Volume 35 Issue 5
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FAN Ya Hui, LI Xin Ling, LIU Xiao Hua, GUO Zhi Feng, YAN Meng Qing, DUAN Xiao Ran, MIAO Wen Bin, WANG Wei. Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers[J]. Biomedical and Environmental Sciences, 2022, 35(5): 448-452. doi: 10.3967/bes2022.060
Citation: FAN Ya Hui, LI Xin Ling, LIU Xiao Hua, GUO Zhi Feng, YAN Meng Qing, DUAN Xiao Ran, MIAO Wen Bin, WANG Wei. Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers[J]. Biomedical and Environmental Sciences, 2022, 35(5): 448-452. doi: 10.3967/bes2022.060

Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers

doi: 10.3967/bes2022.060
Funds:  The work was supported by Programs for Science and Technology Development of Zhengzhou [131PPTGG376] and the Outstanding Youth Grant of Zhengzhou University [1521329035]
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  • Author Bio:

    FAN Ya Hui, female, born in 1996, MPH, majoring in occupational cancer and biomarker

  • Corresponding author: MIAO Wen Bin, E-mail: moumm999@sina.com,Tel: 86-371-67781466; WANG Wei, E-mail: ww375@zzu.edu.cn
  • Received Date: 2021-11-12
  • Accepted Date: 2022-03-29
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  • [1] Chowdhary S, Bhattacharyya R, Banerjee D. Acute organophosphorus poisoning. Clin Chim Acta, 2014; 431, 66−76. doi:  10.1016/j.cca.2014.01.024
    [2] Yu KX, Zeng ZR, Cheng S, et al. TPP1 Enhances the Therapeutic Effects of Transplanted Aged Mesenchymal Stem Cells in Infarcted Hearts via the MRE11/AKT Pathway. Front Cell Dev Biol, 2020; 8, 588023. doi:  10.3389/fcell.2020.588023
    [3] Liu Y, Snow BE, Hande MP, et al. Telomerase-associated protein TEP1 is not essential for telomerase activity or telomere length maintenance in vivo. Mol Cell Biol, 2000; 20, 8178−84. doi:  10.1128/MCB.20.21.8178-8184.2000
    [4] Xin HW, Liu D, Zhou SY. The telosome/shelterin complex and its functions. Genome Biol, 2008; 9, 232. doi:  10.1186/gb-2008-9-9-232
    [5] Gu C, Li Q, Zhu Y, et al. Genetic variants in the TEP1 gene are associated with prostate cancer risk and recurrence. Prostate Cancer Prostatic Dis, 2015; 18, 310−6. doi:  10.1038/pcan.2015.27
    [6] Ding MC, Yang YL, Duan XR, et al. Association of genetic polymorphisms of telomere binding proteins with cholinesterase activity in omethoate-exposed workers. Ecotoxicol Environ Saf, 2018; 161, 563−68. doi:  10.1016/j.ecoenv.2018.06.036
    [7] Zou KL, Zhou XS, Wang W, et al. The association between polymorphisms in miRNA and the cholinesterase activity of workers in an omethoate-exposed environment. Int J Environ Health Res, 2020; 32, 1020−29.
    [8] Duan XR, Yang YL, Wang SH, et al. Changes in the expression of genes involved in cell cycle regulation and the relative telomere length in the process of canceration induced by omethoate. Tumour Biol, 2017; 39.
    [9] Prickett CD, Lister E, Collins M, et al. Alcohol: Friend or Foe? Alcoholic Beverage Hormesis for Cataract and Atherosclerosis is Related to Plasma Antioxidant Activity. Nonlinearity Biol Toxicol Med, 2004; 2, 353−70.
    [10] Hernández AF, Lacasaña M, Gil F, et al. Evaluation of pesticide-induced oxidative stress from a gene-environment interaction perspective. Toxicology, 2013; 307, 95−102. doi:  10.1016/j.tox.2012.09.007
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Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers

doi: 10.3967/bes2022.060
Funds:  The work was supported by Programs for Science and Technology Development of Zhengzhou [131PPTGG376] and the Outstanding Youth Grant of Zhengzhou University [1521329035]
  • Author Bio:

