Application of primer sets for identifying polymorphic site combinations in the preparation of kits for predicting voriconazole blood concentrations and the kits themselves.

Abstract

This invention discloses the application of primer sets for identifying polymorphic site combinations in the preparation of a kit for predicting voriconazole metabolism, and the kit itself. The polymorphic site combinations include rs4244285, rs4986893, rs3740066, rs4149056, and rs4646437. This invention enables effective prediction of voriconazole blood concentrations, overcoming the lag and empirical limitations of traditional therapeutic drug monitoring.

Description

Technical Field

[0001] This invention relates to the field of biotechnology. More specifically, this invention relates to the application of a primer set for identifying polymorphic site combinations in the preparation of a kit for predicting voriconazole blood concentrations, and the kit itself. Background Technology

[0002] Voriconazole, a broad-spectrum triazole antifungal drug, is a core treatment for invasive aspergillosis after lung transplantation. Its efficacy and safety are highly dependent on precise control of the trough serum concentration. The therapeutic window of this drug is significantly narrow (1.5-5.5 mg / L); insufficient concentrations may lead to failure to clear the fungus, while excessively high concentrations can easily cause dose-limiting toxicities such as hepatotoxicity, neurological dysfunction, and visual abnormalities. Maintaining this therapeutic balance is particularly crucial for lung transplant patients with complex pathophysiological conditions.

[0003] Voriconazole's metabolic clearance is influenced by multiple factors. At the genetic level, CYP2C19 gene polymorphism is a core determinant; the US FDA and Health Canada have explicitly warned that slow metabolizers can have up to four times the drug exposure of fast metabolizers. Notably, in addition to CYP2C19 dominating metabolism, CYP3A4 isoenzymes and drug transporters (such as ABCB1 and SLCO2B1) jointly participate in its pharmacokinetic network, forming a multi-pathway interaction system. Simultaneously, non-genetic factors such as age, liver function status, and concomitant medications also play important roles. Furthermore, lung transplant recipients face unique pharmacokinetic challenges. Long-term use of calcineurin inhibitors (such as tacrolimus and cyclosporine) after lung transplantation competitively inhibits CYP3A4, further interfering with voriconazole clearance. Simultaneously, early postoperative inflammation can downregulate CYP enzyme activity, while stable liver function recovery requires dose upregulation.

[0004] Current clinical treatment-dependent drug monitoring (TDM) is used for dose adjustment, but it has significant limitations: lag: the first dose adjustment requires 72 hours after administration, delaying the optimal treatment time; empirical: it ignores the quantitative impact of genotype and drug interaction, leading to repeated trial and error; existing pediatric pharmacokinetic models cannot be extrapolated to the adult lung transplant population—the latter have more complex concomitant medications and more drastic dynamic changes in organ physiological state.

[0005] Therefore, there is an urgent need to develop a technical solution for predicting voriconazole blood concentrations in order to achieve precise dosing of voriconazole to lung transplant patients. Summary of the Invention

[0006] One object of the present invention is to provide an application of a primer set for identifying polymorphic site combinations in the preparation of a kit for predicting voriconazole blood concentration, and a kit thereof, which can effectively predict voriconazole blood concentration and overcome the lag and empirical limitations of traditional therapeutic drug monitoring.

[0007] To achieve these objectives and other advantages of the present invention, according to one aspect of the present invention, the present invention provides the use of primer sets for identifying polymorphic site combinations in the preparation of kits for predicting voriconazole blood concentrations, the polymorphic site combinations including rs4244285, rs4986893, rs3740066, rs4149056 and rs4646437 sites.

[0008] Further, the application method includes: S1: Obtaining the patient's basic vital signs parameters, including patient weight, body surface area, age, and number of days post-lung transplantation; S2: Obtaining the patient's blood biochemical parameters, including alanine aminotransferase (ALT) concentration, total bilirubin concentration, and urea concentration; S3: Obtaining the patient's concurrent medication status parameters, including whether the patient is concurrently using rabeprazole, atenolol, or ethambutol; S4: Obtaining the patient's tacrolimus blood concentration; S5: Identifying the genotypes of the rs4244285, rs4986893, rs3740066, rs4149056, and rs4646437 loci; S6: Inputting the parameters obtained in S1-S5 into a pre-established voriconazole blood concentration prediction formula, and outputting the voriconazole blood concentration.

