Polycyclic aromatic hydrocarbon exposure, miRNA genetic variations, and associated leukocyte mitochondrial DNA copy number: A cross-sectional study in China

Chemosphere 246 (2020) 125773

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Polycyclic aromatic hydrocarbon exposure, miRNA genetic variations, and associated leukocyte mitochondrial DNA copy number: A crosssectional study in China Xiaoran Duan a, b, Yongli Yang c, Hui Zhang a, Bin Liu a, Wan Wei a, Liuya Wang b, Changqing Sun d, Wu Yao a, Liuxin Cui a, Xiaoshan Zhou a, Wei Wang b, * a

Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China Biotherapy Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450052, Henan, China Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China d Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, China b c

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


mtDNAcn decreased with environmental PAH exposure.
miR-210 rs11246190 GG was a protective factor of mtDNAcn.
The other 14 polymorphisms in miRNA had null effects on mtDNAcn.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 18 November 2019 Received in revised form 25 December 2019 Accepted 27 December 2019 Available online 28 December 2019

Mitochondria DNA was preferentially attacked by the exogenous carcinogens including polycyclic aromatic hydrocarbons (PAHs) relative to nuclear DNA, and nuclear gene variants may account for variability in the mitochondrial DNA copy number (mtDNAcn). However, it remains unclear whether miRNA genetic variations are associated with mitochondrial DNA damage in the PAH-exposed workers. Therefore, we measured the leukocyte mtDNAcn, urinary 1-hydroxypyrene (1-OHPYR), environmental PAH exposure, and miRNA genetic polymorphisms among 544 coke oven workers and 238 healthy control participants. We found that the mtDNAcn in the exposure group (0.60 ± 0.29) was significantly lower than that in the control group (1.03 ± 0.31) (t ¼ 18.931, P < 0.001). Spearman correlation analysis showed that the peripheral blood leukocyte mtDNAcn had significantly negative correlations with the levels of 1-OHPYR and environmental PAH exposure (P < 0.001). Covariance analysis indicated that miR-210 rs11246190 AA, miR-210 rs7395206 CC, and miR-126 rs2297538 GG probably promoted a decrease in leukocyte mtDNAcn in the exposure or control groups (P < 0.05). In generalized linear model, miR-210 rs11246190 GG was a protective factor of mtDNAcn, and environmental PAH exposure was the risk factor of the mtDNAcn. In conclusion, the decrease of leukocyte mtDNAcn is the result of a combination of environmental and genetic factors. © 2020 Elsevier Ltd. All rights reserved.

Handling Editor: A. Gies Keywords: Polycyclic aromatic hydrocarbons Mitochondrial DNA copy number rs11246190 miRNA

* Corresponding author. Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, No.100Kexue Road, Zhengzhou, 450001, China. E-mail address: [email protected] (W. Wang). https://doi.org/10.1016/j.chemosphere.2019.125773 0045-6535/© 2020 Elsevier Ltd. All rights reserved.

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X. Duan et al. / Chemosphere 246 (2020) 125773

