PAHs-induced metabolic changes related to inflammation in childhood asthma

PAHs-induced metabolic changes related to inflammation in childhood asthma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PAHs-induced metabolic changes related to inflammation in childhood asthma Hao Wu, Yuling Bao, Tongtong Yan, Hui Huang, Ping Jiang, Zhan Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1470556/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Epidemiological studies have showed that PAHs may exert its adverse effects on childhood asthma. However, the underlying molecular mechanism remains to be fully elucidated. This study aimed to investigate this process in view of metabolic pathway, especially one carbon metabolism and tryptophan metabolism. Methods: Fifty asthmatic children and fifty control subjects were recruited in this study. Serum IgE and IL-17A was detected by ELISA assay. Serum PAHs concentrations were measured by GC-MS. One carbon-related metabolites and tryptophan metabolites were determined by UPLC-Orbitrap-MS. Blood DNA methylation in long interspersed nucleotide element-1 ( LINE-1 ) was analyzed by bisulfite sequencing PCR. ChIP assays were used to examine H3K4me3 enrichment on IL-17A gene. Multivariable linear regression was performed to evaluate the associates between PAHs and one carbon metabolite and tryptophan metabolites and childhood asthma. HE staining in lung tissue, IgE and IL-17A in BALF, metabolic profiles in urine, and AhR , iL-17a and Cyp1a1 gene expression were determined in PAHs-exposed mice. Results: The asthmatic group presented significantly higher total serum IgE and IL-17A concentrations. Serum Fla was associated with childhood asthma (OR=1.380, 95%CI: 1.063-1.792). The asthmatic group displayed an increasing conversion from SAM to SAH and an elevated capacity of methylation reactions. Fla had a great effect on one carbon metabolites, especially SAH, SAM and Ser, which exerted significant mediation effects between the Fla concentration and asthma. What’s more, Fla had a positive effect on LINE-1 DNA methylation (β=0.395, P=0.000) and H3K4 tri-methylation level in the IL-17A promoter region(β=0.293, P=0.002). We did find significant mediation effect between serum Fla and asthma by LINE-1 DNA methylation and H3K4me3 level in the IL-17A promoter region. The differential Trp metabolites, such as Trp, tryptamine, IA, IAA, Indole, IAld and IAAld indicated the asthmatic children had increased indole-AhR pathway. Mediation analysis failed to show a mediator effect of Trp metabolites in the association between PAHs and childhood asthma. Animal study confirmed that PAHs exposure increased methylation levels, and altered Trp metabolites -AhR-IL-17A axis, which may be influenced by gender. Conclusion: PAHs disturbed one carbon metabolism to influence the methyl group refill of DNA methylation and histone methylation, and disturbed tryptophan metabolism to regulate Th17 cell differentiation, which may elevate serum IL-17A concentration in asthmatic children. PAHs asthma metabolism inflammation one carbon metabolite methylation tryptophan IL-17A Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights PAHs induced one carbon metabolic aspect of epigenetics in asthmatic children PAHs influenced tryptophan metabolic profile in asthmatic children PAHs may influence the expression of IL-17A by metabolic mechanism in asthmatic children 1 Introduction Asthma is a complex and multiple etiological disease [Martinez,2007]. It is also a common chronic inflammation in children [Bousquet et al.,2000]. Asthma prevalence under age 18 years released in 2018 in United States was 7.5% [CDC,2018]. The third (2010–2011) national epidemiological survey in China showed that the prevalence of childhood asthma had been up to 3.02% [Chin J Pediatr,2013]. Although no latest official national statistics have been issued on the current prevalence of childhood asthma, a wide range of regional surveys have showed an increasing trend in different cities of China. The predicted prevalence of asthma in 2020 was estimated from 1.11% among rural girls aged 14 years to 10.27% among urban boys aged four years [Li et al.,2020]. Epidemiological studies have demonstrated that exposure to air pollution have been linked to increasing asthma prevalence and asthma onset [Guarnieri and Balmes,2014; Orellano et al.,2017]. Especially, ambient polycyclic aromatic hydrocarbons (PAHs), which are traffic related air pollutants and main organic components of PM 2.5 and PM 10, have been known to contribute to the onset of asthma [Karimi et al.,2015; Liu et al.,2016]. In the process of PAHs biotransformation, a cascade of oxidative stress is triggered leading to cytotoxicity and DNA damage [Rossnerova et al.,2011; Wang et al.,2017; Zhang et al.,2020]. PAHs also stimulate inflammatory responses through increasing the production of IgE [Kepley et al.,2003]. Recently, there is growing evidence to demonstrate that PAHs exposure may alter global and gene-specific DNA methylation patterns [Herbstman et al.,2012]. For example, as global methylation indicators, long interspersed nuclear elements-1 ( LINE-1 ) and short interspersed nuclear elements ( Alu ) was used to indicate the global methylation status and considered as intermediators of prenatal PAHs exposure to birth outcomes [Yang et al.,2018]. For specific gene, increased methylation of FOXP3 gene was associated with chronic PAHs exposure leading to Treg dysfunction in atopic children [Hew et al.,2015]. DNA methylation is a biological process by which methyl groups (-CH 3 ) are added to cytosine residue to form 5-methylcytosine. Lack of methyl groups may result in hypomethylation. S-adenosylmethionine (SAM) is the major methyl donor, regeneration of which is dependent on folate cycle and methionine cycle, i.e. one carbon metabolism [Anderson et al.,2012]. Studies have shown the links between metabolites and epigenetic factors, as folate, choline, betaine, glycine and serine contributing to DNA methylation as methyl donors and co-factors, also to histone methylation [Lillycrop and Burdge,2012]. Histone methylation includes active H3K4me 1/2/3 and H3K36me3, and repressive H3K9me3 and H3K27me3 modification. One carbon metabolism, especially folate cycle and methionine cycle provide universal methyl group to refill epigenetics. While less is known about regulation of metabolic pathway by which PAHs exert its epigenetic effects in childhood asthma. In additon, tryptophan (Trp) metabolic abnormalities were found in asthmatic children [Licari et al.,2019]. Some tryptophan metabolites, such as kynurenine and indole, have been verified to be able to bind and activate the aryl hydrocarbon receptor (AhR). The activated Trp-AhR pathway can induce Th17 cell differentiation and regulate the expression of downstream cytokines such as IL-22 and IL-17, thereby regulating the immune homeostasis [Stevens et al.,2009]. Recent studies have demonstrated that Th17 cells and their signature cytokine IL-17 also play an important role in severe asthma [Ramakrishnan et al.,2019]. It is well known that PAHs such as B[a]P act as AhR ligand. After ligand binding activated AhR may upregulate its target genes such as cytochrome P450 1A1(CYP1A1) expression to mediate the carcinogenic effects. Here, we hypothesized that PAHs may also alter tryptophan metabolism, and aberrant tryptophan metabolites acting on AhRs can induce Th17 cell differentiation and regulate IL-17 production to promote inflammation. Therefore, in this paper, we used targeted metabolomics analysis to analyze the concentrations of metabolites in one-carbon metabolism and tryptophan metabolism in asthmatic children and sought to evaluate the effect of PAHs on childhood asthma from cell metabolism perspective. PAHs can disturb one-carbon metabolism to change global DNA methylation and histone methylation and induced IL-17A expression in asthmatic children. Although there was no medication effect of tryptophan metabolism between PAHs exposure and childhood asthma, animal study confirmed that PAHs can influence tryptophan metabolism to induce inflammation but should take the gender difference into account when analyzing data. Collectively, these data indicated that PAHs could disturb metabolic pathway to promote inflammation in asthma. 2 Methods And Materials 2.1 Subjects The samples included 50 asthmatic subjects and 50 control subjects who were recruited from the Children’s Hospital of Nanjing Medical University and the Affiliated hospital of Nanjing university of Traditional Chinese Medicine from 2020–2021, respectively. Asthmatic subjects were diagnosed by a clinician. The control subjects were with no history of inflammatory disease and atopy. The Nanjing Medical University Clinical Research Ethics Committee, Nanjing, China, reviewed and approved the protocols of this study. Written informed consent was obtained from the participants’ parent for the use of samples in this study. Whole blood samples from each asthmatic or control subjects were collected. The samples were centrifuged at 3000 rpm for 10 min. The supernatant was stored at -20°C until analysis. White blood cell DNA was isolated by using TIANamp Genomic DNA Kit (TIANGEN, DP304-03, China) following the instructions from the manufacturer. Peripheral blood mononuclear cells (PBMC) were isolated from whole blood using Lymphocyte-Human Cell Separation Media (Cedarlane, Southern Ontario, Canada). 2.2 Animal and PAHs exposure C57BL6 mice (Antpedia, Shanghai, China) were used in this study. Ten male and ten female mice (about 6-week-old, 16.0 ± 2.0g) were group housed in pathogen-free conditions in the animal facility at Nanjing Medical University. All experiments were approved by the Nanjing Medical University Institutional Animal Care and Use Committee (IACUC). Twenty mice were divided to two groups. The PAHs-exposed group included five males and five females, and was administrated with 50µg/mg PAHs mixture, i.n.,10µl/nasal. for 2 weeks. The control group included five males and five females with normal saline. The PAHs mixture was produced by our lab according to the proportional distribution of PAHs mixture that was measured in our previous work [Hu et al.,2020] as shown in Table S1 . Urine specimen were collected for metabolomic analysis. Mice were gently restrained and decapitated. Bronchoalveolar lavage fluid (BALF) was collected by normal saline washing. Lung and colon tissues were collected for further analysis. 2.3 Total IgE and IL-17 analysis The determination of total IgE and IL-17 concentrations were performed using Human/Mouse IgE ELISA Kit (AMEKO, Shanghai, China) and Human IL-17A/ Mouse IL-17 ELISA Kit (Cusabio, Wuhan, China) according to the manufacturer’s instructions, respectively. The absorbance was measured at a wavelength of 450nm (Infinite M2000, Tecan Trading AG, Switzerland). 2.4 PAHs analysis by GC-MS Briefly, 0.2 mL of the serum was spiked with internal standards(D 10 -Phe, D 12 -Chr, Accustandard, New Haven, CT, USA). Then 0.5 mL of 6mol/L hydrochloric acid, 0.5 mL of isopropanol and 3mLof n -hexane/ methyl tertiary butyl ether (v/v,1:1) were added and vortexed for 2 min. After centrifugation at 5000 rpm for 10 min, the organic phase was collected. The above extraction procedure was repeatedly carried out for three times. The mixed extract was evaporated under gentle nitrogen, and then was redissolved in 100 µl of n - hexane and prepared for quantification. The quantitative analysis of target PAH compounds in the serum, including fluorene (Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), pyrene (Pyr), benzo(a)anthracene (BaA), chrysene(Chr), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene(BkF), benzo(a)pyrene (BaP), indeno(1,2,3-cd)pyrene (InP), and dibenzo(a,h)anthracene (DBA), were performed using gas chromatograph mass spectrometer (TRACE 1310, Thermo Fisher Scientific, USA) with a chromatographic column (DB-5MS, 30 m, liquid film thickness 0.25 µm, internal diameter 0.25 mm). The program of the GC analysis was described in our previous work [Hu et al.,2020]. The quantification was performed using standard curves by a standard mixture solution (Supelco Company, 20 µg/mL). Isotopically labeled internal standards were used with the recoveries of 97.0% for D 10 -Phe, and 123.7% for D 12 -Chr. Human reference serum (RS10-100-4, BETHYL) was as blank. Low molecular weight PAH isomers (naphthalene, acenaphthylene, acenaphthene) had poor recoveries due to their high volatility. So, they were excluded in the analyte. Limits of detection (LODs) were defined as a signal-to-noise ratio of 3:1. If the concentration was below LOD, it was reported as not detected (ND) and assigned a concentration of zero. INP and DBA were not well separated. Benzo[ghi]perylene was also exclude as the concentrations in a large proportion of samples were below LOD. 2.5 The analysis of one carbon metabolites by UPLC-MS The serum was pretreated according to Wang’s study [Wang et al.,2008]. For metabolite quantitation, isotopically labeled one carbon metabolites including S-adenosylhomocysteine-d4(SAH-d4), L-Methionine-d4 (Met-d4) (Tornoto Research Chemicals, North York, Canada) were used as internal standards. In brief, 200µL of serum was added to 1mL of methanol containing 100µg/mL ascorbic acid, 100µg/mL citric acid and 1.5mg/mL dithiothreitol (DTT). The internal standard solution was spiked at 200ng/ml concentration. After vortexed for 2min and centrifuged at 13000rpm for 15min at 4℃, the supernatant was dried under nitrogen at room temperature. The residue was reconstituted with 100µL of methanol/water (3:1, v/v) containing 10µg/mL of ascorbic acid, citric acid, and DTT, and stored at − 20 ℃ for further analysis. The calibration curve standards, 5-methyltetrahydrofolate (5-MT), serine (Ser), glycine (Gly), methionine (Met), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), homocysteine (Hcy), betaine (Betaine) (Sigma Aldrich, St. Louis, MO, USA), were prepared by spiking the internal standard solutions. Metabolites were quantified using UPLC Ultimate 3000 system (Dionex, Germering, Germany) with an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). The separation of the samples was performed on a Waters ACQUITY BEH-C18 column (2.1mm×100mm, 1.7µm) at a flow rate of 0.3 mL/min. Mobile phase A was water