Urinary Polycyclic Aromatic Hydrocarbon Metabolites and Human

Dec 14, 2016 - ... Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technolo...
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Urinary Polycyclic Aromatic Hydrocarbon Metabolites and Human Semen Quality in China Pan Yang, Yi-Xin Wang, Ying-Jun Chen, Li Sun, Jin Li, Chong Liu, Zhen Huang, Wen-Qing Lu, and Qiang Zeng Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b04810 • Publication Date (Web): 14 Dec 2016 Downloaded from http://pubs.acs.org on December 14, 2016

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Urinary Polycyclic Aromatic Hydrocarbon Metabolites and Human Semen

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Quality in China

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Pan Yang,†,‡ Yi-Xin Wang,†,‡ Ying-Jun Chen,†,‡ Li Sun,†,‡ Jin Li,†,‡ Chong Liu,†,‡ Zhen

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Huang,†,‡ Wen-Qing Lu,†,‡ Qiang Zeng†,‡,*

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† Department of Occupational and Environmental Health, School of Public Health,

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Tongji Medical College, Huazhong University of Science and Technology, Wuhan,

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Hubei, PR China

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‡ Key Laboratory of Environment and Health, Ministry of Education & Ministry of

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Environmental Protection, and State Key Laboratory of Environmental Health

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(incubating), School of Public Health, Tongji Medical College, Huazhong University

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of Science and Technology, Wuhan, Hubei, PR China

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ABSTRACT: Toxicological studies have demonstrated that polycyclic aromatic

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hydrocarbons (PAHs) exposure impairs male reproductive health. However, the

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epidemiological evidence is limited and discordant. Our goal was to investigate the

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relationship between PAH exposures and human semen quality. We analyzed 12

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urinary metabolites of PAHs from 933 men who sought semen quality analysis in an

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infertility clinic in Wuhan, China. Associations with semen quality were assessed

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using a multivariable linear regression. Restricted cubic splines were used to explore

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the dose-response relationships between urinary metabolites of PAHs and semen

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quality. We observed inverse associations between urinary 1-hydroxynaphthalene

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(1-OHNa) and sperm count, sperm concentration, and percentage of normal

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morphology (all p for trends < 0.05) as well as between urinary ∑OHNa (sum of

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1-OHNa and 2-OHNa) and sperm concentration (p for trend = 0.04). Additionally, we

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found inverse associations between urinary 9-hydroxyphenanthrene (9-OHPh) and

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semen volume and sperm straight-line velocity (both p for trends < 0.05) as well as

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between urinary ∑OHPh (sum of 1-, 2-, 3-, 4-, and 9-OHPh) and sperm count (p for

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trend = 0.04). These dose-response relationships were further confirmed in the curves

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of the restricted cubic splines. Our data suggest that exposure to naphthalene and

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phenanthrene is related to decreased semen quality. Our results contribute to the

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growing body of evidence regarding the widespread exposure to PAHs and the

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adverse male reproductive function.

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INTRODUCTION

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Polycyclic aromatic hydrocarbons (PAHs) are one of the ubiquitous classes of

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environmental pollutants that can be formed during the incomplete combustion or

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pyrolysis of garbage, oil, wood, coal, or other organic substances (e.g., grilled meat

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and tobacco). It was estimated that the total global annual emission of PAHs was 504

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Gg in 2007, of which 21% was from China.1 Human exposure to PAHs may occur

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through ingestion, inhalation, and dermal absorption.2,

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been raised about exposure to PAHs due to their potentially adverse health effects.

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Accumulating evidence has shown that PAHs are mutagens and carcinogens and that

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PAH exposures are related to increased risks of various cancers, such as skin, lung,

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bladder, prostate, and cervical cancers.4-10

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Increasing concerns have

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Toxicological studies have also demonstrated that exposure to PAHs induced

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adverse effects on male reproductive function. An early study in adult rats showed

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that exposure to benzo(a)pyrene by an intraperitoneal injection led to the lack of

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spermatids and spermatozoa and the atrophy of the seminiferous tubules.11 Also,

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recent studies have shown that subacute exposure to inhaled benzo(a)pyrene reduces

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testis weight and impairs epididymal function in adult rats.12, 13 Moreover, in vitro

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studies have shown that exposure to benzo(a)pyrene strongly inhibits the progression

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of spermatocytes through meiotic division,14 and exposure to benzo(a)fluoranthene

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and benzo(a)pyrene induce apoptosis in Sertolic cells and disrupt germ cell

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development.15

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Increasing toxicological evidence suggests that PAH exposures may cause a

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detrimental effect on male reproductive health in humans. However, the results of

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limited epidemiological studies exploring the relationship between PAH exposures

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and semen quality have been inconsistent.16-19 Some studies primarily used urinary

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1-hydroxypyrene (1-OHP), a metabolite of pyrene, as an indicator of PAH exposures.

