CN108034708B - System for determining individual effectiveness of tripterygium glycosides tablet in treating rheumatoid arthritis through expression quantity of multiple mRNA - Google Patents
System for determining individual effectiveness of tripterygium glycosides tablet in treating rheumatoid arthritis through expression quantity of multiple mRNA Download PDFInfo
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Abstract
The present disclosure provides a system for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis by the expression of a plurality of mrnas, including MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2. The disclosure also provides a molecular marker for determining the individual effectiveness of the tripterygium glycosides tablet for treating the rheumatoid arthritis, application of the molecular marker in preparing a kit for determining the individual effectiveness of the tripterygium glycosides tablet for treating the rheumatoid arthritis, and application of a reagent for detecting the expression quantity of the molecular marker in preparing a kit for determining the individual effectiveness of the tripterygium glycosides tablet for treating the rheumatoid arthritis. The technical scheme of the invention provides a biomarker with high specificity and high sensitivity and a curative effect prediction model for the individualized diagnosis and treatment of the rheumatoid arthritis, and provides a novel, efficient and noninvasive auxiliary tool for clinically formulating the individualized treatment scheme of the rheumatoid arthritis.
Description
Technical Field
The disclosure relates to the field of biomedicine, in particular to a system for determining the individual effectiveness of tripterygium glycosides for treating rheumatoid arthritis through the expression quantity of a plurality of mRNAs, a molecular marker for determining the individual effectiveness of the tripterygium glycosides for treating rheumatoid arthritis, application of the molecular marker in preparing a kit for determining the individual effectiveness of the tripterygium glycosides for treating rheumatoid arthritis, and application of a reagent for detecting the expression quantity of the molecular marker in preparing a kit for determining the individual effectiveness of the tripterygium glycosides for treating rheumatoid arthritis.
Background
Rheumatoid Arthritis (RA) is a refractory autoimmune disease in the world, is better than young and old, has high morbidity (about 0.36% in China) and high disability rate (about 60% in the course of 5-10 years), has great harm to human health, and is listed as one of five diseases with the largest influence on human health and the highest medical consumption in 25 years in the future by developed countries in recent years.
Tripterygium wilfordii is a traditional Chinese medicine in China, is recorded in Yunnan materia medica at the earliest, is bitter in taste and cold in nature, has the effects of clearing heat and removing toxicity, dispelling wind and removing dampness, relaxing muscles and tendons and activating blood circulation, and reducing swelling and relieving pain, is a pharmaceutical preparation tripterygium wilfordii polyglycoside tablet which is always used by people in China for treating rheumatism and has attracted wide attention of the international medical community, and no Chinese medicine or Chinese patent medicine can replace the tripterygium wilfordii polyglycoside tablet at an important position in the clinical anti-rheumatoid arthritis. However, the clinical popularization and reasonable application are seriously influenced because of the problems of large individual difference of clinical curative effect, equivalent effective dose and toxic dose and the like.
The inventor carries out systematic research on the effect of the tripterygium wilfordii and the active ingredients thereof on treating the rheumatoid arthritis in recent years, and finds that the tripterygium wilfordii and the active ingredients thereof have the effects of relieving the disease condition of the rheumatoid arthritis, inhibiting the synovitis of joints, preventing or slowing the damage of joint structures and improving the disease condition and resisting rheumatism. Meanwhile, starting from the key pathological link of rheumatoid arthritis, the related action mechanism that triptolide, the most main immunological active component of tripterygium, inhibits joint synovitis and angiogenesis, regulates cartilage matrix degradation and an osteoclast differentiation system, inhibits activation of inflammation-related signal pathways, and reduces inflammatory reaction cascade and circulation is explained. The related research results are helpful for understanding the action characteristics of the tripterygium wilfordii and promoting the molecular pharmacology development of the tripterygium wilfordii for resisting rheumatoid arthritis. Based on this, the next consideration is how to lead the research results to more directly guide clinical medication and how to individually apply tripterygium glycosides tablets to achieve the optimal treatment effect, which is also a hotspot in the international rheumatism research field at present and a difficult problem to be solved urgently.
