Suspect-Screening Analysis of Environmental Chemicals in Paired Human Cerebrospinal Fluid and Serum Samples

Long Zhang; Pan Yang; Yaqing Shu; Wei Huang; Wenwen Sun; Xiaotu Liu; Da Chen

doi:10.1289/EHP14120

. 2024 Apr 24;132(4):047701. doi: 10.1289/EHP14120

Suspect-Screening Analysis of Environmental Chemicals in Paired Human Cerebrospinal Fluid and Serum Samples

Long Zhang ¹, Pan Yang ^2,³, Yaqing Shu ⁴, Wei Huang ¹, Wenwen Sun ⁵, Xiaotu Liu ¹, Da Chen ^1,^✉

PMCID: PMC11041624 PMID: 38656168

Introduction

Studies have reported that numerous environmental contaminants may cross the blood–brain barrier into the central nervous system (CNS),¹ some of which may adversely affect neural development and fucntions.² Human cerebrospinal fluid (CSF) is an integral CNS component emerging in parallel with the developing CNS. Detection of exogenous chemicals in CSF raises concern for potential neurological effects.³ Despite reports of select environmental chemicals in CSF, none, to our knowledge, has investigated CSF exposure to a large array of environmental chemicals, particularly those with potential neurotoxic effects. Therefore, the present study aimed to develop a suspect screening-based strategy to identify environmental chemicals with potential neurotoxic effects in human CSF.

Methods

We recruited 180 outpatients ( $lowercase italic n equals 95$ female) diagnosed with mental illness ( $lowercase italic n equals 43$ ), lumbar disc herniation ( $lowercase italic n equals 48$ ), spinal stenosis ( $lowercase italic n equals 37$ ), or viral meningitis ( $lowercase italic n equals 52$ ) from the Third Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) in 2022–2023. Participants were $39 \pm 19$ years of age and all participants completed an informed consent form. CSF and serum samples were collected the same day by doctors or nurses. Field blanks were prepared with high-performance liquid chromatography (HPLC)–grade water using the same procedures. The CSF and serum samples were pretreated following the method described by Huang et al., with minor modifications.⁴ Briefly, $0.2 milliliter$ of serum/CSF was spiked with 21 internal standards ( $5 nanograms$ each) and extracted with a mixture of ethyl acetate and hexane ( $3 milliliters$ ; 3:2, vol/vol, 0.6% formic acid) in three cycles.⁴ The supernatants were collected after each cycle and combined, concentrated to $0.5 milliliter$ , frozen overnight, and centrifuged to collect the supernatant for analysis. It is noted that the modified methodology has not previously been reported to test CSF, to our knowledge. A single pooled extract was prepared by combining $5 microliters$ from each of the 180 CSF or serum extracts. The study was approved by the Human Studies Committee of Sun Yat-sen University.