containing 20mM ammonium formate and 0.15% (v/v) formic acid, and mobile phase B was methanol containing 0.15% (v/v) formic acid. The column temperature was at 35 ± 1°C. The injection volume of samples was 20µL. A linear gradient procedure was described in Table S2 . The effluent was unsplitted. Mass spectrometric analyses in the positive ion mode in full scan MS/SIM mode and the parameters were given in Table S3 . The temperature of the turbo ion electrospray was set at 320°C. The ion spray voltage was 3200V. Metabolite concentrations were calculated from their peak area ratios and the calibration curve. Surrogate standards were used with the recoveries of 74.04% for SAH-d4 and 93.91 for Met-d4. Human reference serum (RS10-100-4, BETHYL) was as blank. Limits of detection (LOD) were defined as a signal-to-noise ratio of 3:1. If the concentration was below LOD, it was reported as not detected (ND) and assigned a concentration of zero. 2.6 The analysis of tryptophan metabolites by UPLC-MS Tryptophan and its metabolites, including L-Tryptophan (Trp), L-kynurenine (Kyn), 2-picolinic acid (PIC), quinolinic acid (QUI), indole acrylic acid (IA), indole-3-propionic acid (IPA), and tryptamine from Aladdin Biochemical Technology Co., Ltd (Shanghai, China);5-Hydroxyindoleacetic acid (5-HIAA), indoleacetaldehyde (IAAld), indoleacetic acid (IAA) and serotonin (5-hydroxytryptamine, 5-HT) hydrochloride from Sigma Aldrich (MO, USA); 5-Hydroxy-L tryptophan (5-HTP) from MAYA-Reagent (Jiaxing, China); Indole-3-aldehyde (IAld) from TCI (Shanghai) Development Co., Ltd., were determined in this study. An isotopically labeled Trp metabolite, tryptophan-d5(Trp-d5) (Toronto Research Chemicals, Toronto, Canada), was used as internal standards. In brief, 50µL of serum was added to 150µL of methanol. The internal standard solution was spiked at 50ng/ml concentration. After vortexed and centrifuged at 13000 rpm for 15 min at 4℃, the supernatant was quantified using UPLC Ultimate 3000 system (Dionex, Germering, Germany) with an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). The separation of the samples was performed on a Hypersile C18 column (100 mm × 2.1 mm, 1.9 µm) at a flow rate of 0.3 mL/min. Mobile phase A was water containing 0.1% (v/v) formic acid, and mobile phase B was acetonitrile containing 0.1% (v/v) formic acid. The column temperature was at 40°C. The injection volume of samples was 10µL. A linear gradient procedure was described in Table S4 . Mass spectrometric analyses in the positive ion mode in full scan MS/SIM mode and the parameters were given in Table S5 . The effluent was unsplitted. The temperature of the turbo ion electrospray was set at 300°C. The ion spray voltage was 3500V. Surrogate standard was used with the recovery of 95.31% for Trp-d5. Human reference serum (RS10-100-4, BETHYL) was as blank. 2.7 Bisulfite sequencing PCR DNA methylation status of the LINE-1 (X58075.1) was detected by bisulfite genomic sequencing PCR amplification (BSP). In silico analyses and detailed databases searches were used to predict the 5'-CpG islands in LINE-1 gene. For LINE-1 , BSPCR primers were designed to amplify a CpG-rich region spanning from 113bp to 357 bp from the transcription start site, which contains 15 CpG sites, and the full length is 275bp. BSPCR primer sequences were 5'-TTATTAGGGAGTGTTAGATAGTGGG-3' for forward; 5'-CCTCTAAACCAAATATAAAATATAATCTC − 3' for reverse. 200 ng of genomic DNA was used for bisulfite treatment using the EZDNA Methylation™ Kit (Zymo Research, CA, USA). The bisulfite treated DNA was amplified with methylation specific primers using GoTaq Green Master Mix (Promega, WI, USA) and optimized PCR condition (95°C for 10 min, 35 cycles of 95°C for 30 sec, 52.6°C for 1 min and 72°C for 2 min, followed by an extension at 72°C for 10 minutes. PCR products were purified by Gel Extraction Kit (E.Z.N.A., USA) and subcloned into pMD 19-T Vector (TaKaRa, Japan). Ten clones from each sample were sequenced (TsingKe Biological Technology, China) to obtain direct measures of DNA methylation at each CpG site in the promoter region. Sequencing data was analyzed with the DNAMAN to examine the methylation status. The percentage of DNA methylation was calculated with the formula: methylated CG / (methylated CG + unmethylated CG) *100%. 2.8 ChIP-qPCR assay for H3K4me3 enrichments Chromatin immunoprecipitation (ChIP) was conducted with a ChIP-IT Express Enzymatic (Active Motif) according to the manufacturer’s protocol. Homogenate was fixed with 1% formaldehyde for 10 min at room temperature to cross-link proteins and DNA, and then add Glycine Stop-Fix Solution (1ml 10× Glycine Buffer,1ml 10× PBS and 8ml distilled H 2 O) rocking at room temperature for 5 minutes to stop cross-linking. After washing with 1× PBS at room temperature three times, the tissue was pelleted by centrifugation for 10 min at 2,500 rpm at 4℃ then resuspended in ice-cold Lysis Buffer supplemented with protease inhibitor cocktail and 100mM PMSF. Transfer the cells to an ice-cold dounce homogenizer. Dounce on ice with 10 strokes to aid in nuclei release and centrifuge for 10 min at 5,000 rpm in a 4℃ microcentrifuge to pellet the nuclei. Add the working stock of Enzymatic Shearing Cocktail (200U/ml) and incubate at 37℃ for 15 minutes and add ice-cold 0.5M EDTA to stop the reaction. Centrifuge for 10 min at 15,000 rpm in a 4℃ microcentrifuge. The supernatants were immunoprecipitated with H3K4me3 (1:50, #9751; Cell Signaling Technology) antibody with rotation after taking out part of as input DNA, which was followed by incubation with protein G magnetic beads for 4 h at 4°C. The anti-IgG (1:1000, #3900; Cell Signaling Technology) was used as negative control. Protein G magnetic beads antibody/chromatin complexes were collected, washed, and eluted. Then, cross-links were reversed, and DNA was purified and analyzed via real-time PCR. The ChIP qPCR primer sequences for human IL-17A were as follows: 5’-CTAGTTCTCATCACTCTCTACTCCC-3’ (forward) and 5’-ATTGAATTTAACAATTCTTTTGTTG-3’ (reverse), -738bp to -512 bp from transcription start site [Liu et al.,2015], and β- actin was used as an internal reference [Wu et al.,2019]. The levels of bound DNA sequences were then calculated using the percent input method (2 − [Ct (ChIP)‑ Ct (Input)] × 100) by calculating the qPCR signal relative to the input sample. 2.9 Metabolic profile analysis based on UPLC-Orbitrap-MS The analyses of metabolomics profile for urine were performed on a UPLC Ultimate 3000 system (Dionex, Germering, Germany), coupled to an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) equipped with a heated electrospray source (HESI) at the resolution of 7×10 5 in both positive and negative mode. The detail was described in our previous work [Hu et al.,2021]. 2.10 Quantitative real-time polymerase chain reaction (qPCR) Total RNA was extracted from frozen tissue using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the instructions of the manufacturer. Genes were measured by qRT-PCR according to our previous work [Xu et al.,2021]. The primers were AhR : 5'-TTGGTTGTGATGCCAAAGGGC-3'for forward; 5'-CATGCGGATGTGGGATTCTGC-3' for reverse [Yang et al.,2020]; Il-17a : 5'-CAGACTACCTCAACCGTTCCAC − 3' for forward; 5'-TCCAGCTTTCCCTCCGCATTGA-3' for reverse ( www.origene.com ); Cyp1a1 : 5'-GGGTTTGACACAGTCACAACT-3'for forward; 5'-GGGACGAAGGATGAATGCCG-3' for reverse[Yang et al.,2020]. Gapdh was used as an internal control: 5‘-AAGAAGGTGGTGAAGCAGG-3’ for forward, and 5‘-GAAGGTGGAAGAGTGGGAGT-3’ for reverse. 2.11 Statistical analyses The differences between asthmatic children and the control were analyzed using student’s t test by GraphPad Prism 8 software (GraphPad Software, La Jolla, CA). Differences were considered statistically significant at P ༜0.05. The association between the PAHs concentrations and asthma was determined with logistic regression. Age and gender were considered as covariates in the regression model. Pearson correlation was used to assess the associations between PAHs and one carbon metabolites and tryptophan metabolites. A redundancy analysis (RDA) was performed to determine the multivariate relationship between PAHs and sample distribution and one carbon metabolites and by R package. In addition, mediation analysis for the association between PAHs and asthma mediated by intermediates was implemented considering one carbon metabolites and tryptophan metabolites as mediators with reference to our previous work [Hu et al.,2021]. 3 Results And Discussion 3.1 The characteristics of the subject in this study In this study, the characteristics of all subjects were shown in Table 1 . The ratio of males to females was 31:19 in the asthmatic group, and 33:17 in the control. The average age was 3.15 ± 2.28 years in the asthmatic group, and 5.78 ± 3.36 years in the control. The blood was collected before medication. Figure. S1 showed the mean of total IgE concentrations was 292.74 ± 168.37 IU/mL (ranged from 31.92-716.67 IU/mL) in the asthmatic group, and 147.37 ± 79.71 IU/mL (ranged from 13.33-308.75 IU/mL) in the control, respectively. The asthmatic group presented significantly higher total serum IgE concentrations. Table 1 The characteristics of all subjects Variables Values Sex Number (Control/Asthma) Male 64 (31:33) Female 36 (19:17) Age 0–1 16(2:14) 2–5 54(25:29) >6 30(23:7) IgE Mean ± SD (IU/mL) Control 147.37 ± 79.71 Asthma 292.74 ± 168.37 3.2 Serum PAH concentrations were associated with childhood asthma As shown in Figure.1 , the distribution of twelve types of PAHs was similar in the asthmatic group and the control. The concentration of PAHs listed in the order was Pyr > Phe > Flu > Fla > Chr > BaA. Serum Pyr showed the highest proportion and the highest detection frequency. There are some reports about the concentrations of PAHs in children serum. For example, Singh et al. reported values ranged from 1.05 ng/mL to 160.6 ng/mL (25th-75th percentile) in the distributions of nine types of PAH concentrations in the blood of children in Lucknow, India [Singh et al.,2008]. Our data showed the concentration of the total PAHs ranged from 8.15 ng/mL to 209.99 ng/mL, and 17.74 ng/mL to 44.49 ng/mL (25th-75th percentile) in the serum of children in Nanjing, China. Table 2 listed the compounds sought in this analysis, detection rate, and the summary statistics for all subjects. After adjusted for sex and age, a logistic regression model showed that Fla, Pyr, BaA, and INP/DBA were associated with childhood asthma shown in Table 2 . In our previous work, we demonstrated that urinary1-hydroxypyrene (1-OHPyr) concentrations were associated with childhood asthma [Hu et al.,2021]. Internal exposure to PAHs has been assessed commonly by urinary 1-OHPyr as a general biomarker [Hansen et al.,2008]. However, environmental exposure to PAHs may be understatedly assessed only based on exposure biomarkers such as urinary OH-PAHs metabolite concentrations [Yang et al.,2021]. High molecular weight PAHs composed of four or more rings (e.g., fluoranthene, pyrene, chrysene, benzo[a]pyrene, dibenz[a,h]anthracene) are dominant components of particle matter and easily taken up by inhalation [Huang et al.,2021]. In developing countries children are exposed to multiple sources of PAHs including heating and cooking from biomass fuel, and industrial coal-burning and traffic emission, and in these situations the inhalation of particle-bound PAHs is at least as important a route of exposure as dietary exposure [Yang et al.,2021;WHO,2010]. And there is mounting evidence of unmetabolized PAHs as a biomarker to reflect body burden [WHO,2010; Sexton et al.,2011], which can directly represent the actual exposure concentrations of the environment. Based on toxicokinetics, PAHs may result in relatively more toxicity through inhalation than after dietary exposure since inhalation avoid the hepatic first-pass effect [Craemer et al.,2016]. Table 2 Serum PAH concentrations of subjects in this study PAHs Detection rate Limit of Detection(ng/mL) Min-Max (ng/mL) Mean ± SD (ng/mL) Median (ng/mL) OR (95%CI) P value Flu 99% 0.049 ND-9.438 2.434 ± 1.412 2.327 1.002(0.535, 1.877) 0.994 Phe 99% 0.029 ND-15.120 3.988 ± 2.683 3.851 1.041(0.802, 1.350) 0.763 Ant 97% 0.014 ND-5.654 1.202 ± 1.031 0.871 0.675 (0.357, 1.276) 0.226 Fla 99% 0.054 ND-15.134 3.468 ± 3.608 2.125 1.380 (1.063, 1.792) 0.016* Pyr 99% 0.013 ND-188.043 23.921 ± 35.201 9.756 1.033 (1.000, 1.067) 0.047* Chr 99% 0.035 ND ~ 10.709 1.725 ± 1.843 1.028 0.498(0.237, 1.047) 0.066 BaA 92% 0.012 ND ~ 11.156 1.719 ± 1.790 0.984 2.266 (1.018, 5.042) 0.045* BbF 91% 0.017 ND ~ 1.771 0.545 ± 0.440 0.445 0.941(0.171, 5.157) 0.944 BkF 90% 0.006 ND ~ 1.353 0.313 ± 0.228 0.279 3.891 (0.062, 246.174) 0.521 BaP 91% 0.011 ND ~ 2.315 0.516 ± 0.467 0.428 1.634(0.272, 9.813) 0.591 INP/DBA 84% 0.004 ND ~ 1.063 0.260 ± 0.238 0.217 32.835 (1.432, 753.007) 0.029* ND: not detected; OR: Odds ratio; CI: confidence interval, * P < 0.05 3.3 PAHs changed the expression of one carbon metabolites in asthmatic children One carbon unit from the folate cycle and betaine metabolism is used to form methionine. The methionine intermediate SAM functions as substrates for DNA methylation and histone methylation [Mentch et al.,2016] ( Figure.2A ). In our previous work, it was found that 7-methylguanine as PAHs-related intermediate showed a mediation effect on the association between urinary 1-OHPyr concentration and childhood asthma [Hu et al.,2021]. Urinary 1-OHPyr concentration was associated with 7-methylguanine which could reflect global DNA methylation in asthmatic children [Wishnok et al.,1993]. So, we compared the concentrations of one carbon metabolites between two groups (Table 3 , Figure.2B ). The asthmatic group displayed a significantly decreasing in SAM abundance and a smaller but corresponding decrease in SAH, which indicated the increasing conversion from SAM to SAH and the elevated capacity of methylation reactions (Figure.2C ). What’s more, the methionine concentrations in the asthmatic group were higher than that in the control. Roy et al reported that methionine restriction can reduce histone H3K4 methylation at the promoter regions of key genes involved in Th17 cell proliferation and cytokine production [Roy et al.,2020]. Therefore, metabolic changes-induced by PAHs has profound effects on epigenetics, especially methylation. Then a