Therefore, further screening new biomarkers closely related to individual differences of tripterygium glycosides tablets in treating rheumatoid arthritis has important significance in disclosing molecular mechanisms of the tripterygium glycosides tablets in treating rheumatoid arthritis and improving the average of individual liquid medicines.
Disclosure of Invention
The purpose of the disclosure is to provide a new biomarker closely related to individual difference of tripterygium glycosides tablets in treating rheumatoid arthritis, and improve the individual administration level of the tripterygium glycosides tablets in treating rheumatoid arthritis, thereby improving the treatment effect of the tripterygium glycosides tablets in treating rheumatoid arthritis.
In order to achieve the above object, in one aspect, the present disclosure provides a system for determining the individual effectiveness of tripterygium glycosides for treating rheumatoid arthritis through the expression levels of a plurality of mrnas, wherein the system comprises a computing device, an input device for inputting the expression levels of a plurality of mrnas of an individual patient with rheumatoid arthritis, and an output device for outputting the individual effectiveness of the tripterygium glycosides for treating the individual patient with rheumatoid arthritis; wherein the plurality of mRNAs comprises MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2; the computing device comprises a memory having a computer program stored therein and a processor configured to execute the computer program stored in the memory to implement a modeling algorithm and an algorithm of a discriminant function as shown in equation (1); the modeling algorithm is a support vector machine algorithm and/or a minimum deviation two-times algorithm;
F(c)＝sgn[f1(c1)+f2(c2)+f3(c3)+f4(c4)+f5(c5)+f6(c6)+b]formula (1)
In the formula (1), F (c) represents the individual effectiveness of the tripterygium glycosides tablet in treating rheumatoid arthritis, F (c) returns that the value is 1 to represent effectiveness, and returns that the value is-1 to represent ineffectiveness; c. C1、c2、c3、c4、c5And c6Sequentially showing the relative expression amounts of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2; the relative expression amount refers to the ratio of the expression amount relative to an internal reference; f. of1(c1)、f2(c2)、f3(c3)、f4(c4)、f5(c5) And f6(c6) The kernel functions are obtained by training according to the modeling algorithm, and b is the critical score values obtained by training according to the modeling algorithm.
In another aspect, the present disclosure also provides a molecular marker for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
In another aspect, the present disclosure also provides a use of a molecular marker in the preparation of a kit for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
In still another aspect, the present disclosure also provides a use of a reagent for detecting an expression amount of a molecular marker in preparing a kit for determining an individual effectiveness of tripterygium glycosides for treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
The rheumatoid arthritis as a systemic immune disease is accompanied by dynamic disorder of gene, protein and molecular interaction networks, and has the characteristics of low cure rate, high disability rate and the like on the whole. With the rapid development of the field of molecular biology, scientists find that various signal molecules are involved in the generation and development of rheumatoid arthritis, the activity of the signal molecules is influenced by various factors in heredity and environment, and the complex interaction and cross interference of regulation loops often make correct recognition and prediction of signal output related to the rheumatoid arthritis difficult. Given the high complexity of rheumatoid arthritis, the therapeutic strategies that have been used to date for a single highly specific target have not been satisfactorily effective.
In the research field of disease diagnosis and treatment biomarkers, differential expression molecules in disease tissues are generally selected as markers, and an artificial neural network, a partial least square method and the like are adopted to construct a disease prediction model. However, this method of analysis is less reproducible. As can be seen, the screening of disease diagnosis biomarkers is far from enough to consider differential expression data.
