CN116356014A - Biological marker for noise susceptibility hearing impairment of workers and application thereof - Google Patents

Abstract

The invention discloses a biomarker for noise susceptibility hearing impairment of workers and application thereof, belonging to the field of biotechnology, wherein clinical information of noise hearing impairment workers and control group workers without hearing impairment in factories is extracted, RNA is extracted from blood cells of noise exposure workers in spot check, the specific gravity of SIRT1 genes and environmental factors in noise hearing impairment is analyzed by using a LightGBM classification algorithm, the correlation between 7 sites of SIRT1 genes and noise exposure is detected, and single nucleotide polymorphism sites rs12778366 and rs7895833 of SIRT1 genes are used as specific gene markers for screening before post of the noise exposure workers.

Description

Biological marker for noise susceptibility hearing impairment of workers and application thereof

Technical Field

The invention belongs to the field of biotechnology, and particularly relates to a biomarker for noise susceptibility hearing impairment of workers and application thereof.

Background

Noise-induced hearing loss (NIHL) refers to progressive sensorineural hearing loss caused by prolonged exposure to a strong degree of Noise, and is affected by factors such as Noise intensity, frequency, exposure time, exposure pattern, genetic genes, etc. With the increasing global industrialization level, NIHL has become a global public health disorder. According to WHO statistics, one tenth of the world's population is exposed to noisy conditions, while more than half of them suffer from NIHL. Studies have shown that in china and the united states, over 1000 tens of thousands and 2200 tens of thousands, respectively, operate in a harmful noise environment every day. Therefore, there is an urgent need to find susceptibility markers that lead to NIHL, and to improve the health level of workers by screening to find high risk groups with exposed noise. Previous studies have suggested that oxidative stress is demonstrated to be an important factor affecting NIHL, whereas oxidative stress can affect the occurrence of NIHL by tightly binding to the sirtuin 1 (SIRT 1)/proliferator-activated receptor-gamma coactivator 1α (PGC-1α) signaling pathway.

Sirtuin family proteins are a class of histone deacetylases (Ilistone deacetvlase, HDAC) that play an important role in cells after translation, including recognition of DNA, catalysis and maintenance of protein stability, and interactions between proteins. Its regulatory effects on cells are manifested in numerous cellular processes such as apoptosis and stress, lipid metabolism and fatty acid oxidation, improving insulin secretion and slowing the progression of aging. SIRT1, a member of the Sirtuin family of proteins, is an enzyme that regulates oxidative stress and proteolytic toxic stress, and can greatly reduce ROS levels and increase cell viability (M Bernier, RKPaul et al 2011). Studies have shown that the expression and activity of the mouse SIRT1 protein exposed to noise is lower than that of the control group, and the content of superoxide dismutase (SOD) is also relatively reduced, thus it is thought that SIRT1 may be involved in the pathogenesis of NIHL by modulating oxidative stress.

Although the environmental causative factors of NIHL have been relatively clear, studies have shown that individuals respond differently to noise under the same environment and the same level of noise exposure, suggesting that genetic differences in individuals may be the focus of studies in which there is a susceptibility difference to noise exposure. Genotype, single nucleotide polymorphism of genes and different alleles thereof in individual gene differences often affect tolerance and poison of individuals.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide a biomarker for noise susceptibility hearing impairment of workers and application thereof, clinical information of noise hearing impairment group workers and normal hearing control group workers in factories is extracted, RNA is extracted from blood cells of noise exposure workers in spot check, the proportion of SIRT1 genes and environmental factors in noise hearing impairment is determined through a machine learning model, the importance of the SIRT1 genes in causing the noise hearing impairment is determined, meanwhile, genotypes and alleles of 7 sites of the SIRT1 genes are detected, gene interaction is performed, the correlation between the sites rs12778366 and rs7895833 of the SIRT1 genes and the noise exposure is verified, the kit is easy to operate, high in screening sensitivity and specificity, and suitable for pre-post job screening of large-scale susceptible people.

The aim of the invention can be achieved by the following technical scheme:

a biomarker for noise susceptibility hearing impairment is rs12778366 or rs7895833 single nucleotide polymorphism site in SIRT1 gene, wherein rs12778366 single nucleotide polymorphism site is shown as SEQ ID NO.1, and rs7895833 single nucleotide polymorphism site is shown as SEQ ID NO. 2.

The application of the biomarker in preparing a noise susceptibility hearing impairment detection kit.