  • Corresponding author: MIAO Wen Bin, E-mail: moumm999@sina.com,Tel: 86-371-67781466;  WANG Wei, E-mail: ww375@zzu.edu.cn
FAN Ya Hui, LI Xin Ling, LIU Xiao Hua, GUO Zhi Feng, YAN Meng Qing, DUAN Xiao Ran, MIAO Wen Bin, WANG Wei. Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers[J]. Biomedical and Environmental Sciences, 2022, 35(5): 448-452. doi: 10.3967/bes2022.060
Citation: FAN Ya Hui, LI Xin Ling, LIU Xiao Hua, GUO Zhi Feng, YAN Meng Qing, DUAN Xiao Ran, MIAO Wen Bin, WANG Wei. Association between Polymorphisms in Telomere-Associated Protein Genes and the Cholinesterase Activity of Omethoate-Exposed Workers[J]. Biomedical and Environmental Sciences, 2022, 35(5): 448-452. doi: 10.3967/bes2022.060
  • Organophosphorus pesticides (OPs) are extensively used for their high efficiency, broad spectrum, and low residue. However, the health hazards caused by long-term, low-dose exposure to OPs are easily ignored. Omethoate is a large class of OPs that is widely used in China. The inhibition of the cholinesterase (ChE) activity is the main toxicity mechanism of OPs, and such an activity is used as a biomarker of exposure to OPs[1].

    Telomeres are composed of noncoding DNA repeats, telomere-binding proteins (TBPs), and telomerase, which gradually shorten during cell division. POT1-TIN2 Organizing Protein (TPP1), a kind of TBP, actively recruits telomerase to telomeres, protects chromosome ends, and regulates telomere length together with POT1[2]. TGF β-regulated and epithelial cell-enriched phosphatase 1 (TEP1), a mammalian telomerase-associated protein, is associated with telomerase activity and the telomerase reverse transcriptase, and it specifically interacts with telomerase RNA[3]. TEP1 and TPP1 are telomere-associated protein genes that participate in telomere length regulation and terminal protection to affect chromosome stability[4, 5]. In addition, studies have shown that telomere- associated proteins first affect chromosome stability and then change the expression level of ChE-related genes, thus affecting ChE production and degradation[6].

    Single nucleotide polymorphism (SNP) is a common form of single-base mutation and can affect the mRNA expression levels of their genes or protein functions. So far, the correlations among the polymorphisms of TPP1, TEP1 genes, and the ChE activity are unclear. Therefore, this study explored the relationship between TPP1, TEP1 gene polymorphisms, and ChE activity.

    A total of 180 workers exposed to omethoate for more than eight years were included in the exposure group. In addition, 115 healthy persons from a company in the same area without a history of exposure to omethoate or other toxicants comprised the control group. Individuals with histories of chronic diseases or other acute and chronic infections were excluded. People who smoked at least one cigarette a day for more than half a year were defined as smoking; people who drank alcohol more than twice a week in the last six months were defined as drinking. Demographic characteristics, occupational histories, and biological samples were collected by trained professionals. All subjects signed informed consent, and the study was approved by the Ethics Committee of Zhengzhou University.

    In this study, whole blood, red blood cell, and plasma ChE activities were measured, and the damage induced by omethoate was represented by the red blood cell ChE activity. The detailed determination method could be seen in our previous study[7].

    Eleven polymorphic loci of TEP1 rs1713449, TEP1 rs1760897, TEP1 rs1760903, TEP1 rs938886, TEP1 rs1760904, TEP1 rs4246977, TPP1 rs1800752, TPP1 rs3758978, TPP1 rs7488, TPP1 rs1128396, and TPP1 rs2555173 were screened through the HapMap, NCBI-SNP, and 1,000 Genomes databases or published works. PCR and single-base extension primers were designed by the Assay Designer 3.1 software and were synthesized by Thermo Fisher Scientific Co., Ltd, 2020 (Supplementary Table S1 available in www.besjournal.com). The SNPs were genotyped with a MassARRAY® matrix-assisted laser desorption/ionization time-of-flight mass spectrometry platform (Agena, Inc., 4.0 San Diego, CA, USA).