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Because PAHs include multiple compounds with various toxicological properties, the

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use of only 1-OHP may not represent an accurate measurement of exposure to

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multiple PAHs.16, 20 Multiple monohydroxy PAHs (OH-PAHs), with different orders

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of magnitude concentrations, have been widely measured in humans’ urine

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samples.21-25 Furthermore, early epidemiology studies with limited sample sizes have

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often been difficult to obtain precise results.16, 19 Therefore, the relationship between

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exposure to PAHs and human semen quality remains uncertain.

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In the present study, we carried out a large-scale cross-sectional study to evaluate

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the relationships between PAH exposures and human semen quality in an infertility

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clinic in Wuhan, China. We measured 12 OH-PAH metabolites in urine as surrogates

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of environmental exposure to multiple PAHs.

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MATERIALS AND METHODS

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Study population. Participants were male partners in sub-fertile couples who were

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enrolled in a study on human male reproductive function and environmental pollutant

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exposures in Wuhan, China. Details regarding the subject recruitment have been

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described previously.26 Briefly, a total of 1247 (83.69%) men, who sought semen

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quality analysis in the infertility clinic of Tongji Hospital between March and June

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2013, were included in this study. We provided each participant with a face-to-face

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interview regarding demographic information, occupational exposures, lifestyle, and

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medical history. We excluded men due to occupational exposure to PAHs (e.g.,

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bitumen workers and coke oven workers, n=8), azoospermia (n=58), having one of

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several self-reported medical characteristics (e.g., hernia repair complicated by

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testicular atrophy, testis injury, undescended testicle, vasectomy, epididymitis,

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orchiditis, varicocele, vesiculitis, diabetes, and endocrine diseases) that may impair

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semen quality (n=121), missing urine samples (n=22), or insufficient urine volume for

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PAH metabolites analysis (n=105). Finally, a total of 933 participants were retained in

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the present analysis. The Tongji Medical College Ethics Committee approved the

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study. Informed consent was obtained from all subjects.

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Semen Quality Parameters Analysis

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Before the semen sample collection, the actual abstinence time of each participant was

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recorded. Semen samples were collected using sterile plastic specimen containers by

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masturbation in a private room of the hospital. After liquefaction of the semen sample

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(37°C, ≤ 30 min), we used a sterile polypropylene pipette to measure the semen 5

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volume. We used a micro-cell slide and computer-aided semen analysis to analyze the

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sperm concentration, sperm motility (progressive motility and non-progressive

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motility), sperm motion parameters [amplitude of lateral head displacement (ALH),

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average path velocity (VAP), beat cross frequency (BCF), curvilinear velocity (VCL),

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and straight-line velocity (VSL)], following the World Health Organization guidelines

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(WHO 2010).27 The sperm morphology parameters, including percentage of abnormal

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heads and percentage of normal morphology, were assessed on fixed and stained

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smears at a high-power magnification (1000 ×), and more than 200 sperm were

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counted.

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The total motility (non-progressive motility + progressive motility), sperm count

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(sperm concentration × semen volume), and linearity (LIN = VSL/VCL × 100) were

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calculated according to the WHO guidelines (2010).27 Of the six sperm motion

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parameters, only VCL, VSL, and LIN were used in the following statistical analysis

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due to a high correlation between some of the measures (see Supporting Information

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Table S1). The VCL, VSL, and LIN are indicators of sperm vigor, progression, and

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swimming pattern, respectively. All the semen quality parameters were analyzed by

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two well-trained inspectors in the infertility clinic of Tongjing Hospital. External

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quality controls have been established in the hospital for the semen analysis,

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following the WHO guidelines (2010)27 and the Quality Control Center of Hubei

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Province.

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PAH Metabolites Analysis

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Urine samples from participants were collected in polypropylene containers. After

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collection, we used an ice cooler to ship them to the lab and frozen at -40°C until

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analysis.