[0009] Furthermore, the primer sets for identifying the rs4244285 site are shown in SEQ ID No. 1 and SEQ ID No. 2; the primer sets for identifying the rs4986893 site are shown in SEQ ID No. 3 and SEQ ID No. 4; the primer sets for identifying the rs3740066 site are shown in SEQ ID No. 5 and SEQ ID No. 6; the primer sets for identifying the rs4149056 site are shown in SEQ ID No. 7 and SEQ ID No. 8; and the primer sets for identifying the rs4646437 site are shown in SEQ ID No. 9 and SEQ ID No. 10.

[0010] Furthermore, the formula for predicting voriconazole blood concentration is as follows: ln(C t )=θ1+θ2·X_dw+θ3·X_bsa+θ4·X_age+θ5·X_pod+θ6·X_tac+θ7·X_alt+θ8·X_tbil+θ9·X_urea+θ 10 ·R+θ 11 ·A+θ 12 ·E+θ 13·G_c2a+θ 14 ·G_c2b+θ 15 ·G_abc+θ 16 ·G_slc+θ 17 ·I_ga+θ 18 ·I_gg+(1|ID);C tX_dw represents the blood concentration of voriconazole; X_dw represents the standardized dose-to-weight ratio, calculated as ln(dose / weight)-ln(1), where dose is the expected dose of voriconazole to be used by the patient and weight is the patient's weight; X_bsa represents the standardized body surface area, calculated as ln(BSA)-ln(1), where BSA is the patient's body surface area; X_age represents the standardized age, calculated as ln(age)-ln(60), where age is the patient's age; X_pod represents the standardized post-transplant days, calculated as ln(POD)-ln(1), where POD is the post-transplant days; X_tac represents the standardized tacrolimus... The blood drug concentration is calculated using the formula ln(Tac_conc)-ln(1), where Tac_conc is the patient's tacrolimus blood drug concentration; X_alt represents the standardized alanine aminotransferase (ALT) concentration, calculated using the formula ln(ALT)-ln(42), where ALT is the patient's ALT concentration; X_tbil represents the standardized total bilirubin concentration, calculated using the formula ln(Tbil)-ln(23), where Tbil is the patient's total bilirubin concentration; X_urea represents the standardized urea concentration, calculated using the formula ln(Urea)-ln(7.85), where Urea is the patient's urea concentration; R represents the rabeprazole dosing status, assigned a value of 0 if not used, and assigned a value if used. 1; A indicates atenolol treatment status, 0 for no use, 1 for use; E indicates ethambutol treatment status, 0 for no use, 1 for use; G_c2a indicates rs4244285 genotype, 0 for GG genotype, 1 for GA or AA genotype; G_c2b indicates rs4986893 genotype, 0 for GG genotype, 1 for GA or AA genotype; G_abc indicates rs3740066 genotype, 0 for CC genotype, 1 for CT genotype, 2 for TT genotype; G_slc indicates rs4149056 genotype, 0 for CC genotype, 1 for TC genotype, 2 for TT genotype; I _ga represents the interaction term between tacrolimus blood concentration and rs4646437 GA genotype. When the patient's rs4646437 genotype is GA, I_ga = X_tac × 1; when the patient's rs4646437 genotype is not GA, I_ga = 0. I_gg represents the interaction term between tacrolimus blood concentration and rs4646437 GG genotype. When the patient's rs4646437 genotype is GG, I_gg = X_tac × 2; when the patient's rs4646437 genotype is not GG, I_gg = 0. (1|ID) represents the individual random effect, assigned a value of 0 when predicting new patients. θ1, θ2, θ3, θ4...θ 18 is a coefficient.

[0011] Furthermore, the fixed effect value for θ1 is -5.2519, for θ2 it is 1.1183, for θ3 it is 2.6762, for θ4 it is 0.5777, for θ5 it is 0.1174, for θ6 it is 0.6078, for θ7 it is 0.1264, for θ8 it is 0.0577, and for θ9 it is 0.2004. 10 The value is 0.7626, θ 11 The value is -0.3207, θ 12 The value is -0.5744, θ 13 The value is 0.2399, θ 14 The value is 0.2541, θ 17 The value is -0.0395, θ 18 The value is -0.0513; when the patient's rs3740066 genotype is CT, θ 15 The value is 0.2455. When the patient's rs3740066 genotype is TT, θ 15 The value is -0.1356; when the patient's rs4149056 genotype is TC, θ 16 The value is 0.9347. When the patient's rs4149056 genotype is TT, θ 16 The value is 0.7592.