redundancy analysis (RDA) was performed to determine the multivariate relationship between the environmental variable-PAHs and sample distribution and one carbon metabolites by R package. RDA-analysis revealed two groups of all subjects, each characterized by a specific set of PAHs-one carbon parameters (groups are indicated on the diagram, Figure.2D ). The effect of PAHs on one carbon metabolites in different groups in the RDA diagram is mainly characterized by the length of PAH variables and by the cosine value of the angle. The metabolites-PAHs correlation was 0.64 for RDA axis 1 and 0.23 for axis 2. Fla had a great effect on one carbon metabolites between two groups. There was a significant negative correlation between Fla and one carbon metabolites (Figure.2E) . We used differential one carbon metabolites to perform mediation analysis to assess the association between the PAHs concentration and asthma mediated by metabolites. The directed acyclic graph (DAG) showed significant mediation effects between the Fla concentration and asthma by SAH, SAM and Ser (Figure.2F, Table S6) . Table 3 The serum concentrations of one carbon metabolites of subjects in this study PAHs Limit of Detection(ng/mL) Min ~ Max value(ng/mL) Mean ± SD(ng/mL) Median(ng/mL) 5-MT 2.0 ND-95.076 22.648 ± 20.435 15.05117 SAH 0.5 ND-25.930 10.245 ± 4.948 10.941 SAM 0.5 ND-0.741 0.179 ± 0.200 0.144 Betaine 1.0 2.563-117.121 34.3651 ± 17.644 31.832 Met 3.0 1065.416-6634.955 3077.496 ± 1212.843 2848.938 Hcy 10.0 2.718-569.948 114.0546 ± 97.510 95.346 Ser 10.0 17.764-334.8852 114.6048 ± 83.428 82.450 His 3.0 45.512-214.226 85.992 ± 35.489 73.125 Gly 1.0 225.477-5208.570 2128.707 ± 1108.04 1985.819 CYSTA 25.0 6.322-213.732 59.242 ± 52.372 36.519 ND: not detected 3.4 PAHs changed epigenetic pattern in asthmatic children To study epigenetic alterations induced by PAHs, firstly, we examined the methylation levels of long interspersed nuclear elements-1 ( LINE-1 ) promoter, which comprise approximately 17% of the human genome and is used to assess global DNA methylation[Lisanti et al.,2013]. The distributions of LINE-1 DNA methylation were presented in Fig. 3A. The geometric mean for LINE-1 methylation were 17.26% in the control, and 34.19% in asthmatic group, respectively, which indicated elevated global DNA methylation in asthmatic group. Fla had a positive effect on LINE-1 methylation (β = 0.395, P = 0.000). There were no any significant associations of other PAHs with global DNA methylation. Because Fla was associated with childhood asthma and LINE-1 methylation, we conducted the mediation analysis to assess global DNA methylation could be mediator of the association between PAHs and asthma. We did find significant mediation effect between serum Fla and asthma by LINE-1 methylation (Figure.3B) . In contrast to our work, current evidence showed that prenatal urinary 2-OHNa and 1-hydroxyphenanthrene were associated with lower Alu and LINE-1 methylation [Yang et al.,2018]. On the other hand, studies have shown a positive association between gene-specific hypermethylation and PAHs exposure. For example, CpG Site-specific hypermethylation of p16 INK4α was found in peripheral blood lymphocytes of PAH-exposed workers by BSP sequencing [Yang et al.,2012]. Interestingly, global DNA hypermethylation levels were associated with asthma severity by assessing the percentage of 5-methylcytosine [Chan et al.,2017]. Perhaps these discrepancies in the literature about the correlation between global DNA methylation and PAHs exposure can be attributed to the fact that the resource of PAHs exposure and the representative indices of global DNA methylation were differentially assessed. In addition, there is evidence that IL-17A markedly contribute to the immune imbalance in asthma [Wang and Liu,2008]. For example, elevated concentrations of IL-17A have been found in the sputum and in bronchoalveolar lavage fluid of patients with asthma[ Molet et al.,2001]. What’ more, Milovanovic et al demonstrated that IL-17A secretion promoted IgE production [Milovanovic et al.,2010]. So, we collected the serum from both groups and performed ELISA to detect the concentration of IL-17A. Figure.3C showed the mean of IL-17A concentrations of 100.20 ± 45.99 pg/mL (ranged from 33.83-195.23 pg/mL) in the asthmatic group, and 40.92 ± 22.41 pg/mL (ranged from 4.56–85.35 pg/mL) in the control, respectively. The results showed that high concentration of IL-17A was detected in asthmatic group when compared with the control. Research has reported some genes that are associated with PAHs-induced methylation and immune dysfunction. For example, Kohli et al. [Kohli et al.,2012] reported that tobacco smoke (in which PAHs are critical constituents) exposure was associated with hypermethylation of the promoter region for IFN-gamma in T effector cells and Foxp3 in regulatory T cells. In the present study, because PAHs can increase methylation capacity by interfering one carbon metabolism including SAM-dependent histone modifications, we hypothesized that H3K4 tri-methylation level (a histone modification associated with active transcription in chromatin structure) may be induced by PAHs exposure. To determine whether PAHs could regulate the production of IL-17A through epigenetic changes, ChIP assay was performed using antibodies against tri-methylated Lys4 of H3( Figure.3C ). Interestingly, Fla could upregulate H3K4 tri-methylation level in the IL-17A promoter region and associated with children asthma (β = 0.293, P = 0.002) ( Figure.3D ). By ChIP-qPCR results we demonstrated that PAHs could promote secretion of IL-17A through changes in histone methylation levels. In a previous study, PAH might affect, through their effects on the aryl hydrocarbon receptor, IL-17 production in asthma [Plé C et al.,2015]. Our data suggested that PAHs might contribute to increased IL-17A production through mechanisms involving not only AhR-dependent but also independent pathways, epigenetics. In addition, we report here that one carbon metabolism forms a function link between metabolic and epigenetic reprogramming to regulate gene expression. Epigenetic modification is induced by the environment with one carbon metabolites function as key substrates for DNA methylation and histone methylation. 3.5 PAHs changed the expression of tryptophan metabolites in asthmatic children Tryptophan is an essential amino acid in all animal, metabolism of which is involved in the regulation of immunity, neuronal function and intestinal homeostasis [Martin et al.,2020]. Trp metabolism includes three major pathways, i.e. the kynurenine pathway, the serotonin (5-hydroxytryptamine [5-HT]) production pathway and a series of molecules, including AhR ligands by microbiota [Zelante et al.,2013]. In this present study, we detected Trp metabolic profile to find out key metabolites associated with PAHs-related childhood asthma (Table 4 ). In Figure.4A , the concentrations of Trp, tryptamine, IA, IAA, and Indole were significantly higher in asthmatic group, and that of IAld and IAAld were relatively lower, which is consistent with Licari’s study [Licari et al.,2019]. The differential Trp metabolites was mainly enriched in AhR ligands derived from microbiota, such as tryptamine, IA, IAA, IAld and Indole, which indicated the asthmatic children had increased indole-AhR pathway. There was no change in the concentration of the metabolites in kynurenine pathway and 5-HT pathway. Reports have shown that circulating Trp concentrations were increased in germ-free mice [El Aidy et al.,2012]. In this present study, the circulating Trp concentration was also increased. Lactobacillus , Clostridium and others can directly utilize Trp. Lactobacillus can metabolize Trp to IAld, which can active AhR anti-inflammatory responses [Zelante et al.,2013]. However, the concentration of IAld in asthmatic children in this study was decreased. What’s more, the microbial diversity was decreased in asthmatic children, especially Lactobacillus in our previous work [Hu et al.,2021]. These data suggested he microbiota-AhR axis can influence host metabolism. Although there was some correlation between PAHs and Trp metabolites ( Figure.4B ), it was also showed that Trp metabolites has direct effects on IL-17A production or childhood asthma, but no mediation effects between PAHs concentration and asthma by Trp metabolites ( Table S7 and S8 ). AhR acting a crucial transcription factor is involved in Th17 cells differentiation [Veldhoen et al.,2008]. IL-17A is secreted from Th17 cells. In agreement with the present studies, increased IL-17A concentration was found in serum of asthmatic children in our study. However, there were controversial results that some AhR such as TCDD induced IL-17A generation in mice and inhibited that in humans [Veldhoen et al.,2008;Ramirez et al.,2010], and this discrepancy may be due to the different ligands and the types of AhR-expressed cells. Additional studies are needed to further explore the effects of PAHs on Trp metabolites, AhR, and IL-17A profiles. Table 4 The serum concentrations of tryptophan metabolites of subjects in this study PAHs Limit of Detection(ng/mL) Min ~ Max value(ng/mL) Mean ± SD(ng/mL) Median(ng/mL) PIC 7.5 84.55-369.543 143.301 ± 44.590 132.231 QUI 10 176.768-453.643 234.826 ± 55.912 217.376 5-HTP 16.67 232.695-1391.512 677.133 ± 256.877 639.341 5-HT 15 52.115-464.017 126.754 ± 79.644 99.651 Kyn 3.75 328.37-1681.422 838.017 ± 251.845 792.212 IA 0.33 9138.89-36006.643 18308.153 ± 6081.868 17380.28 Trp 0.33 9154.257-36424.142 18414.979 ± 6134.758 17391.55 Tryptamine 1.67 ND-96.628 31.223 ± 20.247 28.04 5-HIAA 0.67 3.2-112.644 33.185 ± 20.85 27.204 IAld 0.3 0.996–16.412 6.755 ± 3.489 6.62 IAA 3.75 145.464-9663.26 1229.170 ± 1178.662 1039.154 Indole 75 ND-623.324 209.647 ± 155.352 161.96 IAAld 15 ND-150.284 37.865 ± 24.783 39.544 IPA 2 ND-532.54 142.565 ± 139.532 90.558 ND: not detected 3.6 PAHs induced Il-17A production by altering tryptophan metabolism in mice To validate whether PAHs have the effects on tryptophan metabolism and inducing IL-17A production or not, PAHs mix were exposed on mice. We selected more than four rings PAHs due to more stable and more toxic. The results showed that lung tissue was infiltrated by lymphocytes in PAHs -exposed group ( Figure.5 ). The concentration of IgE in BALF of PAHs-exposed group was higher than that in the control ( Figure.6A) . Interestingly, after stratified by gender, the concentration of Il-17 in BALF of male PAHs-exposed group was higher than that in the control ( Figure. 6B ). In lung tissue, the expression of Ahr was upregulated in PAHs-exposed group. Il-17a gene was downregulated in PAHs-exposed group. Another AhR target genes Cyp1a1 was upregulated in female PAHs-exposed group ( Figure. 6C, 6D and 6E ). In gut tissues, the expression of Ahr was upregulated only in female PAHs-exposed group while Il-17a genes was upregulated in both female and male PAHs-exposed groups. Cyp1a1 was only upregulated in male PAHs-exposed group ( Figure. 6F, 6G and 6H ). Here we found that the transcription of Il-17a was inhibited in lung tissue and induced in gut tissue, while the concentration of IL-17 in BALF was increased in male PAHs-exposed group. There were different AhR-induced responses in lung and gut tissue, respectively. We speculated that gut-derived IL-17A can influence inflammation in lung through gut-lung axis. Reports have shown that tetrachlorodibenzo-p-dioxin (TCDD)-active AhR mediated immunosuppressive effects in human [Kerkvliet,2009], while controversial results have shown that endogenous AhR ligand 6-formylindolo[3,2-b] carbazole (FICZ) induced IL-17A production in mice [Quintana et al.,2008]. Other than TCDD, polycyclic aromatic hydrocarbons are rapidly metabolized by AhR-inducible enzymes that may produce a different type of effects on the immune system. What’s more, active AhR may induce the expressions of AhR target genes, such as IL-6, which can initiate Th17 cell differentiation and promote IL-17 production [Xu and Cao,2010]. But excessive immune reactions lead to inhibit anti-immune responses in the microenvironment and ultimately result in uncontrolled and promoted immunity response. Th17 cell differentiation may be modulated by AhR through transcriptional changes. Although the mechanisms mediating AhR-Th17 axis still remain controversial in human and mice studies, cytokine milieu may be contributed to induce Th17 cell differentiation [Veldhoen et al.,2008]. Besides of as direct ligands of AhR, PAHs may also influence AhR-IL-17A by disturbing tryptophan metabolism. Metabolic profiling was applied to compare the global metabolites in mice with or without PAHs treatment. The differential metabolites partly shaped the gender difference (Figure. 7A ). It was also found that the differential metabolites were mainly enriched in tryptophan metabolism, such as indoleacetic acid (IAA), indoxyl sulfate, kynurenic acid (Kyn), indolelactic acid, 5-hydroxyIndoleacetic acid(5-HIAA), indole-3-carboxylic acid, and indoleacetaldehyde (IAAld), most of which are AhR-ligands, such as IAA, Kyn and IAAld ( Figure. 7B ). IAA and indoxyl sulfate were lower in both PAHs-exposed groups; Kyn and indolelactic acid were higher in male PAHs-exposed group; 5-HIAA, indole-3-carboxylic acid, and IAAld were higher in female PAHs-exposed group. In addition, acetyl-methionine,1-methyladeosine, and 7-methylguanine were higher in PAHs-exposed group. These animal results supported that PAHs altered tryptophan metabolism and disturbed IL-17A production. 