    GeneSNPPrimerPrimer Sequence (5’–3’)
    TEP1rs1713449ForwardACGTTGGATGAAGAGTGGATGCCATAACCG
    ReverseACGTTGGATGCTCTGTGTCTTATCAGCTGG
    UEP-SEQGAGGGGTCAGAGCTTCTGGTGGTAACC
    rs1760897ForwardACGTTGGATGTGTAGACTCTGGAACAAGGG
    ReverseACGTTGGATGACATCCTCTCCTTGGAGAAC
    UEP-SEQCCCCGTGCCTGGCCACCCTC
    rs1760903ForwardACGTTGGATGGTCTGCTTAGGTAGCTCTTC
    ReverseACGTTGGATGCAGATGCCTGGAAATCTGAC
    UEP-SEQTCTGAAGAGGCCGCA
    rs938886ForwardACGTTGGATGCCTCATTTTTGTGTGCCAGC
    ReverseACGTTGGATGTTACCTGTGGTCCATTCTCC
    UEP-SEQGGGTCTGCATTTGGCCAGGTTCCATAG
    rs1760904ForwardACGTTGGATGATGCAGGCATCTCTTGTGTC
    ReverseACGTTGGATGCCCCAGAAAAGTGGAAGAAG
    UEP-SEQCAAGAAAAGTGGAAGAAGACTAATG
    rs4246977ForwardACGTTGGATGCTCCATGACCTAATGACCTC
    ReverseACGTTGGATGGAAACCCTAATCCCAATGCG
    UEP-SEQACCCAATGCGATGGTA
    TPP1rs1800752ForwardACGTTGGATGAGTCAAGCACTGAGTAAGCC
    ReverseACGTTGGATGAGTCTGTGGGTCTCTACAGC
    UEP-SEQCCTACAGCCCACTCACT
    rs3758978ForwardACGTTGGATGGTTAGGGTGTTGAATGGGTC
    ReverseACGTTGGATGTTTCTGTCCATCCCAACTCC
    UEP-SEQCCCACCTCCTGCGATCATTTGAC
    rs7488ForwardACGTTGGATGTGTGCCTACCTCTAGCATTG
    ReverseACGTTGGATGAACGGTCTTGGAAAGGAAGG
    UEP-SEQAAACTGGCCATTTCAATACTA
    rs1128396ForwardACGTTGGATGTTCTCAACCCAAGGCTCTAC
    ReverseACGTTGGATGTGAAAACGTCCACACCCTTC
    UEP-SEQCTTCCATACTTACATCAAAGAG
    rs2555173ForwardACGTTGGATGATGGCTACGGCAGCGCAGTT
    ReverseACGTTGGATGATAGTGGATCTGCGGGTTAG
    UEP-SEQCAGGGCGGAGACCGA
      Note. Forward: upstream primer, Reverse: downstream primer, UEP-SEQ: single base extension primer.

    Table S1.  The primer sequences of polymorphic loci

    All statistical analyses were conducted using SPSS 21.0 software (SPSS Inc., Chicago, IL, USA). The independent samples t-test was performed to compare the ChE activity between the exposure and control groups. Covariance was used to analyze the effects of genetic polymorphisms on the ChE activity, and the Dunnett method was employed to perform the comparisons between the two groups. Generalized linear models (GLMs) were used to determine the influencing factors of the ChE activity. All statistical tests were two-sided, and the statistical significance level was set at α = 0.05.

