Proteomics analysis identified serum biomarkers for occupational benzene exposure and chronic benzene poisoning.
Ontology highlight
ABSTRACT:
SUBMITTER: Li P
PROVIDER: S-EPMC6636960 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Previously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells. In the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S. First, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (<1 to ≥5 ppm). Second, we used SuperLearner (SL) to identify a minimal number of genes for which altered expression could predict <1 ppm benzene exposure, in 44 subjects with a mean air benzene level of 0.55±0.248 ppm (minimum 0.203ppm). nCounter and microarray expression levels were highly correlated (coefficients >0.7, p<0.05) for 26 microarray-selected genes. nCounter and mRNA-Seq levels were poorly correlated for 4 mRNA-Seq-selected genes. Using negative binomial regression with adjustment for covariates and multiple testing, we confirmed differential expression of 23 microarray-selected genes in the entire benzene-exposed group, and 27 genes in the <1 ppm-exposed subgroup, compared with the control group. Using SL, we identified 3 pairs of genes that could predict <1 ppm benzene exposure with cross-validated AUC estimates >0.9 (p<0.0001) and were not predictive of other exposures (nickel, arsenic, smoking, stress). The predictive gene pairs are PRG2/CLEC5A, NFKBI/CLEC5A, and ACSL1/CLEC5A. They play roles in innate immunity and inflammatory responses. Using nCounter and SL, we validated the altered expression of multiple mRNAs by benzene and identified gene pairs predictive of exposure to benzene at levels below the US occupational standard of 1ppm.
2018-09-06 | GSE119533 | GEO
Project description:PurposeScleritis is an extremely painful and potentially blinding inflammation of the sclera with unknown pathogenesis and unpredictable course. To gain insight in its disease process and identify biomarker candidates, we performed extensive proteomics in serum and tear fluid.DesignProspective multicenter cohort study.ParticipantsA total of 121 patients with noninfectious scleritis (of which 39 active cases), 30 healthy controls, and 23 disease controls (uveitis and rheumatoid arthritis) were enrolled in the Netherlands from 2020 to 2022.MethodsSerum, tear fluid of both eyes, and clinical data were gathered. The level of 368 inflammatory proteins was measured using proximity extension assays. Results were validated in an independent cohort of 15 patients with scleritis, and using addressable laser bead immunoassay, or enzyme-linked immunoassays. In addition, we studied an extended panel of matrix metalloproteinases in tear fluid of necrotizing scleritis with addressable laser bead immunoassay.Main outcome measuresStatistically significant differences in the level of inflammatory proteins between patients with scleritis and control groups.ResultsProteomics revealed 18 significantly upregulated or downregulated serum proteins in active scleritis cases compared with all control groups in both the discovery cohort and the validation cohort. The most upregulated protein was nuclear migration protein nudC (NudC; P = 0.0032), a protein involved in neurogenesis. The other significant hits included proteins involved in T-cell activation, apoptosis, epithelial barrier maintenance, and angiogenesis. Our tear fluid analysis showed matrix metalloproteinase 9 (MMP9) to be upregulated in the tear fluid of patients with scleral necrosis.ConclusionsThe results of our proteomics analysis suggest a role for neurogenesis, T-cell activation, disruption of epithelial barrier, and angiogenesis in the pathogenesis of scleritis, and highlight MMP9 and NudC as biomarkers with potential clinical relevance.Funding disclosuresThe authors have no proprietary or commercial interest in any materials discussed in this article.