[0012] The present invention also provides a kit for predicting voriconazole blood concentrations, including primers for identifying rs4244285, rs4986893, rs3740066, rs4149056 and rs4646437 sites.

[0013] Furthermore, the primer sets for identifying the rs4244285 site are shown in SEQ ID No. 1 and SEQ ID No. 2; the primer sets for identifying the rs4986893 site are shown in SEQ ID No. 3 and SEQ ID No. 4; the primer sets for identifying the rs3740066 site are shown in SEQ ID No. 5 and SEQ ID No. 6; the primer sets for identifying the rs4149056 site are shown in SEQ ID No. 7 and SEQ ID No. 8; and the primer sets for identifying the rs4646437 site are shown in SEQ ID No. 9 and SEQ ID No. 10.

[0014] Furthermore, it also includes reagents for detecting alanine aminotransferase (ALT) concentration, aspartate aminotransferase (AST) concentration, total bilirubin concentration, urea concentration, and the patient's tacrolimus blood concentration.

[0015] The present invention has at least the following beneficial effects:

[0016] This invention achieves effective prediction of voriconazole blood concentration through specific polymorphic site combinations, integrating genetic factors with clinical dynamic parameters (such as dosage, body surface area, and concomitant medications), overcoming the lag and empirical limitations of traditional therapeutic drug monitoring, enabling early and precise intervention, optimizing antifungal treatment for adult lung transplant patients, with a clinical effective concentration prediction accuracy of 84.4%, helping to maintain therapeutic window balance and reduce the risk of toxic reactions and treatment failure.

[0017] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Attached Figure Description

[0018] Figure 1A The correlation between weight-corrected dose and voriconazole concentration is shown.

[0019] Figure 1B The correlation between body surface area (BSA) and voriconazole concentration is shown.

[0020] Figure 1C The correlation between age and voriconazole concentration is shown.

[0021] Figure 1D The correlation between body weight and voriconazole concentration is shown.

[0022] Figure 2 The correlation between predicted and actual voriconazole concentrations based on (A) the base model (which only includes dose / weight and body surface area) and (B) the final model. Detailed Implementation

[0023] The present invention will now be described in further detail so that those skilled in the art can implement it based on the description.

[0024] It should be understood that terms such as "having," "comprising," and "including" used in the embodiments of this application do not exclude the presence or addition of one or more other elements or combinations thereof. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationship and movement of components in a specific posture. If the specific posture changes, the directional indication will also change accordingly. When an element is referred to as "fixed to" or "set on" another element, it can be directly on the other element or may have an intervening element present. When an element is referred to as "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element through an intervening element. Descriptions involving "first," "second," etc., in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features.

[0025] It should be noted that the technical solutions of the various embodiments of this application can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by this application.

[0026] A single-center, regression cohort study was conducted to collect data from patients who underwent lung transplantation at the China-Japan Friendship Hospital between July 2017 and February 2023. The inclusion criteria were: (1) postoperative use of voriconazole; (2) postoperative use of tacrolimus immunosuppressive therapy; and (3) age greater than 18 years. The exclusion criteria were: (1) use of voriconazole for less than 5 days; (2) failure to participate in gene testing; and (3) failure of voriconazole concentration to reach steady state (continuous use of the same dose for more than 5 days).

[0027] The study included 76 patients, from whom 441 steady-state voriconazole blood concentration measurements were recorded. Furthermore, pre-voriconazole parameters were collected, specifically: baseline vital signs (including weight, body surface area, age, and number of days post-lung transplantation); blood biochemical parameters (including alanine aminotransferase (ALT), total bilirubin, and urea); concomitant medication status (whether the patient was concurrently using rabeprazole, atenolol, or ethambutol); tacrolimus blood concentration; and single nucleotide polymorphism (SNP) testing was performed to identify genotypes at the rs4244285, rs4986893, rs3740066, rs4149056, and rs4646437 loci.

[0028] The primer sets for identifying the rs4244285 locus are shown in SEQ ID No. 1 and SEQ ID No. 2; the primer sets for identifying the rs4986893 locus are shown in SEQ ID No. 3 and SEQ ID No. 4; the primer sets for identifying the rs3740066 locus are shown in SEQ ID No. 5 and SEQ ID No. 6; the primer sets for identifying the rs4149056 locus are shown in SEQ ID No. 7 and SEQ ID No. 8; and the primer sets for identifying the rs4646437 locus are shown in SEQ ID No. 9 and SEQ ID No. 10.

