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Levels of Blood Organophosphorus Flame Retardants and Association with Changes in Human Sphingolipid Homeostasis Fanrong Zhao, Yi Wan, Haoqi Zhao, Wenxin Hu, Di Mu, Thomas F Webster, and Jianying Hu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b02474 • Publication Date (Web): 19 Jul 2016 Downloaded from http://pubs.acs.org on July 24, 2016
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Levels of Blood Organophosphorus Flame Retardants and Association with Changes in Human Sphingolipid Homeostasis
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Fanrong ZHAO1, Yi WAN1, Haoqi ZHAO1, Wenxin HU1, Di MU1, Thomas F. Webster2, and
5
Jianying HU1*
6 7
1
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Peking University, Beijing 100871, China
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2
10
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences,
Department of Environmental Health, Boston University School of Public Health, Boston,
Massachusetts, USA
11 12 13 14 15 16 17 18 19
Address for Correspondence
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Dr. Jianying HU, College of Urban and Environmental Sciences, Peking University
21
Beijing 100871, China.
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TEL & FAX: 86-10-62765520;
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Email:
[email protected].
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ABSTRACT: While a recent toxicological study has shown that organophosphorus flame
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retardants (OPFRs) may disrupt sphingolipid homeostasis, epidemiologic evidence is
26
currently lacking. In this study, a total of 257 participants were recruited from Shenzhen,
27
China. Eleven OPFRs were for the first time simultaneously determined in the human blood
28
samples by ultraperformance liquid chromatography tandem mass spectrometry. Six OPFRs,
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tributyl phosphate (TNBP), 2-ethylhexyl diphenyl phosphate (EHDPP), tris(2-chloroisopropyl)
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phosphate (TCIPP), tris(2-butoxyethyl) phosphate (TBOEP), triethyl phosphate (TEP), and
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TPHP were detectable in at least 90% of participants, with the median concentrations of 37.8,
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1.22, 0.71, 0.54, 0.49, and 0.43 ng/mL, respectively. Sphingomyelin (SM) levels in the
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highest quartile of EHDPP, TPHP, TNBP, TBOEP, TEP and TCIPP were 45.3% [95%
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confidence interval: 38.1%, 53.0%]; 51.9% (45.5%, 58.6%); 153.6% (145.1%, 162.3%); 20.6%
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(14.5%, 27.0%); 59.0% (52.1%, 66.2%) and 62.8% (55.2%, 70.6%) higher than those in the
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lowest quartile, respectively, after adjusting for covariates. Sphingosine-1-phosphate (S1P)
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levels in the highest quartile of EHDPP, TPHP and TNBP were 36% (-39%, -33%), 16%
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(-19%, -14%) and 36% (-38%, -33%) lower than those in the lowest quartile, respectively. A
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similar pattern emerged when exposures were modeled continuously. We for the first time
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found the associations between OPFRs and changes in human sphingolipid homeostasis.
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Keywords: Sphingomyelin, Sphingosine 1-phosphate; 2-Ethylhexyl diphenyl phosphate;
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Triphenyl phosphate.
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INTRODUCTION
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Organophosphorus flame retardants (OPFRs) are used as plasticizers, anti-foaming
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agents and additives in floor polishes, glue, lubricants, food packaging, and hydraulic fluids.1,
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2
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significantly with the production phase-out and regulation of some brominated flame
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retardants, with annual global production currently reaching approximately 200,000 tons.3
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OPFRs have been detected in various environmental media including sediment, sewage water,
51
drinking water, dust, indoor air and biological samples.1, 4-9 Human may be exposed to OPFRs
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through various exposure pathways including drinking water, food, indoor air, and indoor
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dust.1,
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neurotoxicity, and hemolytic, reproductive and cardiac effects, have been observed in animals
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exposed
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tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) in house dust has been associated with
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hormone levels and semen quality in men.15
The usage of OPFRs as alternative and replacement flame retardants has increased
2, 10
to
Adverse health issues, including skin irritation, carcinogenicity, dermatitis,
OPFRs,2,
11-15
and
exposure
to
triphenyl
phosphate
(TPHP)
and
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The cardiotoxicity of OPFRs is of concern. Increased left ventricular wall thickening,
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which is suggestive of poor cardiovascular performance, has been observed in male rats
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exposed to Firemaster 550 (FM 550) containing TPHP as a major chemical.14 The impacts of
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some OPFRs on cardiac looping and function have also been observed in zebrafish during
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embryogenesis.16 In cardiovascular functions, sphingolipid homeostasis is of vital importance,
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since sphingolipids and biosynthetic intermediates, including sphingomyelin (SM), ceramide
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(Cer), sphingosine (Sph), and sphingosine-1-phosphate (S1P), play essential roles as both
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structural components of cell membranes and signaling molecules that regulate cardiac 3
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development and barrier function of the vasculature.17 Sphigolipid levels are tightly controlled
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by metabolic interplay of the de novo and recycling pathways (Figure S1). Especially, the
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recycling metabolic pathway of sphingolipids including SM, Cer, Sph, and S1P, is the
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dominant pathway to regulate the homeostasis of sphingolipid in most tissues,18, 19 and any
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imbalance can cause stress to the cell and lead to cardiovascular disease.19 Increasing animal
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and epidemiological evidences have shown that elevated SM plasma level is associated with
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atherosclerosis, and sphingolipid homeostasis disorders are implicated in the pathogenesis of
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atherosclerosis19-21 A recent study assessed sphingolipid homeostasis in mice exposed to
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TPHP, in which sphingolipid homeostasis was disrupted as characterized by significant
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increases in the levels of SM and decreases in its metabolite, Cer, and precursor,
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sphinganine.22 However, to our best knowledge, there are no studies on the association of
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OPFRs with the disruption of sphingolipid homeostasis in human.