4 Conclusion In this study, we assessed the effects of PAHs exposure on asthmatic children from the perspective of one carbon metabolism and tryptophan metabolism. Our data gave the evidence that PAHs exposure induced DNA methylation and histone methylation by disturbing one carbon metabolism, and altered Try-AhR pathway to disturb IL-17A production, which could help in identifying the underlying mechanisms of PAHs exposure-related asthma. However, there are limitations in the present study. We found gender differences in the effects of PAHs on inflammation in animal study. Due to the small sample size and low proportion of female subjects in asthmatic children, we did not find the effects of gender on PAHs toxicity. In addition, microbiota-mediated immunodulation have been associated with the etiology of asthma and microbiota can also modulate Trp metabolism. Therefore, we should investigate the effects of PAHs-related microbiota on Trp metabolism and childhood asthma in future work. Abbreviations polycyclic aromatic hydrocarbons (PAHs) aryl hydrocarbon receptors (AhRs) regulatory T cell Treg long interspersed nucleotide element-1 LINE-1 short interspersed nuclear elements Alu S-adenosylmethionine SAM Peripheral blood mononuclear cells PBMC gas chromatograph mass spectrometer GC-MS fluorene Flu phenanthrene Phe anthracene Ant fluoranthene Fla pyrene Pyr benzo(a)anthracene BaA chrysene Chr benzo(b)fluoranthene BbF benzo(k)fluoranthene BkF benzo(a)pyrene BaP indeno(1,2,3-cd)pyrene InP dibenzo(a,h)anthracene DBA ultra-performance liquid chromatography-Orbitrap-mass spectrometry UPLC-Orbitrap-MS 5-methyltetrahydrofolate 5-MT, serine:Ser glycine Gly methionine Met S-adenosylhomocysteine SAH homocysteine Hcy betaine Betaine dithiothreitol DTT Limits of detection LODs L-Tryptophan Trp L-kynurenine Kyn 2-picolinic acid PIC quinolinic acid QUI indole acrylic acid IA indole-3-propionic acid IPA 5-Hydroxyindoleacetic acid 5-HIAA indoleacetaldehyde IAAld indoleacetic acid IAA 5-hydroxytryptamine 5-HT 5-Hydroxy-L tryptophan 5-HTP Indole-3-aldehyde IAld bisulfite genomic sequencing PCR BSP chromatin immunoprecipitation ChIP redundancy analysis RDA 1-hydroxypyrene 1-OHPyr Odds ratio OR confidence interval CI directed acyclic graph DAG indirect effect IE total effect DE Declarations Ethical approval The Nanjing Medical University Clinical Research Ethics Committee, Nanjing, China, reviewed and approved the protocols of this study. Consent to participate Written informed consent was obtained from the participants’ parents for the use of samples in this study. Consent to publish Its publication has been approved by all co-authors Author contribution Conceptualization, Lei Li and Qian Wu; Formal analysis, Hao Wu, Yuling Bao, Tongtong Yan, Hui huang, Ping Jiang, and Zhang Zhan; Funding acquisition, Qian Wu; Investigation, Hao Wu, Yuling Bao and Tongtong Yan; Resources, Yuling Bao, Lei Li and Qian Wu; Writing – original draft, Qian Wu. Funding This work was supported by the National Natural Science Foundation of China (82073630 and 81728018); Natural Science Foundation of Jiangsu Province (BK20161571), Natural Science Foundation of the Higher Education Institution of Jiangsu Province (16KJA330002). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests There are no conflicts to declare. 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University","correspondingAuthor":false,"prefix":"","firstName":"Yuling","middleName":"","lastName":"Bao","suffix":""},{"id":96667433,"identity":"520033d2-7dd9-43a0-818a-44584c4e6705","order_by":2,"name":"Tongtong Yan","email":"","orcid":"","institution":"Nanjing Medical University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Tongtong","middleName":"","lastName":"Yan","suffix":""},{"id":96667434,"identity":"d1fe62f6-9061-4c5f-b668-31bfbaa2a765","order_by":3,"name":"Hui Huang","email":"","orcid":"","institution":"Nanjing Medical University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Huang","suffix":""},{"id":96667435,"identity":"fdd4b576-d02a-4fcb-ae15-f79a27f61311","order_by":4,"name":"Ping Jiang","email":"","orcid":"","institution":"Nanjing Medical University School of Public 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11:12:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1470556/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1470556/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":20187615,"identity":"b7f43fe5-0690-4922-b3d5-8aeed3c121ba","added_by":"auto","created_at":"2022-04-11 13:02:12","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":64596,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1470556/v1/608e4293c50f9beb4603cbfb.jpg"},{"id":20187614,"identity":"b66d546c-01a5-43a0-ab2b-59a1ad74ca58","added_by":"auto","created_at":"2022-04-11 13:02:12","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90562,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with 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version.\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1470556/v1/be675d0ff652b278d114b9ee.jpg"},{"id":20188014,"identity":"bd501377-b8ff-427f-a225-e11d806e9571","added_by":"auto","created_at":"2022-04-11 13:07:12","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":204516,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1470556/v1/e0a2b42f2f1dfb235a17689c.jpg"},{"id":20189130,"identity":"7735ef4f-d502-4b4c-827d-7b4c8ba83dc1","added_by":"auto","created_at":"2022-04-11 13:12:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1362916,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1470556/v1/2021727d-5704-40d2-a2d8-faf251b4e8c2.pdf"},{"id":20189125,"identity":"958f7091-a4c2-468e-badd-895e2202f40e","added_by":"auto","created_at":"2022-04-11 13:12:12","extension":"docx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":86840,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-1470556/v1/9a6e27c607cb72867ce8d087.docx"}],"financialInterests":"","formattedTitle":"PAHs-induced metabolic changes related to inflammation in childhood asthma","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003ePAHs induced one carbon metabolic aspect of epigenetics in asthmatic children\u003c/li\u003e\n \u003cli\u003ePAHs influenced tryptophan metabolic profile in asthmatic children\u003c/li\u003e\n \u003cli\u003ePAHs may influence the expression of IL-17A by metabolic mechanism in asthmatic children\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eAsthma is a complex and multiple etiological disease [Martinez,2007]. It is also a common chronic inflammation in children [Bousquet et al.,2000]. Asthma prevalence under age 18 years released in 2018 in United States was 7.5% [CDC,2018]. The third (2010\u0026ndash;2011) national epidemiological survey in China showed that the prevalence of childhood asthma had been up to 3.02% [Chin J Pediatr,2013]. Although no latest official national statistics have been issued on the current prevalence of childhood asthma, a wide range of regional surveys have showed an increasing trend in different cities of China. The predicted prevalence of asthma in 2020 was estimated from 1.11% among rural girls aged 14 years to 10.27% among urban boys aged four years [Li et al.,2020]. Epidemiological studies have demonstrated that exposure to air pollution have been linked to increasing asthma prevalence and asthma onset [Guarnieri and Balmes,2014; Orellano et al.,2017]. Especially, ambient polycyclic aromatic hydrocarbons (PAHs), which are traffic related air pollutants and main organic components of PM 2.5 and PM 10, have been known to contribute to the onset of asthma [Karimi et al.,2015; Liu et al.,2016]. In the process of PAHs biotransformation, a cascade of oxidative stress is triggered leading to cytotoxicity and DNA damage [Rossnerova et al.,2011; Wang et al.,2017; Zhang et al.,2020]. PAHs also stimulate inflammatory responses through increasing the production of IgE [Kepley et al.,2003].\u003c/p\u003e \u003cp\u003eRecently, there is growing evidence to demonstrate that PAHs exposure may alter global and gene-specific DNA methylation patterns [Herbstman et al.,2012]. For example, as global methylation indicators, long interspersed nuclear elements-1 (\u003cem\u003eLINE-1\u003c/em\u003e) and short interspersed nuclear elements (\u003cem\u003eAlu\u003c/em\u003e) was used to indicate the global methylation status and considered as intermediators of prenatal PAHs exposure to birth outcomes [Yang et al.,2018]. For specific gene, increased methylation of \u003cem\u003eFOXP3\u003c/em\u003e gene was associated with chronic PAHs exposure leading to Treg dysfunction in atopic children [Hew et al.,2015]. DNA methylation is a biological process by which methyl groups (-CH\u003csub\u003e3\u003c/sub\u003e) are added to cytosine residue to form 5-methylcytosine. Lack of methyl groups may result in hypomethylation. S-adenosylmethionine (SAM) is the major methyl donor, regeneration of which is dependent on folate cycle and methionine cycle, i.e. one carbon metabolism [Anderson et al.,2012]. Studies have shown the links between metabolites and epigenetic factors, as folate, choline, betaine, glycine and serine contributing to DNA methylation as methyl donors and co-factors, also to histone methylation [Lillycrop and Burdge,2012]. Histone methylation includes active H3K4me 1/2/3 and H3K36me3, and repressive H3K9me3 and H3K27me3 modification. One carbon metabolism, especially folate cycle and methionine cycle provide universal methyl group to refill epigenetics. While less is known about regulation of metabolic pathway by which PAHs exert its epigenetic effects in childhood asthma.\u003c/p\u003e \u003cp\u003eIn additon, tryptophan (Trp) metabolic abnormalities were found in asthmatic children [Licari et al.,2019]. Some tryptophan metabolites, such as kynurenine and indole, have been verified to be able to bind and activate the aryl hydrocarbon receptor (AhR). The activated Trp-AhR pathway can induce Th17 cell differentiation and regulate the expression of downstream cytokines such as IL-22 and IL-17, thereby regulating the immune homeostasis [Stevens et al.,2009]. Recent studies have demonstrated that Th17 cells and their signature cytokine IL-17 also play an important role in severe asthma [Ramakrishnan et al.,2019]. It is well known that PAHs such as B[a]P act as AhR ligand. After ligand binding activated AhR may upregulate its target genes such as cytochrome P450 1A1(CYP1A1) expression to mediate the carcinogenic effects. Here, we hypothesized that PAHs may also alter tryptophan metabolism, and aberrant tryptophan metabolites acting on AhRs can induce Th17 cell differentiation and regulate IL-17 production to promote inflammation.\u003c/p\u003e \u003cp\u003eTherefore, in this paper, we used targeted metabolomics analysis to analyze the concentrations of metabolites in one-carbon metabolism and tryptophan metabolism in asthmatic children and sought to evaluate the effect of PAHs on childhood asthma from cell metabolism perspective. PAHs can disturb one-carbon metabolism to change global DNA methylation and histone methylation and induced \u003cem\u003eIL-17A\u003c/em\u003e expression in asthmatic children. Although there was no medication effect of tryptophan metabolism between PAHs exposure and childhood asthma, animal study confirmed that PAHs can influence tryptophan metabolism to induce inflammation but should take the gender difference into account when analyzing data. Collectively, these data indicated that PAHs could disturb metabolic pathway to promote inflammation in asthma.\u003c/p\u003e \u003c/div\u003e"},{"header":"2 Methods And Materials","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Subjects\u003c/h2\u003e \u003cp\u003eThe samples included 50 asthmatic subjects and 50 control subjects who were recruited from the Children\u0026rsquo;s Hospital of Nanjing Medical University and the Affiliated hospital of Nanjing university of Traditional Chinese Medicine from 2020\u0026ndash;2021, respectively. Asthmatic subjects were diagnosed by a clinician. The control subjects were with no history of inflammatory disease and atopy. The Nanjing Medical University Clinical Research Ethics Committee, Nanjing, China, reviewed and approved the protocols of this study. Written informed consent was obtained from the participants\u0026rsquo; parent for the use of samples in this study. Whole blood samples from each asthmatic or control subjects were collected. The samples were centrifuged at 3000 rpm for 10 min. The supernatant was stored at -20\u0026deg;C until analysis. White blood cell DNA was isolated by using TIANamp Genomic DNA Kit (TIANGEN, DP304-03, China) following the instructions from the manufacturer. Peripheral blood mononuclear cells (PBMC) were isolated from whole blood using Lymphocyte-Human Cell Separation Media (Cedarlane, Southern Ontario, Canada).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Animal and PAHs exposure\u003c/h2\u003e \u003cp\u003eC57BL6 mice (Antpedia, Shanghai, China) were used in this study. Ten male and ten female mice (about 6-week-old, 16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0g) were group housed in pathogen-free conditions in the animal facility at Nanjing Medical University. All experiments were approved by the Nanjing Medical University Institutional Animal Care and Use Committee (IACUC). Twenty mice were divided to two groups. The PAHs-exposed group included five males and five females, and was administrated with 50\u0026micro;g/mg PAHs mixture, i.n.,10\u0026micro;l/nasal. for 2 weeks. The control group included five males and five females with normal saline. The PAHs mixture was produced by our lab according to the proportional distribution of PAHs mixture that was measured in our previous work [Hu et al.,2020] as shown in \u003cb\u003eTable S1\u003c/b\u003e. Urine specimen were collected for metabolomic analysis. Mice were gently restrained and decapitated. Bronchoalveolar lavage fluid (BALF) was collected by normal saline washing. Lung and colon tissues were collected for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.3 Total IgE and IL-17 analysis\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe determination of total IgE and IL-17 concentrations were performed using Human/Mouse IgE ELISA Kit (AMEKO, Shanghai, China) and Human IL-17A/ Mouse IL-17 ELISA Kit (Cusabio, Wuhan, China) according to the manufacturer\u0026rsquo;s instructions, respectively. The absorbance was measured at a wavelength of 450nm (Infinite M2000, Tecan Trading AG, Switzerland).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4 PAHs analysis by GC-MS\u003c/h2\u003e \u003cp\u003eBriefly, 0.2 mL of the serum was spiked with internal standards(D\u003csub\u003e10\u003c/sub\u003e-Phe, D\u003csub\u003e12\u003c/sub\u003e-Chr, Accustandard, New Haven, CT, USA). Then 0.5 mL of 6mol/L hydrochloric acid, 0.5 mL of isopropanol and 3mLof \u003cem\u003en\u003c/em\u003e-hexane/ methyl tertiary butyl ether (v/v,1:1) were added and vortexed for 2 min. After centrifugation at 5000 rpm for 10 min, the organic phase was collected. The above extraction procedure was repeatedly carried out for three times. The mixed extract was evaporated under gentle nitrogen, and then was redissolved in 100 \u0026micro;l of \u003cem\u003en\u003c/em\u003e- hexane and prepared for quantification.