Changes in Serum Proteins in Firefighters Responding to the 2025 Los Angeles Urban Conflagrations

Abstract

Objective:

The study goal was to evaluate changes in serum proteins following firefighter exposure to the January 2025 Los Angeles area urban conflagrations.

Methods:

The serum proteome was evaluated in 42 firefighters enrolled in the Fire Fighter Cancer Cohort Study (FFCCS) with blood specimens collected in 2024 and in January and February of 2025, an average of 8.6 days after their most recent response to the urban conflagrations.

Results:

Sixty proteins changed significantly from before to after exposure. These proteins were associated with nucleotide synthesis and repair, oxidative stress response, energy metabolism, and other mechanisms. Pathway analysis identified changes in metabolism and oxidative stress, immune and inflammatory responses, cellular barrier integrity and trafficking, and growth/cancer signaling.

Conclusions:

Response to the Los Angeles area urban conflagration was associated with a change in the serum proteome of firefighters.

Graphical Abstract

Introduction:

The Palisades and Eaton fires started on January 7, 2025, spread rapidly due to Santa Ana winds, and burned >23,000 and 14,000 acres, respectively, prior to full containment on January 31 ¹. While residents of the affected areas were evacuated, >7,500 firefighters and other emergency personnel responded to the fires ². Both fires started in the wildland-urban interface (WUI), but quickly became urban conflagrations burning entire structures, vehicles, and other materials and releasing toxic products of combustion. Responding firefighters were exposed to intense amounts of smoke and soot, almost always without respiratory protection.

While firefighters are at increased risk for multiple cancers as determined by the International Agency for Research on Cancer ³, the additional risks of cancer and other diseases associated with responding to urban conflagrations are expected to be greater. Many firefighters who responded to the Los Angeles (LA) area urban conflagrations are comparing their response to the World Trade Center fire and collapse, calling their fires a “west coast 9/11”. The World Trade Center response was associated with significant increases in melanoma and prostate, thyroid, and tonsil cancer rates ⁴, as well as cognitive impairment ⁵.

The LA area urban conflagrations are likely to have released large quantities of pollutants to which firefighters were exposed. Our research group has previously shown that responding to WUI fires is associated with biomarkers of increased cancer risk beyond those associated with regular firefighting activities alone ⁶. However, while serum proteins are important predictors of future diseases ⁷, and wildland firefighters have increased serum inflammatory markers following exposure ⁸, there is currently no information on the acute or chronic health effects of urban conflagrations or the impact of WUI fires on the serum proteome. The Fire Fighter Cancer Cohort Study (FFCCS) collected blood and urine from LA area firefighters in 2024, prior to the fires, and followed up with some of these firefighters Jan 27-Feb 27, 2025, after the fires. This provided a unique opportunity to evaluate changes from baseline to post-exposure in firefighters who fought the LA area urban conflagrations.

Methods:

Study participants

All study participants were enrolled in the FFCCS, a prospective cohort with regular biomonitoring that serves firefighters in the LA region and throughout the United States. The FFCCS, established in 2016 through initial funding from the Federal Emergency Management Agency (FEMA), is a 30-year study evaluating exposures, toxicity resulting from these exposures, and risks for future cancer and other health outcomes prioritized by the fire service, such as reproductive and mental health and neurodegenerative diseases. The FFCCS study protocol has been previously described in detail ⁹. This study was approved by the University of Arizona Institutional Review Board (STUDY00002192). Informed consent was obtained from all study participants. In May through December of 2024, prior to the urban conflagrations, over 450 firefighters in southern California, mostly in the greater LA area, had enrolled in an FFCCS study evaluating per- and polyfluoroalkyl substances (PFAS) serum concentrations, and blood and urine samples collected at this time were processed and stored at −80°C in the FFCCS biorepository. As of Feb 27, 2025, 123 of these firefighters had been followed up after the LA urban conflagrations ended, including 63 firefighters who had spent at least one shift responding to the urban conflagration fires.

