Screening method of p-hydroxyacetophenone exposed biomarker

Abstract

The invention discloses a screening method of a p-hydroxyacetophenone exposed biomarker. According to the method, a series of suspicious exposure marker lists are formed through software simulation on the basis of the I / II phase metabolic transformation rule of PHAC and are included in a mass spectrum targeted screening list, so that the mass spectrum fragment collection efficiency and qualitative analysis capability of target ions are effectively enhanced, and interference of high-abundance endogenous metabolites is eliminated; a PHAC standard substance is used for confirming the retention time of a target peak, compounds with abnormal retention time prediction are excluded, potential targets are further simulated and locked through metabolic site energy, and a fragment ion spectrum intelligent matching algorithm is utilized, so that the accurate molecular structure and metabolic conversion path analysis of the PHAC exposure biomarker is realized; meanwhile, through metabolite peak area semi-quantitative analysis, the PHAC high-sensitivity exposure biomarker capable of monitoring the load in the human body is analyzed and determined for the first time.

Description

Technical Field

[0001] The present invention belongs to the field of environmental pollutant detection, and particularly relates to a screening method for biomarkers of p - hydroxyacetophenone exposure. Background Art

[0002] Biomarkers of organic pollutant exposure refer to pollutant prototypes, metabolites, and adducts formed with endogenous substances that can be quantitatively detected in tissues, body fluids, or excreta of organisms. As a bridge connecting environmental pollution exposure and health effects, such biomarkers provide key technical support for population exposure assessment and environmental health risk warning systems.

[0003] Typical preservatives, parabens, are widely used as additives in various foods, pharmaceuticals, and personal care products and are a class of endocrine disruptors that have received much attention.

[0004] Studies have shown that long - term parabens exposure can lead to metabolic disorders, developmental damage, and endocrine disruption effects. Given the series of adverse health effects caused by long - term parabens exposure, manufacturers have gradually reduced the use of parabens and instead developed their substitutes.

[0005] The structural analogue of parabens, p - hydroxyacetophenone (PHAC), has a 1 - 3 order of magnitude higher burden in children's bodies than parabens, and preliminary studies on the toxic effects of nerve cell exposure reveal that its metabolic interference effect is higher than that of traditional parabens. Therefore, it is particularly important to clarify the exposure health risks of PHAC.

[0006] Identifying biomarkers of PHAC exposure is the primary step in systematically revealing its population exposure health effects and risks. However, as a newly discovered potential substitute for parabens, the research on biomarkers of PHAC exposure is still in its infancy, and it is still unknown which exposure biomarkers can be used to accurately calculate the internal exposure dose. Summary of the Invention

[0007] The purpose of the present invention is to provide a screening method for biomarkers of PHAC exposure, clarify the in - vivo metabolic transformation process of PHAC, and quickly provide exposure biomarkers for monitoring human body burden.