\u003c/p\u003e \u003cp\u003eThe quantitative analysis of target PAH compounds in the serum, including fluorene (Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), pyrene (Pyr), benzo(a)anthracene (BaA), chrysene(Chr), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene(BkF), benzo(a)pyrene (BaP), indeno(1,2,3-cd)pyrene (InP), and dibenzo(a,h)anthracene (DBA), were performed using gas chromatograph mass spectrometer (TRACE 1310, Thermo Fisher Scientific, USA) with a chromatographic column (DB-5MS, 30 m, liquid film thickness 0.25 \u0026micro;m, internal diameter 0.25 mm). The program of the GC analysis was described in our previous work [Hu et al.,2020]. The quantification was performed using standard curves by a standard mixture solution (Supelco Company, 20 \u0026micro;g/mL). Isotopically labeled internal standards were used with the recoveries of 97.0% for D\u003csub\u003e10\u003c/sub\u003e-Phe, and 123.7% for D\u003csub\u003e12\u003c/sub\u003e-Chr. Human reference serum (RS10-100-4, BETHYL) was as blank. Low molecular weight PAH isomers (naphthalene, acenaphthylene, acenaphthene) had poor recoveries due to their high volatility. So, they were excluded in the analyte. Limits of detection (LODs) were defined as a signal-to-noise ratio of 3:1. If the concentration was below LOD, it was reported as not detected (ND) and assigned a concentration of zero. INP and DBA were not well separated. Benzo[ghi]perylene was also exclude as the concentrations in a large proportion of samples were below LOD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.5 The analysis of one carbon metabolites by UPLC-MS\u003c/h2\u003e \u003cp\u003eThe serum was pretreated according to Wang\u0026rsquo;s study [Wang et al.,2008]. For metabolite quantitation, isotopically labeled one carbon metabolites including S-adenosylhomocysteine-d4(SAH-d4), L-Methionine-d4 (Met-d4) (Tornoto Research Chemicals, North York, Canada) were used as internal standards. In brief, 200\u0026micro;L of serum was added to 1mL of methanol containing 100\u0026micro;g/mL ascorbic acid, 100\u0026micro;g/mL citric acid and 1.5mg/mL dithiothreitol (DTT). The internal standard solution was spiked at 200ng/ml concentration. After vortexed for 2min and centrifuged at 13000rpm for 15min at 4℃, the supernatant was dried under nitrogen at room temperature. The residue was reconstituted with 100\u0026micro;L of methanol/water (3:1, v/v) containing 10\u0026micro;g/mL of ascorbic acid, citric acid, and DTT, and stored at \u0026minus;\u0026thinsp;20 ℃ for further analysis. The calibration curve standards, 5-methyltetrahydrofolate (5-MT), serine (Ser), glycine (Gly), methionine (Met), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), homocysteine (Hcy), betaine (Betaine) (Sigma Aldrich, St. Louis, MO, USA), were prepared by spiking the internal standard solutions. Metabolites were quantified using UPLC Ultimate 3000 system (Dionex, Germering, Germany) with an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). The separation of the samples was performed on a Waters ACQUITY BEH-C18 column (2.1mm\u0026times;100mm, 1.7\u0026micro;m) at a flow rate of 0.3 mL/min. Mobile phase A was water containing 20mM ammonium formate and 0.15% (v/v) formic acid, and mobile phase B was methanol containing 0.15% (v/v) formic acid. The column temperature was at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C. The injection volume of samples was 20\u0026micro;L. A linear gradient procedure was described in \u003cb\u003eTable S2\u003c/b\u003e. The effluent was unsplitted. Mass spectrometric analyses in the positive ion mode in full scan MS/SIM mode and the parameters were given in \u003cb\u003eTable S3\u003c/b\u003e. The temperature of the turbo ion electrospray was set at 320\u0026deg;C. The ion spray voltage was 3200V. Metabolite concentrations were calculated from their peak area ratios and the calibration curve. Surrogate standards were used with the recoveries of 74.04% for SAH-d4 and 93.91 for Met-d4. Human reference serum (RS10-100-4, BETHYL) was as blank. Limits of detection (LOD) were defined as a signal-to-noise ratio of 3:1. If the concentration was below LOD, it was reported as not detected (ND) and assigned a concentration of zero.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.6 The analysis of tryptophan metabolites by UPLC-MS\u003c/h2\u003e \u003cp\u003eTryptophan and its metabolites, including L-Tryptophan (Trp), L-kynurenine (Kyn), 2-picolinic acid (PIC), quinolinic acid (QUI), indole acrylic acid (IA), indole-3-propionic acid (IPA), and tryptamine from Aladdin Biochemical Technology Co., Ltd (Shanghai, China);5-Hydroxyindoleacetic acid (5-HIAA), indoleacetaldehyde (IAAld), indoleacetic acid (IAA) and serotonin (5-hydroxytryptamine, 5-HT) hydrochloride from Sigma Aldrich (MO, USA); 5-Hydroxy-L tryptophan (5-HTP) from MAYA-Reagent (Jiaxing, China); Indole-3-aldehyde (IAld) from TCI (Shanghai) Development Co., Ltd., were determined in this study. An isotopically labeled Trp metabolite, tryptophan-d5(Trp-d5) (Toronto Research Chemicals, Toronto, Canada), was used as internal standards. In brief, 50\u0026micro;L of serum was added to 150\u0026micro;L of methanol. The internal standard solution was spiked at 50ng/ml concentration. After vortexed and centrifuged at 13000 rpm for 15 min at 4℃, the supernatant was quantified using UPLC Ultimate 3000 system (Dionex, Germering, Germany) with an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). The separation of the samples was performed on a Hypersile C18 column (100 mm \u0026times; 2.1 mm, 1.9 \u0026micro;m) at a flow rate of 0.3 mL/min. Mobile phase A was water containing 0.1% (v/v) formic acid, and mobile phase B was acetonitrile containing 0.1% (v/v) formic acid. The column temperature was at 40\u0026deg;C. The injection volume of samples was 10\u0026micro;L. A linear gradient procedure was described in \u003cb\u003eTable S4\u003c/b\u003e. Mass spectrometric analyses in the positive ion mode in full scan MS/SIM mode and the parameters were given in \u003cb\u003eTable S5\u003c/b\u003e. The effluent was unsplitted. The temperature of the turbo ion electrospray was set at 300\u0026deg;C. The ion spray voltage was 3500V. Surrogate standard was used with the recovery of 95.31% for Trp-d5. Human reference serum (RS10-100-4, BETHYL) was as blank.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Bisulfite sequencing PCR\u003c/h2\u003e \u003cp\u003eDNA methylation status of the \u003cem\u003eLINE-1\u003c/em\u003e (X58075.1) was detected by bisulfite genomic sequencing PCR amplification (BSP). In \u003cem\u003esilico\u003c/em\u003e analyses and detailed databases searches were used to predict the 5'-CpG islands in \u003cem\u003eLINE-1\u003c/em\u003e gene. For \u003cem\u003eLINE-1\u003c/em\u003e, BSPCR primers were designed to amplify a CpG-rich region spanning from 113bp to 357 bp from the transcription start site, which contains 15 CpG sites, and the full length is 275bp. BSPCR primer sequences were 5'-TTATTAGGGAGTGTTAGATAGTGGG-3' for forward; 5'-CCTCTAAACCAAATATAAAATATAATCTC \u0026minus;\u0026thinsp;3' for reverse. 200 ng of genomic DNA was used for bisulfite treatment using the EZDNA Methylation\u0026trade; Kit (Zymo Research, CA, USA). The bisulfite treated DNA was amplified with methylation specific primers using GoTaq Green Master Mix (Promega, WI, USA) and optimized PCR condition (95\u0026deg;C for 10 min, 35 cycles of 95\u0026deg;C for 30 sec, 52.6\u0026deg;C for 1 min and 72\u0026deg;C for 2 min, followed by an extension at 72\u0026deg;C for 10 minutes. PCR products were purified by Gel Extraction Kit (E.Z.N.A., USA) and subcloned into pMD 19-T Vector (TaKaRa, Japan). Ten clones from each sample were sequenced (TsingKe Biological Technology, China) to obtain direct measures of DNA methylation at each CpG site in the promoter region. Sequencing data was analyzed with the DNAMAN to examine the methylation status. The percentage of DNA methylation was calculated with the formula: methylated CG / (methylated CG\u0026thinsp;+\u0026thinsp;unmethylated CG) *100%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.8 ChIP-qPCR assay for H3K4me3 enrichments\u003c/h2\u003e \u003cp\u003eChromatin immunoprecipitation (ChIP) was conducted with a ChIP-IT Express Enzymatic (Active Motif) according to the manufacturer\u0026rsquo;s protocol. Homogenate was fixed with 1% formaldehyde for 10 min at room temperature to cross-link proteins and DNA, and then add Glycine Stop-Fix Solution (1ml 10\u0026times; Glycine Buffer,1ml 10\u0026times; PBS and 8ml distilled H\u003csub\u003e2\u003c/sub\u003eO) rocking at room temperature for 5 minutes to stop cross-linking. After washing with 1\u0026times; PBS at room temperature three times, the tissue was pelleted by centrifugation for 10 min at 2,500 rpm at 4℃ then resuspended in ice-cold Lysis Buffer supplemented with protease inhibitor cocktail and 100mM PMSF. Transfer the cells to an ice-cold dounce homogenizer. Dounce on ice with 10 strokes to aid in nuclei release and centrifuge for 10 min at 5,000 rpm in a 4℃ microcentrifuge to pellet the nuclei. Add the working stock of Enzymatic Shearing Cocktail (200U/ml) and incubate at 37℃ for 15 minutes and add ice-cold 0.5M EDTA to stop the reaction. Centrifuge for 10 min at 15,000 rpm in a 4℃ microcentrifuge. The supernatants were immunoprecipitated with H3K4me3 (1:50, #9751; Cell Signaling Technology) antibody with rotation after taking out part of as input DNA, which was followed by incubation with protein G magnetic beads for 4 h at 4\u0026deg;C. The anti-IgG (1:1000, #3900; Cell Signaling Technology) was used as negative control. Protein G magnetic beads antibody/chromatin complexes were collected, washed, and eluted. Then, cross-links were reversed, and DNA was purified and analyzed via real-time PCR. The ChIP qPCR primer sequences for human IL-17A were as follows: 5\u0026rsquo;-CTAGTTCTCATCACTCTCTACTCCC-3\u0026rsquo; (forward) and 5\u0026rsquo;-ATTGAATTTAACAATTCTTTTGTTG-3\u0026rsquo; (reverse), -738bp to -512 bp from transcription start site [Liu et al.,2015], and β-\u003cem\u003eactin\u003c/em\u003e was used as an internal reference [Wu et al.,2019]. The levels of bound DNA sequences were then calculated using the percent input method (2\u003csup\u003e\u0026minus; [Ct (ChIP)‑ Ct (Input)]\u003c/sup\u003e \u0026times; 100) by calculating the qPCR signal relative to the input sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Metabolic profile analysis based on UPLC-Orbitrap-MS\u003c/h2\u003e \u003cp\u003eThe analyses of metabolomics profile for urine were performed on a UPLC Ultimate 3000 system (Dionex, Germering, Germany), coupled to an Orbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) equipped with a heated electrospray source (HESI) at the resolution of 7\u0026times;10\u003csup\u003e5\u003c/sup\u003e in both positive and negative mode. The detail was described in our previous work [Hu et al.,2021].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Quantitative real-time polymerase chain reaction (qPCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from frozen tissue using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the instructions of the manufacturer. Genes were measured by qRT-PCR according to our previous work [Xu et al.,2021]. The primers were \u003cem\u003eAhR\u003c/em\u003e: 5'-TTGGTTGTGATGCCAAAGGGC-3'for forward; 5'-CATGCGGATGTGGGATTCTGC-3' for reverse [Yang et al.,2020]; \u003cem\u003eIl-17a\u003c/em\u003e: 5'-CAGACTACCTCAACCGTTCCAC \u0026minus;\u0026thinsp;3' for forward; 5'-TCCAGCTTTCCCTCCGCATTGA-3' for reverse (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.origene.com\" target=\"_blank\"\u003ewww.origene.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.origene.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); \u003cem\u003eCyp1a1\u003c/em\u003e: 5'-GGGTTTGACACAGTCACAACT-3'for forward; 5'-GGGACGAAGGATGAATGCCG-3' for reverse[Yang et al.,2020]. \u003cem\u003eGapdh\u003c/em\u003e was used as an internal control: 5\u0026lsquo;-AAGAAGGTGGTGAAGCAGG-3\u0026rsquo; for forward, and 5\u0026lsquo;-GAAGGTGGAAGAGTGGGAGT-3\u0026rsquo; for reverse.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Statistical analyses\u003c/h2\u003e \u003cp\u003eThe differences between asthmatic children and the control were analyzed using student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test by GraphPad Prism 8 software (GraphPad Software, La Jolla, CA). Differences were considered statistically significant at \u003cem\u003eP\u003c/em\u003e༜0.05. The association between the PAHs concentrations and asthma was determined with logistic regression. Age and gender were considered as covariates in the regression model. Pearson correlation was used to assess the associations between PAHs and one carbon metabolites and tryptophan metabolites. A redundancy analysis (RDA) was performed to determine the multivariate relationship between PAHs and sample distribution and one carbon metabolites and by R package. In addition, mediation analysis for the association between PAHs and asthma mediated by intermediates was implemented considering one carbon metabolites and tryptophan metabolites as mediators with reference to our previous work [Hu et al.,2021].\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results And Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1 The characteristics of the subject in this study\u003c/h2\u003e \u003cp\u003eIn this study, the characteristics of all subjects were shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The ratio of males to females was 31:19 in the asthmatic group, and 33:17 in the control. The average age was 3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 years in the asthmatic group, and 5.