The inventor calculates and analyzes high-flux biomolecule expression profile data from the global angle, integrates characteristic analysis of a biomolecule network, and screens out disease diagnosis and treatment biomarkers with high reliability and corresponding calculation formulas, thereby obtaining the invention. Specifically, firstly, tripterygium glycosides tablets are adopted for treating patients with rheumatoid arthritis, and standard/non-standard treatment groups of the tripterygium glycosides tablets are divided through DAS28, ACR20/50/70 and other curative effect indexes; then, detecting the differential expression conditions of the two groups of genes by using a gene expression profile chip technology; then, analyzing the differential expression data, selecting a differential expression gene spectrum, and establishing a gene expression regulation network; then, screening key mRNAs in the network as biomarkers for evaluating the effect of the tripterygium glycosides tablets on treating rheumatoid arthritis; and finally, constructing a curative effect prediction model of the tripterygium glycosides tablet for individualized treatment of the rheumatoid arthritis by using a support vector machine algorithm and/or a partial least square algorithm according to the expression quantity of the biomarkers, and evaluating the performance of the curative effect prediction model. Evaluation results show that the technical scheme of the disclosure provides a biomarker with high specificity and high sensitivity and a curative effect prediction model for individualized diagnosis and treatment of rheumatoid arthritis, and provides a novel, efficient and noninvasive auxiliary tool for clinically formulating an individualized treatment scheme of rheumatoid arthritis, so that the benefit degree of a patient with rheumatoid arthritis from clinical treatment is effectively predicted, and the individualized drug treatment scheme can be designed and formulated according to the relationship between individual gene detection data and drug effects, so that the effect of a drug on an organism is fully exerted, the effectiveness of a first dose prescription is increased, the treatment effect is improved, the incidence rate of adverse drug reactions is reduced, the defects of the traditional or empirical scheme are overcome, and medical and sanitary resources are saved or reasonably configured.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
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The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is ACC and AUC results for example 2 and comparative example 2.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
In one aspect, the present disclosure provides a system for determining the individual effectiveness of tripterygium glycosides for treating rheumatoid arthritis through the expression levels of a plurality of mrnas, wherein the system comprises a computing device, an input device for inputting the expression levels of a plurality of mrnas of an individual rheumatoid arthritis patient, and an output device for outputting the individual effectiveness of the tripterygium glycosides for treating the rheumatoid arthritis patient; wherein the plurality of mRNAs comprises MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2; the computing device comprises a memory having a computer program stored therein and a processor configured to execute the computer program stored in the memory to implement a modeling algorithm and an algorithm of a discriminant function as shown in equation (1); the modeling algorithm is a support vector machine algorithm and/or a minimum deviation two-times algorithm;
F(c)＝sgn[f1(c1)+f2(c2)+f3(c3)+f4(c4)+f5(c5)+f6(c6)+b]formula (1)
In the formula (1), F (c) represents the individual effectiveness of the tripterygium glycosides tablet in treating rheumatoid arthritis, F (c) returns that the value is 1 to represent effectiveness, and returns that the value is-1 to represent ineffectiveness; c. C1、c2、c3、c4、c5And c6Sequentially showing the relative expression amounts of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2; the relative expression amount refers to the ratio of the expression amount relative to an internal reference; f. of1(c1)、f2(c2)、f3(c3)、f4(c4)、f5(c5) And f6(c6) The kernel functions are obtained by training according to the modeling algorithm, and b is the critical score values obtained by training according to the modeling algorithm. Wherein the support vector machine algorithm and the least-biased two-timesThe algorithm and the manner in which it operates and is trained are known in conventional manner.
Wherein MX1, OASL, SPINK1, CRK, GRAPL and RNF2 refer to the gene name (GeneSymbol) in NCBI database, the specific annotation is shown in Table 1, and the reference sequence in Table 1 is only used for illustration and not for limitation.
TABLE 1
Optionally, the system further comprises a plurality of mRNA expression level detection devices.
Optionally, the device for detecting the expression levels of the multiple mrnas comprises an mRNA expression level detection chip and a chip signal reader, and the mRNA expression level detection chip comprises probes for detecting the expression levels of MX1, OASL, SPINK1, CRK, GRAPL, and RNF2, respectively. Or the detection device for the expression quantities of the multiple mRNAs comprises a real-time quantitative PCR instrument and real-time quantitative PCR primers of the mRNAs, and the real-time quantitative PCR primers of the mRNAs comprise real-time quantitative PCR primers for respectively detecting the expression quantities of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2.
