the following requirements are met, the fragment is considered to be positive for methylation detection.

[0043] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥2%, the specimen is judged to be methylation positive. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 4 below. Table 4 shows the quantitative fluorescence detection results of methylation of a single fragment of the RFLNA gene.

[0044] Table 4

[0045]

[0046] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are PCR1+PCR3, PCR1+PCR2+PCR3, PCR1+PCR2+PCR3+PCR4, and PCR1+PCR2+PCR3+PCR4+PCR5. Therefore, primers and probes designed for these five fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 116 patients with different disease types. The specific detection results are as follows.

[0047] For multiplex qMS-PCR designed for PCR1+PCR3, if the relative expression value of qMS-PCR in the dual-PCR is ≥2%, the methylated sample is considered to be positive for methylation.

[0048] For multiplex qMS-PCR designed for PCR1+PCR2+PCR3 combinations, if the relative expression value of qMS-PCR in the triplet PCR is ≥2%, the methylated sample is considered to be positive for methylation.

[0049] For multiplex qMS-PCR designed for PCR1+PCR2+PCR3+PCR4, if the relative expression value of qMS-PCR in the quadruple PCR is ≥2%, the methylated sample is considered to be positive for methylation.

[0050] qMS-PCR was performed using a multiplex design of PCR1+PCR2+PCR3+PCR4+PCR5. When the relative expression value of qMS-PCR in this five-fold combined PCR was ≥2%, the methylation of the sample was considered positive. The results are shown in Table 5 below. Table 5 shows the quantitative fluorescence detection results of methylation of the RFLNA gene for different fragments in random combinations.

[0051] Table 5

[0052]

[0053] It can be seen that triplet combined real-time PCR has a better overall match rate than dual, quadruple and quintuple combined real-time PCR.

[0054] Next, further tests were conducted on different triplet PCR combinations. When the relative expression value of qMS-PCR in the triplet PCR was ≥2%, the methylation sample was judged to be positive for methylation. The results are shown in Table 6 below. Table 6 shows the quantitative fluorescence detection results of methylation of the RFLNA gene for three random combinations of fragments.

[0055] Table 6

[0056]

[0057] The optimal detection system for the RFLNA gene exhibits the best overall performance in terms of sensitivity and specificity, with a sensitivity of 85.00%, a specificity of 91.23%, and an overall concordance rate of 88.11%.

[0058] Example 2

[0059] The most efficient methylation sites of the F12 gene, representing hepatocyte-specific methylation, were screened. The F12 gene contains 147 CpG genomic DNA sequences, as shown below. Figure 3 As shown. After sulfite treatment, the sequence of this segment becomes... Figure 4 .

[0060] In the sulfite-treated sequence of the F12 gene, primers and probes for methylation quantitative real-time PCR (qMS-PCR) were designed from 5 sequences. The boxes represent the positions of the upstream and downstream primers; the gray area represents the position of the probe. The primer and probe sequences are shown in Table 7. Table 7 shows the 5 sets of qMS-PCR primers and probes designed from the F12 gene sequence containing 147 CpGs.

[0061] Table 7

[0062]

[0063] qMS-PCR was designed targeting the five fragments of the F12 gene. Whole blood samples from 89 patients with different disease types were tested, including 41 negative samples and 48 positive samples. Negative samples came from patients with normal liver function, while positive samples came from patients with various liver impairments, including viral hepatitis, liver fluke disease, biliary cholangitis, fatty liver disease, cirrhosis, and liver cancer. The specific experimental conditions for qMS-PCR were the same as in Example 1.

[0064] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥5%, the specimen is judged to be a methylation positive result. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 8 below. Table 8 shows the quantitative methylation detection results of a single fragment of the F12 gene.

[0065] Table 8

[0066]

[0067] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are likely PCR2+PCR5, PCR2+PCR3+PCR5, PCR1+PCR2+PCR3+PCR5, and PCR1+PCR2+PCR3+PCR4+PCR5. Therefore, primers and probes designed for these five fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 89 patients with different disease types. The specific detection results are as follows.

[0068] For multiplex qMS-PCR designed for PCR2+PCR5, if the relative expression value of qMS-PCR in the dual-PCR is ≥5%, the methylated sample is considered to be positive for methylation.