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While various OPFRs have been detected in milk, adipose tissue and seminal fluid and
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their metabolites have been detected in human urine,1, 9, 23-26 only one paper made an attempt
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to determine 9 OPFRs in human plasma and only TPHP was detected when the authors
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developed a gas chromatography-nitrogen phosphorous detector (GC-NPD) method.9 In this
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paper, 14 OPFRs were analyzed in 257 human blood samples using a sensitive
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ultraperformance liquid chromatography tandem mass spectrometry (UPLC-ESI-MS/MS)
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method. The associations between OPFR exposure levels and changes in sphingolipid levels
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(SM, Cer, Sph, and S1P) were assessed to explore the potential impacts of OPFRs on human
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sphingolipid homeostasis.
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MATERIALS AND METHODS
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Study Population and Blood Collection. A total of 327 residents between 20 and 50 years of
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age were recruited from the general population in Shenzhen, China, in November 2012. The
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study
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(IRB00001052-12058). Participants came to a mobile center for a physical examination and
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to provide blood and urine samples. All participants signed informed consent when enrolled.
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Volunteer participants were asked to fill out interview questionnaires by trained interviewers.
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All subjects were asked to fast for 10 h overnight before collection of the fasting blood
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sample. Blood samples were collected into heparinized brown glass bottles (CNW
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Technologies GmbH, Germany) and stored at -80°C prior to extraction.
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was
approved
by
the
Human
Ethics
Committee
of
Peking
University
We collected data on potential confounding variables through questionnaires. Our models
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included a number of covariates that are important predictors of cardiovascular disease (CVD):
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personal characteristics [age, gender and body mass index (BMI: calculated as weight in
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kilograms divided by height in meters squared)], socioeconomic status (SES: Household
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income was mainly considered) and life-style habits (dietary structure, alcohol intake and
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tobacco use). Of the 327 participants, we finally got 296 blood samples with matching
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questionnaires (Figure S2).
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Materials. Purities of all analytical standards used in this study were ≥95%. The
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standards of tris(2-chloroethyl) phosphate (TCEP), tripropyl phosphate (TPrP), triisopropyl
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phosphate (TiPP), tris(2-chloroisopropyl)phosphate (TCIPP), tributyl phosphate (TNBP), and
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tricresyl phosphate (TMPP) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The
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triethyl phosphate (TEP), tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), tris(2-butoxyethyl) 5
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phosphate (TBOEP), 2-ethylhexyl diphenyl phosphate (EHDPP), and tris(2-ethylhexyl)
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phosphate (TEHP) were purchased from TCI Corp. (Tokyo, Japan). Tris(2,3-dibromopropyl)
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phosphate (TDBPP) was supplied by AccuStandard Inc. (New Haven, CT, USA). Bisphenol A
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bis(diphenyl phosphate) (BPA-BDPP) was purchased from Toronto Research Chemicals Inc.
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(Toronto, Ontario, Canada). The SM, Cer, Sph and S1P were purchased from Avanti Polar
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Lipids (Alabastar, AL, USA). The stable isotope labeled standards, including triethyl-d15
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phosphate (TEP-d15), tri-n-propyl-d21 phosphate (TPrP-d21) and triphenyl-d15 phosphate
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(TPHP-d15), were supplied by C/D/N Isotopes Inc. (Pointe-Claire, Quebec, Canada).