Optionally, the chip for detecting the mRNA expression level further comprises an internal reference probe, wherein the internal reference probe is a probe for detecting the expression level of the RPS18 gene and/or the GAPDH gene, and the chip for detecting the mRNA expression level further comprises an internal reference primer, and the internal reference primer is a real-time quantitative PCR primer for detecting the RPS18 gene and/or the GAPDH gene.
Optionally, wherein, as a set of reference values obtained by training with the GAPDH gene as an internal reference, in formula (1), f1(c1)＝-0.4694×c1，f2(c2)＝-0.2494×c2，f3(c3)＝-0.5592×c3，f4(c4)＝0.3429×c4，f5(c5)＝0.4054×c5，f6(c6)＝0.3504×c6And b is-0.03. That is, the discriminant function can be simplified as shown in equation (2):
F(c)＝sgn(-0.4694×c1-0.2494×c2-0.5592×c3+0.3429×c4+0.4054×c5+0.3504×c6-0.03)
formula (2).
Optionally, wherein, as a set of reference values obtained by training with the RPS18 gene, in the formula (1), f1(c1)＝-0.3031×c1，f2(c2)＝-0.3644×c2，f3(c3)＝-0.6511×c3，f4(c4)＝0.3852×c4，f5(c5)＝0.2624×c5，f6(c6)＝0.3663×c6And b is-0.0036. That is, the discriminant function can be simplified as shown in equation (3):
F(c)＝sgn(-0.3031×c1-0.3644×c2-0.6511×c3+0.3852×c4+0.2624×c5+0.3663×c6-0.0036)
formula (3).
In addition, f is1(c1)、f2(c2)、f3(c3)、f4(c4)、f5(c5)、f6(c6) And b may vary depending on the bias of the means for detecting the expression level of mRNA, or may vary depending on factors such as the size of the data scale of the training data set. The discriminant functions shown in equations (2) and (3) are obtained by training the inventors of the present disclosure with a modeling algorithm of least-squares multiplication according to the data in example 1, and do not limit the scope of the present disclosure. Of course, the discriminant function in the range of formula (1) can also be obtained by selecting the relative expression quantities of MX1, OASL, SPINK1, CRK, GRAPL and RNF2 according to other data and/or selecting a support vector machine algorithm for training.
In another aspect, the present disclosure also provides a molecular marker for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
In another aspect, the present disclosure also provides a use of a molecular marker in the preparation of a kit for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
In still another aspect, the present disclosure also provides a use of a reagent for detecting an expression amount of a molecular marker in preparing a kit for determining an individual effectiveness of tripterygium glycosides for treating rheumatoid arthritis, wherein the molecular marker is a plurality of mrnas, and the plurality of mrnas consists of MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2.
The reagent for detecting the expression level of the molecular marker may be a probe and/or a primer.
The present invention will be described in further detail below with reference to examples.
Example 1
This example serves to illustrate the discovery of biomarkers and the establishment of predictive models of the present disclosure.
Case source and sample size: 40 cases of RA patients who are in outpatient service of rheumatism department and in ward of Guangan hospital of Chinese academy of medical sciences meet the inclusion standard. At the same time, 10 healthy volunteers from the health examination center were selected, and the age and sex were matched with the disease group.
Inclusion criteria were: subjects who never received a tripterygium glycosides tablet treatment or did not receive a tripterygium glycosides tablet treatment within the last 4 weeks met the classification criteria of RA and the classification criteria of 2010 rheumatoid arthritis (ACR/EULAR) in 1987 by the American College of Rheumatology (ACR).