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36 years in the control. The blood was collected before medication. \u003cb\u003eFigure. S1\u003c/b\u003e showed the mean of total IgE concentrations was 292.74\u0026thinsp;\u0026plusmn;\u0026thinsp;168.37 IU/mL (ranged from 31.92-716.67 IU/mL) in the asthmatic group, and 147.37\u0026thinsp;\u0026plusmn;\u0026thinsp;79.71 IU/mL (ranged from 13.33-308.75 IU/mL) in the control, respectively. The asthmatic group presented significantly higher total serum IgE concentrations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of all subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (Control/Asthma)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (31:33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (19:17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16(2:14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54(25:29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30(23:7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIgE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (IU/mL)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147.37\u0026thinsp;\u0026plusmn;\u0026thinsp;79.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e292.74\u0026thinsp;\u0026plusmn;\u0026thinsp;168.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Serum PAH concentrations were associated with childhood asthma\u003c/h2\u003e \u003cp\u003eAs shown in \u003cb\u003eFigure.1\u003c/b\u003e, the distribution of twelve types of PAHs was similar in the asthmatic group and the control. The concentration of PAHs listed in the order was Pyr\u0026thinsp;\u0026gt;\u0026thinsp;Phe\u0026thinsp;\u0026gt;\u0026thinsp;Flu\u0026thinsp;\u0026gt;\u0026thinsp;Fla\u0026thinsp;\u0026gt;\u0026thinsp;Chr\u0026thinsp;\u0026gt;\u0026thinsp;BaA. Serum Pyr showed the highest proportion and the highest detection frequency. There are some reports about the concentrations of PAHs in children serum. For example, Singh \u003cem\u003eet al.\u003c/em\u003e reported values ranged from 1.05 ng/mL to 160.6 ng/mL (25th-75th percentile) in the distributions of nine types of PAH concentrations in the blood of children in Lucknow, India [Singh et al.,2008]. Our data showed the concentration of the total PAHs ranged from 8.15 ng/mL to 209.99 ng/mL, and 17.74 ng/mL to 44.49 ng/mL (25th-75th percentile) in the serum of children in Nanjing, China. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e listed the compounds sought in this analysis, detection rate, and the summary statistics for all subjects. After adjusted for sex and age, a logistic regression model showed that Fla, Pyr, BaA, and INP/DBA were associated with childhood asthma shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In our previous work, we demonstrated that urinary1-hydroxypyrene (1-OHPyr) concentrations were associated with childhood asthma [Hu et al.,2021]. Internal exposure to PAHs has been assessed commonly by urinary 1-OHPyr as a general biomarker [Hansen et al.,2008]. However, environmental exposure to PAHs may be understatedly assessed only based on exposure biomarkers such as urinary OH-PAHs metabolite concentrations [Yang et al.,2021]. High molecular weight PAHs composed of four or more rings (e.g., fluoranthene, pyrene, chrysene, benzo[a]pyrene, dibenz[a,h]anthracene) are dominant components of particle matter and easily taken up by inhalation [Huang et al.,2021]. In developing countries children are exposed to multiple sources of PAHs including heating and cooking from biomass fuel, and industrial coal-burning and traffic emission, and in these situations the inhalation of particle-bound PAHs is at least as important a route of exposure as dietary exposure [Yang et al.,2021;WHO,2010]. And there is mounting evidence of unmetabolized PAHs as a biomarker to reflect body burden [WHO,2010; Sexton et al.,2011], which can directly represent the actual exposure concentrations of the environment. Based on toxicokinetics, PAHs may result in relatively more toxicity through inhalation than after dietary exposure since inhalation avoid the hepatic first-pass effect [Craemer et al.,2016].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSerum PAH concentrations of subjects in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAHs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDetection rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLimit of Detection(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003cp\u003e(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003e(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian (ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND-9.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.434\u0026thinsp;\u0026plusmn;\u0026thinsp;1.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.002(0.535, 1.877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND-15.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.988\u0026thinsp;\u0026plusmn;\u0026thinsp;2.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.041(0.802, 1.350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND-5.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.202\u0026thinsp;\u0026plusmn;\u0026thinsp;1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.675 (0.357, 1.276)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND-15.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.468\u0026thinsp;\u0026plusmn;\u0026thinsp;3.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.380 (1.063, 1.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND-188.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e23.921\u0026thinsp;\u0026plusmn;\u0026thinsp;35.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.033 (1.000, 1.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;10.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.725\u0026thinsp;\u0026plusmn;\u0026thinsp;1.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.498(0.237, 1.047)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;11.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.719\u0026thinsp;\u0026plusmn;\u0026thinsp;1.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.266 (1.018, 5.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBbF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;1.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.545\u0026thinsp;\u0026plusmn;\u0026thinsp;0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.941(0.171, 5.157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBkF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;1.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.313\u0026thinsp;\u0026plusmn;\u0026thinsp;0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.891 (0.062, 246.174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;2.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.516\u0026thinsp;\u0026plusmn;\u0026thinsp;0.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.634(0.272, 9.813)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINP/DBA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u0026thinsp;~\u0026thinsp;1.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.260\u0026thinsp;\u0026plusmn;\u0026thinsp;0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.835 (1.432, 753.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eND: not detected; OR: Odds ratio; CI: confidence interval, * \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.3 PAHs changed the expression of one carbon metabolites in asthmatic children\u003c/h2\u003e \u003cp\u003eOne carbon unit from the folate cycle and betaine metabolism is used to form methionine. The methionine intermediate SAM functions as substrates for DNA methylation and histone methylation [Mentch et al.,2016] (\u003cb\u003eFigure.2A\u003c/b\u003e). In our previous work, it was found that 7-methylguanine as PAHs-related intermediate showed a mediation effect on the association between urinary 1-OHPyr concentration and childhood asthma [Hu et al.,2021]. Urinary 1-OHPyr concentration was associated with 7-methylguanine which could reflect global DNA methylation in asthmatic children [Wishnok et al.,1993]. So, we compared the concentrations of one carbon metabolites between two groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cb\u003eFigure.2B\u003c/b\u003e). The asthmatic group displayed a significantly decreasing in SAM abundance and a smaller but corresponding decrease in SAH, which indicated the increasing conversion from SAM to SAH and the elevated capacity of methylation reactions \u003cb\u003e(Figure.2C\u003c/b\u003e). What\u0026rsquo;s more, the methionine concentrations in the asthmatic group were higher than that in the control. Roy \u003cem\u003eet al\u003c/em\u003e reported that methionine restriction can reduce histone H3K4 methylation at the promoter regions of key genes involved in Th17 cell proliferation and cytokine production [Roy et al.,2020]. Therefore, metabolic changes-induced by PAHs has profound effects on epigenetics, especially methylation. Then a redundancy analysis (RDA) was performed to determine the multivariate relationship between the environmental variable-PAHs and sample distribution and one carbon metabolites by R package. RDA-analysis revealed two groups of all subjects, each characterized by a specific set of PAHs-one carbon parameters (groups are indicated on the diagram, \u003cb\u003eFigure.2D\u003c/b\u003e). The effect of PAHs on one carbon metabolites in different groups in the RDA diagram is mainly characterized by the length of PAH variables and by the cosine value of the angle. The metabolites-PAHs correlation was 0.64 for RDA axis 1 and 0.23 for axis 2. Fla had a great effect on one carbon metabolites between two groups. There was a significant negative correlation between Fla and one carbon metabolites \u003cb\u003e(Figure.2E)\u003c/b\u003e. We used differential one carbon metabolites to perform mediation analysis to assess the association between the PAHs concentration and asthma mediated by metabolites. The directed acyclic graph (DAG) showed significant mediation effects between the Fla concentration and asthma by SAH, SAM and Ser \u003cb\u003e(Figure.2F, Table S6)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe serum concentrations of one carbon metabolites of subjects in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAHs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimit of Detection(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u0026thinsp;~\u0026thinsp;Max value(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-MT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-95.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e22.648\u0026thinsp;\u0026plusmn;\u0026thinsp;20.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.05117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-25.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e10.245\u0026thinsp;\u0026plusmn;\u0026thinsp;4.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.179\u0026thinsp;\u0026plusmn;\u0026thinsp;0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetaine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.563-117.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e34.3651\u0026thinsp;\u0026plusmn;\u0026thinsp;17.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1065.416-6634.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3077.496\u0026thinsp;\u0026plusmn;\u0026thinsp;1212.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2848.938\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHcy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.718-569.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e114.0546\u0026thinsp;\u0026plusmn;\u0026thinsp;97.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.764-334.8852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e114.6048\u0026thinsp;\u0026plusmn;\u0026thinsp;83.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.512-214.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e85.992\u0026thinsp;\u0026plusmn;\u0026thinsp;35.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225.477-5208.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2128.707\u0026thinsp;\u0026plusmn;\u0026thinsp;1108.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1985.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYSTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.322-213.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e59.242\u0026thinsp;\u0026plusmn;\u0026thinsp;52.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eND: not detected\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.4 PAHs changed epigenetic pattern in asthmatic children\u003c/h2\u003e \u003cp\u003eTo study epigenetic alterations induced by PAHs, firstly, we examined the methylation levels of long interspersed nuclear elements-1 (\u003cem\u003eLINE-1\u003c/em\u003e) promoter, which comprise approximately 17% of the human genome and is used to assess global DNA methylation[Lisanti et al.,2013]. The distributions of \u003cem\u003eLINE-1\u003c/em\u003e DNA methylation were presented in \u003cb\u003eFig.\u0026nbsp;3A.\u003c/b\u003e The geometric mean for \u003cem\u003eLINE-1\u003c/em\u003e methylation were 17.26% in the control, and 34.19% in asthmatic group, respectively, which indicated elevated global DNA methylation in asthmatic group. Fla had a positive effect on \u003cem\u003eLINE-1\u003c/em\u003e methylation (β\u0026thinsp;=\u0026thinsp;0.395, P\u0026thinsp;=\u0026thinsp;0.000). There were no any significant associations of other PAHs with global DNA methylation. Because Fla was associated with childhood asthma and \u003cem\u003eLINE-1\u003c/em\u003e methylation, we conducted the mediation analysis to assess global DNA methylation could be mediator of the association between PAHs and asthma. We did find significant mediation effect between serum Fla and asthma by \u003cem\u003eLINE-1\u003c/em\u003e methylation \u003cb\u003e(Figure.3B)\u003c/b\u003e. In contrast to our work, current evidence showed that prenatal urinary 2-OHNa and 1-hydroxyphenanthrene were associated with lower \u003cem\u003eAlu\u003c/em\u003e and \u003cem\u003eLINE-1\u003c/em\u003e methylation [Yang et al.,2018]. On the other hand, studies have shown a positive association between gene-specific hypermethylation and PAHs exposure. For example, CpG Site-specific hypermethylation of \u003cem\u003ep16\u003c/em\u003e\u003csup\u003e\u003cem\u003eINK4α\u003c/em\u003e\u003c/sup\u003e was found in peripheral blood lymphocytes of PAH-exposed workers by BSP sequencing [Yang et al.,2012]. Interestingly, global DNA hypermethylation levels were associated with asthma severity by assessing the percentage of 5-methylcytosine [Chan et al.,2017]. Perhaps these discrepancies in the literature about the correlation between global DNA methylation and PAHs exposure can be attributed to the fact that the resource of PAHs exposure and the representative indices of global DNA methylation were differentially assessed.