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are human carcinogens with a widespread presence in the occupational or general population due to coking production, diets, tobacco smoking, and environmental pollution (Wang et al., 2019a). Long-term exposure to PAHs results in a variety of diseases and tumorigenesis through inducing DNA damage (Moorthy et al., 2015), and exposure to PAHs can also generate sustained reactive oxygen species (ROS), which primarily target the mitochondria DNA (mtDNA) (Cui et al., 2019). Increasing evidence shows that PAHs could induce mitochondrial dysfunction (Bansal et al., 2014). Mitochondria, as a marker of cell senescence, plays an important role in energy metabolism of the body. Mitochondrial gene deletion or mutation could cause decreased respiratory enzyme complex activity and reduced energy metabolism efficiency, leading to a variety of diseases, especially playing an important role in the occurrence and development of tumors (Melkonian et al., 2015). Binding to carcinogenic factors, as well as elevated levels of active oxides caused by the internal environmental changes in cancerous tissues, could cause gene mutations which ultimately result in changes in mtDNA replication and transcription levels (Yang et al., 2016). In recent years, the mitochondrial DNA copy number (mtDNAcn) has become a biomarker of oxidative stress (Kim et al., 2014). The number and size of mitochondria were positively correlated with the mtDNAcn in cells. Compared with the nuclear DNA (nDNA), mtDNA lacked an effective damage repair system, so it was highly vulnerable to exogenous carcinogens and could be regarded as an important target of the carcinogens (Carugno et al., 2012). Therefore, mtDNAcn was expected to be a biomarker that predicted the risks of developing diseases including cancers. The maintenance of mtDNA relies on proteins encoded by nuclear genes (Ronchi et al., 2019). Several studies have suggested that microRNAs (miRNAs) regulate nuclear gene expression in various cancers (Peng et al., 2019; Sabelstrom et al., 2019). Recent studies have suggested that microRNAs can translocate to mitochondria to modulate mitochondrial activities (Li et al., 2019a). Taken together, miRNAs are known to be involved in the regulation of nuclear and mitochondrial genes which ultimately regulate the mitochondrial function. Our previous studies have found that genetic variations in encoding miRNAs genes were associated with the change of leukocyte telomere length (Duan et al., 2019b; Wang et al., 2019b). However, it is unknown whether miRNA genetic variations are involved in the regulation of mtDNAcn. Therefore, we focused on miRNAs that were important in the development of lung cancer such as miR-210, miR-30a, miR-126, miR-145, miR-25 and miR-197 (Shen et al., 2011; Cazzoli et al., 2013; Geng et al., 2014), to explore a susceptible population of coke oven emissions (COEs) from the perspective of epigenetics. In the present study, we investigated the associations between environmental PAH exposure, internal dose (urinary 1-OHPYR), and leukocyte mtDNAcn in 544 coke oven workers and 238 healthy control participants and explored the effects of miRNA genetic polymorphisms on leukocyte mtDNAcn in the exposed workers.

work, and oven top work. Control group: Two hundred thirty-eight healthy participants were from the same region as the exposure group, and they were all without any occupational poison exposure including PAHs. After signing informed consent forms, all eligible participants completed a questionnaire and provided biological samples (blood and urine). Importantly, each investigator was required to undergo rigorous professional training, including the uniform criteria of the investigation, self-inspection of the integrity, and logic errors of the investigation forms. The study protocol and consent form were approved by the Ethics Committee of Zhengzhou University, China. More detailed information for the study could be seen in our previous paper (Duan et al., 2019a). 2.2. Research methods 2.2.1. Determination of environmental exposure Urine samples were collected with 50 ml centrifuge tubes and then stored at 80  C until detection. A medium flow sampler was used to collect the COEs in the air. Detailed detection methods were described in our previous study (Duan et al., 2019a). 2.2.2. Measurement of mtDNA DNA was extracted from the peripheral blood leukocytes using the Large Amount of Whole Blood Genomic DNA Extraction Kit (Beijing BioTeke Corporation). mtDNAcn was determined using a real-time quantitative polymerase chain reaction (PCR) method, which was measured based on the mtND1 gene primers and bglobin gene primers. The mtND1 gene primers were forward, 50 CCTAATGCTTACCGAACGA -30 and reverse, 50 -GGGTGATGGTAGATGTGGC-3’. The b-globin gene was forward, 50 -GCTTCTGACAand reverse, 50 CAACTGTGTTCACTAGC-30 CACCAACTTCATCCACGTTCACC-3’. PCR reaction systems were conducted in a final volume of 10 ml, including 2  SYBR Green qPCR Mix (MQ10201S, Monad Biotech Co., Ltd.; 5 ml/reaction), forward (0.2 ml/reaction-10 mM) and reverse (0.2 ml/reaction-10 mM) primers, DNA sample (1.0 ml/reaction-50 ng/ml), and RNase-free water (3.6 ml/reaction). The PCR thermal cycling profiles were as follows: 95  C for 5 min, followed by 40 cycles of 95  C for 15 s (denaturation step), 60  C for 30 s (anneal and extension step), and then one cycle of 95  C for 15 s, 60  C for 1 min, 95  C for 15 s for the dissolution curves. All PCRs were run in triplicate using a Monad q225 realtime quantitative PCR instrument. 2.2.3. Genotyping of polymorphic loci SNPs were genotyped using the experiment platform of the American Sequenom Massarray (miR-210: rs11246190, rs12364149, rs7395206, and rs7935908; miR-126: rs2297537, rs2297538, and rs4636297; miR-25: rs1527423; miR145: rs41291957, rs353291, and rs4705342; miR-30a: rs763354, rs111456995, and rs2222722; miR-197: rs1889470) (Bio Miao Biological Technology Co., Ltd. Beijing, China). The primer sequences and detailed detection methods were seen in the published paper (Wang et al., 2019b).