The classification of rheumatoid arthritis as amended by the american college of rheumatology in 1987 included:
1. morning stiffness of at least 1 hour (more than or equal to 6 weeks);
arthritis in 2.3 or more than 3 articular zones (more than or equal to 6 weeks);
3. arthritis between the wrist, metacarpophalangeal joints or proximal interphalangeal joints (more than or equal to 6 weeks);
4. symmetric arthritis (more than or equal to 6 weeks);
5. subcutaneous nodules;
6. changing the hand X-ray;
7. positive rheumatoid factor.
Four of the seven items can be diagnosed as rheumatoid arthritis.
The classification criteria of 2010ACR/EULAR rheumatoid arthritis include:
a: affected joint
1 big joint (0 point)
2-10 big joints (1 minute)
1-3 Small joints (with or without big joints) (2 points)
4-10 minor joints (with or without major joints) (3 points)
More than 10 joints (at least one facet joint) (5 points)
B: serology (at least 1 outcome is required)
RF and CCP (anti-cyclic citrullinated peptide antibody) negative (score 0)
RF and CCP, at least one of which is positive for low titre (score 2)
RF and CCP, at least one positive high titer (score 3)
C: acute phase reactants (requiring at least 1 outcome)
CRP and ESR both Normal (score 0)
CRP or ESR anomaly (1 point)
D: duration of symptoms
- < 6 weeks (0 min)
- > 6 weeks (1 min)
Within A-D, the highest score was taken for patient compliance. For example, the patient had 5 small joints and 4 large joints affected, with a score of 3. The sum of the scores is more than or equal to 6 points, and the rheumatoid arthritis is diagnosed.
3) Exclusion criteria: RA patients who cannot adhere to the medicine for 12 weeks for various reasons, patients suffering from other rheumatism, women of childbearing age or women with childbearing requirements.
4) And (3) informed consent: all subjects voluntarily signed an informed consent. The content of the informed consent includes the purpose, meaning and method of the study, the benefits and risks that may be obtained by the subject for participating in the study, the significance of the study and the privacy concerns of the information collected about the subject, particularly in the privacy of the individual, etc.
5) The administration scheme is as follows: tripterygium glycosides tablet 20mg, is administered orally, 3 times daily. The follow-up visit is carried out once every two weeks, and the change of each index during the treatment period of the tripterygium glycosides tablets is investigated according to the questionnaire.
6) The course of treatment is as follows: 12 weeks;
7) observation indexes are as follows: clinical data including sex, age, ethnicity, time to onset, anti-CCP levels, RF levels, and the like are collected from the patient,
Physical and chemical examination (ESR, CRP) and X-ray film/CT, and establishing corresponding database.
8) And (3) judging the curative effect: the efficacy is determined by whether the standard of care (light control) is met. The standard treatment is a treatment scheme aiming at reducing the disease activity of RA patients and achieving clinical remission. The disease evaluation methods such as DAS28, ACR20 and ACR50 are adopted. Specifically, after the patient uses tripterygium glycosides tablets, the patient is evaluated 1 time every two weeks, and whether the disease is improved by more than 20% is observed in each follow-up visit, and whether DAS28 is reached to be less than 2.4 in 12 weeks, if the DAS is reached, the treatment is effective, otherwise, the treatment is ineffective.
DAS28(Disease Activity Score in 28joints, mean Disease Activity Score of 28 joints).
DAS28(4) ═ 0.56 sqrt (t28) +0.28 sqrt (sw28) +0.70 ln (esr) +0.014 GH. (t 28: number of pain in 28 joints; sw 28: number of swollen joints in 28 joints; ESR: blood sedimentation; GH: patient's assessment of disease activity throughout the day (VAS score, unit 100mm), 28joints including 10 proximal interphalangeal joints in the hands, 10 metacarpophalangeal joints in the hands, 2 wrist joints, 2 elbow joints, 2 shoulder joints, 2 knee joints.) disease hyperactivity: not less than 5.1; low disease activity: < 3.2; and (3) relieving the disease condition: < 2.6.