A suspect screening approach was established to detect environmental chemicals in human CSF and serum. First, a suspect list was developed by exploratory searches in the US Environmental Protection Agency’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/) and scientific literature for chemicals with potential neurotoxic effects. Second, the CSF/serum pools were analyzed using ultra-HPLC (UHPLC) coupled to an Orbitrap Exploris 240 mass spectrometer (MS; Thermo Fisher Scientific). The suspect list was imported into the Mass List of Compound Discoverer 3.2. After identifying potential candidates with precursors mass matched with the suspect list ( $Δ mass$ $less than 5 parts per million$ ), their MS/MS spectra were compared with the spectra in the Mass Bank database or predicted by MetFrag. Further positive confirmation constituted a final list of 28 substances for quantitative analysis. Third, a quantitative method was established based on using an LC-30A UHPLC coupled to a Triple Quad 7500 MS (SCIEX).⁴ Quality assurance/control (QA/QC) tests revealed that the analyte recoveries from spiking tests ranged from 72% to 128%, matrix effects 74% to 119%, interbatch coefficients of variation $less than 20 percent$ (50 samples per batch), and absence of background contamination in field and procedural blanks (1 blank processed with 10 samples) for target analytes, except for tributyl phosphate (TBP), triphenyl phosphate (TPHP), tris(2-chloroisopropyl) phosphate (TCIPP), methyl paraben (MeP), mono-(iso)butyl phthalate [M(i)BP], and 2,6-di-tert-butyl-4-hydroxytoluene (BHT). Detailed information on quantitative and qualitative analysis and QA/QC procedures are available on GitHub (https://github.com/ZL1695/EHP-SI). For analytes with detection frequency (DF) $greater than or equal to 60 percent$ , measurements below the limit of detection (LOD) were replaced with the LOD divided by the square root of 2 for statistical analysis. The LOD of a chemical without blank contamination was defined as the analyte response three times the standard deviation (SD) of the noise of a standard solution. For chemicals with blank contamination, the LOD was defined as the average concentration in blanks plus three times the SD of blank contamination. Relationships between serum and CSF concentrations were determined using Spearman correlation analysis (SPSS Statistics 26; IBM); we further assessed correlation between physiochemical properties [molecular weight and volume, logarithmic octanol–water partition coefficient (log $K_{ow}$ ), acid dissociation constant ( ${pK}_{a}$ ), and biodegradation half-life] and the CSF/serum ratio ( $R_{CSF / serum}$ ) to explore how these properties influence the CSF levels of target compounds. Only chemicals with detectable values in $greater than 40$ pairs of CSF and serum samples were included in the analysis. The significance level was set as $lowercase alpha equals 0.05$ (two-tailed).

Results and Discussion

The 28 environmental chemicals included exhibited a range of median concentrations from $less than limit of detection to 10.5 nanograms per milliliter$ in serum and $less than limit of detection to 1.2 nanograms per milliliter$ in CSF (Table 1). They belong to the groups of per- and polyfluoroalkyl substances (PFAS; $lowercase italic n equals 13$ ), organophosphate esters ( $lowercase italic n equals 3$ ), personal care products ( $lowercase italic n equals 4$ ), photoinitiators ( $lowercase italic n equals 2$ ), bisphenols ( $lowercase italic n equals 3$ ), phthalate ester metabolites ( $lowercase italic n equals 2$ ), and antioxidants ( $lowercase italic n equals 1$ ). Four PFAS compounds were detected in $greater than or equal to 60 percent$ of CSF samples ( $lowercase italic n greater than or equal to 108$ ), including perfluorooctanoic acid (PFOA), perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), and 6:2 chlorinated polyfluoroalkyl ether sulfonate (6:2 Cl-PFESA) at median levels ranging from $0.001 to 0.042 nanogram per milliliter$ . Similar or higher concentrations were measured in CSF for M(i)BP ( $1.2 nanograms per milliliter$ ), TBP ( $0.16 nanogram per milliliter$ ), TPHP ( $0.029 nanogram per milliliter$ ), $2,2 prime-dimethoxyphenyl$ acetophenone (PI-651; $0.022 nanogram per milliliter$ ), triclosan ( $0.085 nanogram per milliliter$ ), and methyl and ethyl parabens (0.015 and $0.072 nanogram per milliliter$ ). To the best of our knowledge, only TBP, TPHP, and PFAS have been reported in human CSF prior to this study.

Table 1.

Summary of environmental chemicals detected in human serum and cerebrospinal fluid (CSF) pairs from 180 adults in Guangzhou, China, 2022–2023.