[0069] For multiplex qMS-PCR designed for the combination of PCR2+ PCR3+ PCR5, if the relative expression value of qMS-PCR in the triplet PCR is ≥5%, the methylated sample is considered to be positive for methylation.

[0070] For multiplex qMS-PCR designed for PCR1+PCR2+PCR3+PCR5, if the relative expression value of qMS-PCR in the quadruple PCR is ≥5%, the methylated sample is considered to be positive for methylation.

[0071] qMS-PCR was performed using a multiplex design of PCR1+PCR2+PCR3+PCR4+PCR5. When the relative expression value of qMS-PCR in this five-fold combined PCR was ≥5%, the methylation of the sample was considered positive. The results are shown in Table 9 below. Table 9 shows the quantitative fluorescence detection results of methylation of the F12 gene for different fragments in random combinations.

[0072] Table 9

[0073]

[0074] It can be seen that quadruple combined real-time PCR has a better overall match rate than dual, triple and quintuple combined real-time PCR.

[0075] Next, further tests were conducted on different quadruple combined PCR combinations. When the relative expression value of qMS-PCR in the quadruple combined PCR was ≥5%, the methylation sample was judged to be positive for methylation detection. The results are shown in Table 10 below. Table 10 shows the quantitative fluorescence detection results of methylation of the F12 gene for four random combinations of fragments.

[0076] Table 10

[0077]

[0078] As can be seen from the results of the quadruple combined real-time PCR detection, the combination of PCR1+PCR2+PCR3+PCR5 is the optimal detection system for the F12 gene. Its overall performance in terms of sensitivity and specificity is the best, with a sensitivity of 91.67%, a specificity of 90.24%, and an overall concordance rate of 90.96%.

[0079] Example 3

[0080] The most efficient methylation sites of the ACOXL gene, representing alveolar and bronchial cell-specific methylation, were screened. The ACOXL gene promoter region contains genomic DNA sequences of 94 CpGs, as shown below. Figure 5 As shown, after sulfite treatment, the sequence of this segment is as follows: Figure 6 As shown.

[0081] In the sulfite-treated sequence of the ACOXL gene, primers and probes for methylation quantitative real-time PCR (qMS-PCR) were designed from 6 sequences. The boxes represent the positions of the upstream and downstream primers; the gray area represents the position of the probe. The primer and probe sequences are shown in Table 11. Table 11 shows the 6 sets of qMS-PCR primers and probes designed from the ACOXL gene sequence containing 94 CpGs.

[0082] Table 11

[0083]

[0084] qMS-PCR was designed targeting the six fragments of the ACOXL gene. Whole blood samples from 124 patients with different disease types were tested, including 47 negative samples and 77 positive samples. Negative samples came from patients with normal lung function; positive samples came from patients with various types of impaired lung function, including viral pneumonia, bacterial pneumonia, fungal pneumonia, pulmonary thromboembolism, and lung cancer. The specific experimental conditions for qMS-PCR were the same as in Example 1.

[0085] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥1%, the specimen is judged to be a methylation positive result. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 12 below. Table 12 shows the quantitative methylation detection results of a single fragment of the ACOXL gene.

[0086] Table 12

[0087]

[0088] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are PCR3+PCR5, PCR3+PCR4+PCR5, PCR1+PCR3+PCR4+PCR5, PCR1+PCR3+PCR4+PCR5+PCR6, and PCR1+PCR2+PCR3+PCR4+PCR5+PCR6. Therefore, primers and probes designed for these six fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 124 patients with different disease types. The specific detection results are as follows.

[0089] For multiplex qMS-PCR designed for PCR3+PCR5, if the relative expression value of qMS-PCR in the dual-PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0090] For multiplex qMS-PCR designed for PCR3+ PCR4+ PCR5 combinations, if the relative expression value of qMS-PCR in the triplet PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0091] For multiplex qMS-PCR designed for PCR1+PCR3+PCR4+PCR5, if the relative expression value of qMS-PCR in the quadruple PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0092] For multiplex qMS-PCR designed for PCR1+PCR3+PCR4+PCR5+PCR6, if the relative expression value of qMS-PCR in this five-fold combined PCR is ≥1%, the methylated sample is judged to be positive for methylation detection.

