Method, apparatus and device for determining target drug for predetermined tissue

Abstract

This application provides a method, apparatus, and device for identifying target drugs for predetermined tissues, relating to the field of bioinformatics. The method includes: acquiring multiple candidate drugs for a predetermined disease; identifying all target genes for each candidate drug; identifying quantitative trait gene loci (CTTLs) of target gene expression in a predetermined tissue based on all target genes; using these CTTLs as genetic instrumental variables and employing Mendelian randomization analysis, determining the potential causal relationship between the expression of the combined target genes of the candidate drugs in the predetermined tissue and the predetermined disease; and identifying the target drug for the predetermined tissue based on the potential causal relationship. This method can clearly identify the potential tissue type for drug action, effectively identify target drugs for predetermined tissues, improve the targeting of drug therapy, and reduce drug side effects.

Description

Technical Field

[0001] This application relates to the field of bioinformatics, and more specifically, to methods, apparatus, and equipment for identifying target drugs for predetermined tissues. Background Technology

[0002] With the advancement of precision medicine, personalized treatment and targeted drug therapy for different diseases have become hot topics in current medical research. Tissue-specific drug targeting can not only improve treatment efficacy but also reduce side effects, making it an important direction in modern drug development.

[0003] However, for specific diseases, it is currently difficult to identify tissue-specific drugs among numerous options, which may lead to poor treatment efficacy and significant side effects. Summary of the Invention

[0004] This application proposes a method, apparatus, and device for identifying targeted drugs for a predetermined tissue. The method is used to screen for drugs that are tissue-specific for a specific disease, thereby improving the targeting of drug therapy and reducing drug side effects.

[0005] Specifically, this application provides the following technical solution:

[0006] In a first aspect, this application proposes a method for identifying a target drug for a predetermined tissue. According to an embodiment of this application, the method includes: acquiring multiple candidate drugs for a predetermined disease; identifying all target genes for each candidate drug based on the multiple candidate drugs; identifying quantitative trait loci (QTLs) of expression of all target genes in a predetermined tissue based on the target genes; using the QTLs as genetic instrumental variables and employing Mendelian randomization analysis, determining a potential causal relationship between the combined expression of the target genes of the candidate drugs in the predetermined tissue and the predetermined disease; and identifying a target drug for the predetermined tissue based on the potential causal relationship.

[0007] In some examples of this application, the step of using Mendelian randomization analysis to determine the potential causal relationship between the expression of the comprehensive target gene of the candidate drug in a predetermined tissue and the predetermined disease includes: summarizing the effects of all genetic instrumental variables using an inverse variance weighted method to determine an overall causal estimate between the expression of the comprehensive target gene of the candidate drug in a predetermined tissue and the predetermined disease.

[0008] In some examples of this application, the step of summarizing the effects of all genetic instrumental variables using the inverse variance weighting method to determine the overall causal estimate between the expression of all target genes of the candidate drug in a specific tissue and the predetermined disease includes: performing sensitivity analysis on the overall causal estimate using multiple analytical methods to verify that there is a potential causal relationship between the expression of the comprehensive target genes of the candidate drug in a specific tissue and the predetermined disease.

[0009] In some examples of this application, the sensitivity analysis methods include: weighted median method, weighted pattern method, MR-Egger regression method, Cochran's Q test or MR-Egger intercept test.

[0010] In some examples of this application, a multiple test correction method is used to correct the sensitivity analysis results.

[0011] In some examples of this application, the genetic instrumental variable must simultaneously meet the following conditions: a. It is located within a 100kb region upstream or downstream of the target gene; b. It is statistically significant with the downstream disease phenotype affected by the drug, P < 0.05; c. It is significantly correlated with the expression of the target gene of the candidate drug in a specific tissue, P < 5 × 10⁻⁶. -8 d. Chain disequilibrium threshold r 2 It is 0.1.

[0012] In some examples of this application, determining a target drug for the predetermined tissue based on the potential causal relationship includes: i) determining a causal association between the comprehensive target genes of the candidate drug in the predetermined tissue and the predetermined disease based on the genetic instrumental variable; ii) determining a target drug for the predetermined tissue based on the causal association.