Chemical	LOD	Serum (ng/mL)				CSF (ng/mL)
Chemical	LOD	DF	Min	Median (IQR)	Max	DF	Min	Median (IQR)	Max
Per- and polyfluoroalkyl substances
PFBA	0.02	68	<LOD	0.17 ( $less than limit of detection to 0.27$ )	0.70	35	<LOD	<LOD ( $less than limit of detection to 0.075$ )	0.32
PFHxA	0.007	57	<LOD	0.14 ( $less than limit of detection to 0.57$ )	6.90	35	<LOD	<LOD ( $less than limit of detection to 0.016$ )	0.18
PFHpA	0.004	97	<LOD	0.25 (0.18–0.37)	1.82	47	<LOD	<LOD ( $less than limit of detection to 0.020$ )	0.80
PFOA	0.003	100	0.74	7.2 (4.7–11.7)	91.3	97	<LOD	0.042 (0.022–0.099)	0.87
PFNA	0.010	100	0.15	1.1 (0.79–2.0)	6.91	22	<LOD	<LOD (<LOD to <LOD)	0.41
PFDA	0.002	100	0.13	0.89 (0.47–1.6)	7.26	31	<LOD	<LOD ( $less than limit of detection to 0.003$ )	0.13
PFUdA	0.002	100	0.053	0.81 (0.41–1.9)	12.5	46	<LOD	<LOD ( $less than limit of detection to 0.005$ )	0.14
PFDoA	0.002	100	0.004	0.092 (0.047–0.18)	0.88	18	<LOD	<LOD (<LOD to <LOD)	0.03
PFBS	0.003	88	<LOD	0.022 (0.011–0.040)	0.36	64	<LOD	0.004 ( $less than limit of detection to 0.009$ )	0.03
PFHxS	0.002	100	0.14	0.92 (0.51–1.6)	9.98	86	<LOD	0.006 (0.003–0.012)	0.19
PFHpS	0.004	98	<LOD	0.10 (0.059–0.20)	0.78	47	<LOD	<LOD ( $less than limit of detection to 0.007$ )	0.04
PFOS	0.02	100	0.731	10.5 (6.6–20.8)	70.2	47	<LOD	<LOD ( $less than limit of detection to 0.043$ )	2.03
6:2 Cl-PFESA	0.001	100	0.075	2.0 (0.99–3.8)	22.2	78	<LOD	0.001 ( $less than limit of detection to 0.002$ )	0.38
Organophosphate esters
TBP	0.02	78	<LOD	0.26 (0.024–0.60)	25.2	83	<LOD	0.16 (0.040–0.31)	6.97
TPHP	0.02	85	<LOD	0.10 (0.037–0.23)	4.04	68	<LOD	0.029 ( $less than limit of detection to 0.11$ )	0.46
TCIPP	0.34	67	<LOD	1.7 ( $less than limit of detection to 5.4$ )	38.6	52	<LOD	0.54 ( $less than limit of detection to 2.6$ )	67.2
Personal care products
MeP	0.01	100	0.062	0.61 (0.34–1.3)	19.4	60	<LOD	0.015 ( $less than limit of detection to 0.072$ )	1.81
EtP	0.02	100	0.030	0.55 (0.32–1.1)	256	71	<LOD	0.072 ( $less than limit of detection to 2.5$ )	6.91
BuP	0.01	68	<LOD	0.014 ( $less than limit of detection to 0.027$ )	1.07	15	<LOD	<LOD (<LOD to <LOD)	0.02
TCS	0.01	89	<LOD	0.094 (0.041–0.23)	15.3	83	<LOD	0.085 (0.021–0.18)	14.0
Photoinitiators
MK	0.01	83	<LOD	0.23 (0.076–0.46)	56	71	<LOD	0.035 ( $less than limit of detection to 0.097$ )	6.66
PI-651	0.01	69	<LOD	0.29 ( $less than limit of detection to 0.85$ )	275	63	<LOD	0.022 ( $less than limit of detection to 0.072$ )	0.78
Bisphenols
BPA	0.31	27	<LOD	<LOD ( $less than limit of detection to 0.40$ )	37.5	41	<LOD	<LOD ( $less than limit of detection to 0.42$ )	4.04
BPF	0.03	27	<LOD	<LOD ( $less than limit of detection to 0.27$ )	44.0	19	<LOD	<LOD (<LOD to <LOD)	7.67
BPS	0.01	54	<LOD	0.012 ( $less than limit of detection to 0.038$ )	2.08	48	<LOD	<LOD ( $less than limit of detection to 0.072$ )	0.95
Phthalate ester metabolites
MMP	0.26	100	0.27	2.4 (1.5–4.9)	80.5	55	<LOD	0.42 ( $less than limit of detection to 1.1$ )	16.5
M(i)BP	0.08	76	<LOD	1.4 (0.10–3.1)	104	73	<LOD	1.2 ( $less than limit of detection to 3.1$ )	41.1
Antioxidants
BHT	0.30	78	<LOD	6.4 ( $less than limit of detection to 19.0$ )	84.6	38	<LOD	<LOD ( $less than limit of detection to 3.2$ )	48.8

