Benzene, a ubiquitous aromatic hydrocarbon, remains
a cornerstone of the global petrochemical industry, widely employed
in the synthesis of plastics, resins and synthetic fibers, as well
as in solvents for paints, coatings and adhesives (1). However, its volatility and
lipophilicity render it a pervasive occupational hazard. Despite
stringent engineering controls, chronic exposure to benzene vapor
persists in industries such as shoe manufacturing, chemical
processing and fuel refining, posing a notable threat to global
occupational health (2).
The hematotoxicity and leukemogenicity of benzene
are well-established. Classified as a Group 1 human carcinogen by
the International Agency for Research on Cancer (IARC), benzene is
causally linked to aplastic anemia, myelodysplastic syndromes and
acute myeloid leukemia (AML) (3–5).
Beyond the hematopoietic system, emerging evidence indicates that
benzene exerts systemic toxicity, inducing oxidative stress and
functional impairment in the nervous, immune, reproductive and
respiratory systems (6). The
mechanism of toxicity is complex, primarily involving the hepatic
metabolic activation of benzene by cytochrome P450 2E1 (CYP2E1)
into reactive metabolites (such as benzoquinones and
hydroquinones), which drive DNA damage, chromosomal aberrations and
epigenetic dysregulation (7).
A notable challenge in current occupational health
is the ‘low-dose’ paradox. While regulatory standards, such as
China's occupational exposure limit (PC-TWA of 6 mg/m3)
and the American Conference of Governmental Industrial Hygienists
(ACGIH) threshold limit value (0.5 ppm), aim to protect workers,
recent epidemiological studies reveal that hematotoxicity and
genotoxicity occur at concentrations well below these permissible
limits (8,9). This underscores a notable gap in the
understanding of low-level exposure risks. Furthermore,
conventional monitoring relies heavily on biomarkers such as trans,
trans-muconic acid (tt-MA) or S-phenylmercapturic acid (SPMA).
While superior to the historical marker urinary phenol, these
indicators still face limitations in sensitivity and specificity
when distinguishing low-dose occupational exposure from
environmental background sources (for example smoking or traffic
exhaust) (9).
Therefore, there is a need to elucidate the
molecular mechanisms of benzene toxicity at low doses and to
validate novel, non-invasive biomarkers for early effect monitoring
(10). The present review
synthesizes advances in domestic and international research,
focusing on three key areas: i) The mechanistic basis of
benzene-induced multi-organ toxicity, with a focus on oxidative
stress and immune dysregulation; ii) the evolution of biomarkers,
transitioning from traditional metabolites to emerging
‘omics-based’ markers (metabolomics, microRNA panels and DNA
methylation); and iii) the clinical implications for precise risk
assessment and health surveillance (11). By integrating these perspectives,
the present review aimed to provide a theoretical foundation for
updating occupational health standards and improving early
intervention strategies (12).
Consequently, integrating these multifaceted biomarkers into a
cohesive framework utilizing artificial intelligence represents the
next frontier in occupational medicine. The systematic literature
search and study selection process for this review is detailed in
Fig. 1.
Benzene exerts cumulative neurotoxic effects
involving both the central nervous system and peripheral nervous
system (13). Chronic exposure
induces a spectrum of neurobehavioral deficits-often termed
‘chronic benzene encephalopathy’, characterized by persistent
cephalalgia, dizziness, insomnia and cognitive decline (14). These manifestations are underpinned
by the disruption of neurotransmitter homeostasis. Mechanistic
studies reveal that benzene metabolites inhibit tyrosine
hydroxylase and other rate-limiting enzymes in dopamine and
serotonin synthesis, thereby impairing synaptic transmission and
neuronal signaling efficiency (15,16).
Neurobehavioral batteries corroborate these
findings; for example, exposed workers demonstrate notably
prolonged reaction times and a ~20% reduction in bilateral
coordination scores compared with controls (17). Due to its high lipophilicity,
benzene readily traverses the blood-brain barrier. Its
accumulation, along with bioactive metabolites such as phenol,
induces histopathological alterations in hippocampal neurons,
including vacuolar degeneration and nuclear pyknosis (18). Furthermore, benzene compromises
glial cell integrity, leading to myelin sheath instability and
irregular Node of Ranvier spacing, which consequently reduces nerve
conduction velocity (19).