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Tri-n-butyl-d27 phosphate (TNBP-d27) was purchased from Cambridge Isotope Laboratories
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Inc.
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tris(1,3-dichloro-2-propyl)-d15 phosphate (TDCIPP-d15) were obtained from Toronto Research
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Chemicals Inc. (Toronto, Ontario, Canada). Tri-p-cresyl-d21 phosphate (TMPP-d21) and
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tris(2-ethylhexyl)-d51 phosphate (TEHP-d51) were supplied by Hayashi Pure Chemical Ind.,
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Ltd. (Osaka, Japan). Internal standards SM-d31, Cer-d31, Sph-d7 and S1P-d7 were purchased
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from Avanti Polar Lipids (Alabastar, AL, USA). Solvents, including n-hexane, ethyl acetate
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and methanol (MeOH), were of pesticide residue grade and obtained from Fisher Chemicals
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(New Jersey, USA). Acetone and dichloromethane (pesticide residue grade) were purchased
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from Mallinckrodt Baker Inc. (Phillipsburg, NJ, USA). Formic acid (HPLC grade) was from
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Dikma Technologies Inc. (California, USA). Sep-Pak® Silica (3 cm3, 200 mg) and Sep-Pak®
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C18 (3 cm3, 200 mg) solid phase extraction (SPE) cartridges were purchased from Waters
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(Milford, MA, USA). Lithium-heparin blood collection tubes were from Corning
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Incorporated (Tewksbury, MA, USA). Ultrapure water was prepared using a Milli-Q
(Tewksbury,
MA,
USA).
Tris(2-chloroethyl)-d12
phosphate
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Synthesis water purification system (Millipore, Bedford, MA, USA). A full list of the 14
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target compounds, along with their full chemical names and structures, can be found in Figure
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S3.
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OPFRs analysis. Blood samples were thawed on ice, and prepared immediately for
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analysis. Each whole blood sample (0.4 mL) was transferred into an 8-mL glass centrifuge
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tube, and 20 µL of internal standard solution (10 ng/mL for each surrogate) was added. Ethyl
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acetate (2 ml) was added to the sample, which was shaken for 20 min on an orbital shaker and
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centrifuged at 4000 rpm for 10 min, with the ethyl acetate layer then transferred to a clean
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glass bottle. Extraction from the residue was repeated twice and the organic layers were
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combined, concentrated to near dryness under a gentle stream of nitrogen and redissolved in
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500 µL of n-hexane. The concentrated extract was loaded on a silica cartridge preconditioned
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with 6 mL of hexane/acetone (1:1, v/v), 3 mL of hexane/dichloromethane (7:3, v/v) and 3 mL
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of hexane. After the cartridge was rinsed with 3 mL of hexane and 3 mL of
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hexane/dichloromethane (7:3, v/v), the target analytes was eluted by 3 mL of
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n-hexane/acetone (1:1, v/v). The extracts were then dried and redissolved in 2 mL of methanol
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to pass through a C18-SPE cartridge preconditioned by 6 mL of methanol. The filtrate was
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collected and evaporated to dryness under a gentle stream of nitrogen and reconstituted with
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100 µL of methanol for UPLC-MS/MS analysis.
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Analysis of OPFRs was performed using a Waters Acquity UPLCTM system (Waters,
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Milford, MA, USA). All OPFRs were separated using a Waters Acquity UPLC BEH C8
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column (2.1 mm × 100 mm × 1.8 µm) preceded by a Waters Acquity UPLC BEH C18 guard
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column (2.1 mm × 50 mm × 1.7 µm). The column was maintained at 40°C, with a flow rate of 7
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0.2 mL/min and injection volume of 5 µL. Methanol (A) and ultrapure water containing 0.1%
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(v/v) formic acid (B) were used as the mobile phases. Detailed information on the UPLC
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gradient conditions is shown in the Supporting Information.
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Mass spectrometry was performed using a Waters Micromass Quattro Premier XE triple
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quadruple instrument detector equipped with an electrospray ionization source (Micromass,
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Manchester, UK) in positive ion mode. The optimized parameters were: source temperature,
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110°C; desolvation temperature, 350°C; capillary voltage, 3.50 kV; desolvation gas flow, 800
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L/h; cone gas flow, 50 L/h; and multiplier, 650 V. Finally, MS/MS data acquisition was
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performed in multiple-reaction monitoring (MRM) mode, and time-segmented scanning in
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four functions was used based on the chromatographic separation of target compounds to
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maximize detection sensitivity. The MS/MS parameters for the analytes, including their
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precursors and product ions, cone voltage and collision energy, are summarized in Table S1.