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Note: Quantitative analysis was conducted on an LC-30A ultra-high performance liquid chromatograph interfaced with a Triple Quad 7500 mass spectrometer (SCIEX).⁴ Detailed information on instrumental analysis is available on GitHub (https://github.com/ZL1695/EHP-SI). 6:2 Cl-PFESA, 6:2 chlorinated perfluoroalkyl ether sulfonic acid; BHT, 2,6-di-tert-butyl-4-hydroxytoluene; BPA, 2,2-bis(4-hydroxyphenyl)propane; BPF, $4,4 prime-dihydroxydiphenylmethane$ ; BPS, $4,4 prime-dihydroxydiphenylsulfone$ ; BuP, butyl paraben; DF, detection frequency; EtP, ethyl paraben; IQR, interquartile range; LOD, limit of detection; max, maximum; MeP, methyl paraben; M(i)BP, mono-(iso)butyl phthalate; min, minimum; MK, $4,4 prime bis(dimethylamino)benzophenone$ ; MMP, monomethyl phthalate; PFBA, perfluorobutanoic acid; PFBS, perfluorobutanesulfonic acid; PFDA, perfluorodecanoic acid; PFDoA, perfluorododecanoic acid; PFHpA, perfluoroheptanoic acid; PFHpS, perfluoroheptanesulfonic acid; PFHxA, perfluorohexanoic acid; PFHxS, perfluorohexanesulfonic acid; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctanesulfonic acid; PFUdA, perfluoroundecanoic acid; PI-651, 2,2-dimethoxyphenyl acetophenone; TBP, tributyl phosphate; TCIPP, tris(2-chloroisopropyl) phosphate; TCS, triclosan; TPHP, triphenyl phosphate.

Some chemicals exhibited significant correlations between serum and CSF concentrations, whereas others did not (Table 1). The chemical-specific relationships between serum and CSF may be affected by several factors, including a chemical’s physicochemical properties, pathways through the blood–cerebrospinal fluid barrier (BCSFB), and compromised barrier function.^5,6 The $R_{CSF / serum}$ of a compound appeared to be significantly and negatively correlated with its molecular weight ( $rho = - 0.67$ ; $lowercase italic p less than 0.001$ ) or molecular volume ( $rho = - 0.50$ ; $lowercase italic p equals 0.01$ ; Table 2), indicating that smaller molecules tend to diffuse across the BCSFB. A negative correlation was also observed between $R_{CSF / serum}$ and lipophilicity (represented by log $K_{ow}$ ; $rho = - 0.50$ ; $lowercase italic p equals 0.058$ ), suggesting that binding with lipids and proteins may restrict passive diffusion. The ${pK}_{a}$ was also correlated with $R_{CSF / serum}$ ( $rho = - 0.45$ ; $lowercase italic p equals 0.056$ ); however, no significant relationship was observed for biodegradation half-life and $R_{CSF / serum}$ ( $rho = - 0.34$ ; $lowercase italic p equals 0.13$ ). Our findings align with those of a previous study that reported molecular size and lipophilicity could largely influence the ability of organophosphate esters to penetrate brain barriers.⁵ Other than free passive diffusion, the penetration of exogenous chemicals into the CNS may be limited by efflux transporters distributed between the apical and basolateral membrane domains of the choroidal epithelial cells.⁷ However, barrier functions may be compromised by neurological diseases, infections, trauma, and other factors, subsequently affecting chemical penetration.^6,7 These various factors may collectively impact CSF exposure to environmental chemicals and influence chemical-specific relationships between serum and CSF levels.

Table 2.

Summary of the correlations between cerebrospinal fluid (CSF) and serum concentrations of target environmental chemicals, concentration ratios of a chemical in CSF to that in paired serum samples ( $R_{CSF / serum}$ ), and the correlations between $R_{CSF / serum}$ and selected physicochemical properties of chemicals.