2. Subjects and methods 2.3. Statistical analysis 2.1. Study subjects Exposure group: On the basis of occupational exposure history, a total of 544 healthy workers exposed to coke oven emissions (COEs) for at least one year were enrolled in this study from the Henan Anyang Iron and Steel Group Co., Ltd. in Anyang, Henan Province. They included five representative crafts such as auxiliary production work, office personnel, oven bottom work, oven side

SPSS 21.0 software was used to perform all statistical analyses. Mean ± SD or percentiles (25th, 50th and 75th) were used to present the data according to the distribution of mitochondrial DNA biomarker, urinary 1-OHPYR, and cumulative exposure dose (CED). The Spearman rank correlation was used to analyze the correlations between 1-OHPYR or CED, and mtDNAcn. Confounders, including gender, age, smoking index, drinking, and body mass index (BMI),

X. Duan et al. / Chemosphere 246 (2020) 125773

were appropriately adjusted using a covariance analysis to analyze the effects of gender, age, smoking, drinking, and BMI on mitochondrial DNA copy number (mtDNAcn). We used the generalized linear model to analyze the influencing factors of mtDNAcn. All statistical tests were two-sided, and the test level was a ¼ 0.05. 3. Results 3.1. General characteristics of workers The general characteristics of 544 coke oven workers and 238 controls were described in our published paper (Duan et al., 2019a). All the participants lived in the same region, so that their dietary behaviors and their living environmental exposure to PAHs were similar. The majority of the subjects were male (71.7%) in the exposure group, and 41.0% of the subjects were smokers. However, 58.4% of the control group were male, but only 17.2% were smokers. This may be related to the occupational characteristics of coke oven workers. 3.2. Relationships between environmental exposure levels and mtDNAcn Statistical analysis found that the mtDNAcn in the exposure group (0.60 ± 0.29) was significantly lower than that in the control group (1.03 ± 0.31) (t ¼ 18.931, P < 0.001), and the levels of 1OHPYR and CED in the exposure group [83.80(40.29, 163.55); 1.12(0.34, 2.14)] were significantly higher than that in the control group [5.50(3.03, 9.23); 0.07(0.06, 0.09)] (Z ¼ 13.479, P < 0.001; Z ¼ 22.093, P < 0.001). Next, Spearman correlation analysis showed that the mtDNAcn had significantly negative correlations with the levels of 1-OHPYR and CED (r ¼ 0.375, P < 0.001; r ¼ 0.462, P < 0.001). 3.3. Effects of gender, age, smoking, drinking, and BMI on mtDNAcn We analyzed the associations between the general characteristics and mtDNAcn. After adjusting the confounders, including gender, age, smoking index, drinking, and BMI, covariance analysis showed that no factors were related to the mtDNAcn in the exposure or control groups (P > 0.05). However, the mtDNAcn in each stratification had significant differences between the two groups (P < 0.05) (Table 1). 3.4. Effects of genetic variations of cancer-associated miRNAs on mtDNAcn Table 2 shows a statistical analysis between genetic variations and mtDNAcn. In the analysis process, certain genotypes were merged appropriately. Increasing evidence suggests that mtDNAcn is an aging marker (Bratic and Larsson, 2013; Baek et al., 2019). Scholars also found that average mtDNAcn was specific in sex and age for Drosophila melanogaster (Kristensen et al., 2019). Cigarette smoking, drinking, and higher BMI could decrease leukocyte mtDNAcn (von Wurmb-Schwark et al., 2008; Skuratovskaia et al., 2018; Wu et al., 2019). Therefore, we regarded gender, age, smoking index, drinking, and BMI as the adjusting variables for the multivariate statistical analysis. Covariance analysis showed that the mtDNAcn in mutant homozygous genotype GG for miR-210 rs11246190 locus was significantly higher than that of homozygous genotype AA in the exposure group (P < 0.001). The individuals of CT þ TT genotypes in miR-210 rs7395206 locus had higher mtDNAcn than those of the CC genotype in the control group (P ¼ 0.028). The individuals carrying AG þ AA genotypes had higher mtDNAcn than those of wild homozygous genotype GG for miR-126