[0029] SEQ ID No.1:ACAACCAGAGCTTGGCATATTG

[0030] SEQ ID No.2:CCCGAGGGTTGTTGATGTCC

[0031] SEQ ID No.3: CTGCTCCATTATTTTCCAGAAACG

[0032] SEQ ID No.4:AAAGACTGTAAGTGGTTTCTCAGG

[0033] SEQ ID No.5: TAAGAGGCCTCCGCCAGATT

[0034] SEQ ID No.6: CCATCCAGGCCTTCCTTCAC

[0035] SEQ ID No.7: ATAGGTTGTTTAAAGGAATCTGGG

[0036] SEQ ID No.8: AGAAAGCCCCAATGGTACTA

[0037] SEQ ID No.9:CCCTCTTTCAGGCCAGTGG

[0038] SEQ ID No.10:CAAGGGGCTGCTGATCTCAC

[0039] Patient baseline information before voriconazole use is shown in Table 1.

[0040] Table 1 Baseline information of the study population

[0041]

[0042] All detected SNP sites are shown in Table 2.

[0043] Table 2. Information on the SNPs to be tested and their distribution in the study population.

[0044]

[0045] Table 2 shows all the SNPs tested in this study. All SNPs were in Hardy-Weinberg equilibrium and all sites were included in further analysis.

[0046] We used a linear mixed-effects model to comprehensively validate the effects of various factors on voriconazole concentration. Data were analyzed using the lmer package in the statistical computing language R; voriconazole concentrations below the limit of quantitation (LLOQ, 0.1 mg / L) were defined as 0.05 mg / L; the core model was: ln(concentration) ~ ln(dose / weight) + covariate + (1|subject ID); the effects of clinical factors, genetic information, and concomitant medications on voriconazole concentration were validated. First, we plotted the effects of baseline factors such as dose (weight-corrected dose), body surface area, age, and sex on voriconazole concentration. Figure 1A-Figure 1D The study found that weight-corrected dose and body surface area had a significant effect on voriconazole concentration. Body surface area was further incorporated into the construction of the basic model. That is: ln(C) t ) = i 1+ i 2×(ln(dose / weight)-ln(1mg / kg))+ i 3×(ln(BSA)-ln(1m 2 Age and sex did not show a significant effect on voriconazole concentration and were not included in the baseline model.

[0047] The subsequent inclusion of covariates was carried out on the basic model. The forms of covariate inclusion included the following: (1) When the covariate is a continuous variable (ALT, AST, POD, tacrolimus concentration, etc.), the difference between the logarithmic (ln) value and the logarithmic (ln) reference value is used, that is: ln (variable value) - ln (variable reference value); (2) Factor variables (sex, route of administration, fungal treatment type) are included in the form of factor level (0, 1 or 0, 1, 2, etc.); (3) The numerical value of combined medication is expressed as 0 (no combined medication on the day) and 1 (combined medication on the day); (4) Gene information is expressed as 0 (reference genotype), 1 (heterozygous) or 2 (homozygous variant gene), or 0 (reference genotype) and 1 (heterozygous + homozygous variant gene), and the inclusion of the gene in the model is determined according to the specific meaning of the gene in the form of binary classification (G_c2a, G_c2b, I_ga, I_gg) or tri-class classification (G_abc and G_slc). The genotype was used as the grouping factor with a random intercept, based on the subject pseudo-identifier (ID).

[0048] In the process of building the model, the patient's weight-corrected dose, body surface area, age, sex, transplant type, treatment start time, type of fungal treatment, and biochemical indicators (including ALT, AST, Tbil, Dbil, Urea, UA, CR, and HCT) were first evaluated as potential covariates. The corresponding residuals (ln(measured concentration) - ln(predicted concentration)) were plotted against concomitant medications and gene variants. Then, concomitant medications and gene variants with suspected differences in residuals were evaluated as covariates in the model. Finally, the interaction between drugs and genes was tested. If the corresponding p-value of the effect (or interaction) was <0.05 and the -2 log-likelihood value (-2LL) decreased significantly (the -2LL difference was >3.84 for each additional degree of freedom), the covariate was included in the model. The model was constructed by alternately adding and removing covariates or interactions.