Peripheral neuropathy is equally prevalent (20). In a cohort of shoemaking workers,
~30% reported sensory anomalies, including paresthesia and
hypoesthesia (21).
Electrophysiological assessments confirmed axonal damage,
evidencing motor conduction velocities in median and ulnar nerves
that were 3–5 m/sec slower than population norms (22). Notably, owing to the limited
regenerative capacity of neural tissue, neurological deficits often
persist irreversibly even after exposure cessation (23).
The hematopoietic system represents the primary
target of benzene toxicity, displaying a dose-dependent
vulnerability (24). Chronic
exposure precipitates hematological dyscrasias ranging from
leukopenia (<3.5×109/l) and thrombocytopenia
(<100×109/l) to severe pancytopenia (25). In advanced stages, this progresses
to aplastic anemia or hematologic malignancies (26). The mechanism is driven by hepatic
metabolic activation via CYP2E1, generating reactive electrophiles
(1,4-benzoquinone, hydroquinone) (27) (Fig.
2).
Due to their lipophilic nature and stability in
circulation, these toxic intermediates are readily transported via
the systemic bloodstream to the bone marrow microenvironment. Upon
entering the hematopoietic niche, they induce severe oxidative
stress, rapidly deplete intracellular glutathione reserves and form
covalent adducts with topoisomerase II and DNA, ultimately causing
double-strand breaks (28).
Consequently, the genomic integrity of hematopoietic stem cells
(HSCs) is markedly compromised, forcing the cells to arrest at the
G2/M phase and triggering widespread apoptosis (29) (Fig.
3).
Cutaneous toxicity arises from the solvent
properties and sensitizing potential of benzene (47). As a lipophilic solvent, benzene
extracts epidermal lipids (ceramides, fatty acids), disrupting the
stratum corneum barrier and increasing transepidermal water loss
(48,49). This manifests clinically as
xerosis, scaling and reduced resistance to pathogens. Additionally,
benzene metabolites (such as hydroquinone) act as haptens,
triggering allergic contact dermatitis (50). Symptoms range from erythema to
vesiculation, with chronic exposure leading to lichenification
(51). In rubber manufacturing
cohorts, 42% of exposed workers exhibited dermatoses, with 15%
suffering from recurrent allergic dermatitis (52). Pigmentary disorders, including
hyperpigmentation or vitiligo-like leukoderma, affect ~8% of
long-term workers, likely due to melanocyte toxicity (53). Compromised skin integrity further
predisposes workers to secondary bacterial infections (54).
Beyond leukemia, benzene (IARC Group 1 carcinogen)
is associated with solid tumors (64,65).
Cohort studies indicate a 2.1-fold increased risk of non-Hodgkin
lymphoma and a 1.8-fold increase in multiple myeloma (66). Evidence also links exposure to lung
and gastric cancers; for instance, coking plant workers exhibit a
lung cancer mortality rate of 35 per 100,000 person-years (relative
risk=2.7) (67,68). The carcinogenic mechanism is
multifactorial, involving genotoxicity (DNA adduct formation),
inhibition of DNA repair enzymes (such as XRCC1) and epigenetic
dysregulation (69,70). Benzene simultaneously activates
survival signaling (PI3K/Akt) and suppresses apoptosis (Bax
downregulation), facilitating the clonal expansion of initiated
cells (71). Long-term
surveillance confirms a notably elevated all-cancer mortality rate
in exposed populations (180 vs. 110 per 100,000 person-years)
(72).