    Significant differences were observed in demographic characteristics, including gender, age, smoking, and drinking (P < 0.001), comparing the exposure and control groups (Supplementary Table S2 available in www.besjournal.com), which were described in detail in our previous study[8]. The red blood cell ChE activity in the exposure group was lower than that in the control group (2.09 ± 0.52 vs. 3.06 ± 0.65, P < 0.001) (Supplementary Table S3 available in www.besjournal.com). As illustrated in Figure 1, gender, age, smoking, and drinking had an effect on the red blood cell ChE activity (P < 0.05); in the exposure group, the ChE activity was associated with gender, smoking, and drinking (P < 0.05). However, age and working duration had no effect on the ChE activity in the exposure group (P > 0.05) (Supplementary Table S4 available in www.besjournal.com).

    Figure 1.  Effect of demographic characteristics on cholinesterase activity. The independent samples t-test was utilized to compare the ChE activity between the exposure and control groups. *The difference in the ChE activity between both groups after stratification was statistically significant. #The difference in the control group was statistically significant. &The difference in the exposure group was statistically significant.

    VariablesControl (n = 115)Exposure (n = 180)χ2P
    Gender
     Male54 (47.0)137 (76.1)26.130< 0.001*
     Female61 (53.0)43 (23.9)
    Age
     < 4067 (58.3)53 (29.4)24.146< 0.001*
     ≥ 4048 (41.7)127 (70.6)
    Smoking
     Yes12 (10.4)63 (35.0)22.333< 0.001*
     No103 (89.6)117 (65.0)
    Drinking
     Yes30 (26.1)16 (8.9)15.769< 0.001*
     No85 (73.9)164 (91.1)
    Working duration
     < 1526 (14.4)
     15–30117 (65.0)
     > 3037 (20.6)
      Note. The χ2 test was utilized to compare the general characteristics of exposure and control groups. *The difference was statistically significant.

    Table S2.  General characteristics of exposure and control group, n (%)

    VariablesControlExposuretP
    Whole blood ChE activity3.89 ± 0.802.47 ± 0.5316.790< 0.001*
    Red blood cells ChE activity3.06 ± 0.652.09 ± 0.5213.485< 0.001*
    Plasma ChE activity0.82 ± 0.240.38 ± 0.2116.621< 0.001*
      Note. The independent-samples t-test was utilized to compare the ChE activity between the exposure and control group. ChE: Cholinesterase activity. *The difference was statistically significant.

    Table S3.  The comparison of cholinesterase activity between exposed group and control group

    VariablesExposure ControltP
    n$\bar{{x} }\pm {s}$n$\bar{x} \pm {s}$
    GenderMale1372.16 ± 0.54543.42 ± 0.5414.504< 0.001*
    Female431.87 ± 0.37612.75 ± 0.589.351< 0.001*
    t3.9206.333
    P< 0.001#< 0.001#
    Age≤ 40532.01 ± 0.44673.18 ± 0.5912.332< 0.001*
    > 401272.12 ± 0.54482.90 ± 0.706.921< 0.001*
    t1.426−2.273
    P0.1570.025#
    SmokingYes632.24 ± 0.52123.53 ± 0.428.037< 0.001*
    No1172.01 ± 0.501033.01 ± 0.6512.029< 0.001*
    t2.9953.803
    P0.003#0.001#
    DrinkingYes162.39 ± 0.58303.43 ± 0.536.102< 0.001*
    No1642.06 ± 0.50852.93 ± 0.6410.871< 0.001*
    t2.4833.081
    P0.014#< 0.001#
    Working< 15262.12 ± 0.47
    duration15–301172.09 ± 0.53
    > 30372.07 ± 0.52
    F0.066
    P0.936
      Note. *Indicates the comparisons of ChE activity between exposure group and control group after stratification; #Represents the comparisons among the layers after stratification.