[0049] The final generated model is:

[0050] ln(C t )=θ1+θ2·X_dw+θ3·X_bsa+θ4·X_age+θ5·X_pod+θ6·X_tac+θ7·X_alt+θ8·X_tbil+θ9·X_urea+θ 10 ·R+θ 11 ·A+θ 12 ·E+θ 13 ·G_c2a+θ 14 ·G_c2b+θ 15 ·G_abc+θ 16 ·G_slc+θ 17 ·I_ga+θ18 ·I_gg+(1|ID);

[0051] C t This indicates the blood concentration of voriconazole;

[0052] X_dw represents the standardized dose-to-weight ratio, calculated as ln(dose / weight)-ln(1), where dose is the expected dose of voriconazole to be used by the patient, and weight is the patient's weight;

[0053] X_bsa represents the standardized body surface area, and the calculation formula is ln(BSA)-ln(1), where BSA is the patient's body surface area;

[0054] X_age represents the standardized age, calculated using the formula ln(age)-ln(60), where age is the patient's age (in years).

[0055] X_pod represents the standardized post-transplantation days, calculated using the formula ln(POD)-ln(1), where POD is the number of days post-lung transplantation.

[0056] X_tac represents the standardized tacrolimus blood concentration, calculated using the formula ln(Tac_conc)-ln(1), where Tac_conc is the patient's tacrolimus blood concentration.

[0057] X_alt represents the standardized alanine aminotransferase concentration, and the calculation formula is ln(ALT)-ln(42), where ALT is the patient's alanine aminotransferase concentration;

[0058] X_tbil represents the standardized total bilirubin concentration, and the calculation formula is ln(Tbil)-ln(23), where Tbil is the patient's total bilirubin concentration;

[0059] X_urea represents the standardized urea concentration, calculated using the formula ln(Urea)-ln(7.85), where Urea is the patient's urea concentration.

[0060] R indicates the status of rabeprazole use; 0 is assigned when not in use and 1 is assigned when in use.

[0061] A represents the status of atenolol use; 0 is assigned when not in use and 1 is assigned when in use.

[0062] E represents the status of ethambutol use; 0 is assigned when not in use and 1 is assigned when in use.

[0063] G_c2a represents the rs4244285 genotype, with GG genotype assigned a value of 0 and GA or AA genotype assigned a value of 1;

[0064] G_c2b represents the rs4986893 genotype, with a value of 0 for the GG genotype and 1 for the GA or AA genotype;

[0065] G_abc represents the rs3740066 genotype, CC genotype is assigned a value of 0, CT genotype is assigned a value of 1, and TT genotype is assigned a value of 2.

[0066] G_slc represents the rs4149056 genotype, with CC genotype assigned a value of 0, TC genotype assigned a value of 1, and TT genotype assigned a value of 2;

[0067] I_ga represents the interaction between tacrolimus blood concentration and rs4646437 GA genotype. When the patient's rs4646437 genotype is GA, I_ga = X_tac × 1; when the patient's rs4646437 genotype is not GA, I_ga = 0.

[0068] I_gg represents the interaction term between tacrolimus blood concentration and rs4646437GG genotype. When the patient's rs4646437 genotype is GG, I_gg = X_tac × 2. When the patient's rs4646437 genotype is not GG, I_gg = 0.

[0069] (1|ID) represents the individual random effect, assigned a value of 0 for new patients; if it is necessary to predict the concentration of a specific individual (the individual used in model construction), its random effect must be considered: the value of the random effect follows a normal distribution N(0, σ²_id), where σ_id = 0.298 (Table 1). During calculation, the value is derived from N(0, 0.298). 2 A random value b_i (representing the random offset of the individual) is extracted from the formula and substituted into it for calculation.

[0070] The following are examples of 10 IDs corresponding to (1|ID): ZRLT001: -0.133788359; ZRLT002: 0.005826071; ZRLT003: 0.103545152; ZRLT004: 0.107865396; ZRLT005: 0.067198467; ZRLT007: -0.298297015; ZRLT009: 0.060090301; ZRLT010: ​​-0.027757161.