[0008] The purpose of the present invention is achieved by the following technical solutions: A screening method for biomarkers of p - hydroxyacetophenone (PHAC) exposure, comprising the following steps: (1) Exposure and sample preparation: Experimental animals are exposed for at least 8 consecutive days, and then samples are collected for further analysis; The poisoning mentioned above can be carried out by routes such as intraperitoneal injection or gavage administration; when using intraperitoneal injection, the dosage of p - hydroxyacetophenone is preferably 12.5 mg / kg / d; The experimental animals mentioned above include rodents or non - rodents; The rodents are preferably rats and mice; The non - rodents are preferably rabbits, dogs, monkeys, or others; The sample can be serum or urine; before analysis, the serum and urine can be purified and enriched; (2)Construction of the theoretical exposure biomarker molecular formula library: Use BioTransformer 3.0 to predict the transformation products of PHAC, set the maximum number of phase I reactions to 3 and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; Use the Expected Compound module in Compound Discovery, according to the metabolic reaction combination rules, set the maximum number of phase I reactions to 3 and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; For the phase I reaction mentioned above, the reaction types include oxidation reaction, reduction reaction, hydrolysis reaction, and desaturation reaction; For the phase II reaction mentioned above, the reaction types include acetylation reaction, methylation reaction, glucuronidation reaction, sulfation reaction, and amino acid complexation reaction; Combine the predicted transformation products formed by Biotransformer and Compound Discovery to construct the theoretical exposure biomarker molecular formula library, and incorporate this library into the targeted ion inclusion list in step (3) to enhance the acquisition efficiency of secondary daughter ion fragments and improve the qualitative quality of the results; (3)Mass spectrometry data acquisition: Use an ultra - high performance liquid chromatography tandem quadrupole / orbitrap high - resolution mass spectrometer to acquire fragment spectra; The acquisition mentioned above includes full - scan mass spectrometry, dynamic exclusion, targeted ion inclusion list, and fragment ion scanning; (4)Suspected screening analysis of exposure biomarkers: Screen the fragment spectra acquired in step (3) through Compound Discoverer software, match the theoretical exposure biomarker molecular formula library with the measured mass spectrometry data, and use the set of biomarkers with a mass error <5 ppm as the candidate set of potential PHAC exposure biomarker molecular formulas; The screening mentioned above includes one or more operations such as peak extraction, peak alignment, expected compound screening, expected compound combination, compound identification and annotation, and fragment ion search scoring; (5)Structural analysis and screening of exposure biomarkers: The metabolic simulation platform is used to evaluate the activation energy thresholds of each reaction site of PHAC molecules, locate the highly inclined metabolic active sites, and deduce the preliminary structural formula of the candidate biomarkers from the candidate set of potential PHAC exposure biomarker molecular formulas based on the principle of preferential selection of metabolic energy; The preliminary structural formula is further confirmed by the results of retention time prediction and the matching degree of secondary fragment ions, including: Retention time prediction: The retention time of PHAC is confirmed using the standard product, and the direction of the change in the retention time of the PHAC exposure biomarker (earlier or later elution) is judged based on the hydrophilicity or hydrophobicity of the binding / reacting groups, and the compounds with abnormal retention time prediction are excluded; Matching degree of secondary fragment ions: The preliminary structural formula is imported into the Compound Discoverer software, and the intelligent matching engine of fragment ions is enabled. The system compares the characteristic ion clusters between the measured mass spectrometry fragments (HCD multi-level spectrum) of the analyte and the theoretical fragments of the preliminary structural formula, and completes the structural confirmation according to the spectrum similarity threshold, and selects the molecular structural formula with the highest matching degree; Then, the metabolic site prediction and mass spectrometry verification data are integrated to construct a multi-pathway metabolic transformation network diagram of PHAC; Finally, based on the evaluation of sensitivity, specificity and stability, the exposure biomarker with the best comprehensive performance is screened out, specifically including: Sensitivity evaluation: Through the normalization analysis of the characteristic peak area, the exposure biomarkers with the top 20% peak intensities are screened out; Specificity evaluation: The exposure biomarker will only be generated when a specific exposure occurs, which is mainly characterized by the difference in the concentration levels of the exposure biomarker between the exposed group and the control group; Stability evaluation: Specifically refers to whether the exposure biomarker can be stably formed under the exposure dose of a fixed quantity, which is mainly characterized by the coefficient of variation between days.

[0009] The preferred metabolic simulation platforms described above are ADMET Predictor™ and / or BioTransformer.

[0010] Through the above steps of structural analysis and verification of the exposure biomarker, the present invention has identified a total of 11 PHAC exposure biomarkers (Table 4), and the formation of these exposure biomarkers mainly involves reactions such as oxidation, reduction, methylation, and sulfation.

[0011] The present invention has the following advantages and effects compared with the prior art: 1. Based on the phase I / II metabolic transformation rules of PHAC, the present invention forms a series of suspected exposure biomarker lists through software simulation, and incorporates them into the mass spectrometry targeted screening list, effectively enhancing the mass spectrometry fragment collection efficiency and qualitative analysis ability of target ions, and excluding the interference of high-abundance endogenous metabolites; 2. The present invention uses PHAC reference standards to confirm the retention time of target peaks, excludes compounds with abnormal retention time predictions, further locks potential targets through metabolic site energy simulation, and uses a fragmentation ion map intelligent matching algorithm to achieve the precise molecular structure and metabolic transformation path analysis of PHAC exposure biomarkers; at the same time, through semi-quantitative analysis of metabolite peak areas, for the first time, highly sensitive exposure biomarkers of PHAC for in vivo load monitoring are analyzed and established. Description of the Drawings

[0012] Figure 1 To reveal the differences in exposure biomarkers in urine between the solvent control group and the exposure group based on principal component analysis.