Benzene is a potent immunotoxicant, compromising
both innate and adaptive immunity (73). Inhalation studies demonstrate
thymic atrophy and splenic T-cell depletion (30–40% reduction)
(74). Human data reveal a global
immunosuppressive profile: 15–20% lymphopenia, inverted
CD4+/CD8+ ratios and hypogammaglobulinemia
(IgG, IgA reduced by 10–15%) (75). Functionally, this manifests as
increased susceptibility to infection. In influenza challenge
models, benzene-exposed mice exhibited 45% mortality compared with
12% in controls (76). At the
cellular level, oxidative stress impairs lymphocyte proliferation
and cytokine production (IL-2, IFN-γ), thereby weakening immune
surveillance against pathogens and neoplastic cells (77).
As detailed, benzene exerts profound multi-organ
toxicity, affecting the nervous, cardiovascular and reproductive
systems. However, it must be noted that the current landscape of
validated benzene biomarkers notably skews toward hematotoxicity
and genotoxicity (90). Specific
effect biomarkers designed to reflect early benzene-induced
neurotoxicity or cardiovascular dysfunction are currently lacking
or remain strictly in the exploratory experimental phase (91). Therefore, the biomarkers discussed
in the following sections primarily represent internal dose
monitoring and hematopoietic/genomic impairments, highlighting a
gap that future non-hematopoietic biomarker research must address
(92). As summarized in Fig. 4, the landscape of benzene
biomonitoring can be systematically categorized into exposure,
effect and susceptibility biomarkers.
Exposure biomarkers reflect the internal dose of
benzene absorbed by the human body (90). They mainly include the parent
compound and its metabolites, which can be measured in biological
samples such as blood, urine and exhaled air (89). These indicators provide objective
and direct evidence for assessing exposure levels in both
occupational and environmental contexts (93).
Exhaled air analysis offers a non-invasive approach
to monitoring benzene exposure and is associated with blood
concentrations (102). Since a
fraction of absorbed benzene is excreted via respiration at a
relatively stable rate, this biomarker is well-suited for real-time
exposure assessment in occupational settings (103). For example, exhaled air
collection during paint-spraying operations allows immediate
estimation of exposure levels during work shifts (104).
The commonly used detection technique is solid-phase
microextraction coupled with GC-MS) (105). Here, benzene is adsorbed onto a
solid-phase microextraction fiber, desorbed into the chromatograph,
and identified by MS (106). This
approach provides high sensitivity, operational simplicity and
notably, the advantage of being repeatable and non-invasive, making
it suitable for large-scale workplace screening (107).
Nevertheless, exhaled benzene concentrations are
easily influenced by respiratory parameters (such as breathing rate
and depth) and ambient environmental contamination (108). Thus, standardized sampling
protocols and strict quality control are essential to ensure
reliability (109).
Phenol is one of the principal urinary metabolites
of benzene and has long been used as a biomarker for occupational
exposure (110). After benzene is
metabolized by the hepatic cytochrome P450 enzyme system, phenol is
produced and subsequently conjugated with sulfuric acid or
glucuronic acid (111). A total
of ~30% of benzene is excreted as conjugated phenol, whereas free
phenol accounts for only ~5% (112). Urinary phenol levels generally
associate with the extent of benzene exposure and typically
normalize within 24–48 h after exposure cessation (113).
However, urinary phenol has limitations. Baseline
levels in the general population range from 0.15–0.25 mg/l (and can
be higher in smokers), which reduces specificity for low-level
exposures (117). Moreover,
notable inter-individual variability exists-phenol excretion under
similar exposure conditions may differ by as much as 12-fold,
partly due to differences in liver function and the influence of
medications (such as phenobarbital), which alter cytochrome P450
activity (118). Therefore,
urinary phenol is more reliable for monitoring high-concentration
exposure, whereas its sensitivity for low-level exposure remains
inadequate (119).
Hydroquinone is a more specific urinary metabolite
of benzene compared with phenol and provides enhanced accuracy for
exposure assessment (120).
Following benzene oxidation to benzene oxide, further metabolism
yields hydroquinone, which is excreted in urine (121). Quantification is typically
performed using high-performance liquid chromatography (HPLC) with
ultraviolet detection after appropriate sample pretreatment
(122).