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Table 1 The effects of sex, age, smoking, drinking, and BMI on mtDNAcn. Variables

Exposure n

Gender Male 390 Female 154 b F Pb Age Group (years) <41 273  271 Fb b P Smoking Status No 321 Yes 223 Fb Pb Drinking Status No 248 Yes 296 b F Pb BMI <24.0 236 24.0e27.9 230 28 78 b F b P

Controls

Fa

Pa

mean ± SD

n

mean ± SD

0.59 ± 0.30 0.62 ± 0.29 0.231 0.631

139 99

1.00 ± 0.28 1.08 ± 0.34 3.085 0.080

201.939 133.108

<0.001c <0.001c

0.60 ± 0.28 0.60 ± 0.31 0.062 0.804

142 96

1.05 ± 0.31 1.01 ± 0.30 0.816 0.367

223.722 114.037

<0.001c <0.001c

0.60 ± 0.29 0.59 ± 0.29 0.201 0.654

197 41

1.04 ± 0.32 0.99 ± 0.27 0.030 0.863

257.887 64.900

<0.001c <0.001c

0.61 ± 0.30 0.58 ± 0.29 0.650 0.420

138 100

1.05 ± 0.33 1.01 ± 0.27 0.065 0.800

168.387 164.549

<0.001c <0.001c

0.62 ± 0.30 0.58 ± 0.28 0.58 ± 0.33 0.783 0.458

113 101 24

1.01 ± 0.33 1.06 ± 0.29 1.03 ± 0.30 1.530 0.219

115.375 194.732 32.382

<0.001c <0.001c <0.001c

a Covariance analysis was used to compare the mtDNAcn between two groups with the appropriate adjustment of gender, age, smoking index, drinking status and BMI. b Covariance analysis was used to analyze the effects of gender, age, smoking, drinking, and BMI on mtDNAcn in the exposure or control group, appropriately adjusting gender, age, smoking index, drinking status, and BMI. c Statistical differences.

rs2297538 locus in the exposure group (P ¼ 0.036). We found that no other loci were associated with the mtDNAcn in the exposure or control groups (P > 0.05). 3.5. Influencing factors of mtDNAcn using the generalized linear model Table 3 shows the influencing factors of mtDNAcn using the generalized linear model. The independent variables included age, smoking index, BMI, drinking (No ¼ 0, Yes ¼ 1), PAH-exposure (control ¼ 0, exposure ¼ 1), gender (female ¼ 0, male ¼ 1), and genetic polymorphism loci (miR-210 rs11246190: AA þ AG ¼ 0, GG ¼ 1; miR-210 rs7395206: CC ¼ 0, CT þ TT ¼ 1; miR-126 rs2297538: GG ¼ 0, AG þ AA ¼ 1). We found that PAH exposure and miR-210 rs11246190 were associated with the mtDNAcn (P < 0.05). 3.6. The combined effects of genetic polymorphisms and environmental exposure on mtDNAcn To further analyze the relationships between genetic variations and environmental exposure, we analyzed the combined effect of miR-210 rs11246190 and environmental exposure on mtDNAcn (Table 4), and found that the combined effects of the miR-210 rs11246190 locus genotype and PAH exposure on mtDNAcn were statistically significant (P < 0.001). However, the interaction between the GG genotype and PAH exposure had no effect on mtDNAcn (c2 ¼ 0.213, P ¼ 0.137). 4. Discussion PAHs have a widespread presence in the living environment,

