Biomarker for predicting hepatotoxicity of statins and application

Abstract

The invention discloses a biomarker for predicting hepatotoxicity of statins and application of the biomarker, the genetic marker comprises a combination of one or more of the following components: rs2319727, rs11942221, rs4354683, rs10030581, rs10466452, rs28765517, HLA-DOB, WASHC1, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, LOC100996437, TOP3BP1 and GNB1-DT. The biomarker is a statins hepatotoxicity genetic marker which is remarkable in genome level and suitable for Chinese population, the prediction accuracy of the statins hepatotoxicity is high, the application population can be expanded, and the the occurrence of hepatotoxicity is reduced, and the medication compliance of statin users is improved. In addition, the invention also provides a metabolic marker and application thereof.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedicine, and in particular to a biomarker for predicting statin hepatotoxicity, and an application of the biomarker for predicting statin hepatotoxicity. Background Art

[0002] Statins are the cornerstone drugs for lipid management and primary and secondary prevention of cardiovascular disease, which are consistently recommended by domestic and international guidelines. However, statins can cause adverse liver reactions such as abnormal transaminases and bilirubin. The incidence of liver symptoms in the Chinese population taking statins is as high as 1.295%. Due to the high prevalence of hepatitis in the Chinese population, the safety concerns about the use of statins in the Chinese population have deepened, and the Chinese population has also increased its attention to the liver toxicity of statins. When patients have mild abnormal transaminases or bilirubin, their compliance with statins becomes worse, and intermittent use of statins will increase the risk of major adverse cardiovascular events.

[0003] At present, the research on genetic markers of statin hepatotoxicity at home and abroad mainly focuses on genes such as CYP3A5, the metabolic enzyme that affects the metabolic dynamics of statins, and the transporter SLCO1B1, ABCB1 and ABCG2. However, no studies at home and abroad have found significant results at the genome level (p < 5×10 –8 ) SNP sites, and there are no studies on genetic markers from the perspective of toxicity mechanism and drug target. There are also no large-scale genome-wide association studies (GWAS) and no studies on genetic markers that reveal a causal relationship with statin hepatotoxicity.

[0004] There are no literature or patent reports on metabolic markers of statin hepatotoxicity. Summary of the invention

[0005] In order to overcome the defects of the prior art, the technical problem to be solved by the present invention is to provide a biomarker for predicting statin hepatotoxicity, which is a significant genetic marker for statin hepatotoxicity at the genomic level and is suitable for the Chinese population. It has a high prediction accuracy for statin hepatotoxicity, can expand the application population, reduce the occurrence of hepatotoxicity, and improve the medication compliance of the statin user population.

[0006] The technical solution of the present invention is: a biomarker for predicting statin hepatotoxicity, which is a genetic marker and includes one or more combinations of the following: rs2319727, rs11942221, rs4354683, rs10030581, rs10466452, rs28765517, HLA-DOB, WASHC1, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, LOC100996437, TOP3BP1, and GNB1-DT.

[0007] The beneficial effects of the present invention are: for the first time, a significant genetic marker of statin hepatotoxicity at the genomic level suitable for the Chinese population is provided, the prediction accuracy of statin hepatotoxicity is high, the application population can be expanded, the occurrence of hepatotoxicity can be reduced, and the medication compliance of the statin user population can be improved.

[0008] Also provided is an application of this biomarker for predicting statin hepatotoxicity. The statin hepatotoxicity-related SNP sites are analyzed by GWAS chi-square test. When any of the following results is found, the risk of statin hepatotoxicity is increased: rs2319727 is allele A, rs11942221 is allele G, rs4354683 is allele A, rs10030581 is allele C, rs10466452 is allele A, and rs28765517 is allele T.

[0009] Also provided is an application of this biomarker for predicting statin hepatotoxicity, wherein gene fine positioning is performed using the SuSiE model, and the risk of statin hepatotoxicity is increased when any of the following results are obtained: rs2319727 is allele A, and rs28765517 is allele T.