Epidemiological investigations show that urinary
hydroquinone levels exhibit a notable dose-response relationship
with benzene exposure concentration (123). Compared with phenol, hydroquinone
is less affected by confounding factors and therefore more reliable
in detecting low-concentration exposures (124). Nonetheless, hydroquinone
measurement is not completely specific, as certain dietary
components or medications may also elevate urinary hydroquinone,
necessitating combined measurement with phenol or other metabolites
to improve diagnostic accuracy (125).
Catechol is a minor urinary metabolite of benzene
and may serve as a supplementary biomarker of exposure (126). Its metabolic pathway is similar
to that of hydroquinone, both being products of benzene oxidative
metabolism (127). Although
catechol is less commonly employed than phenol and hydroquinone in
routine biomonitoring, several studies suggest that combined
analysis of catechol with other metabolites can provide a more
comprehensive picture of benzene biotransformation and exposure
burden (128–131). Detection is typically performed
using HPLC (129). However, its
relatively low urinary concentration and susceptibility to various
endogenous and exogenous interferences limit its specificity and
sensitivity (130). At present,
catechol is primarily used as an auxiliary indicator within a
biomarker panel rather than as a standalone marker of benzene
exposure (131).
tt-MA is a benzene metabolite generated via the
epoxidation pathway, with a half-life of ~16 h (132). This relatively long persistence
makes tt-MA suitable for detecting low-dose or subacute benzene
exposure (133). Benzene oxide,
an intermediate metabolite, is further metabolized into muconic
acid, among which tt-MA is the predominant isomer (134).
Detection methods such as GC-MS and HPLC-MS/MS
enable accurate qualitative and quantitative analysis of tt-MA in
urine (135). Epidemiological
studies have demonstrated that urinary tt-MA levels are positively
associated with both the concentration and duration of occupational
benzene exposure (135,136). Furthermore, tt-MA decreases
relatively slowly after cessation of exposure, thus serving as a
retrospective indicator of recent exposure (137). Accordingly, tt-MA is widely
recognized as a valuable biomarker for monitoring low-level
occupational benzene exposure and plays an notable role in
environmental health risk assessment (138).
SPMA is produced via the conjugation of benzene
oxide with glutathione under the catalysis of glutathione
S-transferases (GSTs), followed by subsequent metabolic reactions
leading to urinary excretion (139). SPMA is considered a markedly
specific and sensitive biomarker of benzene exposure, even at low
concentrations (140). Studies
indicate that urinary SPMA levels notably increase in workers
exposed to low ambient benzene levels, and these levels associate
with biomarkers of oxidative stress, such as
8-hydroxy-2′-deoxyguanosine, suggesting potential genotoxic risk
even at low-dose exposure (140,141).
Advanced analytical techniques such as HPLC-MS/MS
allow sensitive detection of trace SPMA in urine with minimal
interference from other sources (142). Given its high specificity, SPMA
is increasingly regarded as a robust biomarker for early biological
monitoring of benzene exposure and has promising potential for
occupational health surveillance and risk prevention (143). As comprehensively compared in
Table II, while traditional
metabolites such as phenol suffer from low specificity and high
background interference, emerging biomarkers such as SPMA and tt-MA
offer superior sensitivity for low-dose exposure assessments,
underscoring the critical transition in modern biomonitoring
strategies.
Effect biomarkers reflect biological damage or
functional alterations induced by benzene exposure (144). Since the hematopoietic system is
the primary toxicological target of benzene, most effect biomarkers
are associated with hematopoietic suppression and genotoxicity
(145).
A decrease in peripheral WBC count, particularly
neutropenia, is a common early hematological effect of benzene
exposure (146). Benzene and its
metabolites impair the proliferation and differentiation of
hematopoietic stem and progenitor cells, resulting in reduced
leukocyte production (147).
Occupational studies have shown that chronic low-level benzene
exposure leads to a gradual decline in WBC count, which positively
associates with exposure intensity and duration (148,149). For instance, health examinations
in benzene-exposed shoe factory workers revealed notably lower WBC
counts and neutrophil proportions compared with reference values,
indicating compromised immune function and increased susceptibility
to infection (149).