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All analytical procedures were checked for accuracy, precision, reproducibility, linearity,
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blank contamination, matrix spikes, method limits of detection (LODs) and limits of
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quantification (LOQs). Matrix-spiked recoveries of individual OPFRs through the analytical
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procedure were estimated by spiking the target analytes at 5, 50 and 100 ng/mL for TNBP, 1,
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10 and 20 ng/mL for EHDPP, TCEP and TCIPP, 0.25, 1 and 10 ng/mL for TEP, and 0.1, 1 and
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10 ng/mL for the others into sample matrices (n=6). The low concentrations of spiked
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analytes were similar to those in samples. The method recoveries of all target analytes were
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calculated by subtracting background concentrations in nonspiked samples from spiked
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samples, and the recoveries ranged from 74% to 98% (with a RSD of 3−15%), 73% to 101%
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(RSD: 2−7%) and 73% to 99% (RSD: 2−11%) for the low, medium and high concentrations, 8
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respectively. Relative standard deviation (RSD) was used to evaluate precision. The inter-day
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precisions were calculated based on the means of six spiked samples at three different levels
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during five days and the inter-day precisions of all substances were within 15%. To prevent
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possible specimen contamination, only pretreated glassware (500°C, 6 h) were used
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throughout the study, and aluminized paper was used in all plastic seals to minimize possible
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contamination of the samples during sampling, storage, transport and extraction. The SPE
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cartridges, silica and C18 were pre-rinsed with n-hexane/acetone (1:1, v/v) and MeOH prior
183
to use, respectively, to minimize the contamination of the SPE procedure. For each batch of
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20 samples analyzed, 2 procedural blanks were processed. Procedural blanks were prepared
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by substitution of 0.4 mL of Milli-Q water for blood, followed by passage through the entire
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analytical procedure. TEP, TCEP, TCIPP, TPHP, TDCIPP, TNBP, TMPP, TBOEP, EHDPP,
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BPA-BDPP, and TEHP were detected in the procedural blanks at the concentrations of
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0.076±0.010, 0.106±0.031, 0.53±0.062, 0.084±0.007, 0.052±0.007, 0.64±0.17, 0.082±0.006,
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0.012±0.005, 0.024±0.004, 0.018±0.002 and 0.016±0.002 ng/mL, respectively.
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(n = 6) were performed by transferring 8 mL of Milli-Q water (with the same vacuum tubes
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used for collecting blood samples) into sampling containers, storing and processing them as
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samples. The concentrations of target compounds in field blanks were almost equal to those in
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procedural blanks. Calibration curves of standards of target analytes were calculated with a
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concentration series of 0.01, 0.05, 0.1, 0.5, 1, 5, 10, 50 and 100 ng/mL, except for TNBP and
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TCEP (0.1, 0.5, 1, 5, 10, 50, 100, 500 and 1000 ng/mL). All calibration curves provided
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adequate linearity (r2>0.995), and the signal-to-noise ratios for the lowest concentration on
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calibration curves of OPFRs were 13−98. Concentrations of TCEP and TNBP in two samples 9
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were reanalyzed after diluting the extracts by 4-10 times due to the extremely high
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concentrations.
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Identification of the target analytes was accomplished by comparing the retention time
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(within 2%) and ratio (within 20%) of the two selected precursor ion-produced ion transitions
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with those of the standards. Quantification was accomplished using the MRM transitions. To
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automatically correct for the losses of analytes during extraction or sample preparation and to
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compensate for variations in instrumental response from injection to injection, quantification
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of the analytes was achieved using an internal standard method with calibration against
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standard solutions. TEP-d15 was used as the surrogate standard for TEP; TCEP-d12 for TCEP
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and TCIPP; TDCIPP-d15 for TDCIPP and TDBPP; TPrP-d21 for TiPP and TPrP; TPHP-d15 for
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TPHP and EHDPP; TNBP-d27 for TNBP; TMPP-d21 for TMPP; and TEHP-d51 for TBOEP,
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BPA-BDPP and TEHP. For chemicals with detectable blank contamination, the LODs and
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LOQs were calculated as three and ten times the standard deviations of procedural blanks,
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respectively, and final concentrations were calculated by the initial concentrations subtracting
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the blank values. For TiPP, TPrP and TDBPP, which were not detected in the blanks, LODs
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and LOQs were calculated based on signal-to-noise ratios of 3 and 10 in matrix-spiked
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samples, respectively. The LODs and LOQs were 0.004–0.52 and 0.02–1.73 ng/mL,
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respectively (Table S2), which are significantly lower than the LODs of OPFRs in human
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plasma (0.2–1.8 ng/mL) in a previous paper,27 showing high sensitivity using developed
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method.