[0093] Multiplex qMS-PCR was performed using PCR1+PCR2+PCR3+PCR4+PCR5+PCR6. When the relative expression value of qMS-PCR in this six-fold combined PCR was ≥1%, the methylated sample was considered positive for methylation. The results are shown in Table 13 below. Table 13 shows the quantitative PCR results of methylation of the ACOXL gene for different fragments in random combinations.

[0094] Table 13

[0095]

[0096] It can be seen that triplet combined real-time PCR has a better overall match rate than dual, quadruple, quintuple and hexaple combined real-time PCR.

[0097] Next, further tests were conducted on different triplet PCR combinations. Considering that PCR2 had the lowest overall concordance rate, it was excluded from subsequent combination tests. When the relative expression value of qMS-PCR in the triplet PCR was ≥1%, the methylated sample was judged to be positive for methylation. The results are shown in Table 14 below. Table 14 shows the quantitative fluorescence detection results of methylation of the ACOXL gene for three random combinations of fragments.

[0098] Table 14

[0099]

[0100] As can be seen from the triple combined real-time PCR detection results, the PCR3+PCR4+PCR5 combination is the optimal detection system for the ACOXL gene. Its overall performance in terms of sensitivity and specificity is the best, with a sensitivity of 89.61%, a specificity of 89.36%, and an overall concordance rate of 89.49%.

[0101] Example 4

[0102] The most efficient methylation sites of the PAX2 gene, representing kidney cell-specific methylation, were screened. The PAX2 gene promoter region contains 188 CpG genomic DNA sequences, such as... Figure 7 As shown, after sulfite treatment, the sequence of this segment is as follows: Figure 8 As shown.

[0103] In the sulfite-treated sequence of the PAX2 gene, primers and probes for methylation quantitative real-time PCR (qMS-PCR) were designed from 5 sequences. The boxes represent the positions of the upstream and downstream primers; the gray area represents the position of the probe. The primer and probe sequences are shown in Table 15. Table 15 shows the 5 sets of qMS-PCR primers and probes designed from the PAX2 gene sequence containing 188 CpGs.

[0104] Table 15

[0105]

[0106] qMS-PCR was designed targeting the five fragments of the PAX2 gene. Whole blood samples from 93 patients with different disease types were tested, including 40 negative samples and 53 positive samples. Negative samples came from patients with normal renal function, while positive samples came from patients with various types of renal impairment, including nephrotic syndrome, nephritis syndrome, uremia, lupus erythematosus, and diabetic nephropathy. The specific experimental conditions for qMS-PCR were the same as in Example 1.

[0107] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥1%, the specimen is judged to be a methylation positive result. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 16 below. Table 16 shows the quantitative methylation detection results of a single fragment of the PAX2 gene.

[0108] Table 16

[0109]

[0110] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are likely PCR2+PCR4, PCR2+PCR4+PCR5, PCR1+PCR2+PCR4+PCR5, and PCR1+PCR2+PCR3+PCR4+PCR5. Therefore, primers and probes designed for these five fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 93 patients with different disease types. The specific detection results are as follows.

[0111] For multiplex qMS-PCR designed for PCR2+PCR4, if the relative expression value of qMS-PCR in the dual-PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0112] For multiplex qMS-PCR designed for the combination of PCR2+ PCR4+ PCR5, if the relative expression value of qMS-PCR in the triplet PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0113] For multiplex qMS-PCR designed for PCR1+PCR2+PCR4+PCR5, if the relative expression value of qMS-PCR in the quadruple PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0114] qMS-PCR was performed using a multiplex design of PCR1+PCR2+PCR3+PCR4+PCR5. When the relative expression value of qMS-PCR in this five-fold combined PCR was ≥1%, the methylation of the sample was considered positive. The results are shown in Table 17 below. Table 17 shows the quantitative fluorescence detection results of methylation of the PAX2 gene for different fragments in random combinations.

[0115] Table 17

[0116]

[0117] It can be seen that dual-pair combined real-time PCR has a better overall match rate than triple, quadruple, and quintuple combined real-time PCR.

[0118] Next, further tests were conducted on different duplex PCR combinations. When the relative expression value of qMS-PCR in the duplex PCR was ≥1%, the methylated sample was judged to be positive for methylation. The results are shown in Table 18 below. Table 18 shows the quantitative fluorescence detection results of methylation of the PAX2 gene for two random combinations of fragments.