\u003c/p\u003e \u003cp\u003eIn addition, there is evidence that IL-17A markedly contribute to the immune imbalance in asthma [Wang and Liu,2008]. For example, elevated concentrations of IL-17A have been found in the sputum and in bronchoalveolar lavage fluid of patients with asthma[ Molet et al.,2001]. What\u0026rsquo; more, Milovanovic \u003cem\u003eet al\u003c/em\u003e demonstrated that IL-17A secretion promoted IgE production [Milovanovic et al.,2010]. So, we collected the serum from both groups and performed ELISA to detect the concentration of IL-17A. \u003cb\u003eFigure.3C\u003c/b\u003e showed the mean of IL-17A concentrations of 100.20\u0026thinsp;\u0026plusmn;\u0026thinsp;45.99 pg/mL (ranged from 33.83-195.23 pg/mL) in the asthmatic group, and 40.92\u0026thinsp;\u0026plusmn;\u0026thinsp;22.41 pg/mL (ranged from 4.56\u0026ndash;85.35 pg/mL) in the control, respectively. The results showed that high concentration of IL-17A was detected in asthmatic group when compared with the control. Research has reported some genes that are associated with PAHs-induced methylation and immune dysfunction. For example, Kohli \u003cem\u003eet al.\u003c/em\u003e [Kohli et al.,2012] reported that tobacco smoke (in which PAHs are critical constituents) exposure was associated with hypermethylation of the promoter region for \u003cem\u003eIFN-gamma\u003c/em\u003e in T effector cells and \u003cem\u003eFoxp3\u003c/em\u003e in regulatory T cells. In the present study, because PAHs can increase methylation capacity by interfering one carbon metabolism including SAM-dependent histone modifications, we hypothesized that H3K4 tri-methylation level (a histone modification associated with active transcription in chromatin structure) may be induced by PAHs exposure. To determine whether PAHs could regulate the production of IL-17A through epigenetic changes, ChIP assay was performed using antibodies against tri-methylated Lys4 of H3(\u003cb\u003eFigure.3C\u003c/b\u003e). Interestingly, Fla could upregulate H3K4 tri-methylation level in the \u003cem\u003eIL-17A\u003c/em\u003e promoter region and associated with children asthma (β\u0026thinsp;=\u0026thinsp;0.293, P\u0026thinsp;=\u0026thinsp;0.002) (\u003cb\u003eFigure.3D\u003c/b\u003e). By ChIP-qPCR results we demonstrated that PAHs could promote secretion of IL-17A through changes in histone methylation levels. In a previous study, PAH might affect, through their effects on the aryl hydrocarbon receptor, IL-17 production in asthma [Pl\u0026eacute; C et al.,2015]. Our data suggested that PAHs might contribute to increased IL-17A production through mechanisms involving not only AhR-dependent but also independent pathways, epigenetics. In addition, we report here that one carbon metabolism forms a function link between metabolic and epigenetic reprogramming to regulate gene expression. Epigenetic modification is induced by the environment with one carbon metabolites function as key substrates for DNA methylation and histone methylation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.5 PAHs changed the expression of tryptophan metabolites in asthmatic children\u003c/h2\u003e \u003cp\u003eTryptophan is an essential amino acid in all animal, metabolism of which is involved in the regulation of immunity, neuronal function and intestinal homeostasis [Martin et al.,2020]. Trp metabolism includes three major pathways, i.e. the kynurenine pathway, the serotonin (5-hydroxytryptamine [5-HT]) production pathway and a series of molecules, including AhR ligands by microbiota [Zelante et al.,2013]. In this present study, we detected Trp metabolic profile to find out key metabolites associated with PAHs-related childhood asthma (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In \u003cb\u003eFigure.4A\u003c/b\u003e, the concentrations of Trp, tryptamine, IA, IAA, and Indole were significantly higher in asthmatic group, and that of IAld and IAAld were relatively lower, which is consistent with Licari\u0026rsquo;s study [Licari et al.,2019]. The differential Trp metabolites was mainly enriched in AhR ligands derived from microbiota, such as tryptamine, IA, IAA, IAld and Indole, which indicated the asthmatic children had increased indole-AhR pathway. There was no change in the concentration of the metabolites in kynurenine pathway and 5-HT pathway. Reports have shown that circulating Trp concentrations were increased in germ-free mice [El Aidy et al.,2012]. In this present study, the circulating Trp concentration was also increased. \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e and others can directly utilize Trp. \u003cem\u003eLactobacillus\u003c/em\u003e can metabolize Trp to IAld, which can active AhR anti-inflammatory responses [Zelante et al.,2013]. However, the concentration of IAld in asthmatic children in this study was decreased. What\u0026rsquo;s more, the microbial diversity was decreased in asthmatic children, especially \u003cem\u003eLactobacillus\u003c/em\u003e in our previous work [Hu et al.,2021]. These data suggested he microbiota-AhR axis can influence host metabolism. Although there was some correlation between PAHs and Trp metabolites (\u003cb\u003eFigure.4B\u003c/b\u003e), it was also showed that Trp metabolites has direct effects on IL-17A production or childhood asthma, but no mediation effects between PAHs concentration and asthma by Trp metabolites (\u003cb\u003eTable S7 and S8\u003c/b\u003e). AhR acting a crucial transcription factor is involved in Th17 cells differentiation [Veldhoen et al.,2008]. IL-17A is secreted from Th17 cells. In agreement with the present studies, increased IL-17A concentration was found in serum of asthmatic children in our study. However, there were controversial results that some AhR such as TCDD induced IL-17A generation in mice and inhibited that in humans [Veldhoen et al.,2008;Ramirez et al.,2010], and this discrepancy may be due to the different ligands and the types of AhR-expressed cells. Additional studies are needed to further explore the effects of PAHs on Trp metabolites, AhR, and IL-17A profiles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe serum concentrations of tryptophan metabolites of subjects in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAHs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimit of Detection(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin\u0026thinsp;~\u0026thinsp;Max value(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian(ng/mL)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.55-369.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e143.301\u0026thinsp;\u0026plusmn;\u0026thinsp;44.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e132.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176.768-453.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e234.826\u0026thinsp;\u0026plusmn;\u0026thinsp;55.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e217.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HTP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232.695-1391.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e677.133\u0026thinsp;\u0026plusmn;\u0026thinsp;256.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e639.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.115-464.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e126.754\u0026thinsp;\u0026plusmn;\u0026thinsp;79.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKyn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328.37-1681.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e838.017\u0026thinsp;\u0026plusmn;\u0026thinsp;251.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e792.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9138.89-36006.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e18308.153\u0026thinsp;\u0026plusmn;\u0026thinsp;6081.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17380.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9154.257-36424.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e18414.979\u0026thinsp;\u0026plusmn;\u0026thinsp;6134.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17391.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTryptamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-96.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.223\u0026thinsp;\u0026plusmn;\u0026thinsp;20.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HIAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2-112.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e33.185\u0026thinsp;\u0026plusmn;\u0026thinsp;20.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.996\u0026ndash;16.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.755\u0026thinsp;\u0026plusmn;\u0026thinsp;3.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145.464-9663.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1229.170\u0026thinsp;\u0026plusmn;\u0026thinsp;1178.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1039.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-623.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e209.647\u0026thinsp;\u0026plusmn;\u0026thinsp;155.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAAld\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-150.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.865\u0026thinsp;\u0026plusmn;\u0026thinsp;24.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND-532.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e142.565\u0026thinsp;\u0026plusmn;\u0026thinsp;139.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.558\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eND: not detected\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.6 PAHs induced Il-17A production by altering tryptophan metabolism in mice\u003c/h2\u003e \u003cp\u003eTo validate whether PAHs have the effects on tryptophan metabolism and inducing IL-17A production or not, PAHs mix were exposed on mice. We selected more than four rings PAHs due to more stable and more toxic. The results showed that lung tissue was infiltrated by lymphocytes in PAHs -exposed group (\u003cb\u003eFigure.5\u003c/b\u003e). The concentration of IgE in BALF of PAHs-exposed group was higher than that in the control (\u003cb\u003eFigure.6A)\u003c/b\u003e. Interestingly, after stratified by gender, the concentration of Il-17 in BALF of male PAHs-exposed group was higher than that in the control (\u003cb\u003eFigure. 6B\u003c/b\u003e). In lung tissue, the expression of \u003cem\u003eAhr\u003c/em\u003e was upregulated in PAHs-exposed group. \u003cem\u003eIl-17a\u003c/em\u003e gene was downregulated in PAHs-exposed group. Another AhR target genes \u003cem\u003eCyp1a1\u003c/em\u003e was upregulated in female PAHs-exposed group (\u003cb\u003eFigure. 6C, 6D and 6E\u003c/b\u003e). In gut tissues, the expression of \u003cem\u003eAhr\u003c/em\u003e was upregulated only in female PAHs-exposed group while \u003cem\u003eIl-17a\u003c/em\u003e genes was upregulated in both female and male PAHs-exposed groups. \u003cem\u003eCyp1a1\u003c/em\u003e was only upregulated in male PAHs-exposed group (\u003cb\u003eFigure. 6F, 6G and 6H\u003c/b\u003e). Here we found that the transcription of \u003cem\u003eIl-17a\u003c/em\u003e was inhibited in lung tissue and induced in gut tissue, while the concentration of IL-17 in BALF was increased in male PAHs-exposed group. There were different AhR-induced responses in lung and gut tissue, respectively. We speculated that gut-derived IL-17A can influence inflammation in lung through gut-lung axis. Reports have shown that tetrachlorodibenzo-p-dioxin (TCDD)-active AhR mediated immunosuppressive effects in human [Kerkvliet,2009], while controversial results have shown that endogenous AhR ligand 6-formylindolo[3,2-b] carbazole (FICZ) induced IL-17A production in mice [Quintana et al.,2008]. Other than TCDD, polycyclic aromatic hydrocarbons are rapidly metabolized by AhR-inducible enzymes that may produce a different type of effects on the immune system. What\u0026rsquo;s more, active AhR may induce the expressions of AhR target genes, such as IL-6, which can initiate Th17 cell differentiation and promote IL-17 production [Xu and Cao,2010]. But excessive immune reactions lead to inhibit anti-immune responses in the microenvironment and ultimately result in uncontrolled and promoted immunity response. Th17 cell differentiation may be modulated by AhR through transcriptional changes. Although the mechanisms mediating AhR-Th17 axis still remain controversial in human and mice studies, cytokine milieu may be contributed to induce Th17 cell differentiation [Veldhoen et al.,2008]. Besides of as direct ligands of AhR, PAHs may also influence AhR-IL-17A by disturbing tryptophan metabolism. Metabolic profiling was applied to compare the global metabolites in mice with or without PAHs treatment. The differential metabolites partly shaped the gender difference \u003cb\u003e(Figure. 7A\u003c/b\u003e). It was also found that the differential metabolites were mainly enriched in tryptophan metabolism, such as indoleacetic acid (IAA), indoxyl sulfate, kynurenic acid (Kyn), indolelactic acid, 5-hydroxyIndoleacetic acid(5-HIAA), indole-3-carboxylic acid, and indoleacetaldehyde (IAAld), most of which are AhR-ligands, such as IAA, Kyn and IAAld (\u003cb\u003eFigure. 7B\u003c/b\u003e). IAA and indoxyl sulfate were lower in both PAHs-exposed groups; Kyn and indolelactic acid were higher in male PAHs-exposed group; 5-HIAA, indole-3-carboxylic acid, and IAAld were higher in female PAHs-exposed group. In addition, acetyl-methionine,1-methyladeosine, and 7-methylguanine were higher in PAHs-exposed group. These animal results supported that PAHs altered tryptophan metabolism and disturbed IL-17A production.