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X. Duan et al. / Chemosphere 246 (2020) 125773

Table 2 The relationships between genetic polymorphism of encoding miRNA gene and mtDNAcn. SNPs

Exposure n

miR-210 rs11246190 AA 135 0.58 AG 316 0.57 GG 68 0.76 miR-210 rs12364149 CC 350 0.61 CG þ GG 169 0.56 miR-210 rs7395206 CC 65 0.58 CT þ TT 476 0.60 miR-210 rs7935908 CC 55 0.57 CT 234 0.58 TT 242 0.61 miR-25 rs1527423 CC þ CT 156 0.61 TT 381 0.59 miR-126 rs2297537 CC 346 0.59 CG þ GG 180 0.58 miR-126 rs2297538 GG 390 0.58 AG þ AA 137 0.63 miR-126 rs4636297 GG 378 0.59 AG þ AA 148 0.60 miR-145 rs41291957 AA 54 0.60 AG 217 0.59 GG 249 0.59 miR-145 rs353291 AA 176 0.61 AG 118 0.61 GG 243 0.57 miR-145 rs4705342 TT 241 0.59 CT 248 0.59 CC 52 0.65 miR-30a rs763354 GG 197 0.58 AG 243 0.60 AA 80 0.58 miR-30a rs111456995 / 66 0.62 -/T 248 0.59 TT 210 0.59 miR-30a rs2222722 TT 94 0.61 CT 259 0.61 CC 179 0.58 miR-197 rs1889470 GG 37 0.63 AG 207 0.61 AA 286 0.59