[0119] Table 18

[0120]

[0121] As can be seen from the results of the dual-combination quantitative PCR detection, the PCR2+PCR4 combination is the optimal detection system for the PAX2 gene, with the best overall performance in terms of sensitivity and specificity. The sensitivity is 90.57%, the specificity is 95.00%, and the overall concordance rate is 92.78%.

[0122] Example 5

[0123] The most efficient methylation sites of the MUC12 gene, representing intestinal cell-specific methylation, were screened. A CpG island containing 23 CpGs is located 5 kb upstream of the MUC12 gene. The genomic DNA sequences of this CpG island and its upstream and downstream 500 bp are as follows: Figure 9 As shown, after sulfite treatment, the sequence of this segment becomes... Figure 10 As shown.

[0124] In the sulfite-treated sequence of the MUC12 gene, primers and probes for methylation quantitative real-time PCR (qMS-PCR) were designed from 5 sequences. The boxes represent the positions of the upstream and downstream primers; the gray area represents the position of the probe. The primer and probe sequences are shown in Table 19. Table 19 shows the 5 sets of qMS-PCR primers and probes designed from the sequence of the MUC12 gene containing 66 CpGs.

[0125] Table 19

[0126]

[0127] qMS-PCR targeting the five fragments of the MUC12 gene was designed and tested using whole blood samples from 92 patients with different disease types, including 40 negative samples and 52 positive samples. The negative samples came from patients with normal bowel function, while the positive samples came from patients with various bowel dysfunctions, including Crohn's disease, ulcerative colitis, dysentery, intestinal obstruction, intestinal perforation, peritonitis, and colorectal cancer. The specific experimental conditions for qMS-PCR were the same as in Example 1.

[0128] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥1%, the specimen is judged to be a methylation positive result. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 20 below. Table 20 shows the quantitative methylation detection results of a single fragment of the MUC12 gene.

[0129] Table 20

[0130]

[0131] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are PCR4+PCR5, PCR2+PCR4+PCR5, PCR1+PCR2+PCR4+PCR5, and PCR1+PCR2+PCR3+PCR4+PCR5. Therefore, primers and probes designed for these five fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 92 patients with different disease types. The specific detection results are as follows.

[0132] For multiplex qMS-PCR designed for PCR4+PCR5, if the relative expression value of qMS-PCR in the dual-PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0133] For multiplex qMS-PCR designed for the combination of PCR2+ PCR4+ PCR5, if the relative expression value of qMS-PCR in the triplet PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0134] For multiplex qMS-PCR designed for PCR1+PCR2+PCR4+PCR5, if the relative expression value of qMS-PCR in the quadruple PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0135] qMS-PCR was performed using a multiplex design of PCR1+PCR2+PCR3+PCR4+PCR5. When the relative expression value of qMS-PCR in this five-fold combined PCR was ≥1%, the methylation of the sample was considered positive. The results are shown in Table 21 below. Table 21 shows the quantitative fluorescence detection results of methylation of the MUC12 gene for different random combinations of fragments.

[0136] Table 21

[0137]

[0138] It can be seen that triplet combined real-time PCR has a better overall match rate than dual, quadruple and quintuple combined real-time PCR.

[0139] Next, further tests were conducted on different triplet PCR combinations. When the relative expression value of qMS-PCR in the triplet PCR was ≥1%, the methylated sample was judged to be positive for methylation. The results are shown in Table 22 below. Table 22 shows the quantitative fluorescence detection results of methylation of the MUC12 gene for three random combinations of fragments.

[0140] Table 22

[0141]

[0142] As can be seen from the triple combined real-time PCR detection results, the combination of PCR2+PCR4+PCR5 is the optimal detection system for the MUC12 gene. Its overall performance in terms of sensitivity and specificity is the best, with a sensitivity of 92.31%, a specificity of 95.00%, and a total concordance rate of 93.65%.

[0143] Example 6

[0144] The most efficient methylation sites of the CH5 gene, representing pancreatic cell-specific methylation, were screened. The CH5 gene contains a CpG island, and the genomic DNA sequences of this CpG island and its upstream and downstream 500 bp are shown below. Figure 11 As shown, after sulfite treatment, the sequence of this segment becomes... Figure 12 As shown.