[0013] In a second aspect, this application proposes a target drug identification device for a predetermined tissue. According to an embodiment of this application, the device includes: a candidate drug acquisition module for acquiring multiple candidate drugs for a predetermined disease; a target gene identification module for identifying all target genes of each candidate drug based on the multiple candidate drugs; a causal reasoning module for determining the expression quantitative trait loci of all target genes in the predetermined tissue based on the target genes, using the expression quantitative trait loci as genetic instrumental variables, and employing Mendelian randomization analysis to determine the potential causal relationship between the expression of the combined target genes of the candidate drugs in the predetermined tissue and the predetermined disease; and a target drug identification module for identifying a target drug for the predetermined tissue based on the potential causal relationship.

[0014] In a third aspect, this application proposes an electronic device. According to an embodiment of this application, the electronic device includes: a processor and a memory; the memory for storing a computer program; and the processor for executing the computer program to implement the target drug determination method for a predetermined tissue as described in the first aspect.

[0015] In a fourth aspect, this application provides a computer-readable storage medium. According to an embodiment of this application, the computer-readable storage medium stores computer instructions or programs that, when executed on a computer, cause the method for determining a target drug for a predetermined tissue as described in the first aspect to be performed.

[0016] The technical solution of this application can clearly identify the potential tissue types for drug action, effectively determine the target drug for the predetermined tissue, improve the targeting of drug therapy, and reduce drug side effects.

[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This application provides some examples of a flowchart illustrating a method for identifying a target drug for a predetermined organization;

[0020] Figure 2 These are schematic diagrams of a target drug determination device for a predetermined tissue, provided in some examples of this application;

[0021] Figure 3 These are schematic diagrams of electronic devices provided in this application;

[0022] Figure 4 These are schematic diagrams illustrating the effects of cardiovascular and metabolic drugs on diseases in an organizational context, provided by some examples in this application. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0025] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0026] As mentioned above, the current availability of tissue-specific drugs for specific diseases leads to poor treatment efficacy and significant side effects. To address this technical problem, this application proposes a method for determining target drugs for a predetermined tissue.

[0027] The technical solution of this application will be described in detail below:

[0028] Figure 1 This is a flowchart illustrating a method for identifying a target drug in a predetermined tissue, provided as an embodiment of this application. The method can be executed by a device, such as a computing device, a computer program product, a computer-readable storage medium, etc., but is not limited thereto. Figure 1 As shown, the method may include:

[0029] S100, to obtain multiple drug candidates for a predetermined disease;

[0030] In some examples of this application, the aforementioned predetermined disease may be one or more. For example, the predetermined disease is selected from cardiovascular metabolic diseases. The aforementioned cardiovascular metabolic diseases include at least one of type 2 diabetes (T2D), coronary artery disease (CAD), or abdominal aortic aneurysm (AAA).

[0031] Once the disease type is determined, candidate drugs for that disease can be obtained through publicly available medical literature or disease treatment guidelines. In some examples of this application, the aforementioned candidate drugs include at least one of the following: sulfonylureas, hypoglycemic agents, statins, or calcium channel blockers.

[0032] For example, the predetermined disease is type II diabetes, and the candidate drugs may be selected from a variety of drugs, including gliburide, glipizide, glimepiride, metformin, repaglinide, or nateglinide.

[0033] It is understandable that the above is just an example. For other types of diseases, there are also multiple candidate drugs for the disease, which will not be elaborated here.

[0034] S200, based on the multiple candidate drugs, determine all target genes for each candidate drug;

[0035] In some examples of this application, based on the candidate drugs selected in step S100, all target genes for each candidate drug are identified using publicly available drug databases (such as DrugBank, ChEMBL, etc.). It is understood that all the aforementioned target genes can be any target genes that interact with the candidate drug.