    Table S4.  The effects of sex, age, smoking, drinking and working duration on ChE activity

    The genotypic distribution of each polymorphic locus accorded with Hardy-Weinberg balance (P > 0.05) indicated that the selected samples were representative. We analyzed the differences in the ChE activity between different genotypes of TPP1 and TEP1 polymorphisms (Table 1). The CT and CC genotypes of TPP1 rs1800752 had a similar ChE activity, so they were combined. TPP1 rs3758978, TPP1 rs7488, and TPP1 rs1128396 were the same. The ChE activity of the TPP1 rs1800752 CT + CC genotype was lower than that of the TT genotype (2.02 ± 0.54 vs. 2.18 ± 0.46, P = 0.006). The ChE activity of the TPP1 rs3758978 CG + GG genotype was lower than that of the CC genotype (2.01 ± 0.54 vs. 2.19 ± 0.46, P = 0.003). The ChE activity of the TPP1 rs1128396 AT + TT genotype was lower than that of the AA genotype (2.00 ± 0.53 vs. 2.17 ± 0.50, P = 0.002). Moreover, the ChE activity of the TPP1 rs2555173 AC + AA genotype was lower than that of the CC genotype (2.03 ± 0.55 vs. 2.13 ± 0.49, P = 0.037). No significant difference in genotypes was found in other loci (P > 0.05). C Gu et al.[5] identified that TEP1 rs1760904 AG/AA genotypes were significantly associated with a decreased risk of prostate cancer compared with the GG genotype. However, we found no statistically significant difference among the different genotypes of TEP1 rs1760904.

    SNPn#ControlPn#ExposureP
    $\bar{{x} }\pm {{s} }$$\bar{{x} }\pm {{s} }$
    TEP1 rs1713449
     TT162.77 ± 0.59Ref272.02 ± 0.53Ref
     CT483.08 ± 0.620.136592.06 ± 0540.851
     CC493.13 ± 0.700.057922.12 ± 0.500.669
     CT+CC1133.10 ± 0.660.0671512.10 ± 0.520.724
    TEP1 rs1760897
     CC63.20 ± 0.61Ref102.02 ± 0.40Ref
     CT383.01 ± 0.670.650622.01 ± 0.510.789
     TT673.09 ± 0.670.7271062.14 ± 0.530.635
     CT+TT1053.06 ± 0.660.6911682.09 ± 0.520.845
    TEP1 rs1760903
     TT482.97 ± 0.66Ref642.02 ± 0.46Ref
     CT443.17 ± 0.680.311792.12 ± 0.560.523
     CC213.09 ± 0.600.446362.14 ± 0.510.450
     CT+CC653.14 ± 0.650.2731152.12 ± 0.540.432
    TEP1 rs938886
     CC122.97 ± 0.64Ref241.99 ± 0.53Ref
     CG483.07 ± 0.620.973602.06 ± 0.550.632
     GG503.12 ± 0.690.589902.13 ± 0.500.492
     CG+GG983.10 ± 0.650.7501502.10 ± 0.520.521
    TEP1 rs1760904
     CC462.98 ± 0.66Ref642.01 ± 0.46Ref
     CT463.16 ± 0.670.319762.14 ± 0.560.345
     TT213.05 ± 0.620.803372.12 ± 0.530.559
     CT+TT673.13 ± 0.650.3921132.13 ± 0.550.346
    TEP1 rs4246977
     TT593.01 ± 0.70Ref752.06 ± 0.52Ref
     CT503.11 ± 0.600.507812.09 ± 0.500.292
     CC53.21 ± 0.670.437202.18 ± 0.600.269
     CT+CC553.12 ± 0.600.4181012.11 ± 0.520.212
    TPP1 rs1800752
     TT433.06 ± 0.62Ref702.18 ± 0.46Ref
     CT563.10 ± 0.690.762802.01 ± 0.560.007*
     CC123.04 ± 0.610.805272.04 ± 0.510.098
     CT+CC683.09 ± 0.670.8491072.02 ± 0.540.006*
    TPP1 rs3758978
     CC453.02 ± 0.63Ref712.19 ± 0.46Ref
     CG553.09 ± 0.690.665802.01 ± 0.550.004*
     GG123.04 ± 0.610.916272.04 ± 0.510.080
     CG+GG673.08 ± 0.680.7301072.01 ± 0.540.003*
    TPP1 rs7488
     AA953.06 ± 0.66Ref1402.11 ± 0.51Ref
     AG163.09 ± 0.650.303352.00 ± 0.550.605
     GG0032.04 ± 0.160.895
     AG+GG163.09 ± 0.650.303382.00 ± 0.530.646
    TPP1 rs1128396
     AA593.04 ± 0.64Ref952.17 ± 0.50Ref
     AT453.11 ± 0.690.676662.00 ± 0.530.004*
     TT83.02 ± 0.660.516142.02 ± 0.560.093
     AT+TT533.09 ± 0.680.856802.00 ± 0.530.002*
    TPP1 rs2555173
     CC623.06 ± 0.66Ref1022.13 ± 0.49Ref
     AC443.09 ± 0.660.791652.05 ± 0.550.097
     AA82.97 ± 0.710.571111.87 ± 0.550.037*
     AC+AA523.07 ± 0.660.681762.03 ± 0.550.037*
      Note. The covariance was obtained to compare the difference in the ChE activity among the genotypes, adjusted for gender, age, smoking, drinking, and working duration. Ref: The reference group for comparing different genotypes. SNP: Single nucleotide polymorphism. #Some samples were missing due to limitations of detection methods. *The difference was statistically significant