[0013] Figure 2 It is the map of the parent ion (MS1) and fragment ions (MS2) of M0 qualitatively identified in urine and the inter-group peak area response difference map.

[0014] Figure 3 It is the map of the parent ion (MS1) and fragment ions (MS2) of M1 qualitatively identified in urine and the inter-group peak area response difference map.

[0015] Figure 4 It is the map of the parent ion (MS1) and fragment ions (MS2) of M2 qualitatively identified in urine and the inter-group peak area response difference map.

[0016] Figure 5 It is the map of the parent ion (MS1) and fragment ions (MS2) of M3 qualitatively identified in urine and the inter-group peak area response difference map.

[0017] Figure 6 It is the map of the parent ion (MS1) and fragment ions (MS2) of M4 qualitatively identified in urine and the inter-group peak area response difference map.

[0018] Figure 7 It is the map of the parent ion (MS1) and fragment ions (MS2) of M5 qualitatively identified in urine and the inter-group peak area response difference map.

[0019] Figure 8 It is the map of the parent ion (MS1) and fragment ions (MS2) of M0 qualitatively identified in serum.

[0020] Figure 9 It is the map of the parent ion (MS1) and fragment ions (MS2) of M1 qualitatively identified in serum.

[0021] Figure 10 It is the map of the parent ion (MS1) and fragment ions (MS2) of M2 qualitatively identified in serum.

[0022] Figure 11 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M3 qualitatively identified in serum.

[0023] Figure 12 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M4 qualitatively identified in serum.

[0024] Figure 13 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M5 qualitatively identified in serum.

[0025] Figure 14 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M6 qualitatively identified in serum.

[0026] Figure 15 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M7 qualitatively identified in serum.

[0027] Figure 16 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M8 qualitatively identified in serum.

[0028] Figure 17 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M9 qualitatively identified in serum.

[0029] Figure 18 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M10 qualitatively identified in serum.

[0030] Figures 19 - 20 The mass spectra of the precursor ions (MS1) and fragment ions (MS2) of M11 qualitatively identified in serum.

[0031] Figure 21 The in vivo metabolic transformation pathways of 11 PHAC exposure biomarkers in rats.

[0032] Figure 22 The detected abundances of PHAC and its 5 exposure biomarkers in urine over different days. Specific implementation manners

[0033] The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the implementation manners of the present invention are not limited thereto.

[0034] Embodiment A screening method for PHAC exposure biomarkers, comprising the following steps: (1)Grouping and dosing regimen: Male SPF-grade SD rats (Southern Medical University) at 8 weeks of age were adaptively fed for 1 week in a natural light environment at 25 ± 1 °C and humidity of 45% ± 5%. Then they were randomly divided into a 10% ethanol vehicle control group and a 12.5 mg / kg / d PHAC exposure group, and continuously dosed by intraperitoneal injection for 8 days. Urine specimens were collected daily.

[0035] (2)Serum sample collection: After the last dose, the rats were fasted for 6 h, anesthetized with isoflurane, and blood was collected from the abdominal aorta in the supine position. The serum was separated by centrifugation at 3500 rpm / min for 5 min, aliquoted, and stored frozen at -80 °C.

[0036] (3)Serum purification and enrichment: 0.9 mL of serum was aliquoted into 3 tubes, and 0.9 mL of pre-cooled methanol at -20 °C was added to each tube (0.3 mL). After vortex mixing for 30 seconds, the mixture was left to stand at -80 °C for 60 minutes. After centrifugation at 14000 rpm for 15 min (4 °C), 600 μL of the supernatant was taken from each tube and combined into a 1.8 mL mixture, which was then dried under vacuum. The residue was reconstituted with 200 μL of methanol solution, and centrifuged again at 14000 rpm for 15 min (4 °C). Finally, 120 μL of the supernatant was transferred to an injection vial, and 30 μL of methyl paraben-D4 isotope internal standard was added.