Control Pa

n

x±s

Pa

± 0.29 ± 0.29 ± 0.26

Ref 0.816 <0.001b

86 133 19

1.00 ± 0.29 1.05 ± 0.33 1.08 ± 0.21

Ref 0.128 0.248

± 0.30 ± 0.27

Ref 0.083

160 76

1.01 ± 0.31 1.09 ± 0.31

Ref 0.106

± 0.28 ± 0.30

Ref 0.781

28 205

0.91 ± 0.29 1.05 ± 0.31

Ref 0.028b

± 0.26 ± 0.28 ± 0.31

Ref 0.933 0.336

26 97 109

0.95 ± 0.26 1.09 ± 0.32 1.01 ± 0.31

Ref 0.074 0.338

± 0.29 ± 0.30

Ref 0.574

59 177

0.98 ± 0.28 1.05 ± 0.32

Ref 0.124

± 0.30 ± 0.28

Ref 0.719

158 79

1.05 ± 0.31 1.00 ± 0.31

Ref 0.153

± 0.29 ± 0.30

Ref 0.036b

180 55

1.02 ± 0.31 1.08 ± 0.28

Ref 0.136

± 0.30 ± 0.29

Ref 0.630

159 78

1.04 ± 0.32 1.03 ± 0.29

Ref 0.974

± 0.24 ± 0.30 ± 0.30

Ref 0.762 0.788

30 101 107

1.05 ± 0.41 1.05 ± 0.31 1.01 ± 0.27

Ref 0.986 0.675

± 0.28 ± 0.26 ± 0.32

Ref 0.960 0.279

76 47 109

1.07 ± 0.36 1.05 ± 0.26 1.01 ± 0.28

Ref 0.701 0.103

± 0.30 ± 0.30 ± 0.25

Ref 0.998 0.227

101 97 33

1.02 ± 0.28 1.03 ± 0.30 1.07 ± 0.42

Ref 0.900 0.584

± 0.30 ± 0.30 ± 0.28

Ref 0.436 0.996

75 123 36

1.02 ± 0.32 1.06 ± 0.31 1.00 ± 0.29

Ref 0.397 0.729

± 0.32 ± 0.27 ± 0.31

Ref 0.460 0.489

36 96 100

0.98 ± 0.31 1.02 ± 0.34 1.07 ± 0.25

Ref 0.421 0.101

± 0.28 ± 0.30 ± 0.29

Ref 1.000 0.451

38 122 70

1.00 ± 0.28 1.05 ± 0.31 1.03 ± 0.33

Ref 0.403 0.674

± 0.28 ± 0.31 ± 0.29

Ref 0.588 0.372

21 91 118

1.12 ± 0.36 0.99 ± 0.28 1.06 ± 0.32

Ref 0.094 0.356

x±s

Ref: The reference group of pairwise comparisons, using LSD method. a The covariance was adopted to compare the difference of mtDNAcn between genotypes, adjusted for gender, age, smoking index, drinking, and BMI. b Statistical differences.

Table 3 Influencing factors of mtDNAcn using the generalized linear model. Variables

b (95% CI)

c2

P

PAH-exposure miR-210 rs11246190 (GG)

0.439 (-0.485, 0.392) 0.136 (0.069, 0.203)

337.707 15.816

<0.001 <0.001

Note: Generalized linear model analyzed the influencing factors of mtDNAcn. The independent variables included age, smoking index, BMI, drinking, PAH-exposure, gender, miR-210 rs11246190, miR-210 rs7395206, and miR-126 rs2297538.

produced by inadequate combustion of organic compounds. Sources of PAHs include natural disasters, such as volcanic eruptions and forest fires, as well as human factors, such as cooking, heating, smoking, automobile exhaust, and industrial production (Duan et al., 2019a; Han et al., 2019). PAHs produce carcinogenic effects through a series of complex metabolic processes. In this study, we found that the workers exposed to PAHs had lower mtDNAcn than the healthy control population. Ling et al. (2017) have reported that low exposure levels of PAHs could decrease the sperm mtDNAcn. Increasing evidence suggests that the mtDNAcn have an association with age (Bratic and Larsson, 2013), gender (Kristensen et al., 2019), cigarette consumption (Wu et al., 2019), drinking (von WurmbSchwark et al., 2008), and BMI (Skuratovskaia et al., 2018). However, our study showed that these factors were not related to the mtDNAcn in the exposure or control groups. This may be because the effect of occupational exposure on mtDNAcn was much greater than that of these factors or the different levels of these factors were small. Studies have suggested that male idiopathic infertility risks were related to increasing PAH exposure levels (Xia et al., 2009; Jeng et al., 2013). It can be seen that PAHs have a powerful influence on the body, and mtDNAcn may serve as a sensitive predictor of cancers. Single nucleotide polymorphisms (SNPs) are genetic variations of a single base, causing the changes in DNA sequences. As early as 1996, Lander, an American scholar, listed it as the third generation of DNA genetic marker after restriction fragment length polymorphism and microsatellite polymorphism (Sachidanandam et al., 2001). The establishment of the Hapmap database provided researchers with the information on genetic variations and linked these mutations to specific disease risks, providing new insights into the prevention, diagnosis, and treatment of diseases. SNPs were also present in the genes encoding miRNAs, and these SNPs were involved in the expression and regulation of miRNAs and played an important role in the development of diseases (Lin et al., 2012a; Hecker et al., 2019). Recent studies have suggested that microRNAs could translocate to mitochondria to modulate mitochondrial activities (Li et al., 2019a). Taken together, miRNAs are known to be involved in the regulation of nuclear and mitochondrial genes, which ultimately regulate the mitochondrial function. Studies have shown the specific expression of miR-210, miR-30a, miR-126, miR-145, miR-25, and miR-197 in the plasma of patients with lung cancer (Shen et al., 2011; Cazzoli et al., 2013; Geng et al., 2014). HapMap or 1000 Genomes databases showed that there were genetic variations in the genes encoding these miRNAs. We found that the mtDNAcn was significantly associated with the genetic variations in miR-210 and miR-126 by the covariance analysis. miRNA-210 (miR-210) is a hypoxia-related miRNA involved in various biological processes, including cell proliferation, differentiation, cell death, and tumorigenesis (Qin et al., 2014). Chan et al. (2009) firstly reported that miR-210 regulated the mitochondrial metabolism in the conditions of hypoxia by targeting ISCU1/2 gene. In addition to the ISCU gene, COX10, GPD1L, SDHD, and NDUFA4 genes, involved in mitochondrial function regulation, were also confirmed as direct targets (Chen et al., 2010; Favaro et al., 2010; Kelly et al., 2011). In this study, our results showed that the mtDNAcn in mutant homozygous genotype GG for miR-210 rs11246190 locus was significantly higher than that of homozygous genotype AA in the exposure group (P < 0.001). The individuals with CT þ TT genotypes in the miR-210 rs7395206 locus had higher mtDNAcn than those of CC genotype in the control group (P ¼ 0.028). Further analysis showed that only the miR-210 rs11246190 locus had an effect on mtDNAcn (b ¼ 0.136, P < 0.001), and miR-210 rs11246190 had the combined function in mtDNAcn with environmental exposure (P < 0.001), suggesting that the change in mtDNAcn was the result of a combination of gene-