Biological Specimen Collection and Analyses

Serum samples were collected by a trained phlebotomist, paramedic, or nurse, and were transported to the University of Arizona laboratory for processing and storage as previously described ⁹. Baseline and post-conflagration serum samples collected from the first 42 of the 63 participants responding to urban conflagrations were sent for proteomic testing using the SomaScan Assay (SomaLogic^®, Boulder, CO) which quantified the abundance of 11,000 proteins in each sample. Serum samples were sent frozen on dry ice to the SomaLogic laboratory, where samples were bound to SOMAmers. Then the samples underwent partitioning and wash steps followed by hybridization to microarrays. Quality control procedures included calibration controls, blanks, and replicates in each sample batch. The recommended data standardization pipeline to remove assay and sample bias from the assay were followed, providing standardized relative abundance (measured in relative fluorescent units for each SOMAmer (annotated protein) in a sample. The standardization pipeline applies several normalization, calibration, and other quality control steps, which are described in greater detail on the SomaLogic website ¹⁰. All samples passed quality control checks performed after each step.

Statistical Analyses

Linear mixed effects regression was applied with a random effect for participant, and fixed effects for timepoint, fire department, and age to evaluate whether proteins changed from baseline to post-fire. The effect estimate for timepoint is reported as a fold change, which reflects the average fold change for follow-up compared to baseline. A false discovery rate (FDR) cut-off of q<0.05 was employed, and for all proteins that met the FDR cutoff both raw and corrected p-values are reported. SOMAmers were annotated to their genes with the SomaScan provided annotation database. To evaluate pathways, gene set enrichment analyses for KEGG pathways was used based on the ranked p-values for all SOMAmers, using the associated Entrez ID. Pathways were limited to pathway sizes with a minimum of 5 and a maximum of 500 genes. Analyses were performed using the fgseaMultiLevel function, an adaptive multilevel splitting Monte Carlo approach. Significant pathways are those with an FDR cut off of q<0.05.

Results:

The study participants were predominantly male (n=40, 95.2%) and averaged 42.5 years of age (sd=7.9) and 17.6 years (sd=7.8) in the fire service. All were career firefighters and were directly involved in fire suppression activities. Twenty-four participants were from The Los Angeles City Fire Department, with the remaining from Orange County Fire Authority and Oxnard Fire Department. Of the 42 total participants, 38 reported their start and end date of response, while four were uncertain about the start and/or end dates. Of the 38, 31 (82%) responded during the initial four days of the urban conflagrations, when the firefighters reported the heaviest exposures. At the time of post-fire blood collection, the time since the participating firefighters’ last response to the urban conflagration fires averaged 8.6 days, with a range of 0 to 44.

Out of approximately 11,000 SOMAmers tested, 60 were significantly different between baseline and post-exposure after FDR correction (Table 1). Most of these proteins were upregulated after responding to the fire. This list of proteins includes those that may be particularly relevant for detoxification, inflammation, and oxidative stress in response to the LA fires, including PRDX3, HSD17B10, LanCL2, annexins, the protein kinase c isoforms, NAP1L1, NAP1L4, and RBBP7.

Table 1.

Average fold change for individual serum proteins pre-post LA fires (n=42, FDR q<0.05)