[0145] In the sulfite-treated sequence of the CH5 gene, primers and probes for methylation quantitative real-time PCR (qMS-PCR) were designed from 5 sequences. The boxes represent the positions of the upstream and downstream primers; the gray area represents the position of the probe. The primer and probe sequences are shown in Table 23. Table 23 shows the 5 sets of qMS-PCR primers and probes designed from the CH5 gene sequence containing 49 CpGs.

[0146] Table 23

[0147]

[0148] qMS-PCR was designed targeting the five fragments of the CH5 gene. Whole blood samples from 105 patients with different disease types were tested, including 48 negative samples and 57 positive samples. Negative samples came from patients with normal pancreatic function, while positive samples came from patients with various types of impaired pancreatic function, including acute pancreatitis such as pancreatic edema, hemorrhage, and necrosis, as well as pancreatic cancer and pancreatic head cancer. The specific experimental conditions for qMS-PCR were the same as in Example 1.

[0149] The judgment criteria are as follows: when the relative expression value of a single fragment by qMS-PCR is ≥1%, the specimen is judged to be a methylation positive result. The sensitivity, specificity, and total concordance rate of the detection results compared with the pathological results are shown in Table 24 below. Table 24 shows the quantitative methylation detection results of a single fragment of the CH5 gene.

[0150] Table 24

[0151]

[0152] The results above show that the sensitivity of a single fragment is low. Analysis of the detection data revealed that combined detection of single fragments significantly improves sensitivity. The optimal detection systems are PCR2+PCR4, PCR2+PCR3+PCR4, PCR2+PCR3+PCR4+PCR5, and PCR1+PCR2+PCR3+PCR4+PCR5. Therefore, primers and probes designed for these five fragments were randomly mixed into a single tube for multiplex qPCR reactions. Each combination was then used to test whole blood samples from 105 patients with different disease types. The specific detection results are as follows.

[0153] For multiplex qMS-PCR designed for PCR2+PCR4, if the relative expression value of qMS-PCR in the dual-PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0154] For multiplex qMS-PCR designed for PCR2+ PCR3+ PCR4 combinations, if the relative expression value of qMS-PCR in the triplet PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0155] For multiplex qMS-PCR designed for PCR2+ PCR3+ PCR4+ PCR5, if the relative expression value of qMS-PCR in the quadruple PCR is ≥1%, the methylated sample is considered to be positive for methylation.

[0156] qMS-PCR was performed using a multiplex design of PCR1+PCR2+PCR3+PCR4+PCR5. When the relative expression value of qMS-PCR in this five-fold combined PCR was ≥1%, the methylation of the sample was considered positive. The results are shown in Table 25 below. Table 25 shows the quantitative fluorescence detection results of methylation of the CH5 gene for different fragments in random combinations.

[0157] Table 25

[0158]

[0159] It can be seen that triplet combined real-time PCR has a better overall match rate than dual, quadruple and quintuple combined real-time PCR.

[0160] Next, further tests were conducted on different triplet PCR combinations. When the relative expression value of qMS-PCR in the triplet PCR was ≥1%, the methylation sample was judged to be positive for methylation. The results are shown in Table 26 below. Table 26 shows the quantitative fluorescence detection results of methylation of the CH5 gene for three random combinations of fragments.

[0161] Table 26

[0162]

[0163] As can be seen from the triple combined real-time PCR detection results, the PCR2+PCR3+PCR4 combination is the optimal detection system for the CH5 gene. Its overall performance in terms of sensitivity and specificity is the best, with a sensitivity of 96.49%, a specificity of 95.83%, and a total concordance rate of 96.16%.

[0164] In summary, analysis of the detection results revealed that combined detection of multiple methylation fragments for each target gene significantly improves sensitivity. Optimal detection systems for methylation genes specific to six tissue cells—heart, liver, lung, kidney, intestine, and pancreas—were identified, enabling high sensitivity and specificity in detecting these methylation genes. This allows for the non-invasive detection and monitoring of tissue- and organ-specific damage.

[0165] It should be understood that the disclosed invention is not limited to the specific methods, schemes, and substances described, as these are all subject to variation. It should also be understood that the terminology used herein is for the purpose of describing specific embodiments only and is not intended to limit the scope of the invention, which is limited only by the appended claims.