ACR reaction criteria included: the degree of improvement in the number of tenderness of joints and the degree of improvement in the number of swelling of joints. And includes 3 of the following 5:
evaluation of pain by patients
Patient global assessment of disease activity
General evaluation of disease Activity by physicians
Evaluation of physical Functions by patients (HAQ)
Values of acute phase reactants (ESR, CRP)
Percent improvement of each index is (pre-treatment value-post-treatment value)/pre-treatment value x 100%
ACR 20: the improvement degree of the joint tenderness number and the joint swelling number is more than or equal to 20 percent, and the improvement degree of at least 3 of the other 5 items is more than or equal to 20 percent
ACR 50: the improvement degree of the joint tenderness number and the joint swelling number is more than or equal to 50 percent, and the improvement degree of at least 3 of the other 5 items is more than or equal to 50 percent
ACR 70: the improvement degree of the joint tenderness number and the joint swelling number is more than or equal to 70 percent, and the improvement degree of at least 3 of the other 5 items is more than or equal to 70 percent
9) And (4) safety observation: the functions of liver and kidney, the blood routine, the urine routine and the like are rechecked regularly, and the side effects which can not be endured by the serious patients occur,
or the patient is determined to have the symptoms caused by taking the medicine through clinical judgment when new medicine contraindications are found to be combined,
the original medicine is not used or reduced, and other medicines are used instead.
The method comprises the steps of taking tripterygium glycosides for 12 weeks by 40 RA patients, periodically detecting indexes of standard treatment according to follow-up examination during the period, dividing the RA patients into two groups according to a clinical survey scale, namely a standard treatment group and an unqualified treatment group, selecting 10 healthy volunteers as a control group, separating PBMCs of the patients, carrying out gene expression profile detection by using Affymetrix EG1.0 chip, scanning hybridized chips by using Affymetrix GeneChip Scanner 30007G Scanner to obtain chip original data, standardizing the original data, wherein the internal parameters are RPS18 gene and GAPDH gene respectively, screening differentially expressed mRNAs, wherein the screening standard is P value and Fold Change (Fold Change), screening an mRNA list related to individual difference of curative effect of tripterygium glycosides treatment RA by using a bioinformatics differential expression data analysis method, screening an mRNA list related to individual difference of curative effect of tripterygium glycosides treatment RA curative effect, establishing an mRNA coexpression which has significant coexpression correlation with other mRNA, wherein the target gene expression of the above-mRNAs and the above-related to the above-mentioned mRNA is obtained by using the related to the target gene expression of the above-related to the target gene expression of the above-related to the relevant gene is established mRNA, the related to the relevant gene expression of the target gene expression of the above-related to the relevant gene is established network, the relevant gene is established by the related to the target gene expression of the related to the target gene expression of the related to the target gene expression of the target gene of.
Based on the expression quantity of the biomarkers, a partial least square algorithm is adopted to construct a curative effect prediction model of tripterygium glycosides for individual treatment of RA, and the method specifically comprises the following steps: dividing an mRNA expression profile data set obtained by an mRNA expression profile chip detection technology into a training set and an independent test set at random, and repeating for 100 times; training the weight value (weight) and score threshold (cutoff) of each component (mRNA marker) in the model with a training set; performing performance evaluation by using an independent test set; repeatedly verifying for 100 times, and calculating the prediction accuracy and the mean value and standard deviation of the area under the ROC curve; performing quintupling cross validation to evaluate the stability of the model; the model is shown as formula (1).