[0010] Also provided is the application of this biomarker for predicting statin hepatotoxicity, through Mendelian randomization and colocalization analysis, when any of the following is upregulated, the risk of statin hepatotoxicity is increased: HLA-DOB, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, GNB1-DT.

[0011] Also provided is the use of such biomarkers for predicting statin hepatotoxicity, where the risk of statin hepatotoxicity is increased when any of the following is downregulated by Mendelian randomization and colocalization analysis: WASHC1, LOC100996437, TOP3BP1.

[0012] Another biomarker for predicting statin hepatotoxicity is also provided. The biomarker is a metabolic marker and includes a combination of one or more of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine.

[0013] Also provided is the use of such biomarkers for predicting statin hepatotoxicity, where the risk of statin hepatotoxicity increases with increasing plasma concentrations of any of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine, by Mendelian randomization and colocalization analysis.

[0014] Furthermore, statin hepatotoxicity is defined as an alanine aminotransferase (ALT) value greater than 40 U / L (units / liter) or an aspartate aminotransferase (AST) value greater than 42 U / L after taking statins.

[0015] Also provided is an application of a biomarker for predicting statin hepatotoxicity, which is a kit, and a storage medium of the kit stores the biomarker for predicting statin hepatotoxicity. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a Locuszoom diagram of single nucleotide polymorphism (SNP) sites significantly associated with statin hepatotoxicity. The figure shows the SNP signal, genetic recombination rate, and gene annotation within ±1.5Mb of the rs2319727 site. The potential causal variant rs28765517 discovered by fine positioning has been annotated. Among them, chromosome is chromosome and recombination rate is recombination rate.

[0017] Figure 2 The forest plot shows the causal relationship between whole blood and liver expressed genes and statin hepatotoxicity. The odds ratio (OR) and its 95% confidence interval (95% CI) of the incidence of statin-induced hepatotoxicity when the gene transcription level increases by one standard deviation. The light black error bars represent the GTEs eQTLs V8 whole blood dataset, the gray error bars represent the GTEs eQTLs V8 liver dataset, and the black error bars represent the eQTLsGen phase Ⅰ dataset.

[0018] Figure 3 Figure 2. Forest plot of the causal relationship between plasma acylcarnitine concentration and statin hepatotoxicity. The odds ratio (OR) and 95% confidence interval (95% CI) of the incidence of statin-induced hepatotoxicity when the plasma metabolite level increased by one standard deviation. DETAILED DESCRIPTION

[0019] The present invention provides a biomarker for predicting statin hepatotoxicity, which is a genetic marker and includes one or more combinations of the following: rs2319727, rs11942221, rs4354683, rs10030581, rs10466452, rs28765517, HLA-DOB, WASHC1, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, LOC100996437, TOP3BP1, and GNB1-DT.

[0020] The beneficial effects of the present invention are: for the first time, a significant genetic marker of statin hepatotoxicity at the genomic level suitable for the Chinese population is provided, the prediction accuracy of statin hepatotoxicity is high, the application population can be expanded, the occurrence of hepatotoxicity can be reduced, and the medication compliance of the statin user population can be improved.

[0021] The invention also provides an application of the biomarker for predicting statin hepatotoxicity. The single nucleotide polymorphism (SNP) sites related to statin hepatotoxicity are analyzed by GWAS chi-square test. When any of the following results is shown, the risk of statin hepatotoxicity is increased: rs2319727 is allele A, rs11942221 is allele G, rs4354683 is allele A, rs10030581 is allele C, rs10466452 is allele A, and rs28765517 is allele T.

[0022] Also provided is an application of this biomarker for predicting statin hepatotoxicity, wherein gene fine positioning is performed using the SuSiE model, and the risk of statin hepatotoxicity is increased when any of the following results are obtained: rs2319727 is allele A, and rs28765517 is allele T.