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1-hydroxynaphthalene (1-OHNa), 2-OHNa, 1-hydroxyphenanthrene (1-OHPh),

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2-OHPh, 3-OHPh, 4-OHPh, 9-OHPh, 2-hydroxyfluorene (2-OHFlu), 9-OHFlu,

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3-hydroxybenzo(a)pyrene (3-OHBaP), and 6-hydroxychrysene (6-OHChr), were

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measured by gas chromatography (GC)-mass spectrometry (MS), which has been

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described previously with some modifications.28 The standard chemicals were

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obtained from AccuStandard (6-OHChr) (New Haven, CT), Toronto Research

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Chemicals Inc. (2-, 9-OHFlu, 1-OHP, and 3-OHBaP) (Ontario, Canada), Dr.

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Ehrenstorfer (1-, 2-, 3-, and 4-OHPh) (Augsburg, Germany), and Sigma-Aldrich (1-,

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2-OHNa, and 9-OHPh) (Munich, Germany). The internal standards were purchased

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from C/D/N isotopes Inc. {[2H9]1-hydroxypyrene (1-OHPd9)} (Quebec, Canada) and

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Toronto Research Chemicals Inc. {[2H7]1-Hydroxynaphthalene (1-OHNad7)}

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(Ontario, Canada).

Twelve

urinary

metabolites

of

PAHs,

including

1-OHP,

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The urine sample was removed from the refrigerated storage and equilibrated to

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room temperature. One mL of an acetate acid buffer (PH 5.0, 0.5 M), 20 µL of

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β-Glucuronidase/sulphatase (Sigma-Aldrich, Munich, Germany), and 20 µL mixture

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of the internal standard solution were added to a 2.0 mL of urine sample and then

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incubated overnight at 37°C. After that, the samples were saturated with 1.5 mg of

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MgSO4·7H2O. We used 1.5 mL of n-hexane to extract the samples twice and then

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used a moderately continuous stream of nitrogen to evaporate the organic extracts. 7

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One hundred µL of bis-trimethylsilyl-trifluoroacetamide (BSTFA) was added to the

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organic residue and incubated for 90 min at 45°C. After derivatization, 1 µL of the

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sample was injected into the GC/MS system. The carrier gas was the high-purity

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helium at a fixed velocity of 1.0 mL/min.

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The urinary concentrations of OH-PAHs were quantified through a standard curve

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based on the peak area and mass-to-charge ratio. A standard curve was run for 80

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urinary samples. Each analysis run included one blank sample (2 mL of purified water)

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and two quality control samples (urine samples containing the target PAH

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metabolites). The limits of detection (LOD) of the urinary PAH metabolites ranged

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from 0.03 µg/L to 0.18 µg/L. The average recoveries of the urinary PAH metabolites

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ranged from 77.67% to 115.98%, and the relative standard deviations were ≤ 10.00%.

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We excluded 6-OHChr and 3-OHBaP from further analyses because they were below

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their LODs. Concentrations < the LOD were imputed a value of the LOD divided by

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the square root of 2 for all analyses. We corrected for urine dilution by urinary

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creatinine based on the Jaffe reaction.

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Statistical Analysis

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Basic descriptive statistics were derived to characterize the demographic information,

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urinary metabolites of PAHs, and semen quality parameters of the study population.

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We defined ∑OHNa as the sum of 1- and 2-OHNa. We designated ∑OHFlu as the

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sum of 2- and 9-OHFlu. We determined ∑OHPh as the sum of 1-, 2-, 3-, 4-, and

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9-OHPh. We characterized ∑OH-PAHs as the sum of 1-OHP, 1-, 2-, 3-, 4-, 9-OHPh,

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1-, 2-OHNa, 2-, and 9-OHFlu. Correlations between the urinary OH-PAH

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concentrations were explored using Spearman's rank correlation test.

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We used multivariable linear regression models to examine the associations

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between the continuous measurements of the semen quality parameters and the

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urinary OH-PAH concentrations. This method can be used to explore trends in the

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data, increase the statistical power against a Type II error, and understand the

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statistically significant mean differences. Because of the right-skewed distributions

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for the sperm count and the sperm concentration, these data were transformed by the

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natural logarithm (ln) to meet the normality assumptions of the statistical analysis.