    Table 1.  Relationships between genetic polymorphism and ChE activity

    The factors affecting the ChE activity of workers exposed to omethoate were analyzed using GLMs. The adjusted age, smoking, working duration, drinking, omethoate exposure, gender, and interaction between the TPP1 rs3758978 CC genotype and omethoate exposure might be the influencing factors of the ChE activity of omethoate-exposed workers (P < 0.05) (Table 2). The ChE activity of females was lower than that of males, indicating that women were more susceptible to omethoate than men. Drinking might be another potential protective factor in the ChE activity, which was similar to the finding that moderate alcohol consumption could increase antioxidant activity[9], suggesting that drinking might have played a similar role in workers exposed to omethoate. Hernandez et al.[10] evaluated pesticide-induced oxidative stress and found an interaction between pesticide exposures and genes. They suggested that the interaction between these genes and the pesticides may play a key role in the development of many chronic and degenerative diseases.

    Parameterβ (95% CI)χ2P
    Constant2.808 (2.556, 3.061)474.301< 0.001*
    Drinking0.271 (0.078, 0.463)7.6150.006*
    Exposure−0.903 (−1.235, −0.571)28.392< 0.001*
    Female−0.408 (−0.555, −0.262)29.918< 0.001*
    TPP1 rs3758978 CC−0.034 (−0.229, 0.161)0.1140.736
    Exposure ×
    rs3758978 CC
    0.250 (0.001, 0.499)3.8670.049*
      Note. Adjusted for age, smoking, and working duration by using the GLM method. GML: Generalized linear models. *The difference was statistically significant.

    Table 2.  Influencing factors of the ChE activity

    This study observed an interaction of telomere-associated protein genes and environmental factors that affects human health, thereby providing clues for the screening of susceptible workers exposed to omethoate and the mechanism of inheritance variation. However, this research has some limitations. First, it is a cross-sectional study, which may require further follow-up to confirm its correlation. Second, the OPs were metabolized and excreted in the urine, usually within 24−48 hours of exposure. Therefore, the relationship of urinary metabolites with the ChE activity and gene polymorphism may need to be further evaluated.

    In conclusion, this study suggests that drinking, omethoate exposure, gender, and the interaction between the TPP1rs3758978 CC genotype and omethoate exposure may be the influencing factors of the ChE activity of omethoate-exposed workers.

    No potential conflicts of interest were disclosed.

    The authors express their gratitude to all the individuals who volunteered to participate in this study.

    FAN Ya Hui, data analysis and manuscript drafting; LI Xin Ling, LIU Xiao Hua, GUO Zhi Feng, and YAN Meng Qing, project investigation and quality control; DUAN Xiao Ran, experiment; MIAO Wen Bin, manuscript revision; WANG Wei, funding acquisition and project design; all authors commented on the article before submission.

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