X. Duan et al. / Chemosphere 246 (2020) 125773

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Table 4 The combined effect of miR-210 rs11246190 and environmental exposure on mtDNAcn. rs11246190 (GG) e þ e þ

Exposure

mtDNAcn (M±SD)

b (95% CI) a

c2

Pa

e

1.03 ± 0.32

Ref

e þ

1.08 ± 0.21 0.58 ± 0.29

0.053 (-0.085, 0.190) 0.446 (-0.494, 0.397)

0.564 326.540

0.452 <0.001

þ

0.76 ± 0.26

0.274 (-0.354, 0.194)

45.398

<0.001

Rs11246190 (GG): "þ" GG; "-" AA þ AG. Ref: The reference group. a Generalized linear model analyzed the combined effect of genetic variations and environmental exposure on mtDNAcn, adjusted for gender, age, smoking index, drinking, and BMI.

environment in the exposure group. According to the database of the National Institutes of Health (NIH) (https://snpinfo.niehs.nih. gov/snpinfo/snpfunc.html), the rs11246190 locus is located in the promoter region of miR-210 and may be the binding site of the transcription factor. Therefore, genetic variation in the rs11246190 locus is likely to regulate the pri-miRNA transcription of miR-210 which further regulated its targeted genes involved in mitochondrial function. Furthermore, the results emphasized the need to determine the functional effect of rs11246190 mutation locus on the mtDNAcn. miR-126 is an endothelium-specific microRNA, which showed a low expression level in NSCLC patients (Lin et al., 2012b; Huang and Chu, 2014). In NSCLC cell lines, some scholers also found that miR126e5p could suppress mitochondrial respiration to cause cell death by targeting MDH1 specifically (Lima Queiroz et al., 2018). It could inhibit the proliferation of tumor cells in vivo by targeting epidermal growth factor-like domain 7 (EGFL7) (Sun et al., 2010). It has also been reported that miR-126 regulates mitochondrial energy metabolism, resulting in malignant mesothelioma (MM) suppression (Tomasetti et al., 2014). Therefore, this study analyzed the effects of genetic variations (rs2297537, rs2297538 and rs4636297 loci) on mtDNAcn in encoding the miR-126 gene. In this study, the results revealed that the individuals carrying AG þ AA genotypes had higher mtDNAcn than those of wild homozygous genotype GG for the miR-126 rs2297538 locus in the exposure group (P ¼ 0.036). However, multivariate analysis found that the rs2297538 locus was not associated with mtDNAcn using a generalized linear model. The rs2297538 locus is located in the promoter region of this gene, its function is currently unknown, and we need to expand the sample size for further validation. The rs2297537 site is also located in the promoter region, and the rs4636297 site is located at the 30 near of the gene. It is predicted by the NIH database that the rs2297537 and rs4636297 loci may be the binding sites of transcription factors. Li et al. (2019b) revealed that the GG genotype in the rs4636297 locus was associated with lower total cholesterol (TC) in type 2 diabetes mellitus (T2DM), and this mutation locus was involved in the GLUT4 pathway. However, we did not find that the rs4636297 locus was related to the change of mtDNAcn in this study, which might be related to the developing stage or the types of diseases. In conclusion, the workers exposed to coke oven emissions exhibited significantly lower leukocyte mtDNAcn, suggesting that mtDNAcn could predict the cancer risks induced by the PAH exposure, and miR-210 rs11246190 and PAH-exposure had a significant association with the mtDNAcn by generalized linear model. Although these results imply that the decrease of leukocyte mtDNAcn is the result of a combination of environmental and genetic factors, whether genetic variations mediate the mitochondrial damage induced by PAH exposure should be determined in future mechanistic investigations.