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Percent changes in the sperm count and sperm concentration were calculated

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according to the following equation: 100 × [exp(beta)-1], where beta is the regression

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coefficient for a given exposure variable. The sperm motion parameters, total motility,

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progressive motility, and sperm morphology parameters were approximately normal

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distribution, and thus, these data were not transformed in statistical analysis. We

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divided all urinary OH-PAH concentrations into quartiles according to the overall

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population distribution. We used integer values (1- 4) for ordinal OH-PAHs to

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evaluate the tests for trends in the regression models.

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Covariates [age and body mass index (BMI) as continuous variables; smoking

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status (current and former smoker vs. non-smoker) as a dummy variable; income (
6000 yuan per month) and abstinence time (≤ 2, 3, 4, 5, and ≥

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6 days) as ordinal variables; having ever biologically fathered a child (yes vs. no),

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education (< high school vs. ≥ high school), and alcohol use (yes vs. no) as 9

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dichotomous variables] were considered in the multivariable models with statistical

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and biologic considerations. We applied the "change-in-effect" criterion to ascertain

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which the covariates were included in the final regression models.29 For each effect

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variable, covariates resulted in ≥ 10% change in the estimated exposure-effect

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(regression coefficients) for at least one of the exposure variables in bivariate analysis

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that were incorporated into the final model. We found that all the covariates met the

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inclusion criteria and thus were included in the final multivariable models. Urinary

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creatinine, as a separate independent variable, was incorporated in all the models.30

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For the multivariable models with significant statistical associations, we applied

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restricted cubic splines to further explore the shape of the dose-response relationships

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between the exposure measurements and effects.31 We used this method to overcome

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the inherent limitation of the categorical analysis. The 5th, 50th, and 95th percentiles

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of the urinary OH-PAH distributions were set as knots. The median was defined as the

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referent value by default in the SAS macro.31 A sensitivity analysis was performed

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after precluding urine samples (n = 85) that were highly diluted (creatinine < 0.3 g/L)

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or concentrated (creatinine > 3 g/L). Statistically significant was considered at p-value

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< 0.05. We used SAS statistical software (version 9.3; SAS Institute, Inc., Cary, NC,

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USA) to perform all statistical tests.

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RESULTS

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Descriptive Statistics of the Participants

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Table 1 shows the demographic characteristics of the subjects. The mean (± SD) age

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for the study participants was 32.05 (± 5.30) years. Of the 933 subjects, 40.8%

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biologically fathered a child, 61.2% were non-drinkers, and 38.6% were non-smokers.

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In total, 573 men (61.4%) reported that their education was more than high school,

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and 174 men (18.6%) disclosed that their household income was more than 6000

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RMB yuan/month.

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Distribution of the Semen Parameters and Urinary PAH Metabolites

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Table 2 shows the distributions of the semen parameters for the subjects. The

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median sperm count, sperm concentration, progressive sperm motility, total sperm

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motility, and semen volume were 119.65 million, 43.39 million/mL, 42.22%, 49.12%,

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and 3.00 mL, respectively. There was a wide distribution of urinary PAH metabolites

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for the participants with detection rates > 93% (Table 3). The geometric mean

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concentrations of ∑OHNa were the highest (8.06 µg/L), followed, in decreasing order,

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by ∑OHPh (6.75 µg/L), ∑OHFlu (5.60 µg/L), and 1-OHP (1.05 µg/L). There were

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significant correlations between the urinary OH-PAH metabolites (p < 0.05), except

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for 1-OHP, 3-OHPh, and 9-OHPh (data not shown).

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Associations of the Semen Parameters with Urinary PAH Metabolites

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For the conventional semen quality parameters, we found that urinary 1-OHNa and

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∑OHNa were related to a decreased sperm concentration with estimated mean

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decreases of 22.66% (95% CI: -34.49%, -8.70%) and 16.47% (95% CI: -29.39%,

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-1.19%), respectively, for the fourth vs. first quartile (both p for trends < 0.05) (Figure 11

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1). These dose-response relationships were then confirmed in the curves of restricted

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cubic spline (Figure 4). We found that urinary 1-OHNa and ∑OHPh were associated

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with a decreased sperm count with estimated mean decreases of 19.99% (95% CI:

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-33.83%, -3.34%) and 21.02% (95% CI: -33.83%, -5.82%), respectively, for the

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fourth vs. first quartile (both p for trends < 0.05) (Figure 1). Furthermore, these

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dose-response relationships were observed in the curves of restricted cubic spline

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(Figure 4). Additionally, inverse associations between urinary 4-OHPh and 9-OHPh

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and semen volume were found with estimated mean decreases of 0.31 mL (95% CI:

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-0.61, -0.01) and 0.43 mL (95% CI: -0.74, -0.12), respectively, for the fourth vs. first

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quartile (both p for trends < 0.05). In the cubic spline analysis, only the dose-response

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relationship between urinary 9-OHPh and semen volume was further confirmed

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(Figure 4). There were no indications of any associations between the urinary PAH

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metabolites and the total sperm motility and progressive sperm motility.