[0166] Those skilled in the art will also recognize, or be able to identify, many equivalents of the specific embodiments of the invention described herein using no more than conventional experiments. These equivalents are also included in the appended claims.

Claims

1. A monitoring system for multiple organ dysfunction syndrome, characterized in that, The system is used to monitor tissue-specific methylated genes associated with damage to six organs: heart, liver, lung, kidney, intestine, and pancreas. Specifically, the methylated gene for monitoring heart tissue is the RFLNA gene promoter region >hg38 range=chr12: 124294884-124295760strand=+ genomic DNA sequence; the methylated gene for monitoring liver tissue is the F12 gene >hg38 range=chr5:177403275-177404638 strand=+ genomic DNA sequence; the methylated gene for monitoring lung tissue is the ACOXL gene promoter region >hg38 range=chr2:110732401-110733307 strand=+ genomic DNA sequence; and the methylated gene for monitoring kidney tissue is the PAX2 gene promoter region >hg38 range=chr10:100744157-100746389. The methylation gene used for monitoring intestinal organ tissues is the MUC12 gene > hg38_cpgIslandExt_CpG: 23 range=chr7:100965212-100966455 5'pad=500 3'pad=500 strand=+ genomic DNA sequence, and the methylation gene used for monitoring pancreatic organ tissues is the CH5 gene > hg38 range=chr5:1701671-1702963 strand=+ genomic DNA sequence; The reagent used for monitoring cardiac tissue and organs is a triple-linked quantitative PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 1, SEQ ID No. 2, and SEQ ID No. 3, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 4, SEQ ID No. 5, and SEQ ID No. 6, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 7, SEQ ID No. 8, and SEQ ID No. 9, respectively. The reagent used for monitoring liver tissue and organs is a quadruple combined real-time PCR detection reagent, which is used to simultaneously detect four fragments in the genomic DNA sequence. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 16, SEQ ID No. 17, and SEQ ID No. 18, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 19, SEQ ID No. 20, and SEQ ID No. 21, respectively; the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 22, SEQ ID No. 23, and SEQ ID No. 24, respectively; and the upstream and downstream primers and probes for detecting the fourth fragment are SEQ ID No. 28, SEQ ID No. 29, and SEQ ID No. 30, respectively. The reagent used for monitoring lung organ tissue is a triple-linked real-time PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence >hg38range=chr2:110732401-110733307 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 37, SEQ ID No. 38, and SEQ ID No. 39, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 40, SEQ ID No. 41, and SEQ ID No. 42, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 43, SEQ ID No. 44, and SEQ ID No. 45, respectively. The reagent used for monitoring kidney organ tissue is a dual-linked real-time PCR detection reagent, which is used to simultaneously detect two fragments in the genomic DNA sequence >hg38range=chr10:100744157-100746389 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 52, SEQ ID No. 53 and SEQ ID No. 54, respectively, and the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 58, SEQ ID No. 59 and SEQ ID No. 60, respectively. The reagent used for monitoring intestinal organ tissues is a triple-linked real-time PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence >hg38_cpgIslandExt_CpG: 23 range=chr7:100965212-100966455 5'pad=500 3'pad=500strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 67, SEQ ID No. 68, and SEQ ID No. 69, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 73, SEQ ID No. 74, and SEQ ID No. 75, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 76, SEQ ID No. 77, and SEQ ID No. 78, respectively. The reagent used for monitoring pancreatic organ tissue is a triple-linked quantitative PCR detection reagent, which is used to simultaneously detect three fragments in the genomic DNA sequence >hg38 range=chr5:1701671-1702963 strand=+. The upstream and downstream primers and probes for detecting the first fragment are SEQ ID No. 82, SEQ ID No. 83, and SEQ ID No. 84, respectively; the upstream and downstream primers and probes for detecting the second fragment are SEQ ID No. 85, SEQ ID No. 86, and SEQ ID No. 87, respectively; and the upstream and downstream primers and probes for detecting the third fragment are SEQ ID No. 88, SEQ ID No. 89, and SEQ ID No. 90, respectively.

2. The application of the multiple organ dysfunction syndrome monitoring system according to claim 1 in the preparation of reagents for detecting multiple organ dysfunction syndrome.

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