[0037] (4)Urine purification and enrichment: 2 mL of urine was added to a 10 mL plastic tube, and 6 mL of pre-cooled methanol at -20 °C was added. After vortex mixing for 30 seconds, the mixture was aliquoted into 5 tubes of 2 mL plastic tubes and left to stand at -80 °C for 60 minutes. After centrifugation at 14000 rpm for 15 min, 1 mL of the supernatant was taken from each tube and combined into a 5 mL mixture, which was then dried under vacuum. The residue was reconstituted with 400 μL of methanol solution, and centrifuged again at 14000 rpm for 15 min (4 °C). Finally, 120 μL of the supernatant was transferred to an injection vial, and 30 μL of methyl paraben-D4 isotope internal standard was added.

[0038] (5)Construction of the theoretical exposure biomarker molecular formula library: Use BioTransformer 3.0 (mainly based on the prediction of metabolic reaction sites) to predict the transformation products of PHAC, set the maximum number of phase I reactions to 3 and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; Use the Expected Compound module in Compound Discovery (mainly based on the free combination of metabolic reaction rules), according to the metabolic reaction combination rules, that is, set the maximum number of phase I reactions to 3 and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; The types of metabolic reactions cover phase I reactions such as oxidation, reduction, hydrolysis, desaturation, etc. and phase II reactions such as acetylation, methylation, glucuronidation, sulfation, and various amino acid complexation reactions; The predicted transformation products formed by combining Biotransformer and Compound Discovery were used to construct a theoretical exposure biomarker molecular formula library (Tables 1 and 2), and this library was incorporated into the targeted ion inclusion list in step (6) to enhance the acquisition efficiency of secondary daughter ion fragments and improve the qualitative quality of the results.

[0039] (6) Mass spectrometry data acquisition: An ultra-high performance liquid chromatography tandem quadrupole / orbitrap high-resolution mass spectrometer (UPLC-Orbitrap Exploris 240) was used. Hypersil GOLD AQ C18 column (150×2.1 mm, 1.9 μm) was used for chromatographic separation. The mobile phase was methanol (organic phase B) and 0.05% acetic acid in water (aqueous phase A). The column temperature was 35 °C, the flow rate was 0.3 mL / min, and the injection volume was 2 μL. Gradient elution program: 2% B from 0 to 1 min; linearly increased to 98% B from 1 to 8 min; maintained at 98% B from 8 to 11 min; equilibrated to 2% B from 11.01 to 14 min. Mass spectrometry detection was performed in the ESI negative ion mode (spray voltage –3.2 kV). Ion source parameters: sheath gas 45 Arb, auxiliary gas 8 Arb, purge gas 1 Arb, transfer line 320 °C, vaporizer 350 °C. The data acquisition process included full-scan mass spectrometry, dynamic exclusion, targeted ion inclusion list, and fragment ion scanning. Among them, the targeted ion inclusion list incorporated the pre-established theoretical exposure biomarker molecular formula library in potential step (5) to enhance the acquisition efficiency of target exposure biomarkers and improve the qualitative identification ability, greatly solving the problem of low acquisition efficiency of fragment ions of target peaks caused by co-elution of high-abundance endogenous substances. The full-scan resolution was 240000 (m / z 90 - 600). Fragment ion scanning settings: isolation window 2 m / z, HCD collision energy ladder 20% - 80% (step size 20%), resolution 15000, and 10 fragment spectra were synchronously acquired.

[0040] (7) Suspected screening analysis of exposure biomarkers: An automated screening process for the fragment spectra obtained in step (6) was established through Compound Discoverer software (covering modules such as peak extraction, peak alignment, screening of expected compounds, combination of expected compounds, compound identification and annotation, and fragment ion search scoring). The theoretical exposure biomarker molecular formula library was accurately matched with the measured high-resolution mass spectrometry data (mass error <5 ppm) to screen out a candidate set of potential PHAC exposure biomarker molecular formulas (Table 3).