F(c)＝sgn[f1(c1)+f2(c2)+f3(c3)+f4(c4)+f5(c5)+f6(c6)+b]Formula (1)
In the formula (1), F (c) represents the individual effectiveness of the tripterygium glycosides tablet in treating rheumatoid arthritis, F (c) returns that the value is 1 to represent effectiveness, and returns that the value is-1 to represent ineffectiveness; c. C1、c2、c3、c4、c5And c6Sequentially showing the relative expression amounts of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2; the relative expression amount refers to the ratio of the expression amount relative to an internal reference; f. of1(c1)、f2(c2)、f3(c3)、f4(c4)、f5(c5) And f6(c6) Respectively obtaining kernel functions obtained by training according to the modeling algorithm, and b obtaining critical score values obtained by training according to the modeling algorithm; specifically, when the GAPDH gene is used as an internal reference, in the formula (1), f1(c1)＝-0.4694×c1，f2(c2)＝-0.2494×c2，f3(c3)＝-0.5592×c3，f4(c4)＝0.3429×c4，f5(c5)＝0.4054×c5，f6(c6)＝0.3504×c6And b is-0.03, that is to say the discriminant function is specifically:
F(c)＝sgn(-0.4694×c1-0.2494×c2-0.5592×c3+0.3429×c4+0.4054×c5+0.3504×c6-0.03)
formula (2).
Specifically, when the RPS18 gene is used as an internal reference, in the formula (1), f1(c1)＝-0.3031×c1，f2(c2)＝-0.3644×c2，f3(c3)＝-0.6511×c3，f4(c4)＝0.3852×c4，f5(c5)＝0.2624×c5，f6(c6)＝0.3663×c6And b is-0.0036. That is, the discriminant function is specifically:
F(c)＝sgn(-0.3031×c1-0.3644×c2-0.6511×c3+0.3852×c4+0.2624×c5+0.3663×c6-0.0036)
formula (3).
Example 2
This example serves to illustrate the validation of the biomarkers and predictive models of the present disclosure.
60 RA patients are selected as independent test sets again, and the inclusion and exclusion criteria are the same as those in example 1; taking Tripterygium glycosides tablets for 12 weeks, periodically detecting index of standard treatment, and dividing RA patients into two groups according to clinical survey scale: a standard treatment group and a non-standard treatment group; the expression quantities of MX1, OASL, SPINK1, CRK, GRAPL and RNF2 in the independent test samples are detected by utilizing real-time quantitative PCR (qRT-PCR), the performance of a curative effect prediction model of the tripterygium glycosides individualized therapy RA is further verified, and evaluation indexes comprise area under the operating characteristic curve (ROC curve for short) of the recipients of prediction Accuracy (ACC). When the GAPDH gene was used as an internal reference, the ACC result of the discrimination formula (2) was 80.20%, and the AUC result was 0.825. When the RPS18 gene was used as an internal reference, the ACC result of the discrimination expression of expression (3) was 83.10%, and the AUC result was 0.802.
The primers used for real-time quantitative PCR (qRT-PCR) are shown in Table 2:
TABLE 2
Comparative example 1
In the same time of example 1, mRNA combinations different from the combination of MX1, OASL, SPINK1, CRK, GRAPL and RNF2 were selected from the screened differentially expressed mRNAs as biomarkers for evaluating Tripterygium glycosides tablet therapy, specifically ACTL6B, IGF1, RNF8, RPL23, GHR and ZNF 384.
When example 2 was carried out and the evaluation was carried out in the same manner as in example 2, it was revealed that the ACC result was 44.44% and the AUC result was 0.650 with the GAPDH gene as an internal reference. When the RPS18 gene was used as the reference, the ACC result was 58.12%, and the AUC result was 0.625.
Comparative example 2
The comparative example compares the expression levels of the six screened mRNAs, MX1, OASL, SPINK1, CRK, GRAPL and RNF2 alone or the average expression level thereof to predict the efficacy of tripterygium glycosides tablets, and the comparison results are shown in Table 3 and FIG. 1. The PLS model in fig. 1 is referred to RPS 18.