Declaration of competing interest The authors declare that they have no conflict of interest. CRediT authorship contribution statement Xiaoran Duan: Writing - original draft, Writing - review & editing. Yongli Yang: Data curation, Writing - review & editing. Hui Zhang: Data curation, Writing - review & editing. Bin Liu: Data curation, Writing - review & editing. Wan Wei: Data curation, Writing - review & editing. Liuya Wang: Data curation, Writing review & editing. Wei Wang: Methodology. Acknowledgments The authors express their gratitude to all the individuals who volunteered to participate in this study. We also thank the Programs for the National Natural Science Foundation of China (81872597) and Natural Science Foundation of Henan Province (U170410430). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.chemosphere.2019.125773. References Baek, J.H., Son, H., Jeong, Y.H., Park, S.W., Kim, H.J., 2019. Chronological Aging Standard Curves of Telomere Length and Mitochondrial DNA Copy Number in Twelve Tissues of C57BL/6 Male Mouse. Cells 8. Bansal, S., Leu, A.N., Gonzalez, F.J., Guengerich, F.P., Chowdhury, A.R., Anandatheerthavarada, H.K., Avadhani, N.G., 2014. Mitochondrial targeting of cytochrome P450 (CYP) 1B1 and its role in polycyclic aromatic hydrocarboninduced mitochondrial dysfunction. J. Biol. Chem. 289, 9936e9951. Bratic, A., Larsson, N.G., 2013. The role of mitochondria in aging. J. Clin. Investig. 123, 951e957. Carugno, M., Pesatori, A.C., Dioni, L., Hoxha, M., Bollati, V., Albetti, B., Byun, H.M., Bonzini, M., Fustinoni, S., Cocco, P., Satta, G., Zucca, M., Merlo, D.F., Cipolla, M., Bertazzi, P.A., Baccarelli, A., 2012. Increased mitochondrial DNA copy number in occupations associated with low-dose benzene exposure. Environ. Health Perspect. 120, 210e215. Cazzoli, R., Buttitta, F., Di Nicola, M., Malatesta, S., Marchetti, A., Rom, W.N., Pass, H.I., 2013. microRNAs derived from circulating exosomes as noninvasive biomarkers for screening and diagnosing lung cancer. J. Thorac. Oncol. 8, 1156e1162 official publication of the International Association for the Study of Lung Cancer. Chan, S.Y., Zhang, Y.Y., Hemann, C., Mahoney, C.E., Zweier, J.L., Loscalzo, J., 2009. MicroRNA-210 controls mitochondrial metabolism during hypoxia by repressing the iron-sulfur cluster assembly proteins ISCU1/2. Cell Metabol. 10, 273e284. Chen, Z., Li, Y., Zhang, H., Huang, P., Luthra, R., 2010. Hypoxia-regulated microRNA210 modulates mitochondrial function and decreases ISCU and COX10 expression. Oncogene 29, 4362e4368. Cui, Q., Chen, F.Y., Chen, H.Y., Peng, H., Wang, K.J., 2019. Benzo[a]pyrene (BaP) exposure generates persistent reactive oxygen species (ROS) to inhibit the NFkappaB pathway in medaka (Oryzias melastigma). Environ. Pollut. 251, 502e509. Duan, X., Yang, Y., Zhang, D., Wang, S., Feng, X., Wang, T., Wang, P., Ding, M., Zhang, H., Liu, B., Wei, W., Yao, W., Cui, L., Zhou, X., Wang, W., 2019a. Genetic

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