[0041] Table 1: List of molecular formulas of potential exposure biomarkers of PHAC formed by BioTransformation

[0042] Table 2: List of molecular formulas of potential exposure biomarkers of PHAC formed by Compound Discoverer

[0043] (8) Structural analysis and screening of exposure biomarkers: Using the ADMET Predictor™ and BioTransformer 3.0 metabolic simulation platforms, the activation energy thresholds of each reaction site of PHAC molecules are evaluated through quantum chemical calculations (density functional theory model) to accurately locate metabolic active sites such as oxidation, reduction, and sulfation. Based on the principle of metabolic energy preference, candidate biomarkers and their preliminary structural formulas are derived from the candidate set of molecular formulas of potential PHAC exposure biomarkers.

[0044] The preliminary structural formula is further confirmed by the results of retention time prediction and secondary fragment ion matching degree, specifically including: Retention time prediction: The retention time of PHAC is confirmed using a reference standard, and the direction of change in the retention time of PHAC exposure biomarkers (earlier or later elution) is judged based on the hydrophilicity or hydrophobicity of the binding / reaction groups, excluding compounds with abnormal retention time predictions; Secondary fragment ion matching degree: The preliminary structural formula is imported into the compound annotation editor module of the Compound Discoverer 3.3 SP2 software, and the fragment ion intelligent matching engine (FISh) is enabled. The system compares the characteristic ion clusters between the measured mass spectrometry fragments (HCD multi-level spectrum) of the analyte and the theoretical fragments of the preliminary structural formula, and completes the structural confirmation according to the spectrum similarity threshold (m / z deviation < 5 ppm), and selects the molecular structural formula with the highest matching degree. Finally, integrating the metabolic site prediction and mass spectrometry verification data, a multi-pathway metabolic transformation network diagram of PHAC is constructed; Finally, based on the evaluation of sensitivity, specificity, and stability, the exposure biomarkers with the best comprehensive performance are screened out, specifically including: Sensitivity evaluation: Through characteristic peak area normalization analysis, the exposure biomarkers with the top 20% peak intensity are screened out; Specificity evaluation: Exposure biomarkers will only be produced when specific exposure occurs, which is mainly characterized by the difference in the concentration levels of exposure biomarkers between the exposed group and the control group; Stability assessment: Specifically refers to whether exposure biomarkers can be stably formed under a quantitative exposure dose, mainly characterized by the coefficient of variation between days.

[0045] (8) Experimental results: Principal component analysis showed that the urine samples of the solvent control group and the PHAC exposure group were extremely significantly separated ( Figure 1 ), indicating that a series of significantly different exposure biomarkers were formed in the PHAC exposure group. Through the above steps of exposure biomarker structure analysis and verification, a total of 11 PHAC exposure biomarkers were identified in the present invention (Tables 3 and 4). The formation of these exposure biomarkers mainly involves reactions such as oxidation, reduction, methylation, and sulfation. The parent ion isotope matching degrees of the PHAC parent compound (M0) and its 11 exposure biomarkers are all 100%. Except for M7, at least two fragment ions were matched in the database and the mass deviation <5 ppm (Table 3), and the structural confidence level can reach L2. The mother ion (MS1) and fragment ion (MS2) spectra of PHAC and its exposure biomarkers qualitatively identified in urine and serum are as Figures 2 - 20 shown.