[0071] For a detailed description of each variable parameter, please refer to Table 3. i 1 to i 18 The values ​​are all the corresponding values ​​in the fixed effects column of Table 3. i The two values ​​represent the expected dose of voriconazole used by the patient. i Three items represent the patient's body surface area. i The four items represent the patient's age. i The five items represent the number of days after transplantation. i Six items represent recent tacrolimus concentrations. i 7 to i Nine biochemical indicators representing the patient's own health status were used; the corresponding variables simply needed to be input from the patient's actual values ​​during the calculation. i 10 to i 12 The item represents combined medication (0 indicates no combined medication, 1 indicates combined medication). i 13 to i 16 This item represents the patient's genetic testing (0 if the genotype at the corresponding locus is the reference genotype; otherwise, it is calculated according to its respective fixed effect, specifically: i 13 In CYP2C19 rs4244285, GA and AA are assigned the value 1; i 14 In CYP2C19 rs4986893, GA and AA are assigned the value 1; i 15 ABCC2 rs3740066 CT is assigned the value 1. i 15 ABCC2rs3740066 TT is assigned the value 2; i 16 SLCO1B1 rs4149056 TC is assigned the value 1. i 16 SLCO1B1 rs4149056 TT is assigned the value 2). i 17 to i 18 The term represents the interaction term. i 17 ln(Tacrolimus concentration, ng / mL) - ln(1 ng / mL): rs4646437GA. In this case, rs4646437GA is assigned a value of 1, and its interaction is calculated by multiplying it by the ln value of the Tacrolimus concentration. i 18 ln(Tacrolimus concentration, ng / mL) - ln(1ng / mL): rs4646437GG is assigned a value of 2, and the interaction is calculated by multiplying the tacrolimus concentration ln value.

[0072] Table 3 Fitting parameters and reference values ​​of the final model

[0073]

[0074] We compared the fit between the base model (the model using only weight-corrected dose and body surface area) and the final model with the actually measured concentration values, and the results are as follows: Figure 2 As shown. The final model has a good fit to voriconazole concentration ( ). Figure 2 B). Final model R² (fixed + random effects): 0.6645549, marginal R² (fixed effects only): 0.4634273. Correlation between predicted and actual concentrations: r = 0.749, p < 0.001. Accuracy in predicting clinically effective concentrations: 84.4%.

[0075] In clinical applications, a kit for predicting voriconazole blood concentrations was constructed. This kit includes primers for identifying rs4244285, rs4986893, rs3740066, rs4149056, and rs4646437 loci, as well as reagents for detecting alanine aminotransferase (ALT), total bilirubin, urea, and tacrolimus blood concentrations. Basic patient vital signs parameters, including weight, body surface area, age, and number of days post-lung transplantation, were obtained. Blood biochemical parameters and tacrolimus blood concentrations, including ALT, total bilirubin, and urea, were obtained using the kit. Concomitant medication status parameters, including whether the patient was concurrently using rabeprazole, atenolol, or ethambutol, were also obtained. The obtained parameters and the intended dosage were input into the final model to obtain the predicted voriconazole concentration in that scenario, allowing for determination of dosage appropriateness and achieving the goal of individualized dosing. Tests have shown that the above parameters, obtained within 5 days, have a high accuracy rate.

[0076] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and embodiments shown and described herein.