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Regarding the sperm morphology parameters, we found that urinary 1-OHNa was

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associated with a decreased percentage of normal morphology (-2.35%; 95% CI:

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-4.24%, -0.46% for the fourth vs. first quartile; p for trend = 0.046) (Figure 2).

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Regarding the sperm motion parameters, we discovered that urinary 9-OHPh was

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correlated with a decreased sperm VSL (-1.34 µm/sec; 95% CI: -2.37, -0.31 for the

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fourth vs. first quartile; p for trend = 0.019) and VCL (-2.30 µm/sec; 95% CI: -4.06,

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-0.54 for the fourth vs. first quartile; p for trend = 0.041) (Figure 3). These

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dose-response relationships were proven in the curves of restricted cubic spline,

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except for the association between urinary 9-OHPh and sperm VCL (Figure 4). The 12

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sensitivity analysis did not significantly change the above observed associations (see

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Supporting Information Figures S1-S3).

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DISCUSSION

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In a Chinese population, we measured 12 urinary metabolites of PAHs to evaluate the

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effect of multiple PAH exposures at environment levels on semen quality. We

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observed significant dose-response relationships between urinary 1-OHNa and

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decreased sperm count, sperm concentration, and percentage of normal morphology

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as well as between urinary ∑OHNa and decreased sperm concentration. Also, we

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observed significant dose-response relationships between urinary 9-OHPh and

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decreased semen volume and sperm VSL as well as between urinary ∑OHPh and

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decreased sperm count. Our results provided evidence of an association between

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environmental exposure to naphthalene and phenanthrene and decreased semen

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quality in human.

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As the main metabolite of pyrene, urinary 1-OHP has been considered one of the

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biomarkers for exposure to PAHs. In our study, no associations were found between

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urinary 1-OHP and the semen quality parameters. Similar results were also identified

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in early studies conducted in coke oven workers and the general population.16,20

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However, Xia et al.19 and Jurewicz et al.17 found a negative association between

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urinary 1-OHP and semen quality in an infertile population. The discrepancy among

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the studies may be correlated with the different PAH exposure concentrations,

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composition of the study populations, and study sizes. Additionally, we found that

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urinary 2-OHFLu and 9-OHFLu, the metabolites of fluorine, were not associated with

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semen quality. Our results were in accordance with early studies conducted in infertile

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population and the general population.16, 19 These data indicate that environmental

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exposure to fluorine may not have detrimental effects on human semen quality.

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Urinary 1-OHNa and 2-OHNa are the metabolites of naphthalene, but 1-OHNa is

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also a metabolite of carbaryl pesticides.32 In this study, we observed a low

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1-OHNa/2-OHNa ratio, indicating naphthalene exposure. We found no association

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between urinary 2-OHNa and semen quality, which reaffirmed observations in a

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previous general population.16 Similarly, Xia et al.19 found that urinary 1-OHNa and

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2-OHNa were not related to semen quality in an infertile population. However, we

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discovered that urinary 1-OHNa and ∑OHNa were related to decreased semen quality.

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Different creatinine adjustment approaches may be responsible for the discrepancy.

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Xia et al.19 used urinary PAH metabolites divided by the creatinine concentration to

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estimate the effect of PAH exposure on semen quality. However, such a creatinine

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adjustment may not accurately classify the exposure status of individuals due to

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dramatic variant urinary creatinine concentrations among different demographic

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groups.30, 33 The limited sample sizes in the previous study resulted in a low statistical

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power that may also contribute to the discrepancy.