[0046] M1 (m / z: 151.0401) ( Figure 3 and Figure 9 ) and M6 (m / z: 151.0401) ( Figure 14 ) are oxidation products of PHAC, and the FISh coverage rates are 45.1% and 51.7% respectively; M2 (m / z: 230.9965) ( Figure 4 and Figure 10 ) is a sulfation product of M1, and the FISh coverage rate reaches 40.7%; M3 (m / z: 165.0557) ( Figure 5 and Figure 11 ) is a methylation product of M1, and the FISh coverage rate reaches 37.5%; M4 (m / z: 215.0018) ( Figure 6 and Figure 12 ) is a sulfation product of PHAC, and the FISh coverage rate reaches 58.8%; M5 (m / z: 217.0176) ( Figure 7 and Figure 13 ) is a sulfation product after reduction of PHAC, and the FISh coverage rate reaches 35.0%; M7 (m / z: 149.0608) ( Figure 15 ) is a methylation product of PHAC, and the FISh coverage rate reaches 33.3%; M8 (m / z: 375.2905) ( Figure 16 ) is a reduced palmitoyl complex of PHAC, and the FISh coverage rate reaches 33.3%; M9 (m / z: 199.0072) ( Figure 17is the reduction, dehydration, and sulfation product of PHAC, with a FISh coverage of 19.5%; M10 (m / z: 181.0504) ( Figure 18 is the oxidation, oxidation, and methylation product of PHAC, with a FISh coverage of 73.5%; M11 (m / z: 327.0722) ( Figure 19 and Figure 20 is the glucuronic acid complex after oxidation of PHAC, with a FISh coverage of 73.3%. Based on the rules of metabolic transformation reactions, the in vivo metabolic transformation pathways of 11 PHAC exposure biomarkers were further drawn ( Figure 21 ).

[0047] In addition, the 11 PHAC exposure biomarkers were semi-quantified based on the standardized peak area (Table 3) to evaluate the sensitivity of the exposure biomarkers. The results showed that: in urine, the exposure biomarker with the highest relative proportion was M4 (49.2%), followed by M0 (36.4%) and M5 (12.3%). Therefore, the sulfated complex is the main urine exposure biomarker of PHAC, and M4 can be used as the sensitive exposure biomarker of PHAC. In serum, the exposure biomarker with the highest relative proportion was M7 (39.3%), followed by M4 (25.1%) and M5 (10.1%). Therefore, the methylated and sulfated complexes are the main serum exposure biomarkers of PHAC, and either M7 or M4 can be used as the sensitive exposure biomarker of PHAC. Generally speaking, the peak area of urine exposure biomarkers is generally 1-2 orders of magnitude higher than that of serum. Therefore, based on the principles of non-invasiveness, sampling convenience, and sensitivity of exposure biomarkers, M4 or M0 should be comprehensively selected as the exposure biomarker for monitoring the human body burden of PHAC.

[0048] Further evaluations were carried out on the specificity and stability of M4 and M0, and the results are as follows: From the perspective of specificity evaluation ( Figure 2 and Figure 6 's upper right bar graph), the peak areas of M4 and M0 in the urine of the control group were 3.74×10 8 and 3.68×10 8 respectively, while the peak areas in the PHAC exposure group were 3.73×10 10 and 2.51×10 10 respectively. The ratios of the peak areas between the exposure and control groups were 99.8 and 68.1, showing extremely significant inter-group differences ( p <0.001). Therefore, both M4 and M0 have strong specificity.

[0049] From the perspective of stability evaluation ( Figure 22), The continuous 8-day monitoring of exposure biomarkers in rat urine found that, except for fluctuations on the fourth day, both M4 and M0 showed good stability, with an inter-day coefficient of variation less than 30%, indicating strong stability.

[0050] Based on the above research results, M4 and M0 in urine can be used as highly sensitive, specific, and stable biomarkers for indicating PHAC exposure.

[0051] Table 3: 11 PHAC exposure biomarkers identified in urine and serum (M0 is the PHAC parent compound)

[0052] Table 4: List of 11 PHAC exposure biomarkers and their molecular structural formulas (M0 is the PHAC parent compound)