[0036] S300, based on the target genes, determine the expression quantitative trait loci (eQTLs) of all target genes in a predetermined tissue, and use the eQTLs as genetic instrumental variables, employing Mendelian randomization analysis, to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drug in the predetermined tissue and the predetermined disease.

[0037] Based on multiple target genes, eQTLs associated with predetermined tissues are obtained from publicly available databases (such as GTEx). In this application, the aforementioned eQTLs refer to genomic regions associated with changes in gene expression levels. Specifically, an eQTL is a regulatory genetic variation that regulates gene activity and expression patterns by affecting RNA-level expression.

[0038] In some examples of this application, the predetermined tissue may include at least one of the following: liver, pancreas, aorta, skeletal muscle, subcutaneous fat, visceral fat, coronary artery, or whole blood.

[0039] Further screening of the obtained eQTLs from the predetermined tissues, and Mendelian randomization analysis of the screened eQTLs as genetic instrumental variables, to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drug in the predetermined tissues and the predetermined disease.

[0040] In some examples of this application, to be used as a genetic instrumental variable, it must simultaneously meet the following conditions: a. located within a 100kb region upstream or downstream of the target gene; b. statistically significant with the downstream disease phenotype affected by the drug, P < 0.05; c. significantly correlated with the expression of the target gene of the candidate drug in a specific tissue, P < 5 × 10⁻⁶. -8 d. Chain disequilibrium threshold r 2 The value was 0.1. By setting multiple conditions for screening genetic instrumental variables (including target gene distance, biological relevance, statistical significance, and linkage disequilibrium independence), the reliability and accuracy of instrumental variables in causal inference were achieved. This not only ensures the true association between the screened genetic variations and target genes, candidate drugs, and diseases, but also reduces variable redundancy and improves analytical efficiency.

[0041] Using qualified eQTLs as genetic instrumental variables, Mendelian randomization analysis was employed to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drugs in predetermined tissues and the predetermined disease.

[0042] In this application, Mendelian randomization (MR) is a method that uses genetic variation as an instrumental variable to infer the causal relationship between an exposure factor and an outcome. Its core idea is to utilize the random allocation characteristics of genetic variation to avoid the interference of confounding factors and reverse causal relationships on causal inference, which are common in traditional observational studies. Mendelian randomization analysis relies on three basic assumptions: the instrumental variable is significantly associated with the exposure factor; the instrumental variable is not associated with potential confounding factors; and the instrumental variable only affects the outcome through the exposure factor and does not directly affect the outcome.

[0043] In Mendelian randomization analysis, the first step is to select genetic variations significantly associated with the exposure factor as instrumental variables, such as expressed quantitative trait loci (eQTLs). These instrumental variables can indirectly reflect the influence of the exposure factor by regulating gene expression levels. Subsequently, association analysis is used to estimate the regulatory effect of the instrumental variables on exposure and their impact on the outcome. Finally, the effect data of multiple instrumental variables are integrated, and statistical methods (such as inverse variance weighting) are used to calculate the overall causal effect estimate, thereby inferring the potential causal relationship between exposure and outcome.

[0044] In this application, Mendelian randomization is used to analyze the causal relationship between candidate drug target genes and diseases, and to screen for target drugs targeting predetermined tissues. Specifically, firstly, the expression quantitative trait loci (eQTLs) of candidate drug target genes in predetermined tissues are used as genetic instrumental variables. These instrumental variables are the main regulators of target gene expression and can reflect changes in gene expression levels. Subsequently, Mendelian randomization analysis is used to infer the potential causal relationship between the expression level of target genes in predetermined tissues and predetermined diseases using these instrumental variables.

[0045] In the causal effect analysis, this approach uses the inverse variance weighted method to summarize the effects of multiple instrumental variables and calculate the overall causal estimate between the expression of candidate drug target genes in the predetermined tissues and the disease. This process can accurately screen target genes with significant causal effects, thus providing a reliable basis for the screening of target drugs. Finally, based on the causal analysis results, target drugs that can effectively act on the predetermined tissues are identified.