Although WBC monitoring is useful for early
detection of hematotoxicity, it lacks specificity since infections,
medications and other conditions can also reduce leukocyte levels
(150). Thus, WBC count should be
interpreted in conjunction with other biomarkers (151).
Thrombocytopenia is another hematological effect of
benzene exposure, reflecting bone marrow suppression of
megakaryocyte development and platelet production, as well as
enhanced platelet destruction (152). Clinically, benzene-related
thrombocytopenia often manifests as coagulation dysfunction,
including epistaxis, gingival bleeding and cutaneous ecchymoses
(153). Platelet reduction is
dose-dependent, with more pronounced decreases in populations
exposed to higher benzene concentrations (154). Given its simplicity and clinical
availability, platelet count is a valuable indicator of
benzene-induced hematotoxicity, although differential diagnoses
such as autoimmune diseases or hypersplenism must be excluded
(155).
Chronic benzene exposure may result in anemia,
characterized by reduced red blood cell count or hemoglobin
concentration (156).
Mechanistically, benzene inhibits hematopoietic stem cell activity
and disrupts key enzymes involved in erythropoiesis (157). Additionally, oxidative stress
induced by benzene metabolites can damage erythrocyte membranes and
shorten red cell lifespan. Clinically, patients with chronic
benzene poisoning often present with pallor, fatigue and dizziness,
alongside hematological findings of anemia (158). Routine monitoring of red blood
cell indices in exposed populations is useful for early detection
of hematopoietic impairment, although the multifactorial etiology
of anemia necessitates comprehensive evaluation (159).
Benzene metabolites are genotoxic and can induce
structural chromosome aberrations such as breaks, translocations
and deletions (160). Cytogenetic
analysis of bone marrow cells, often via chromosome banding,
enables visualization of these aberrations and quantification of
their frequency (161).
Occupational studies consistently report elevated rates of
chromosomal abnormalities in benzene-exposed populations, with a
dose-response relationship observed (162–164). Since chromosomal aberrations are
generally irreversible, they may predispose to genetic instability
and tumorigenesis (163). Despite
its diagnostic value, chromosomal aberration testing requires
specialized expertise and high-quality samples, limiting its
application in large-scale screening (164).
Micronuclei are extranuclear chromatin bodies formed
during mitosis when chromosome fragments or whole chromosomes fail
to be incorporated into daughter nuclei (170). Elevated micronucleus frequency in
peripheral lymphocytes or bone marrow cells indicates chromosomal
damage and is widely used as a biomarker of genotoxicity (171). Detection methods include
conventional Giemsa staining and flow cytometry, both of which
facilitate quantification of micronucleated cells (172). Multiple studies have documented
notably higher micronucleus rates in benzene-exposed populations,
with a positive dose-response relationship (173,174). Micronucleus assays are simple and
suitable for large-scale biomonitoring, although their low
specificity necessitates complementary testing (174).
DNA adducts are covalent complexes formed between
reactive benzene metabolites (such as benzoquinone) and DNA,
directly reflecting molecular damage (175). Adduct formation interferes with
DNA replication and transcription, thereby increasing mutagenic and
carcinogenic risk (176).
Detection methods include ELISA, which utilizes specific antibodies
for semiquantitative analysis, and HPLC-MS/MS, which provides
precise structural and quantitative information (177). In benzene-exposed populations,
multiple types of DNA adducts have been identified, with levels
linked to exposure intensity (178). DNA adduct analysis is therefore
crucial for elucidating benzene genotoxic mechanisms and evaluating
long-term health risks, and it remains a research focus in
toxicogenomics (179).
Hemoglobin adducts are stable complexes formed
between benzene metabolites and hemoglobin residues (180). Given the long half-life of
hemoglobin, these adducts provide an integrated measure of
cumulative benzene exposure over weeks to months (181). MS-based techniques enable their
detection and quantification (182). Occupational studies, such as
those involving long-term gasoline station attendants, have
reported elevated hemoglobin adduct levels, associating with
exposure duration and intensity (183). This biomarker offers unique
advantages in tracing chronic low-level exposure, although
specialized instrumentation and further research on dose-response
relationships are required to strengthen its utility in health risk
assessment (184).