Chemical^a	$N$ ^b	MW^c	$S_{v}$ ^d	log $K_{ow}$ ^e	${pK}_{a}$ ^f	Biodeg. half-life^g	rho^h	$p$ -Valueⁱ	$R_{CSF / serum}$ ^j (IQR)
PFBA	41	214.0	135.2	2.14	$negative 0.21$	4.47	0.051	0.750	0.33 (0.26–0.44)
PFHpA	82	364.0	223.5	4.15	0.06	4.47	$negative 0.41$	$less than 0.001$	0.072 (0.039–0.26)
PFOA	174	414.0	252.9	4.81	0.34	4.90	0.31	$less than 0.001$	0.005 (0.003–0.011)
PFNA	40	464.0	282.3	5.48	0.23	4.90	$negative 0.071$	0.644	0.030 (0.015–0.048)
PFDA	56	514.0	311.7	6.15	0.4	4.90	0.006	0.965	0.007 (0.004–0.015)
PFUdA	83	564.0	341.2	6.82	0.54	4.90	0.037	0.741	0.007 (0.002–0.015)
PFDoA	47	614.0	370.6	7.49	0.54	5.50	$negative 0.013$	0.945	0.025 (0.013–0.061)
PFBS	107	300.0	177.2	1.82	$negative 1.61$	4.47	0.33	$less than 0.001$	0.26 (0.14–0.57)
PFHxS	155	399.9	236.1	3.16	$negative 1.64$	4.47	0.57	$less than 0.001$	0.007 (0.005–0.012)
PFHpS	84	449.9	265.5	3.82	$negative 1.81$	4.47	0.47	$less than 0.001$	0.052 (0.03–0.084)
PFOS	85	499.9	295.0	4.49	$negative 1.64$	4.90	0.50	$less than 0.001$	0.003 (0.002–0.005)
6:2 Cl-PFESA	140	569.9	312.9	3.10	1.58	4.68	0.45	$less than 0.001$	0.001 (0.0004–0.002)
TBP	124	266.2	271.1	3.82	NA	3.72	0.057	0.531	0.59 (0.19–1.01)
TPHP	103	326.1	281.4	4.7	NA	6.17	$negative 0.29$	0.003	0.54 (0.12–1.56)
TCIPP	140	326.0	264.8	2.89	NA	3.72	0.21	0.093	2.04 (0.65–4.82)
MeP	108	152.0	139.5	2.00	8.44	3.55	0.20	0.043	0.07 (0.021–0.18)
EtP	128	166.1	156.8	2.49	9.24	3.55	$negative 0.074$	0.409	0.24 (0.036–7.38)
TCS	138	288.0	217.0	4.66	8.66	4.47	0.35	$less than 0.001$	0.77 (0.23–1.52)
MK	114	268.2	268.4	3.50	3.04	5.5	0.19	0.046	0.17 (0.071–0.39)
PI-651	71	256.1	246.7	2.95	NA	4.9	$negative 0.26$	0.031	0.094 (0.019–0.41)
MMP	99	180.0	162.9	1.37	5.31	3.55	0.29	0.004	0.46 (0.25–0.85)
M(i)BP	128	222.1	214.8	2.77	4.66	3.55	0.28	0.003	1.33 (0.75–2.44)
BHT	54	220.2	245.6	5.03	11.8	14.8	0.06	0.664	0.32 (0.11–1.05)
rho ( $p$ -value)^k	—	$negative 0.67$ ( $less than 0.001$ )	$negative 0.50$ (0.01)	$negative 0.40$ (0.058)	0.45 (0.056)	$negative 0.34$ (0.13)	—	—	—