TABLE 3
Comparative example 3
The comparative example compares the prediction performance of the common clinical characteristic value on the curative effect of the tripterygium glycosides tablets with the prediction performance of a PLS model, and the results are shown in Table 4:
TABLE 4
According to the comparison between the example 2 and the comparative examples 1 to 3, the technical scheme of the disclosure provides a biomarker with high specificity and high sensitivity and a curative effect prediction model for the individualized diagnosis and treatment of rheumatoid arthritis.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
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Claims (9)
1. A system for determining the effectiveness of tripterygium glycosides for treating rheumatoid arthritis through the expression levels of a plurality of mRNAs is characterized by comprising a computing device, an input device for inputting the expression levels of a plurality of mRNAs of individuals suffering from rheumatoid arthritis and an output device for outputting the effectiveness of the tripterygium glycosides for treating the individuals suffering from rheumatoid arthritis; wherein the plurality of mRNAs comprises MX1, OASL, SPINK1, CRK, GRAPL, and RNF 2; the computing device comprises a memory having a computer program stored therein and a processor configured to execute the computer program stored in the memory to implement a modeling algorithm and an algorithm of a discriminant function as shown in equation (1); the modeling algorithm is a support vector machine algorithm and/or a minimum deviation two-times algorithm;
F(c)＝sgn[f1(c1)+f2(c2)+f3(c3)+f4(c4)+f5(c5)+f6(c6)+b]formula (1)
In the formula (1), F (c) represents the individual effectiveness of the tripterygium glycosides tablet in treating rheumatoid arthritis, F (c) returns that the value is 1 to represent effectiveness, and returns that the value is-1 to represent ineffectiveness; c. C1、c2、c3、c4、c5And c6Sequentially showing the relative expression amounts of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2; the relative expression amount refers to the ratio of the expression amount relative to an internal reference; f. of1(c1)、f2(c2)、f3(c3)、f4(c4)、f5(c5) And f6(c6) Respectively, kernel functions obtained by training according to the modeling algorithm, b is temporary functions obtained by training according to the modeling algorithmThe score value is bounded.
2. The system of claim 1, further comprising a plurality of means for detecting the expression level of mRNA.
3. The system of claim 2, wherein the means for detecting the expression levels of the plurality of mRNAs comprises an mRNA expression level detecting chip comprising probes for detecting the expression levels of MX1, OASL, SPINK1, CRK, GRAPL and RNF2, respectively, and a chip signal reader.
4. The system according to claim 3, wherein the mRNA expression level detection chip further comprises an internal reference probe, and the internal reference probe is a probe for detecting the expression level of RPS18 gene and/or GAPDH gene.
5. The system of claim 2, wherein the means for detecting the expression levels of the plurality of mRNAs comprises a real-time quantitative PCR instrument and real-time quantitative PCR primers for mRNAs, and the real-time quantitative PCR primers for mRNAs comprise real-time quantitative PCR primers for detecting the expression levels of MX1, OASL, SPINK1, CRK, GRAPL and RNF2, respectively.
6. The system of claim 5, wherein the real-time quantitative PCR primers for mRNA further comprise internal reference primers, wherein the internal reference primers are real-time quantitative PCR primers for detecting RPS18 gene and/or GAPDH gene.
7. The system according to claim 1, wherein in formula (1), f1(c1)＝-0.4694×c1，f2(c2)＝-0.2494×c2，f3(c3)＝-0.5592×c3，f4(c4)＝0.3429×c4，f5(c5)＝0.4054×c5，f6(c6)＝0.3504×c6B is-0.03; or, in the formula (1), f1(c1)＝-0.3031×c1，f2(c2)＝-0.3644×c2，f3(c3)＝-0.6511×c3，f4(c4)＝0.3852×c4，f5(c5)＝0.2624×c5，f6(c6)＝0.3663×c6，b＝-0.0036。
8. A molecular marker for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis, wherein the molecular marker is a plurality of mRNAs, and the mRNAs consist of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2.
9. The application of a reagent for detecting the expression quantity of a molecular marker in preparing a kit for determining the individual effectiveness of tripterygium glycosides tablets in treating rheumatoid arthritis is characterized in that the molecular marker is a plurality of mRNAs, and the mRNAs consist of MX1, OASL, SPINK1, CRK, GRAPL and RNF 2.
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