A noise-susceptible hearing impairment detection reagent, comprising a reagent for detecting single nucleotide polymorphism loci rs12778366, rs7895833 of a SIRT1 gene;

the reagent comprises an RT primer of a SIRT1 gene polymorphism site and an SIRT1 gene RT primer;

the RT primer of the SIRT1 gene polymorphism site comprises an rs12778366-F end primer and an rs12778366-R end primer; or rs7895833-F terminal primer and rs7895833-R terminal primer

The SIRT1 gene RT primer comprises a SIRT1-F end primer and a SIRT1-R end primer;

wherein the rs12778366-F end primer and the rs12778366-R end primer are shown as SEQ ID NO.3 and SEQ ID NO. 4;

or rs7895833-F end primer and rs7895833-R end primer, as shown in SEQ ID NO.5 and SEQ ID NO. 6;

SIRT1-F terminal primer and SIRT1-R terminal primer are shown as SEQ ID NO.7 and SEQ ID NO. 8.

A kit for detecting noise-susceptible hearing impairment, the kit comprising the above-described reagent.

The invention has the beneficial effects that:

the invention extracts RNA from blood cells of spot check workers, determines the proportion of SIRT1 genes and environmental factors in noise hearing injury through a machine learning model, determines the importance of the SIRT1 genes in the noise hearing injury, detects the genotypes of 7 sites of the SIRT1 genes, effects alleles and gene interactions, verifies the correlation between the rs12778366 and rs7895833 sites of the SIRT1 genes and noise exposure, has simple operation and high screening sensitivity specificity, and is suitable for on-duty screening of large-scale susceptible people.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort.

FIG. 1 is a diagram of the primary variable duty cycle of the machine learning model of the present invention;

FIG. 2 is a thermal graph of the interaction of the sites in the NIHL group and the control group of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

A biomarker for noise susceptibility hearing impairment of workers and application thereof,

example 1:

selection of study objects

The subject was from a total of 1251 workers, 576 workers from the noise-impaired group and 675 workers from the control group, who included the noise-exposed factory. The study signed relevant informed consent by ethical review of the ethical committee of disease prevention control center in Jiangsu province.

Questionnaires and audiometry

The investigation content includes: (1) panelist informed consent; (2) General demographics (gender, age, cultural level, job, etc.); (3) lifestyle and behavioral habits (smoking, drinking); and (4) noise receiving time.

Audiometry requirements: (1) The study object needs to be separated from the noise environment for at least 12-48 hours before being examined; (2) In the case of a pair of studies on sexual hearing measurements, it is ensured that the noise floor of the sound-insulating room is less than 25dB (A); (3) Performing pure-tone sound-guiding threshold tests of 6 frequencies of 5000, 1000, 2000, 3000, 4000 and 6000Hz on ears of all subjects respectively; (4) The audiometric values of the study subjects were age and sex corrected and then high frequency hearing loss was calculated.

Determination of individual noise exposure

The detection of noise exposure intensity in all subject work environments was performed by using a QuestNoisePro-DL type multifunctional personal noise dosimeter (Quest, USA) according to workplace physical factor measurement noise (GBZ/T189.8.2007). The detection method comprises the following steps: (1) In the production state, the multifunctional personal noise dosimeter is fixed on the ears of workers, and the sound receiving part faces to the sound source; (2) When steady-state noise measurement is carried out, each measuring point is required to be measured for 3 times, and an average value is taken as a detection result of the measuring point; (3) When the unsteady noise measurement is carried out, the measurement time is divided according to the sound level change, and the data is recorded.

The study uses an 8 hour equivalent continuous A weighting sound pressure level (normalized continuousA-weighted soundpressure level equivalentto an h-working-day, LEX,8 h) to represent the noise exposure intensity of the study subjects. National occupational health Standard provision L _EX，8h And more than or equal to 80dB (A) is noise operation.

Peripheral blood collection and treatment

5ml of fasting venous blood of a study object in the morning is extracted, 1000g is rapidly centrifuged for 10min at room temperature, lower plasma is collected after centrifugation, blood cells are used for extracting RNA, and the RNA is put into an ice chest for freezing at the temperature of minus 80 ℃ and then carried back to a laboratory for detection. And extracting blood cell RNA by adopting a Trizol Reagent according to the operation steps of the specification, detecting the purity of the extracted RNA by using a Nanodrop OneC ultra-micro ultraviolet spectrophotometer, and when the absorbance (A) 260/A280 is between 1.8 and 2.0, indicating that the purity of the extracted RNA is higher, and the extracted RNA can be used for subsequent PCR experiments.

Real-time fluorescent quantitative PCR

cDNA is obtained by reverse transcription of RNA extracted from blood cells, and then RT-PCR reaction is carried out, GAPDH is used as an internal reference, and primer sequences are shown as SEQ ID NO.7 and SEQ ID NO. 8. Gene expression levels were calculated by the 2- ΔΔCt method.