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Phenanthrene, a feature closely associated with carcinogenic PAHs, presents high

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excretion through urine (40.4%).34 Toxicological research has shown that low dosage

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(0.06 µg/L) and high dosage (6 µg/L) of phenanthrene exposures inhibit

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spermatogenesis in male Sebastiscus marmoratus.35 Limited epidemiological studies

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examine the association between phenanthrene exposure and semen quality. A

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previous study in the general population found no association between urinary 15

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9-OHPh and semen quality.16 However, we identified that urinary 9-OHPh was related

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to a decreased semen volume and sperm VSL and that urinary ∑OHPh was related to

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a decreased sperm count. In support of our findings, Song et al.36, examining the male

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partner in couples attending an infertility clinic, found that blood phenanthrene levels

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were associated with decreased semen quality.

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Smoking has been reported to cause a detrimental effect on male reproductive

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health and contribute to PAH exposure.37-39 Given that these effects may operate on

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similar pathways, we further analyzed the associations between urinary OH-PAHs and

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semen quality by smoking status. We showed that urinary 1-OHNa and ∑OHNa were

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associated with decreased semen quality parameters among currently smoking men

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and that the urinary 9-OHPh and ∑OHPh that were affiliated with the decreased

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semen quality parameters were shown among non-smoking men (see Supporting

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Information Tables S2-S3). These results indicated that the effect of the decrease in

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semen quality due to exposure to naphthalene is stronger among men who smoke,

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whereas exposure to phenanthrene is stronger among men who never smoke. A

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previous study also reported that smoking status modulated the risk of exposure to

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PAHs on semen quality in an infertile population.17

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Several biological mechanisms have been suggested to be involved in PAH

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exposure associated with impaired semen quality. PAHs can be oxidized into reactive

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compounds that increase the formation of reactive oxygen species (ROS).40 The

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excessive formation of ROS causes oxidative stress and alterations in antioxidant

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enzymes;41 thus, it causes sperm DNA damage,42-44 resulting in decreased semen 16

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quality. Additionally, in vitro studies have suggested that PAHs and their metabolites

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can bind and stimulate acryl hydrocarbon receptor (AhR),45,46 which may, in turn,

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induce increased levels of PAH metabolites to biologically active products.47 In vivo

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studies have shown that diesel exhaust particles, which contain PAHs, can bind to

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AhR, suppress spermatogenesis, and decrease sperm production.48,49 Moreover, an in

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vitro study found that PAHs could induce cytotoxicity in cultured rat's Sertoli cells

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through apoptosis,15 which adversely affects spermatogenesis.

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There were ubiquitous PAH exposures based on the metabolites measured in the

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urine of this study population. The geometric mean concentrations of urinary PAH

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metabolites, except for 1-OHNa, were higher than those of the U.S. general

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population according to the National Health and Nutrition Examination Survey

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(NHANES 2001-2002).21 Similarly, the mean concentrations of 1-OHP, 2-OHFlu, and

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OHPhs (2-, 3-, 4-, and 9-OHPh) were also higher than those of the general

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populations from some Asian countries, such as Korea, Japan, Vietnam, Malaysia,

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and Kuwait. However, the mean concentrations of 1-OHNa and 2-OHNa were

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comparable to populations from Korea, Kuwait, Vietnam, and India.50 The median

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concentrations of urinary PAH metabolites in our population were also proportionate

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to the general population in Wuhan, China.51 The poor air quality and conventional

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dietary habits, including heavily fried, smoked, or grilled foods, may result in the

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higher levels of exposure to PAHs for the Chinese population.

328

The larger sample size and multiple PAH metabolites, measured in urine sample to

329

assess environmental PAH exposure, were major strengths to our study. However, 17

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some limitations need to be addressed. First, because the half-lives of PAH

331

metabolites are short, we measured multiple PAH metabolites in a single urine sample

332

that may not accurately reflect the individual’s long-term exposure levels. The

333

spermatogenesis occurs approximately 90 days. A previous study found temporal

334

variability in PAH metabolite levels over the course of two weeks.19 Thus, a single

335

urine measurement for exposure assessment may not effectively capture the

336

etiologically relevant time frame for the outcomes. Second, we conducted this study

337

in an infertility clinic, resulting in more sub-fertile participants in our study population,

338

though the study design increases the participation rate. Hence, our results should be

339

interpreted cautiously for the general population. Additionally, we were not able to

340

exclude the possibility that the results from our study have occurred by chance due to

341

multiple comparisons. We did not adjust for the multiple comparisons in this study