| S-EPMC10694766 | biostudies-literature
Project description:Benzene is an important industrial chemical and environmental contaminant that causes leukemia. To obtain mechanistic insight into benzene's mechanism of action, we examined the impact of benzene on the human serum proteome in a study of exposed healthy shoe-factory workers and unexposed controls. Two sequential studies were performed, each using sera from 10 workers exposed to benzene (overall mean benzene air level >30 ppm) and 10 controls. Serum samples were subjected to anion-exchange fractionation and bound to three types of ProteinChip arrays (Ciphergen Biosystems, Fremont, CA) [hydrophobic (H50), metal affinity (IMAC3-Cu), and cation exchange (WCX2)]. Protein-expression patterns were detected by surface-enhanced laser desorption/ionization (SELDI)-TOF MS. Three proteins (4.1, 7.7, and 9.3 kDa) were consistently down-regulated in exposed compared with control subjects in both studies. All proteins were highly inversely correlated with individual estimates of benzene exposure (r > 0.75). The 7.7- and 9.3-kDa proteins were subsequently identified as platelet factor (PF)4 and connective tissue activating peptide (CTAP)-III. Initial proteomic results for PF4 and CTAP-III were subsequently confirmed in a single experiment using a ProteinChip-array-based immunoassay(Ciphergen Biosystems). The altered expression of the platelet-derived CXC-chemokines (40% and 63% for PF4 and CTAP-III, respectively) could not be explained by changes in absolute platelet counts. Thus, SELDI-TOF analysis of a limited number of exposed and unexposed subjects revealed that lowered expression of PF4 and CTAP-III proteins is a potential biomarker of benzene's early biologic effects and may play a role in the immunosuppressive effects of benzene.
| S-EPMC1288009 | biostudies-literature
Project description:Serum components of sepsis patients vary with the severity of infection, the resulting inflammatory response, per individual, and even over time. Tracking these changes is crucial in properly treating sepsis. Hence, several blood-derived biomarkers have been studied for their potential in assessing sepsis severity. However, the classical approach of selecting individual biomarkers is problematic in terms of accuracy and efficiency. We therefore present a novel approach for detecting biomarkers using longitudinal proteomics data. This does not require a predetermined set of proteins and can therefore reveal previously unknown related proteins. Our approach involves examining changes over time of both protein abundance and post-translational modifications in serum, using two-dimensional gel electrophoresis (2D-PAGE). 2D-PAGE was conducted using serum from n = 20 patients, collected at five time points, starting from the onset of sepsis. Changes in protein spots were examined using 49 spots for which the signal intensity changed by at least two-fold over time. These were then screened for significant spikes or dips in intensity that occurred exclusively in patients with adverse outcome. Individual level variation was handled by a mixed effects model. Finally, for each time transition, partial correlations between spots were estimated through a Gaussian graphical model (GGM) based on the ridge penalty. Identifications of spots of interest by tandem mass spectrometry revealed that many were either known biomarkers for inflammation (complement components), or had previously been suggested as biomarkers for kidney failure (haptoglobin) or liver failure (ceruloplasmin). The latter two are common complications in severe sepsis. In the GGM, many of the tightly connected spots shared known biological functions or even belonged to the same protein; including hemoglobin chains and acute phase proteins. Altogether, these results suggest that our screening method can successfully identify biomarkers for disease states and cluster biologically related proteins using longitudinal proteomics data derived from 2D-PAGE.
| S-EPMC6768476 | biostudies-literature
Project description:The current study aimed to systematically review the studies concerning the biological monitoring of benzene exposure in occupational settings. A systematic literature review was conducted in Scopus, EMBASE, Web of Science, and Medline from 1985 through July 2021. We included peer-reviewed original articles that investigated the association between occupational exposure to benzene and biological monitoring. We identified 4786 unique citations, of which 64 cross-sectional, one case-control, and one cohort study met our inclusion criteria. The most studied biomarkers were urinary trans-trans muconic acid, S- phenyl mercapturic acid, and urinary benzene, respectively. We found the airborne concentration of benzene as a key indicator for choosing a suitable biomarker. We suggest considering urinary benzene at low (0.5-5.0 TLV), urinary SPMA and TTMA at medium (5.0-25 and 25-50 TLV, respectively), and urinary phenol and hydroquinone and catechol at very high concentrations (500 and 1000 TLV ≤, respectively). Genetic polymorphism of glutathione S-transferase and oral intake of sorbic acid have confounding effects on the level of U-SPMA and U-TTMA, respectively. The airborne concentration, smoking habit, oral consumption of sorbic acid, and genetic polymorphism of workers should be considered in order to choose the appropriate indicator for biological monitoring of benzene exposure.