Susceptibility biomarkers reflect inter-individual
genetic variations that influence vulnerability to benzene toxicity
(185). They are mainly
associated with polymorphisms in genes encoding metabolic enzymes
and DNA repair proteins (186).
Such biomarkers can help identify high-risk populations and support
the development of personalized protection strategies in
occupational and environmental settings (187).
Combinatorial assessment of these genetic
polymorphisms allows the construction of susceptibility scoring
models for benzene toxicity, offering a more comprehensive tool for
individualized risk evaluation and occupational health management
(221). To systematically
illustrate this, Table III
details the specific functional consequences and quantitative
risks-such as elevated odds ratios for leukemia and
hematotoxicity-associated with key polymorphisms across
bioactivation, detoxification, and DNA repair pathways, which
directly correspond to the integrated susceptibility network mapped
in Fig. 5.
As detailed in the preceding subsections, ethnic
differences in gene frequency play a pivotal role in
population-specific susceptibility, with Asian populations often
exhibiting higher frequencies of vulnerable genotypes (GSTM1 null,
CYP2E1*5B and NQO1*2) (201–203). These distinct genetic landscapes
raise a critical regulatory question regarding Occupational
Exposure Limits (OELs) (203).
Currently, OELs vary markedly across regions, such as China's
PC-TWA of 6 mg/m3 vs. the US ACGIH TLV of 0.5 ppm. Given
these genetic disparities, relying on a universal or less stringent
OEL may leave substantial proportions of the workforce inadequately
protected (204). Consequently,
future standard-setting bodies must factor in ethnic genetic
susceptibility, potentially moving toward region-specific or
genetically tailored occupational exposure thresholds (205).
With advances in analytical technologies, exhaled
breath metabolomics and multi-biomarker integration strategies have
emerged as novel approaches for benzene exposure assessment
(222). These methods overcome
the limitations of single biomarkers and improve both monitoring
accuracy and early warning efficiency (223).
Exhaled breath metabolomics is a newly developed
non-invasive technique characterized by convenient sample
collection, real-time monitoring and suitability for longitudinal
surveillance. It employs high-resolution analytical platforms-such
GC-MS, LC-MS and proton transfer reaction (PTR)-MS, to profile
small-molecule metabolites (typically <1,000 Da) in exhaled air,
and links them to physiological or pathological states (224).
Animal studies have identified two metabolite
classes negatively associated with peripheral WBC decline:
ω-carboxylic fatty acids (such as valeric acid-ω-carboxylic acid,
C5H10O3; hexanoic
acid-ω-carboxylic acid, C6H12O3)
and glutamic acid. Elevated ω-carboxylic fatty acids, intermediates
of β-oxidation, may indicate disrupted energy metabolism in the
bone marrow hematopoietic microenvironment (225). Conversely, reduced glutamic acid
levels may reflect impaired immune cell production or function,
showing causal links with WBC reduction (226).
These findings suggest exhaled breath metabolites
as promising non-invasive markers of hematopoietic impairment.
Portable devices enable real-time, bedside analysis, making this
approach particularly valuable for long-term surveillance of
exposed workers or patients undergoing chemotherapy (227). Preliminary cohort data from
benzene-exposed workers show correlation coefficients (r=−0.62 to
−0.71) between exhaled
C5H10O3/C6H12O3
and WBC counts, consistent with animal results (r=−0.58 to −0.67),
thereby confirming translational potential (228–230).
Single biomarkers often fail to capture low-dose
pollutant exposure-effect relationships due to limited specificity,
interference and narrow coverage (231). By contrast, the multi-marker
integration strategy achieves a comprehensive evaluation of
exposure intensity and accumulated damage by combining multiple
biomarkers across temporal and mechanistic dimensions (230–232). This approach has been validated
in low-dose exposure scenarios involving benzene, formaldehyde, and
polycyclic aromatic hydrocarbons (PAHs) (231).