342

because there are concerns regarding the methods of multiplicity adjustment. A

343

Bonferroni correction is badly conservative, tending to increase the number of wrong

344

rejections of true hypotheses as the number of hypotheses being simultaneously tested

345

increases. The false discovery rate may be inappropriate for some data because the

346

p-value under the null hypothesis should conform to independent and uniform

347

distribution. Third, we lacked the information on dietary habits and air pollution. The

348

dietary habits are the main exposure sources of PAHs. Air pollution also contributes to

349

PAH exposure and has shown to be associated with poor semen quality.25,52 These

350

lacking factors may confound the observed associations. However, a previous study

351

found that the confounding effects, resulting from grilled and smoked food ingestion, 18

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were not significant.16 Prospective studies with improved study designs should

353

longitudinally confirm our findings.

354

In this large-scale Chinese population, we found that multiple urinary OH-PAH

355

metabolites (1-OHNa, ∑OHNa, 9-OHPh, and ∑OHPh) were associated with various

356

decreased semen parameters. Our results were consistent with previous toxicological

357

data. This suggests that environmental exposure to naphthalene and phenanthrene may

358

have detrimental effects on human semen quality. Given that there is ubiquitous

359

human exposure to PAHs, our findings highlight a significant potential public health

360

issue. However, a comprehensive explanation of the effect of exposure to PAHs on

361

human semen quality still warrants further studies.

19

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362

ASSOCIATED CONTENT

363

Supporting Information Available

364

Tables S1-S3 and Figures S1-S3. This information is available free of charge via the

365

Internet at http://pubs.acs.org.

366 367

AUTHOR INFORMATION

368

Corresponding author:

369

*Phone: +86-27-83610149; Fax: +86-27-83657765; e-mail: [email protected].

370 371

Notes

372

All authors declare they have no financial interests.

373 374

ACKNOWLEDGMENTS

375

We sincerely thank all the participants of this study for providing the semen and urine

376

samples. We also thank the technicians in the Reproductive Center of Tongji Hospital

377

in Wuhan for analyzing the semen quality parameters. This study was supported by

378

the National Natural Science Foundation of China (No. 81502784), the Nature

379

Science Foundation of Hubei Province (No. 2015CFB308) and the China Postdoctoral

380

Science Foundation (No. 2015M580645).

381 382 383 20

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aromatic hydrocarbon metabolites on heart rate variability based on the Framingham

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Pollut. 2014, 187, 145-152.

553

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554 555

Table 1. Demographic characteristics of the study population (n=933a). Characteristics

556 557 558

Mean ± SD

Age, years

32.05 ± 5.30

Body mass index, kg/m2

23.36 ± 3.16

Abstinence time, days

N (%)

≤2

105 (11.3)

3

224 (24.0)

4

205 (22.0)

5

172 (18.4)

≥6

226 (24.2)

559 560 561 562

Ever biologically fathered a pregnancy

563 564

Yes

381 (40.8)

No

546 (58.5)

Alcohol use 565 566

Yes

362 (38.8)

No

571 (61.2)

Smoking status 567 568 569

360 (38.6)

Former

101 (10.8)

Current

472 (50.6)

Education

570 571

Never

< High school

353 (37.8)

≥ High school

573 (61.4)

Income, RMB yuan/month

572 573

6000

174 (18.6)

574

a

575

biologically fathered a pregnancy, seven missing education.

Two missing age, one missing abstinence time, six missing ever

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Table 2. Distribution of semen parameters for the participants (n=933). Semen parameters

Mean

Median

Concentration ( million/mL)

52.15

Count (million)

Percentile 5th

25th

50th

75th

95th

43.39

10.96

26.71

43.39

67.91

119.77

142.58

119.65

23.06

69.87

119.65

186.67

361.72

Total motility (%)

50.51

49.12

13.00

36.50

42.22

66.28

72.00

Progressive motility (%)

43.13

42.22

16.10

30.45

49.12

56.72

82.44

Volume (ml)

2.96

3.00

1.00

2.00

3.00

4.00

6.00

Normal morphology (%)

20.02

21.00

5.00

15.00

21.00

24.00

35.00

Abnormal head (%)

66.92

65.00

51.00

59.00

65.00

76.00

85.30

VSL (µm/sec)

27.67

27.92

19.53

24.79

43.84

30.74

35.32

VCL (µm/sec)

43.98

43.84

30.09

38.65

27.92

49.89

57.41

LIN (%)