[0046] Specifically, this includes: summarizing the effects of all genetic instrumental variables using an inverse variance weighting method to determine an overall causal estimate between the expression of the comprehensive target gene of the candidate drug in a predetermined tissue and the predetermined disease.

[0047] Furthermore, sensitivity analysis was used to verify the robustness of the overall causal estimate, confirming a potential causal relationship between the expression of the comprehensive target genes of the candidate drug in specific tissues and the predetermined disease. Sensitivity analysis can verify the robustness and reliability of the research results. Validation using different analytical methods can eliminate the influence of genetic pleiotropy on the results, ensuring the accuracy of causal relationship inferences. Sensitivity analysis can also help assess the heterogeneity among instrumental variables, identifying potential problems, such as inconsistencies between some instrumental variables and the overall analysis results, suggesting the need for further model adjustments.

[0048] The methods used for the aforementioned sensitivity analysis include: weighted median method, weighted pattern method, MR-Egger regression method, Cochran's Q test, or MR-Egger intercept test.

[0049] Based on the above sensitivity analysis results, a multiple test correction method was employed to correct the results. Multiple test correction (such as FDR correction) effectively reduces the risk of false positives in multiple statistical tests. Without correction, numerous accidental significant results may occur during multiple tests, leading to erroneous conclusions. Multiple test correction controls the global significance level, ensuring the high reliability of the final selected results.

[0050] S400, based on the potential causal relationship, determine the target drug for the predetermined tissue.

[0051] The aforementioned determination of target drugs for the predetermined tissue based on the potential causal relationship includes: i) determining the causal association between the comprehensive target genes of candidate drugs in the predetermined tissue and the predetermined disease based on the genetic instrumental variables; for example, if the expression level of a target gene of a candidate drug in liver tissue is related to the occurrence of diabetes, then a causal association between the target gene of the drug in liver tissue and diabetes can be determined. ii) determining target drugs for the predetermined tissue based on the causal association. For example, if a target gene of a drug is found to have a significant causal relationship with diabetes in liver tissue, then that drug is likely to become a target drug for the treatment of diabetes. Through this screening process, it is possible to identify which drugs are most suitable for the treatment of diseases in specific tissues, thereby improving treatment efficacy and reducing side effects.

[0052] Targeted drug identification device for a predetermined organization

[0053] On the other hand, this application proposes a target drug determination device for a predetermined tissue, referring to... Figure 2 The device 200 includes: a candidate drug acquisition module 210, a target gene determination module 220, a causal reasoning module 230, and a target drug determination module 240. Specifically, the candidate drug acquisition module 210 is used to determine all target genes for each candidate drug based on the multiple candidate drugs; the target gene determination module 220 is used to determine all target genes for each candidate drug based on the multiple candidate drugs; the causal reasoning module 230 is used to determine the expression quantitative trait loci of all target genes in a predetermined tissue based on the target genes, and using the expression quantitative trait loci as genetic instrumental variables, employs Mendelian randomization analysis to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drugs in the predetermined tissue and the predetermined disease; and the target drug determination module 240 determines the target drug for the predetermined tissue based on the potential causal relationship.

[0054] In some examples of this application, the causal reasoning module 230 is specifically used to: determine a genetic instrumental variable based on all of the following conditions: a. located 100kb upstream or 100kb downstream of the target gene; b. statistically significant with the downstream disease phenotype affected by the drug, P < 0.05; c. significantly correlated with the expression of multiple target genes of the candidate drug in a specific tissue, P < 5 × 10⁻⁶. -8 d. Chain disequilibrium threshold r 2 It is 0.1.

[0055] In some examples of this application, the causal reasoning module 230 is specifically used to: summarize the effects of all genetic instrumental variables using an inverse variance weighting method to determine an overall causal estimate between the expression of the comprehensive target gene of the candidate drug in a predetermined tissue and the predetermined disease.

[0056] In some examples of this application, the causal reasoning module 230 is specifically used to: verify the robustness of the overall causal estimate through sensitivity analysis, and confirm that there is a potential causal relationship between the expression of the comprehensive target genes of the candidate drug in a specific tissue and the predetermined disease.