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Sphingolipids Analysis. Sphingolipids were analyzed by UPLC-MS/MS using the
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method previously reported with minor modifications.16,17 Briefly, after loading blood 10
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samples (100 µL for each test) into a 1.5 ml centrifuge tube, MeOH (880 µL) and 20 µl
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internal standard solution (2000 ng/mL for each) were added to the same tube, which was then
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shaken vigorously for 1 min. The concentrated extract (1 mL) was stored at -20°C for 24 h,
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and most of the precipitated or suspended lipids were easily removed by filtration. After
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centrifugation at 12,000 rpm for 15 min, the supernatant was collected and analysis of
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shingolipid was performed by a Waters Acquity UPLCTM system. A Waters Acquity UPLC
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BEH phenyl column (2.1 mm × 100 mm × 1.8 µm) was used for chromatographic separation.
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Methanol (A) and ultrapure water containing 0.5% formic acid (B) were used as the mobile
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phases. The gradient started at 10% A and then increased linearly to 60% in 6 min, 100% at 6
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min and kept for 2 min, followed by a decrease to the initial conditions of 10% A and held for
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2 min to allow for equilibration. The column was maintained at 40°C, with a flow rate of 0.3
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mL/min and injection volume of 5 µL. Quantification of sphingolipids was accomplished
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using the MRM transitions. The optimized MS/MS parameters for the analyses, including
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precursor and product ions, cone voltage and collision energy, are shown in Table S3.
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Mean recoveries of SM-d31, Cer-d3, Sph-d7 and S1P-d7 were 88% ± 9%, 91% ± 8%, 106%
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± 4% and 103% ± 6%, respectively, by spiking internal standards into blood samples at low,
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median and high levels (100, 500, and 1000 ng/mL for SM-d31; 1000, 5000 and 10000 ng/mL
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for Cer-d31; 200, 1000 and 2000 ng/mL for Sph-d7 and 2000, 10000 and 20000 ng/mL for
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S1P-d7) (n = 6 for each level). The LOQs for internal standards of SM, Cer, Sph, and S1P in
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matrix-spiked samples were estimated to be 7.3, 40, 12 and 25 ng/mL, respectively based on
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the peak-to-peak noise of the baseline and on a minimum signal-to-noise value of 10,
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respectively. Calibration curves of standards of target analytes were calculated with a 11
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concentration series of 50, 100, 500, 1000, 2000, 5000, 10000, and 50000 ng/mL. All
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calibration curves showed strong linearity (correlation coefficients >0.99) with good precision
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(RSD ≤ 5%).
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Statistical Analysis. Basic descriptive statistics were derived for population
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characteristics, blood sphingolipid levels and blood OPFR levels. Whole blood samples with
247
non-detectable OPFR concentrations were assigned a value as the LOQ divided by the square
248
root of 2. Spearman correlation coefficients were calculated to assess bivariate relationships
249
between OPFR concentrations and sphingolipid levels. Sphingolipid concentrations were
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transformed to the natural log for statistical analyses as they were log-normally distributed.
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For OPFRs detected at over 90%, we used multivariate linear regression to assess associations
252
between OPFR concentrations and sphingolipid levels, while adjusting for all the relevant
253
covariates (age, gender, BMI, SES, dietary structure, alcohol intake and tobacco use). Quartile
254
variables were constructed for individual OPFRs in multivariate linear regression models. We
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presented effect estimates for each quartile compared with the first quartile and their
256
corresponding 95% confidence intervals (CIs). Tests for trends in quartile analyses were
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performed by treating the OPFR category as a linear predictor in the models. To further
258
confirm the associations between sphingolipid and OPFR concentrations, OPFRs were also
259
modeled as continuous predictors.
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All analyses excluded those with a history of cardiovascular events (coronary event or
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stroke) or heart failure. In addition, subjects who reported current use of medications or who
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were missing this variable were also excluded. The details of people in the exclusion group
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were shown in Figure S2. 12
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Data analysis was performed using SPSS, Version 22.0 (IBM, Corp, 2013). Models were
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adjusted for relevant covariates. For all tests, an alpha level of 0.05 was chosen; p-values of
90% of participants; TEHP, TMPP, TCEP, TDCIPP and
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BPA-BDPP were detected in 71.6%, 66.1%, 63.0%, 47.1% and 41.2% of participants,
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respectively (Table 3). Among the 11 detected OPFRs, TNBP was the most abundant with a
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median value of 37.8 ng/mL (