63.58

63.39

53.17

59.27

63.39

68.15

75.31

Conventional semen quality

Semen morphology

Sperm motion

Abbreviations: VSL, straight-line velocity; VCL, curvilinear velocity; LIN, linearity. 576 577

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Table 3. Distribution of urinary PAH metabolite concentrations (µg/L) for the participants (n=933). Metabolite

% >LOD

Mean ± SD

GM (95% CI)

1-OHNa

97.32

4.43 ± 6.16

2-OHNa

93.78

2-OHFlu

Percentile 10th

25th

75th

90th

2.07 (1.90, 2.27)

0.32

0.95

5.63

10.56

9.70 ± 8.93

4.99 (4.53, 5.46)

0.67

2.75

13.48

22.88

89.92

3.85 ± 4.11

1.95 (1.79, 2.14)

0.08

1.06

5.31

8.64

9-OHFlu

99.89

3.53 ± 2.64

2.89 (2.78, 3.00)

1.43

1.93

4.27

6.35

1-OHPh

96.36

1.00 ± 0.88

0.70 (0.66, 0.75)

0.23

0.44

1.33

2.04

2-OHPh

96.36

1.57 ± 1.59

1.09 (1.03, 1.16)

0.38

0.65

2.00

3.05

3-OHPh

93.57

1.32 ± 1.19

0.91 (0.86, 0.97)

0.22

0.58

1.71

2.54

4-OHPh

100.00

1.57 ± 1.16

1.29 (1.23, 1.34)

0.73

0.99

1.81

2.50

9-OHPh

100.00

2.32 ± 1.28

2.03 (1.97, 2.10)

0.99

1.39

2.94

3.68

1-OHP

96.46

1.37 ± 1.10

1.05 (0.99, 1.10)

0.37

0.81

1.68

2.43

∑OHNa

-

14.13 ± 12.81

8.06 (7.40, 8.83)

1.47

4.40

20.32

32.24

∑OHFlu

-

7.38 ± 6.04

5.60 (5.35, 5.89)

2.01

3.23

9.52

14.41

∑OHPh

-

7.79 ± 4.68

6.75 (6.54, 6.99)

3.56

4.58

9.75

13.37

∑OH-PAHs

-

30.67 ± 19.83

24.93(23.86, 26.01)

9.54

15.24

40.99

57.00

Abbreviations: GM, geometric mean. 578 579

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580

Figure Legends

581 582

Figure 1. Regression coefficients (95% CIs) for changes in conventional semen

583

quality parameters associated with PAH metabolite concentrations (n = 933), adjusted

584

for age, BMI, urinary creatinine, abstinence time, income, smoking status, alcohol use,

585

education, and having ever biologically fathered a pregnancy.

586 587

Figure 2. Regression coefficients (95% CIs) for changes in sperm morphology

588

parameters associated with PAH metabolite concentrations (n = 933), adjusted for age,

589

BMI, urinary creatinine, abstinence time, income, smoking status, alcohol use,

590

education, and having ever biologically fathered a pregnancy.

591 592

Figure 3. Regression coefficients (95% CIs) for changes in sperm motion parameters

593

associated with PAH metabolite concentrations (n = 933), adjusted for age, BMI,

594

urinary creatinine, abstinence time, income, smoking status, alcohol use, education,

595

and having ever biologically fathered a pregnancy.

596 597

Figure 4. Restricted cubic splines representing the relationships between urinary

598

1-OHNa, urinary 2-OHFlu, urinary 4-OHPh, urinary 9-OHPh, urinary ∑OHNa, and

599

urinary ∑OHPh and semen quality parameters, adjusted for age, BMI, urinary

600

creatinine, abstinence time, income, smoking status, alcohol use, education, and

601

having ever biologically fathered a pregnancy. (Reference group is the median

602

OH-PAH exposure level; dashed lines represent 95% CIs.)

603

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604

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Figure 1.

605 606 607

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608

Figure 2.

609 610 611 612

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613

Environmental Science & Technology

Figure 3.

614 615

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Environmental Science & Technology

616

Figure 4.

617 36

ACS Paragon Plus Environment

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Page 37 of 38

Environmental Science & Technology

618 619 620 621

37

ACS Paragon Plus Environment

Environmental Science & Technology

622 623 624

TOC ART

625 626

38

ACS Paragon Plus Environment

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