The strategy of ‘interference correction + effect
complementation’ improves exposure assessment accuracy, therefore,
improving low-dose exposure assessment (232). For instance, tt-MA, a specific
benzene metabolite, can be confounded by smoking and dietary
factors, as urinary tt-MA levels in smokers are ~4-fold higher than
in non-smokers (233). A study on
benzene-exposed workers proposed a composite detection protocol
integrating tt-MA, PAH-DNA adducts (PLG) and peripheral blood
micronucleus frequency: i) tt-MA, reflects short-term exposure (1–3
days); interference corrected via smoking questionnaires (234); ii) PLG, indicates medium-term
cumulative exposure (half-life 1–3 months), unaffected by smoking
(235); and iii) micronucleus
frequency, reflects chromosomal damage, establishing a causal link
between exposure and genotoxicity (236). This combined approach achieved
89% accuracy in identifying low-dose benzene exposure (8 h TWA
<0.5 mg/m3), compared with 62% using tt-MA alone
(237).
Multi-marker integration can be structured along
exposure timelines, forming a chain of ‘acute response-cumulative
damage’, therefore, allowing dynamic monitoring. Acute phase (hours
to days): Short half-life metabolic biomarkers (such as tt-MA and
SPMA) allow rapid detection (238). For example, in the 2024 styrene
storage tank leakage incident, urinary SPMA screening within 6 h
identified three overexposed workers, preventing acute poisoning
(239). Cumulative phase (months
to years): Long half-life biomarkers (hemoglobin adducts, DNA
adducts) and epigenetic markers (STAT3 methylation) are
employed (240). Workers with
>5 years of benzene exposure showed a STAT3 methylation
positivity rate of 68 vs. 21% in those exposed <1 year, with
methylation levels negatively associated with WBC count (241).
Clinical applications are increasingly adopting a
combined panel of acute, cumulative, and epigenetic biomarkers in
annual occupational health surveillance. Tracking biomarker
trajectories over 3 years enables prediction of hematopoietic
impairment 1–2 years in advance, extending the early warning window
beyond traditional hematological testing (242).
Taken together, exhaled breath metabolomics and
multi-biomarker integration strategies represent two complementary
directions at the frontier of benzene exposure monitoring (243). Exhaled breath metabolomics, with
its advantages of non-invasiveness, convenience and real-time
assessment, provides novel insights into dynamic changes in
hematopoietic function and holds translational promise for
large-scale occupational surveillance (244). Multi-marker integration, by
combining exposure biomarkers, effect biomarkers and epigenetic
signatures, overcomes the inherent limitations of single indicators
and enables a more comprehensive evaluation of both short-term
exposure and long-term cumulative effects (245).
To actualize this paradigm shift, AI and machine
learning (ML) algorithms are increasingly being employed to decode
complex multi-omics datasets. Advanced ML models, such as Random
Forest and Support Vector Machines, excel at identifying non-linear
patterns within high-dimensional metabolomic and genomic data
(246). By feeding simultaneous
variables-such as exhaled ω-carboxylic fatty acids, genetic
polymorphisms (GSTM1 null) and traditional metabolites
(SPMA)-into these AI algorithms, researchers can construct robust
predictive models (247). These
AI-driven frameworks not only enhance the accuracy of detecting
low-dose exposures but also automatically stratify workers into
personalized risk tiers, alerting occupational physicians to
sub-clinical hematotoxicity before irreversible bone marrow failure
occurs (248).
Looking ahead, these approaches are expected to
converge into integrated monitoring frameworks that leverage
high-throughput omics platforms and AI-driven data analytics
(246). Such frameworks may
facilitate the construction of individualized biomarker panels that
are predictive of early hematotoxicity and long-term carcinogenic
risks (247). To operationalize
the dynamic monitoring paradigm illustrated in Fig. 6, we propose a hierarchical strategy
for integrated benzene health surveillance (Table IV). This approach stratifies
occupational monitoring into four actionable clinical tiers,
ranging from acute exposure screening (Tier 1) to lifetime
susceptibility profiling (Tier 4). However, despite the promise of
exhaled breath metabolomics (Tier 2) and epigenetic profiling (Tier
3), their routine implementation in large-scale occupational
surveillance faces notable clinical and logistical hurdles
(246,247). Cost-effectiveness remains a
primary barrier, as high-resolution LC-MS/MS or epigenetic
sequencing is substantially more expensive than traditional
complete blood counts. Furthermore, deploying portable analytical
devices, such as PTR-MS, in resource-limited factory settings
presents standardization challenges. The stability of breath
metabolites can be severely compromised by field conditions,
including high ambient humidity and fluctuating factory
temperatures. Therefore, optimizing sample collection protocols and
developing robust point-of-care devices are prerequisite steps
before these advanced tiers can be broadly integrated into
occupational health guidelines (248).