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Note: Paired samples are from 180 adults in Guangzhou, China, 2022–2023. —, Not applicable; 6:2 Cl-PFESA, 6:2 chlorinated perfluoroalkyl ether sulfonic acid; BHT, 2,6-di-tert-butyl-4-hydroxytoluene; biodeg, biodegradation; EtP, ethyl paraben; IQR, interquartile range; LOD, limit of detection; MeP, methyl paraben; M(i)BP, mono-(iso)butyl phthalate; MK, $4,4 prime bis(dimethylamino) benzophenone$ ; MMP, monomethyl phthalate; NA, not available; PFBA, perfluorobutanoic acid; PFBS, perfluorobutanesulfonic acid; PFDA, perfluorodecanoic acid; PFDoA, perfluorododecanoic acid; PFHpA, perfluoroheptanoic acid; PFHpS, perfluoroheptanesulfonic acid; PFHxS, perfluorohexanesulfonic acid; PFNA, perfluorononanoic acid; PFOA, perfluorooctanoic acid; PFOS, perfluorooctanesulfonic acid; PFUdA, perfluoroundecanoic acid; PI-651, 2,2-dimethoxyphenyl acetophenone; TBP, tributyl phosphate; TCIPP, tris(2-chloroisopropyl) phosphate; TCS, triclosan; TPHP, triphenyl phosphate.

^{^a}

Only chemicals with measurements >LOD in $more than 40$ pairs of serum and CSF samples were included for correlation analysis.

^{^b}

$N$ represents the pairs of CSF and serum samples with measurements >LOD.

^{^c}

MW: molecular weight (g/mol).

^{^d}

$S_{v}$ ( $angstrom 3 per molecule$ ): van der Waals volume calculated with a model provided by Zhao et al., used to represent the molecular volume.⁸

^{^e}

log $K_{ow}$ : log-transformed octanol–water partition coefficient, predicted with the US Environmental Protection Agency Estimation Program Interface, version 4.11.

^{^f}

${pK}_{a}$ represents the negative logarithm of the acid dissociation constant ( $K_{a}$ ) of a solution, predicted with the Open (Quantitative) Structure-activity/property Relationship APP (OPERA) version 2.6.⁹

^{^g}

Biodegradation half-life (day), predicted with OPERA 2.6.

^{^h}

Spearman correlation coefficient (rho) between paired serum and CSF samples (SPSS Statistics 26; IBM).

^ⁱ

$p$ -Values for the Spearman correlation between paired serum and CSF samples, with a two-sided $lowercase italic p less than 0.05$ considered statistically significant.

^{^j}

$R_{CSF / serum}$ represents the concentration ratio of a chemical in CSF to that in paired serum samples, reported as median and IQR values.

^{^k}

Spearman correlation coefficient (rho) and $p$ -value (in parenthesis) between $R_{CSF / serum}$ and a chemical’s physicochemical properties.

Our exploratory study documents a large number and breadth of potentially neurotoxic substances detected in human CSF. Chemical-specific relationships between serum and CSF concentrations raise the need for further elucidation of factors influencing the cross-BCSFB transfer of environmental chemicals. Our study highlights that efficient and accurate prediction of environmental chemicals’ distribution in CSF is important to the exploration of their potential impact on neurological health, considering the difficulty in obtaining CSF samples for clinical and epidemiological studies.

Acknowledgments

We thank the volunteers participating in the study. The present study was financially supported by the National Natural Science Foundation of China [22176072 and 41977373 (both to Da Chen) and 42177407 (to Xiaotu Liu)] and Fundamental Research Funds for the Central Universities [21620105 (to Da Chen)].

Conclusions and opinions are those of the individual authors and do not necessarily reflect the policies or views of EHP Publishing or the National Institute of Environmental Health Sciences.

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PERMALINK

Suspect-Screening Analysis of Environmental Chemicals in Paired Human Cerebrospinal Fluid and Serum Samples

Long Zhang

Pan Yang

Yaqing Shu

Wei Huang

Wenwen Sun

Xiaotu Liu

Da Chen

Introduction

Methods

Results and Discussion

Table 1.

Table 2.

Acknowledgments

References

ACTIONS

PERMALINK

RESOURCES

Cite

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PERMALINK

Suspect-Screening Analysis of Environmental Chemicals in Paired Human Cerebrospinal Fluid and Serum Samples

Long Zhang

Pan Yang

Yaqing Shu

Wei Huang

Wenwen Sun

Xiaotu Liu

Da Chen

Introduction

Methods

Results and Discussion

Table 1.

Table 2.

Acknowledgments

References

ACTIONS

PERMALINK

RESOURCES

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