Claims

1. Use of a primer set of a combination of polymorphic sites in the preparation of a kit for predicting the blood concentration of voriconazole, characterized in that, The combination of polymorphic sites includes rs4244285 site, rs4986893 site, rs3740066 site, rs4149056 site and rs4646437 site; The application method comprises: S1: acquiring patient basic vital sign parameters, the basic vital sign parameters including patient weight, body surface area, age and post-lung transplantation days; S2: acquiring patient blood biochemical index parameters, the blood biochemical index parameters including glutamic-pyruvic transaminase concentration, total bilirubin concentration and urea concentration; S3: acquiring patient combined medication state parameters, the combined medication state parameters including whether the patient simultaneously uses rabeprazole, atenolol or ethambutol; S4: acquiring patient tacrolimus blood drug concentration; S5: identifying the genotypes of rs4244285 site, rs4986893 site, rs3740066 site, rs4149056 site and rs4646437 site; S6: inputting the parameters acquired in S1-S5 into a pre-established voriconazole blood drug concentration prediction formula, and outputting the voriconazole blood drug concentration; The voriconazole blood drug concentration prediction formula is as follows: ln(C t )=θ1+θ2·X_dw+θ3·X_bsa+θ4·X_age+θ5·X_pod+θ6·X_tac+θ7·X_alt+θ8·X_tbil+θ9·X_urea+θ 10 ·R+θ 11 ·A+θ 12 ·E+θ 13 ·G_c2a+θ 14 ·G_c2b+θ 15 ·G_abc+θ 16 ·G_slc+θ 17 ·I_ga+θ 18 ·I_gg+(1|ID); C t Voriconazole plasma concentration is represented by C; X_dw represents a standardized dose-weight ratio, the calculation formula being ln(dose / weight)-ln(1), dose being the expected voriconazole dose of the patient, and weight being the patient weight; X_bsa represents a standardized body surface area, the calculation formula being ln(BSA)-ln(1), BSA being the patient body surface area; X_age represents a standardized age, the calculation formula being ln(age)-ln(60), age being the patient age; X_pod represents a standardized post-transplantation day, the calculation formula being ln(POD)-ln(1), POD being the post-lung transplantation day; X_tac represents a standardized tacrolimus blood drug concentration, the calculation formula being ln(Tac_conc)-ln(1), Tac_conc being the patient tacrolimus blood drug concentration; X_alt represents a standardized glutamic-pyruvic transaminase concentration, the calculation formula being ln(ALT)-ln(42), ALT being the patient glutamic-pyruvic transaminase concentration; X_tbil represents a standardized total bilirubin concentration, the calculation formula being ln(Tbil)-ln(23), Tbil being the patient total bilirubin concentration; X_urea represents a standardized urea concentration, the calculation formula being ln(Urea)-ln(7.85), Urea being the patient urea concentration; R represents the rabeprazole medication state, and is assigned a value of 0 when not used and a value of 1 when used; A represents the atenolol medication state, and is assigned a value of 0 when not used and a value of 1 when used; E represents the ethambutol medication state, and is assigned a value of 0 when not used and a value of 1 when used; G_c2a represents the rs4244285 genotype, and is assigned a value of 0 when the genotype is GG, and a value of 1 when the genotype is GA or AA; G_c2b represents the rs4986893 genotype, and is assigned a value of 0 when the genotype is GG, and a value of 1 when the genotype is GA or AA; G_abc represents the rs3740066 genotype, and is assigned a value of 0 when the genotype is CC, a value of 1 when the genotype is CT, and a value of 2 when the genotype is TT; G_slc represents rs4149056 genotype, CC genotype is assigned 0, TC genotype is assigned 1, and TT genotype is assigned 2; I_ga represents the interaction term of tacrolimus blood concentration and rs4646437 GA genotype, when the patient's rs4646437 genotype is GA, I_ga = X_tac * 1, when the patient's rs4646437 genotype is not GA, I_ga = 0; I_gg represents the interaction term of tacrolimus blood concentration and rs4646437 GG genotype, when the patient's rs4646437 genotype is GG, I_gg = X_tac * 2, when the patient's rs4646437 genotype is not GG, I_gg = 0; (1|ID) represents the individual random effect, which is assigned 0 when predicting a new patient; The fixed effect value of θ1 is -5.2519, the fixed effect value of θ2 is 1.1183, the fixed effect value of θ3 is 2.6762, the value of θ4 is 0.5777, the value of θ5 is 0.1174, the value of θ6 is 0.6078, the value of θ7 is 0.1264, the value of θ8 is 0.0577, the value of θ9 is 0.2004, the value of θ 10 is 0.7626, the value of θ 11 is -0.3207, the value of θ 12 is -0.5744, the value of θ 13 is 0.2399, the value of θ 14 is 0.2541, the value of θ 17 is -0.0395, the value of θ 18 is -0.0513; When the patient rs3740066 genotype is CT, the value of θ 15 is 0.2455, and when the patient rs3740066 genotype is TT, the value of θ 15 is -0.1356. When the patient rs4149056 genotype is TC, the value of 0 16 is 0.9347, and when the patient rs4149056 genotype is TT, the value of 0 16 is 0.7592.

2. Use of the primer set of the combination of the polymorphic sites according to claim 1 for the manufacture of a kit for predicting the blood concentration of voriconazole, characterized in that, The primer set for identifying the rs4244285 site is shown in SEQ ID No. 1 and SEQ ID No. 2; The primer set for identifying the rs4986893 site is shown in SEQ ID No. 3 and SEQ ID No. 4; The primer set for identifying the rs3740066 site is shown in SEQ ID No. 5 and SEQ ID No. 6; The primer set for identifying the rs4149056 site is shown in SEQ ID No. 7 and SEQ ID No. 8; The primer set for identifying the rs4646437 site is shown in SEQ ID No. 9 and SEQ ID No. 10.

Images