Blood cell gene SNP typing method

(1) Extraction of RNA

Blood cell RNA is extracted by adopting a Trizol Reagent according to the operation steps of the specification, and then the purity of the extracted RNA is detected by using a Nanodrop OneC ultra-micro ultraviolet spectrophotometer.

(2) Selection of SNPs loci

All SNPs sites in SIRT1 gene were determined by UCSC database, thousand genome project chinese population data information, and following site inclusion criteria. Inclusion criteria were as follows:

a the SNPs sites with a minimum allele frequency (minor allele frequency, MAF) >0.05 and a P-value of the hadi-winberg equilibrium >0.05 were selected.

And b, carrying out linkage disequilibrium analysis on the genes by using Haploview 4.2 software to select SNPs.

c, selecting functional SNPs loci related to SIRT1 genes through literature retrieval.

(3) SNP typing

Genotyping analysis was performed on the incorporated SNPs by the ABI 7900 real-time PCR system.

Statistical analysis

Statistical analysis was performed using SPSS25.0 software (IBM, armonk, NY, USA). Analysis of continuous variables and normalized distribution and variance alignment was examined using Student's t, and classification variables were Pearson's X ² And (6) test. The non-normal continuous variable adopts Mann-Whitney rank sum test; and (3) establishing a machine learning model of the LightGBM algorithm by adopting python3.11.1, and evaluating the diagnosis effect of the LightGBM algorithm model through the accuracy and the correct rate of the results of the training set and the testing set. By using goodness of fit X ² The genotype distribution of each SNP locus in the whole population was examined for compliance with the Hardy-Winberg genetic balance (Hardy-Weinberg equilibrium, HWE). The ratio of allele frequencies at sex, post-age SIRT1 loci to NIHL susceptibility (odds ratio, OR) and 95% confidence interval (95%confidence intervals,CIs) were adjusted using logistic regression analysis. Check-level α=0.05. Gene-gene interactions were analyzed by generalized multifactor dimensionality reduction soft V0.9 (generalized multifactor dimensionality reduction V0.9.0.9, GMDR V0.9).

Results:

description of basic characteristics of study object

Table 1 shows general demographic and clinical data for study population, with no statistical differences in age, gender, smoking, alcohol consumption, noise exposure time, and noise exposure levels in the NIHL and Control groups. The NIHL and Control groups had statistical significance in high-level hearing impairment (P < 0.001).

TABLE 1 demographic and clinical characteristics of noise exposed workers

Detection of SIRT1 expression levels

The gene expression level of the obtained cDNA was calculated by RT-PCR through a 2-delta Ct method, which showed that the gene expression level of SIRT1 was significantly lower in the NIHL group than in the Control group, and the difference was statistically significant (p <0.001, table 2). The SIRT1 gene in blood cells is therefore considered a biomarker for screening high risk workers for noise exposure.

TABLE 2 SIRT1 Gene expression levels in the NIHL and Control groups

Note that: a, performing Mann-Whitney rank sum test on two independent samples;

establishment of machine learning model

The SIRT1 expression level, the demographics of the investigated workers, the exposure condition and other indexes are imported into the LightGBM algorithm, so that a machine learning model for the NIHL group and the Control group is built. In this model, the SIRT1 gene is 48.4% (FIG. 1). The accuracy of the model in the training set is 98.2%, the accuracy in the test set is 67.9% (table 3), the predictive evaluation indexes of the cross validation set, the training set and the test set are shown in the table, and the predictive effect of the LightGBM is measured through the quantitative indexes.

TABLE 3 diagnosis of training and testing sets by model

Allele association analysis

In Table 4, alleles at 7 sites of SIRT1 are detected and analyzed for allele versus NIHL. From the table we can see that of these 7 loci, only the allele distribution at 2 loci of SIRT1 (rs 12778366, rs 7895833) is statistically significant (P < 0.05) in the difference between NIHL and Control groups, indicating that there is a correlation between two loci rs12778366, rs7895833 and NIHL, and that, in combination with the OR value, two loci rs12778366, rs7895833 are considered to have a positive correlation with NIHL.

TABLE 4 allele distribution in NIHL and Control groups

Note that: a, checking by double-side X2;

genotype association analysis

Table 5 shows the genotyping results for SNPs. From the table we can see that the genotype distribution at the rs12778366, rs7895833 locus of the SIRT1 gene is statistically significant (P < 0.05) between the NIHL group and the Control group. There was no deviation from Hardy-Weinberg equilibrium in the genotype and allele distribution of SNPs in the NIHL and Control groups adjusted by age, sex, education and alcohol consumption.