[0057] In some examples of this application, the sensitivity analysis includes: weighted median method, weighted pattern method, MR-Egger regression method, Cochran's Q test or MR-Egger intercept test.

[0058] In some examples of this application, the causal reasoning module 230 is specifically used to: correct the results of the sensitivity analysis by employing a multiple test correction method.

[0059] In some examples of this application, the target drug determination module 240 is specifically used to: i) determine the causal association between the comprehensive target genes of the candidate drugs in the predetermined tissue and the predetermined disease based on the genetic instrumental variables; ii) determine the target drug for the predetermined tissue based on the causal association.

[0060] It should be understood that the device embodiments and method embodiments can correspond to each other, and similar descriptions can be referred to the method embodiments. To avoid repetition, further details will not be provided here. Specifically, Figure 2 The device shown can perform Figure 1 The corresponding method embodiments, and the foregoing and other operations and / or functions of each module in the device, are respectively for implementing Figure 1 For the sake of brevity, the corresponding processes in each method are not described in detail here.

[0061] The apparatus of this application embodiment has been described above from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that this functional module can be implemented in hardware, in software instructions, or in a combination of hardware and software modules. Specifically, the steps of the method embodiments in this application can be completed by integrated logic circuits in the processor's hardware and / or by software instructions. The steps of the method disclosed in this application embodiment can be directly embodied as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. Optionally, the software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps in the above method embodiments.

[0062] Electronic devices and computer-readable storage media

[0063] Furthermore, this application proposes an electronic device and a computer-readable storage medium. The electronic device and computer-readable storage medium enable the aforementioned method for identifying a target drug for a predetermined tissue to be performed.

[0064] The term "electronic device" is intended to refer to various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Computing devices can also refer to various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0065] like Figure 3 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 502 or a computer program loaded from storage unit 508 into RAM (Random Access Memory) 503. The RAM 503 can also store various programs and data required for the operation of the device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0066] Multiple components in device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0067] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a method for identifying a target drug for a predetermined tissue. For example, in some embodiments, the method for identifying a target drug for a predetermined tissue may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the aforementioned target drug determination method for a predetermined tissue by any other suitable means (e.g., by means of firmware).

[0068] In this application, the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, a computer-readable medium can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory. The various computer-readable storage media described in this invention can represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" can include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0069] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0070] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0071] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0072] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0073] Embodiments of the present invention will now be described in more detail, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0074] Example 1: Tissue-specific MR analysis

[0075] Methods: The GWAS data in this study (Table 1) were obtained from the database.

[0076] Table 1. Basic information on genome-wide association study data for outcome variables.

[0077]

[0078] To infer the tissue-level effects of the drugs, all target genes of four cardiovascular and metabolic drugs of interest were identified by querying the DrugBank and ChEMBL databases (Table 2). For each tissue, the eQTLs of these target genes were summarized as exposure data. Eight disease-related tissues from GTEx were selected, including liver, pancreas, aorta, skeletal muscle, subcutaneous fat, visceral fat, coronary artery, and whole blood. Data were required to meet the following criteria: (i) cis-eQTLs located within ±100 kb of each gene; (ii) nominal significance of SNVs in downstream molecular phenotypic GWAS (P < 0.05); and (iii) p-values ​​of eQTLs less than 5 × 10⁻⁶. -8 r 2The threshold was 0.1. For multiple eQTLs as instrumental variables, inverse variance weighting was used. Validation was also performed using the weighted median, weighted pattern, and MR-Egger regression methods, and heterogeneity and pleiotropy among genetic instruments were assessed using Cochran's Q test and MR-Egger intercept test. FDR correction was applied to establish multiple test-adjusted significance thresholds for sensitivity analysis.