[0023] Also provided is the application of this biomarker for predicting statin hepatotoxicity, through Mendelian randomization and colocalization analysis, when any of the following is upregulated, the risk of statin hepatotoxicity is increased: HLA-DOB, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, GNB1-DT.

[0024] Also provided is the use of such biomarkers for predicting statin hepatotoxicity, where the risk of statin hepatotoxicity is increased when any of the following is downregulated by Mendelian randomization and colocalization analysis: WASHC1, LOC100996437, TOP3BP1.

[0025] Another biomarker for predicting statin hepatotoxicity is also provided. The biomarker is a metabolic marker and includes a combination of one or more of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine.

[0026] Also provided is the use of such biomarkers for predicting statin hepatotoxicity, where the risk of statin hepatotoxicity increases with increasing plasma concentrations of any of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine, by Mendelian randomization and colocalization analysis.

[0027] Furthermore, statin hepatotoxicity is defined as an alanine aminotransferase (ALT) value greater than 40 U / L or an aspartate aminotransferase (AST) value greater than 42 U / L after taking statins.

[0028] Also provided is an application of a biomarker for predicting statin hepatotoxicity, which is a kit, and a storage medium of the kit stores the biomarker for predicting statin hepatotoxicity.

[0029] The embodiments of the present invention are described in detail below.

[0030] In the present invention, a total of 1321 patients taking statins were collected, 320 patients without ALT or AST detection were excluded, and a total of 1001 patients were included. According to the ALT detection value greater than 40 U / L and the AST detection value greater than 42 U / L after taking statins, 178 patients were divided into a hepatotoxicity group and 823 patients in a control group.

[0031] Given that previous studies have established the effectiveness of Infinium Asian Screening Array-24+ v1.0 gene chips in SNP site genotyping, this example further optimizes and expands the scope of application of this technology, especially in evaluating genetic risk factors for statin-induced hepatotoxicity. Peripheral blood samples were collected from enrolled patients, and high-throughput genotyping of SNP sites was performed using the advanced Infinium Asian Screening Array-24+ v1.0 gene chip. Impute 2 software was used for genotype interpolation based on reference genome data (1000 Genomes Project phase 3). PLINK v1.9 software was used for correlation analysis, and the p value was less than 5×10 –8Defined as genomic significance. The SuSiE (Sum of Single Effects) model combined with the susieR software package performs fine positioning in the Top SNP and the 1.5 Mb region upstream and downstream, and accurately calculates the posterior inclusion probability (PIPs) and 95% confidence interval of the SNP site. Locuszoomr draws SNP signal maps and integrates genetic recombination rate information and gene annotations.

[0032] Significant cis-eQTLs in liver and whole blood were screened from multiple eQTLs authoritative databases (such as GTEs eQTLs V8, eQTLsGen phase Ⅰ, etc.) as exposure data, combined with the GWAS results of statin hepatotoxicity as outcome data, and two-sample Mendelian randomization analysis (using the TwoSampleMR software package) was used to deeply explore the potential causal relationship between gene expression variation and adverse drug reactions. Furthermore, metabolite-related QTLs (mQTLs) data from studies such as Chen Y et al., Karjalainen MK et al., and Ottensmann L et al. were included, and the analysis was extended to the whole blood metabolite level. Through co-localization analysis (using the coloc software package), the co-localization pattern between gene expression, metabolite levels and statin hepatotoxicity was comprehensively evaluated.

[0033] The present invention uses GWAS chi-square test to find 6 new SNP sites significantly associated with statin-induced hepatotoxicity at the genome level, which are located in 3 loci, as shown in Table 1. Among them, rs2319727 (allele A), rs11942221 (allele G), rs4354683 (allele A), rs10030581 (allele C), rs10466452 (allele A), and rs28765517 (allele T) are significant risk factors for statin hepatotoxicity, as shown in Table 1.