| S-EPMC10660043 | biostudies-literature
Project description:BackgroundPreviously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells.ObjectivesIn the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S.MethodsFirst, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (<1 to ≥5 ppm). Second, we used SuperLearner (SL) to identify a minimal number of genes for which altered expression could predict <1 ppm benzene exposure, in 44 subjects with a mean air benzene level of 0.55±0.248 ppm (minimum 0.203ppm).ResultsnCounter and microarray expression levels were highly correlated (coefficients >0.7, p<0.05) for 26 microarray-selected genes. nCounter and mRNA-Seq levels were poorly correlated for 4 mRNA-Seq-selected genes. Using negative binomial regression with adjustment for covariates and multiple testing, we confirmed differential expression of 23 microarray-selected genes in the entire benzene-exposed group, and 27 genes in the <1 ppm-exposed subgroup, compared with the control group. Using SL, we identified 3 pairs of genes that could predict <1 ppm benzene exposure with cross-validated AUC estimates >0.9 (p<0.0001) and were not predictive of other exposures (nickel, arsenic, smoking, stress). The predictive gene pairs are PRG2/CLEC5A, NFKBI/CLEC5A, and ACSL1/CLEC5A. They play roles in innate immunity and inflammatory responses.ConclusionsUsing nCounter and SL, we validated the altered expression of multiple mRNAs by benzene and identified gene pairs predictive of exposure to benzene at levels below the US occupational standard of 1ppm.
| S-EPMC6177191 | biostudies-literature
Project description:ObjectivesIndividual variations in the capacity of DNA repair machinery to relieve benzene-induced DNA damage may be the key to developing chronic benzene poisoning (CBP), an increasingly prevalent occupational disease in China. ERCC1 (Excision repair cross complementation group 1) is located on chromosome 19q13.2-3 and participates in the crucial steps of Nucleotide Excision Repair (NER); moreover, we determined that one of its polymorphisms, ERCC1 rs11615, is a biomarker for CBP susceptibility in our previous report. Our aim is to further explore the deeper association between some genetic variations related to ERCC1 polymorphisms and CBP risk.MethodsNine single nucleotide polymorphisms (SNPs) of XRCC1 (X-ray repair cross-complementing 1), CD3EAP (CD3e molecule, epsilon associated protein), PPP1R13L (protein phosphatase 1, regulatory subunit 13 like), XPB (Xeroderma pigmentosum group B), XPC (Xeroderma pigmentosum group C) and XPF (Xeroderma pigmentosum group F) were genotyped by the Snapshot and TaqMan-MGB® probe techniques, in a study involving 102 CBP patients and 204 controls. The potential interactions between these SNPs and lifestyle factors, such as smoking and drinking, were assessed using a stratified analysis.ResultsAn XRCC1 allele, rs25487, was related to a higher risk of CBP (P<0.001) even after stratifying for potential confounders. Carriers of the TT genotype of XRCC1 rs1799782 who were alcohol drinkers (OR = 8.000; 95% CI: 1.316-48.645; P = 0.022), male (OR = 9.333; 95% CI: 1.593-54.672; P = 0.019), and had an exposure of ≤12 years (OR = 2.612; 95% CI: 1.048-6.510; P = 0.035) had an increased risk of CBP. However, the T allele in PPP1R13L rs1005165 (P<0.05) and the GA allele in CD3EAP rs967591 (OR = 0.162; 95% CI: 0039~0.666; P = 0.037) decreased the risk of CBP in men. The haplotype analysis of XRCC1 indicated that XRCC1 rs25487A, rs25489G and rs1799782T (OR = 15.469; 95% CI: 5.536-43.225; P<0.001) were associated with a high risk of CBP.ConclusionsThe findings showed that the rs25487 and rs1799782 polymorphisms of XRCC1 may contribute to an individual's susceptibility to CBP and may be used as valid biomarkers. Overall, the genes on chromosome 19q13.2-3 may have a special significance in the development of CBP in occupationally exposed Chinese populations.