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eIn this study, we assessed the effects of PAHs exposure on asthmatic children from the perspective of one carbon metabolism and tryptophan metabolism. Our data gave the evidence that PAHs exposure induced DNA methylation and histone methylation by disturbing one carbon metabolism, and altered Try-AhR pathway to disturb IL-17A production, which could help in identifying the underlying mechanisms of PAHs exposure-related asthma. However, there are limitations in the present study. We found gender differences in the effects of PAHs on inflammation in animal study. Due to the small sample size and low proportion of female subjects in asthmatic children, we did not find the effects of gender on PAHs toxicity. In addition, microbiota-mediated immunodulation have been associated with the etiology of asthma and microbiota can also modulate Trp metabolism. Therefore, we should investigate the effects of PAHs-related microbiota on Trp metabolism and childhood asthma in future work.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003epolycyclic aromatic hydrocarbons\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e(PAHs)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003earyl hydrocarbon receptors (AhRs)\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eregulatory T cell\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTreg\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003elong interspersed nucleotide element-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eLINE-1\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eshort interspersed nuclear elements\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eAlu\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS-adenosylmethionine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSAM\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePeripheral blood mononuclear cells\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePBMC\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003egas chromatograph mass spectrometer\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGC-MS\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003efluorene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFlu\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ephenanthrene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhe\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eanthracene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnt\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003efluoranthene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFla\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003epyrene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePyr\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebenzo(a)anthracene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBaA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003echrysene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChr\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebenzo(b)fluoranthene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBbF\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebenzo(k)fluoranthene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBkF\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebenzo(a)pyrene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBaP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindeno(1,2,3-cd)pyrene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edibenzo(a,h)anthracene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDBA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eultra-performance liquid chromatography-Orbitrap-mass spectrometry\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUPLC-Orbitrap-MS\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-methyltetrahydrofolate\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-MT, serine:Ser\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eglycine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGly\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emethionine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMet\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eS-adenosylhomocysteine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSAH\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ehomocysteine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHcy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebetaine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBetaine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edithiothreitol\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDTT\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLimits of detection\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLODs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eL-Tryptophan\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTrp\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eL-kynurenine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyn\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e2-picolinic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003equinolinic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQUI\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindole acrylic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindole-3-propionic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIPA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-Hydroxyindoleacetic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-HIAA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindoleacetaldehyde\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIAAld\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindoleacetic acid\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIAA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-hydroxytryptamine\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-HT\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e5-Hydroxy-L tryptophan\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e5-HTP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIndole-3-aldehyde\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIAld\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebisulfite genomic sequencing PCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBSP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003echromatin immunoprecipitation\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChIP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eredundancy analysis\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRDA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e1-hydroxypyrene\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e1-OHPyr\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOdds ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003econfidence interval\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edirected acyclic graph\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDAG\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eindirect effect\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIE\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003etotal effect\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDE\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical approval\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe Nanjing Medical University Clinical Research Ethics Committee, Nanjing, China, reviewed and approved the protocols of this study.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent to participate\u003c/h2\u003e\n\u003cp\u003eWritten informed consent was obtained from the participants\u0026rsquo; parents for the use of samples in this study.\u003c/p\u003e\n\u003ch2\u003eConsent to publish\u003c/h2\u003e\n\u003cp\u003eIts publication has been approved by all co-authors\u003c/p\u003e\n\u003ch2\u003eAuthor contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization, Lei Li and Qian Wu; Formal analysis, Hao Wu, Yuling Bao, Tongtong Yan, Hui huang, Ping Jiang, and Zhang Zhan; Funding acquisition, Qian Wu; Investigation, Hao Wu, Yuling Bao and Tongtong Yan; Resources, Yuling Bao, Lei Li and Qian Wu; Writing \u0026ndash; original draft, Qian Wu.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82073630 and\u0026nbsp;81728018); Natural Science Foundation of Jiangsu Province (BK20161571), Natural Science Foundation of the Higher Education Institution of Jiangsu Province (16KJA330002). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThere are no conflicts to declare.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\n\u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAnderson OS, Sant KE, Dolinoy DC. Nutrition and epigenetics: an interplay of dietary methyl donors, one-carbon metabolism and DNA methylation. J Nutr Biochem. 2012,23(8):853-859.\u003c/li\u003e\n \u003cli\u003eBousquet J, Jeffery PK, Busse WW, Johnson M, Vignola AM. Asthma. From bronchoconstriction to airways inflammation and remodeling. 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Intestinal microbiota-derived short-chain fatty acids regulation of immune cell IL-22 production and gut immunity. Nat Commun. 2020,1(1):4457.\u003c/li\u003e\n \u003cli\u003eYang Z, Guo C, Li Q, Zhong Y, Ma S, Zhou J, Li X, Huang R, Yu Y. Human health risks estimations from polycyclic aromatic hydrocarbons in serum and their hydroxylated metabolites in paired urine samples. Environ Pollut. 2021,290:117975.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZelante T, Iannitti RG, Cunha C, De Luca A, Giovannini G, Pieraccini G, Zecchi R, D\u0026apos;Angelo C, Massi-Benedetti C, Fallarino F, Carvalho A, Puccetti P, Romani L. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity. 2013,39(2):372-85.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZhang H, Han Y, Qiu X, Wang Y, Li W, Liu J, Chen X, Li R, Xu F, Chen W, Yang Q, Fang Y, Fan Y, Wang J, Zhang H, Zhu T. Association of internal exposure to polycyclic aromatic hydrocarbons with inflammation and oxidative stress in prediabetic and healthy individuals. Chemosphere. 2020,253:126748.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"PAHs, asthma, metabolism, inflammation, one carbon metabolite, methylation, tryptophan, IL-17A","lastPublishedDoi":"10.21203/rs.3.rs-1470556/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1470556/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u0026nbsp;Epidemiological studies have showed that PAHs may exert its adverse effects on childhood asthma. However, the underlying molecular\u0026nbsp;mechanism remains to be fully elucidated. This study aimed to investigate this process in view of metabolic pathway, especially one carbon metabolism and tryptophan metabolism.\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFifty asthmatic children and fifty control subjects were recruited in this study.\u003cstrong\u003e \u003c/strong\u003eSerum IgE and IL-17A was detected by ELISA assay. Serum PAHs concentrations were measured by GC-MS. One carbon-related metabolites and tryptophan metabolites were determined by UPLC-Orbitrap-MS. Blood DNA methylation in long interspersed nucleotide element-1 (\u003cem\u003eLINE-1\u003c/em\u003e) was analyzed by bisulfite sequencing PCR. ChIP assays were used to examine H3K4me3 enrichment on \u003cem\u003eIL-17A\u003c/em\u003e gene. Multivariable linear regression was performed to evaluate the associates between PAHs and one carbon metabolite and tryptophan metabolites and childhood asthma. HE staining in lung tissue, IgE and IL-17A in BALF, metabolic profiles in urine, and \u003cem\u003eAhR\u003c/em\u003e, \u003cem\u003eiL-17a\u003c/em\u003e and\u003cem\u003e Cyp1a1\u003c/em\u003e gene expression were determined in PAHs-exposed mice.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe\u0026nbsp;asthmatic group\u0026nbsp;presented significantly\u0026nbsp;higher total serum IgE and IL-17A concentrations.\u003cstrong\u003e \u003c/strong\u003eSerum Fla was associated with childhood asthma (OR=1.380, 95%CI: 1.063-1.792). The asthmatic group displayed an increasing conversion from SAM to SAH and an elevated capacity of methylation reactions. Fla had a great effect on one carbon metabolites, especially SAH, SAM and Ser, which exerted significant mediation effects between the Fla concentration and asthma. What’s more, Fla had a positive effect on \u003cem\u003eLINE-1\u003c/em\u003e DNA methylation (β=0.395, P=0.000) and H3K4 tri-methylation level in the \u003cem\u003eIL-17A\u003c/em\u003e promoter region(β=0.293, P=0.002). We did find significant mediation effect between serum Fla and asthma by \u003cem\u003eLINE-1\u003c/em\u003e DNA methylation and H3K4me3 level in the \u003cem\u003eIL-17A\u003c/em\u003e promoter region. The differential Trp metabolites, such as Trp, tryptamine, IA, IAA, Indole, IAld and IAAld indicated the asthmatic children had increased indole-AhR pathway. Mediation analysis failed to show a mediator effect of Trp metabolites in the association between PAHs and childhood asthma. Animal study confirmed that PAHs exposure increased methylation levels, and altered Trp metabolites -AhR-IL-17A axis, which may be influenced by gender.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003ePAHs disturbed one carbon metabolism to influence the methyl group refill of DNA methylation and histone methylation, and disturbed tryptophan metabolism to regulate Th17 cell differentiation, which may elevate serum IL-17A concentration in asthmatic children.\u003c/p\u003e","manuscriptTitle":"PAHs-induced metabolic changes related to inflammation in childhood asthma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-04-11 13:02:10","doi":"10.21203/rs.3.rs-1470556/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2022-08-03T03:02:58+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2022-06-14T10:49:29+00:00","index":0,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-07T15:18:15+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-04-06T16:46:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Environmental Science and Pollution Research","date":"2022-04-05T21:16:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-03-30T05:26:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2022-03-20T07:11:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7e217ef7-b5fa-472d-8c95-d71f31984884","owner":[],"postedDate":"April 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-09-14T15:34:23+00:00","versionOfRecord":[],"versionCreatedAt":"2022-04-11 13:02:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1470556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1470556","identity":"rs-1470556","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}