[0079] Table 2. Correspondence between drugs and their target genes

[0080]

[0081]

[0082]

[0083] Results: The effects of drugs on three diseases were investigated in eight tissues using tissue-based drug target MR analysis. Metformin, a hypoglycemic agent, showed protective effects against T2D in the liver and against AAA in the liver and adipose tissue. Another T2D drug, sulfonylureas, is known to promote insulin secretion in the pancreas and provide protection against T2D in the pancreas and liver, while also reducing the risk of AAA in the liver, skeletal muscle, and adipose tissue. Calcium channel blockers, as antihypertensive agents, showed benefits for all three diseases in the aorta, adipose tissue, and whole blood. However, in evaluable skeletal muscle, statins were beneficial for AAA and CAD but increased the risk of T2D. Figure 4 These results reveal the tissue-specific effects of drugs on diseases, further providing insights into drug function in vivo.

[0084] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0085] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application without departing from the principles and spirit of this application.

Claims

1. A method for identifying a target drug for a predetermined tissue, characterized in that, include: Obtain multiple drug candidates for the intended disease; Based on the aforementioned multiple candidate drugs, all target genes for each candidate drug were identified; Based on the target genes, the expression quantitative trait gene loci of all target genes in the predetermined tissue are determined. Using the expression quantitative trait gene loci as genetic instrumental variables, Mendelian randomization analysis is used to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drug in the predetermined tissue and the predetermined disease. Based on the potential causal relationship, a target drug for the predetermined tissue is identified.

2. The method according to claim 1, characterized in that, The step of using Mendelian randomization analysis to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drug in predetermined tissues and the predetermined disease includes: The effects of all genetic instrumental variables are summarized using the inverse variance weighting method to determine the overall causal estimate between the expression of the comprehensive target gene of the candidate drug in a predetermined tissue and the predetermined disease.

3. The method according to claim 2, characterized in that, The method of summarizing the effects of all genetic instrumental variables using the inverse variance weighting method to determine the overall causal estimate between the expression of all target genes of the candidate drug in a specific tissue and the predetermined disease includes: The robustness of the overall causal estimate was verified by sensitivity analysis, confirming a potential causal relationship between the expression of the candidate drug's comprehensive target genes in a specific tissue and the predetermined disease.

4. The method according to claim 3, characterized in that, The sensitivity analyses include: weighted median method, weighted pattern method, MR-Egger regression method, Cochran's Q test or MR-Egger intercept test.

5. The method according to claim 3, characterized in that, The results of the sensitivity analysis were corrected using a multiple test correction method.

6. The method according to any one of claims 1-5, characterized in that, The genetic instrumental variable must simultaneously meet the following conditions: a. A region located 100kb upstream or 100kb downstream of the target gene; b. The effect of the drug on downstream disease phenotypes was statistically significant (P < 0.05). c. Significantly correlated with the expression of the target gene of the candidate drug in specific tissues, P < 5 × 10⁻⁶. -8 ; d. Chain disequilibrium threshold r 2 It is 0.

1.

7. The method according to any one of claims 6, characterized in that, The process of determining the target drug for the predetermined tissue based on the potential causal relationship includes: i) Based on the genetic instrument variables, determine the causal association between the comprehensive target genes of the candidate drugs in the predetermined tissue and the predetermined disease; ii) Based on the causal relationship, determine the target drug for the predetermined tissue.

8. A target drug identification device for a predetermined tissue, characterized in that, include: The candidate drug acquisition module is used to acquire multiple candidate drugs for a predetermined disease; The target gene determination module is used to determine all target genes of each candidate drug based on the multiple candidate drugs. The causal reasoning module is used to determine the expression quantitative trait gene loci of all target genes in a predetermined tissue based on the target genes, and to determine the potential causal relationship between the expression of the comprehensive target genes of the candidate drug in the predetermined tissue and the predetermined disease using the expression quantitative trait gene loci as genetic instrumental variables and Mendelian randomization analysis. The target drug identification module identifies a target drug for the predetermined tissue based on the potential causal relationship.

9. An electronic device, characterized in that, include: Processor and memory; The memory is used to store computer programs; The processor is configured to execute the computer program to implement the method for identifying a target drug for a predetermined tissue as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions or programs that, when executed on a computer, cause the method for determining a target drug for a predetermined tissue as described in any one of claims 1 to 7 to be performed.

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