Benzene remains a pervasive occupational hazard,
inducing profound multi-systemic toxicity that extends far beyond
classic hematopoiesis to encompass neurotoxic, cardiovascular and
reproductive impairments. Despite decades of research, traditional
reactive monitoring strategies, heavily reliant on late-stage
hematological indices and low-specificity markers such as urinary
phenol, are inadequate for chronic low-dose exposure scenarios
(245–248).
The present review underscores a necessary paradigm
shift. The integration of high-specificity exposure markers (SPMA),
advanced effect markers (exhaled breath metabolomics) and
susceptibility profiling (GSTM1/CYP2E1 polymorphisms)
provides a robust foundation for early warning systems. Notably,
the pronounced ethnicity disparities in genetic susceptibility
dictate that a ‘one-size-fits-all’ regulatory approach is no longer
tenable; future OELs must be re-evaluated through the lens of
population-specific genetic vulnerability. Moving forward, bridging
the gap between molecular insights and occupational health
applications requires overcoming logistical barriers-such as the
cost and field-stability of multi-omics tools-and harnessing
AI-driven analytics to manage complex biomarker datasets. By
transitioning to proactive, individualized and multi-dimensional
biomarker frameworks, occupational health authorities can achieve
precision risk stratification, ultimately mitigating the global
burden of benzene-induced malignancies and systemic diseases.
The authors would like to acknowledge Professor Dr
Li Sheng and Mr. Li Wang from Chongqing Medical and Pharmaceutical
College (Chongqing, China) for their invaluable contributions to
the data collection process; their meticulous efforts ensured the
accuracy and reliability of the research findings.
The authors declare that financial support was received for the
research, authorship and publication of this article. The present
work was funded by the Scientific Research Project of AnShun
University, Guizhou Province [grant nos. asxybsjj (202307) and
asxykypt (202402)], the Natural Science Research Project of Guizhou
Provincial Department of Education (grant no. Qian Jiao He KY
[2020] No. 063), the Guizhou Provincial Department of Education
(grant no. Qian Ke He KY [2013] No. 130), the Guizhou Provincial
Department of Science and Technology (grant no. Qian Ke He LH
[2015] No. 7687), the 2023 Chongqing Medical Scientific Research
Project (Joint Project of Chongqing Health Commission and Science
and Technology Bureau) (grant no. 2023GGXM006), the Joint Project
of Chongqing Health Commission and Science and Technology Bureau
(Joint Key Laboratory Open Project) (grant no. 2026KFXM051), the
Chongqing Municipal Education Commission Youth Project (grant nos.
KJQN202402821 and KJQN202502819), the Natural Science Foundation of
Chongqing (grant no. CSTB2025NSCO-GPX1116), the 2026 Key Project of
Special Scientific Research of First Affiliated Hospital of
Chongqing Medical and Pharmaceutical College (grant no.
YGZZKFS2026104) and The Key Laboratory Project of Chongqing Medical
and Pharmaceutical College (grant no. YGZPT2025101).
Not applicable.
YH, ZX, JM and XL contributed to the writing of the
original draft and the preparation of figures. YH contributed to
the systematic literature search, data extraction, and synthesis of
the reviewed studies. JM and XL reviewed and edited the manuscript,
and provided supervision. All authors read and approved the final
version of the manuscript. Data authentication not applicable.
Not applicable.
Not applicable.
The authors declare that they have no competing
interests.
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