TABLE 5 genotype distribution of SNPs in NIHL group and Control group

Note that: a P value of the Hardy-Wenberg equilibrium test;

b, checking with X2 on two sides;

analysis of Gene-Gene interaction

As shown in Table 6, the present study uses GMDR v0.9 software to analyze the interaction between 7 SNPs of SIRT1 gene, and the analysis results were corrected according to age, smoking, drinking, noise receiving time, and noise exposure level, and the effect of the interaction between 7 SNPs of SIRT1 gene is shown in FIG. 2.

TABLE 6 interaction of sites in NIHL group and control group

Note that: a, checking by double-side X2;

as shown in FIG. 2, 7 SNPs of SIRT1 gene have significant effects of gene interaction

The application adopts a SNP genotyping method to detect the genotype of the locus rs12778366 and rs7895833 of the SIRT1 gene of a tested person, and the single nucleotide polymorphism locus of the SIRT1 gene is shown as follows:

wherein the nucleotide sequence of the rs12778366 single nucleotide polymorphism site is shown in SEQ ID NO. 1:

CAGGGCCGGCGCGGCTTGAGGCCGC[G/T]AGGGTCTGGAGGGGGCGT CTATTCT，

the nucleotide sequence of the rs7895833 single nucleotide polymorphism site is shown in SEQ ID NO. 2:

ACACTGAAGGAGCTGTAGCATCCAA[G/C]AATACTAGATACCTTTAATC CTCC。

the RT primer containing SIRT1 gene polymorphism sites in the kit is as follows:

wherein the nucleotide sequence of rs12778366-F is shown in SEQ ID NO. 3:

TTAAAATACTGAAACACTGCCTCC

the nucleotide sequence of rs12778366-R is shown in SEQ ID NO. 4:

AAGATATGTACTCTTGGATGGGTG；

the nucleotide sequence of rs7895833-F is shown in SEQ ID NO. 5:

ATGCCCTCCTACTACTTACTATTG

the nucleotide sequence of rs7895833-R is shown in SEQ ID NO. 6:

AAAATAGAATCAAAGCCTCACTTG；

the kit contains SIRT1 gene RT primers as follows:

the nucleotide sequence of SIRT1-F is shown in SEQ ID NO. 7:

GGGTGTCTGTTTCATGTGG

the nucleotide sequence of SIRT1-R is shown in SEQ ID NO. 8:

CAGCAAGGCGAGCATA。

starting from single nucleotide polymorphism of SIRT1 genes, 7 single nucleotide polymorphism sites of SIRT1 genes are selected by using a Hapmap database and an NCBI database and referring to related documents, wherein the single nucleotide polymorphism sites are respectively rs12778366, rs10997868, rs12049646, rs2236319, rs2273773, rs3758391 and rs7895833. Through genotyping and correlation research analysis, the relation between rs12778366 and rs7895833 in SIRT1 genes and susceptibility of noise exposure people is detected and finally verified.

In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims.

Claims (5)

1. A biomarker for noise susceptibility hearing impairment is characterized in that the biomarker is an rs12778366 or rs7895833 single nucleotide polymorphism site in SIRT1 genes, wherein the rs12778366 single nucleotide polymorphism site is shown as SEQ ID NO.1, and the rs7895833 single nucleotide polymorphism site is shown as SEQ ID NO. 2.

2. Use of the biomarker of claim 1 for the preparation of a noise-susceptible hearing impairment detection reagent.

3. A reagent for detecting noise susceptibility hearing impairment, which is characterized by comprising a single nucleotide polymorphism site for detecting SIRT1 genes rs12778366 and rs 7895833;

the reagent comprises an RT primer of a SIRT1 gene polymorphism site and an SIRT1 gene RT primer;

the RT primer of the SIRT1 gene polymorphism site comprises an rs12778366-F end primer and an rs12778366-R end primer; or rs7895833-F terminal primer and rs7895833-R terminal primer

The SIRT1 gene RT primer comprises a SIRT1-F end primer and a SIRT1-R end primer;

wherein the rs12778366-F end primer and the rs12778366-R end primer are shown as SEQ ID NO.3 and SEQ ID NO. 4;

or rs7895833-F end primer and rs7895833-R end primer, as shown in SEQ ID NO.5 and SEQ ID NO. 6;

SIRT1-F terminal primer and SIRT1-R terminal primer are shown as SEQ ID NO.7 and SEQ ID NO. 8.

4. A noise-susceptible hearing impairment detection kit, comprising the reagent of claim 3.

5. Use of the reagent of claim 3 for preparing a noise susceptibility hearing impairment detection kit.

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