[0053] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. Screening method for biomarkers of p - hydroxyacetophenone exposure, characterized in that It includes the following steps: (1) Poisoning and sample preparation: The experimental animals are poisoned for at least 8 consecutive days, and then samples are collected for the next analysis; (2) Construction of the theoretical exposure biomarker molecular formula library: Use BioTransformer 3.0 to predict the transformation products of p-hydroxyacetophenone, set the maximum number of phase I reactions to 3, and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; Use the Expected Compound module in Compound Discovery, based on the metabolic reaction combination rules, set the maximum number of phase I reactions to 3, and the maximum number of phase II metabolic reactions to 1 to form a series of transformation products; For the phase I reaction described above, the reaction types include oxidation reaction, reduction reaction, hydrolysis reaction, and desaturation reaction; For the phase II reaction described above, the reaction types include acetylation reaction, methylation reaction, glucuronidation reaction, sulfation reaction, and amino acid complexation reaction; Combine the predicted transformation products formed by Biotransformer and Compound Discovery, construct the theoretical exposure biomarker molecular formula library, and incorporate this library into the targeted ion inclusion list in step (3) to enhance the acquisition efficiency of secondary daughter ion fragments and improve the qualitative quality of the results; (3) Mass spectrometry data acquisition: Use an ultra-high performance liquid chromatography tandem quadrupole / orbitrap high-resolution mass spectrometer to acquire fragment spectra; The acquisition described above includes full-scan mass spectrometry, dynamic exclusion, targeted ion inclusion list, and fragment ion scanning; (4) Suspected screening analysis of exposure biomarkers: Screen the fragment spectra collected in step (3) through Compound Discoverer software, match the theoretical exposure biomarker molecular formula library with the measured mass spectrometry data, and use the set of biomarkers with a mass error < 5 ppm as the candidate set of potential p-hydroxyacetophenone exposure biomarker molecular formulas; The screening described above includes one or more operations among peak extraction, peak alignment, expected compound screening, expected compound combination, compound identification and annotation, and fragment ion search scoring; (5) Structural analysis and screening of exposure biomarkers: Use a metabolic simulation platform to evaluate the activation energy threshold of each reaction site of the p-hydroxyacetophenone molecule, locate the high-tendency metabolic active sites, and deduce the preliminary structural formula of the candidate biomarker from the candidate set of potential p-hydroxyacetophenone exposure biomarker molecular formulas based on the principle of preferred metabolic energy; The preliminary structural formula is further confirmed by the results of retention time prediction and secondary fragment ion matching degree, including: Retention time prediction: Use a standard product to confirm the retention time of p-hydroxyacetophenone, and judge the direction of the change in the retention time of the p-hydroxyacetophenone exposure biomarker based on the hydrophilicity or hydrophobicity of the binding / reacting group, and exclude the compounds with abnormal retention time prediction; Secondary fragment ion matching degree: Import the preliminary structural formula into the Compound Discoverer software, enable the intelligent matching engine for fragment ions, the system compares the characteristic ion clusters between the actually measured mass spectrometry fragments of the analyte and the theoretical fragments of the preliminary structural formula, completes the structure confirmation according to the spectral similarity threshold, and selects the molecular structural formula with the highest matching degree; Next, integrate the metabolic site prediction and mass spectrometry verification data to construct a multi-pathway metabolic transformation network diagram of p-hydroxyacetophenone; Finally, based on the sensitivity assessment, specificity assessment and stability assessment, screen out the exposure biomarker with the best comprehensive performance.

2. The screening method according to claim 1, characterized in that: The sensitivity assessment described in step (5) is to screen out the exposure biomarkers with the top 20% peak intensities through the normalization analysis of characteristic peak areas.

3. The screening method according to claim 1, characterized in that: The specificity assessment described in step (5) is characterized by the difference in the concentration levels of exposure biomarkers between the exposed group and the control group.

4. The screening method according to claim 1, characterized in that: The stability assessment described in step (5) is characterized by the coefficient of variation between days.

5. The screening method according to claim 1, characterized in that: The metabolic simulation platform described in step (5) is ADMETPredictor™ and / or BioTransformer.

6. The screening method according to claim 1, characterized in that: The administration of the toxicant described in step (1) is by intraperitoneal injection or gavage.

7. The screening method according to claim 6, characterized in that: When performing intraperitoneal injection, the administration dose of p-hydroxyacetophenone is 12.5 mg / kg / d.

8. The screening method according to claim 1, characterized in that: The sample is serum or urine.

9. The screening method according to claim 8, characterized in that: Before analysis, the serum and urine are purified and enriched.

10. The screening method according to claim 1, characterized in that: The experimental animals described in step (1) include rodents or non-rodents.

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