[0034] Table 1. Significant correlation between statin hepatotoxicity and genomic levels (p < 5 × 10 -8 ) SNP site

[0035] The present invention applied the SuSiE algorithm to finely map the GWAS signals of the Top SNP + / - 1.5 Mb region of the three loci, and successfully identified two potential causal variants, as shown in Table 2. It was found that rs2319727 (allele A) and rs28765517 (allele T) were significant risk factors for statin hepatotoxicity. The Locuszoom diagram shows the SNP signals, annotated genes and genetic recombination rates within the Top SNP + / - 1.5 Mb range, as shown in Table 2. Figure 1 .

[0036] Table 2. Fine mapping of SNP sites significantly associated with statin hepatotoxicity

[0037] Through Mendelian randomization and colocalization analysis, the present invention found that 11 genes expressed in the liver and whole blood were causally related to statin hepatotoxicity, and the relevant eQTLs were colocalized with the sites of statin hepatotoxicity (PP.H4>0.7), see Figure 2 The up-regulation of HLA-DOB, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, and GNB1-DT, and the down-regulation of WASHC1, LOC100996437, and TOP3BP1 were significant risk factors for statin hepatotoxicity.

[0038] Mendelian randomization and colocalization analysis of the causal relationship between plasma metabolites and statin hepatotoxicity found that increased plasma hexanoylcarnitine (C6), octanoylcarnitine (C8), and decanoylcarnitine (C10) concentrations were significant risk factors for statin hepatotoxicity. Figure 3 .

[0039] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. A biomarker for predicting statin hepatotoxicity, characterized by: The biomarker is a genetic marker and includes one or more combinations of the following: rs2319727, rs11942221, rs4354683, rs10030581, rs10466452, rs28765517, HLA-DOB, WASHC1, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, LOC100996437, TOP3BP1, and GNB1-DT.

2. The use of a biomarker for predicting statin hepatotoxicity according to claim 1, characterized in that: The GWAS chi-square test was used to analyze the SNP sites associated with statin hepatotoxicity. The risk of statin hepatotoxicity increased when any of the following results were found: rs2319727 was allele A, rs11942221 was allele G, rs4354683 was allele A, rs10030581 was allele C, rs10466452 was allele A, and rs28765517 was allele T.

3. The use of a biomarker for predicting statin hepatotoxicity according to claim 1, characterized in that: Gene fine-mapping was performed using the SuSiE model, and the risk of statin hepatotoxicity was increased when any of the following results were found: rs2319727 was allele A and rs28765517 was allele T.

4. The use of a biomarker for predicting statin hepatotoxicity according to claim 1, characterized in that: By Mendelian randomization and colocalization analysis, the risk of statin hepatotoxicity was increased when any of the following was upregulated: HLA-DOB, SNX19, SPATA20, CEACAM21, DNTTIP1, CCDC82, LINC00174, GNB1-DT.

5. The use of a biomarker for predicting statin hepatotoxicity according to claim 1, characterized in that: By Mendelian randomization and colocalization analysis, the risk of statin hepatotoxicity was increased when any of the following were downregulated: WASHC1, LOC100996437, TOP3BP1.

6. A biomarker for predicting statin hepatotoxicity, characterized in that: The biomarker is a metabolic marker, including one or more combinations of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine.

7. The use of a biomarker for predicting statin hepatotoxicity according to claim 6, characterized in that: By Mendelian randomization and colocalization analysis, the risk of statin hepatotoxicity increased with increasing plasma concentrations of any of the following: hexanoylcarnitine, octanoylcarnitine, and decanoylcarnitine.

8. The use of a biomarker for predicting statin hepatotoxicity according to any one of claims 2, 3, 4, 5, and 7, characterized in that: Statin hepatotoxicity was defined as an alanine aminotransferase (ALT) value greater than 40 U / L or an aspartate aminotransferase (AST) value greater than 42 U / L after taking statins.

9. The use of a biomarker for predicting statin hepatotoxicity according to claim 1 or 6, characterized in that: The kit is a reagent kit, and the storage medium of the kit stores the biomarker for predicting statin hepatotoxicity.

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