| S-EPMC4683048 | biostudies-literature
Project description:Benzene is an established cause of leukemia, and possibly lymphoma, in humans, but the underlying molecular pathways remain largely undetermined. We used two microarray platforms to identify global gene expression changes associated with well-characterized occupational benzene exposure in the peripheral blood mononuclear cells (PBMC) of a population of shoe-factory workers. Differential expression of 2692 genes (Affymetrix) and 1828 genes (Illumina) was found and the concordance was 50% (based on an average fold-change > or =1.3 from the two platforms), with similar expression ratios among the concordant genes. Four genes (CXCL16, ZNF331, JUN and PF4), which we previously identified by microarray and confirmed by real-time PCR, were among the top 100 genes identified by both platforms in the current study. Gene ontology analysis showed overrepresentation of genes involved in apoptosis among the concordant genes while pathway analysis identified pathways related to lipid metabolism. The two-platform approach allows for robust changes in the PBMC transcriptome of benzene-exposed individuals to be identified.
| S-EPMC2693268 | biostudies-literature
Project description:BackgroundBenzene, an important component of organic solvents, is commonly used in industry. Meanwhile, benzene is a human carcinogen leading to leukemia. Although the links between benzene and various types of genetic damage indicators have been evaluated in several studies, but their results remain inconsistent. So we conducted a meta-analysis, and to explore the influence of low concentration benzene exposure on workers' genetic damage indicators using 3.25 mg/m3 as the boundary value, in order to provide a basis for improved prevention and control of the harm from benzene exposure to the occupational population.MethodsWe conducted a search of five databases, including Pub Med, Web of Science, China National Knowledge Infrastructure (CNKI), Wan Fang Data and Chongqing VIP, to identify relevant articles up to December 25, 2018. Two researchers independently extracted and evaluated the data according to the inclusion and exclusion criteria of the literature. The imported articles were managed by Endnote X7, and the data were extracted and sorted by Excel 2013. We utilized Stata 12.0 software to perform the meta-analysis in the present study.ResultsA total of 68 eligible articles were finally included for the synthetic analyses. The meta-analysis results showed that occupational benzene exposure led to significantly increased Micronucleus (MN) frequency, Sister chromatid exchange (SCE) frequency, Chromosome aberration (CA) frequency, Olive Tail moment (OTM), Tail moment (TM), Tail length (TL), and Tail DNA% (T DNA%) compared to the control group (P < 0.05), and the pooled effect value estimates were 1.36, 0.98, 0.76, 1.06, 0.96, 1.78, and 1.42, respectively. Subsequent analysis of the effect of low concentration benzene exposure on genetic damage found significantly increased MN frequency increased compared with the control group (P < 0.05).ConclusionsOccupational benzene exposure can affect multiple genetic damage indicators. Even at an exposure concentration lower than 3.25 mg/m3, benzene exposure has genotoxicity. These data provide an important scientific basis for the further revision of occupational disease prevention strategies. At the same time, increased attention should be focused on the health monitoring of the occupational population exposed to benzene, and health management should be strengthened to improve the health of the occupational population.
| S-EPMC7362416 | biostudies-literature
Project description:Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled P-values <0.05, in the mean and variance of methylation at 22 and 318 CpG sites, respectively, and in mean methylation of a large genomic region. Pathway analysis of genes corresponding to benzene-associated differential methylation sites revealed an impact on the AMPK signalling pathway. In formaldehyde-exposed subjects compared to controls, 9 CpGs in the DUSP22 gene promoter had genome-wide significant decreased methylation variability and a large region of the HOXA5 promoter with 44 CpGs was hypomethylated. Our findings suggest that DNA methylation may contribute to the pathogenesis of diseases related to benzene and formaldehyde exposure. Aberrant expression and methylation of HOXA5 previously has been shown to be clinically significant in myeloid leukaemias. The tumour suppressor gene DUSP22 is a potential biomarker of exposure to formaldehyde, and irregularities have been associated with multiple exposures and diseases.
| S-EPMC9665125 | biostudies-literature