SOMAmer	Fold Change	Annotated Gene Description	Entrez ID	Raw p-value	FDR q value
seq.4187.49	1.058 (1.034, 1.084)	phosphogluconate dehydrogenase	PGD	2.5e-05	3.3e-02
seq.10088.37	1.054 (1.029, 1.079)	adenine phosphoribosyltransferase	APRT	1.1e-04	4.3e-02
seq.21147.9	1.051 (1.029, 1.074)	fructosamine 3 kinase	FN3K	3.6e-05	3.3e-02
seq.15607.56	1.049 (1.025, 1.073)	pyruvate kinase L/R	PKLR	1.8e-04	4.4e-02
seq.10039.32	1.044 (1.023, 1.065)	purine nucleoside phosphorylase	PNP	1.5e-04	4.3e-02
seq.12628.31	1.044 (1.023, 1.065)	LanC like glutathione S-transferase 2	LANCL2	1.6e-04	4.3e-02
seq.23363.41	1.043 (1.022, 1.063)	poly(rC) binding protein 2	PCBP2	1.5e-04	4.3e-02
seq.15435.4	1.041 (1.021, 1.061)	purine nucleoside phosphorylase	PNP	1.8e-04	4.4e-02
seq.29233.4	1.040 (1.022, 1.057)	copine 2	CPNE2	5.7e-05	3.5e-02
seq.14203.3	1.039 (1.022, 1.057)	annexin A7	ANXA7	6.2e-05	3.6e-02
seq.29154.87	1.039 (1.021, 1.057)	ubiquitin conjugating enzyme E2 O	UBE2O	7.4e-05	3.9e-02
seq.25033.194	1.039 (1.021, 1.057)	valosin containing protein	VCP	1.1e-04	4.3e-02
seq.12395.86	1.039 (1.020, 1.059)	aspartyl-tRNA synthetase 2, mitochondrial	DARS2	2.7e-04	5.0e-02
seq.26038.1	1.039 (1.020, 1.057)	copine 3	CPNE3	1.4e-04	4.3e-02
seq.20167.6	1.038 (1.020, 1.057)	RAB8B, member RAS oncogene family	RAB8B	1.4e-04	4.3e-02
seq.19188.21	1.038 (1.020, 1.057)	nucleosome assembly protein 1 like 4	NAP1L4	2.0e-04	4.5e-02
seq.3868.8	1.038 (1.020, 1.056)	small glutamine rich tetratricopeptide repeat co-chaperone alpha	SGTA	1.3e-04	4.3e-02
seq.5225.50	1.038 (1.018, 1.057)	casein kinase 2 beta	CSNK2B	2.1e-04	4.5e-02
seq.5225.50	1.038 (1.018, 1.057)	casein kinase 2 alpha 1	CSNK2A1	2.1e-04	4.5e-02
seq.18244.1	1.037 (1.021, 1.053)	annexin A7	ANXA7	5.1e-05	3.3e-02
seq.17513.11	1.035 (1.020, 1.050)	annexin A11	ANXA11	4.3e-05	3.3e-02
seq.4960.72	1.034 (1.021, 1.048)	annexin A1	ANXA1	9.8e-06	3.3e-02
seq.30830.164	1.033 (1.018, 1.049)	N-glycanase 1	NGLY1	1.1e-04	4.3e-02
seq.13969.24	1.033 (1.017, 1.049)	karyopherin subunit alpha 6	KPNA6	1.5e-04	4.3e-02
seq.19150.20	1.033 (1.017, 1.049)	phosphoribosyl pyrophosphate synthetase associated protein 2	PRPSAP2	1.5e-04	4.3e-02
seq.5475.10	1.031 (1.018, 1.045)	protein kinase C beta	PRKCB	2.7e-05	3.3e-02
seq.19262.219	1.030 (1.017, 1.044)	acyl-CoA dehydrogenase very long chain	ACADVL	3.7e-05	3.3e-02
seq.5346.24	1.030 (1.017, 1.044)	copine 1	CPNE1	7.5e-05	3.9e-02
seq.18309.18	1.030 (1.015, 1.044)	citrate synthase	CS	2.5e-04	4.7e-02
seq.21752.10	1.029 (1.017, 1.041)	ras homolog family member T1	RHOT1	2.3e-05	3.3e-02
seq.13636.20	1.028 (1.015, 1.042)	nucleosome assembly protein 1 like 1	NAP1L1	1.3e-04	4.3e-02
seq.33659.9	1.027 (1.014, 1.039)	RB binding protein 7, chromatin remodeling factor	RBBP7	1.5e-04	4.3e-02
seq.17819.30	1.026 (1.013, 1.038)	fumarylacetoacetate hydrolase domain containing 1	FAHD1	1.5e-04	4.3e-02
seq.15534.26	1.026 (1.013, 1.038)	malate dehydrogenase 2	MDH2	2.5e-04	4.7e-02
seq.8358.30	1.024 (1.014, 1.033)	peroxiredoxin 3	PRDX3	1.4e-05	3.3e-02
seq.31905.18	1.023 (1.012, 1.035)	muskelin 1	MKLN1	2.6e-04	4.9e-02
seq.2644.11	1.022 (1.012, 1.033)	protein kinase C alpha	PRKCA	1.3e-04	4.3e-02
seq.23665.35	1.022 (1.011, 1.032)	proteasome 26S subunit, ATPase 3	PSMC3	2.1e-04	4.5e-02
seq.20433.19	1.022 (1.011, 1.032)	mitochondrial ribosomal protein L1	MRPL1	2.1e-04	4.5e-02
seq.2668.70	1.021 (1.011, 1.031)	calpain small subunit 1	CAPNS1	1.2e-04	4.3e-02
seq.2668.70	1.021 (1.011, 1.031)	calpain 1	CAPN1	1.2e-04	4.3e-02
seq.17333.20	1.020 (1.011, 1.030)	acyl-CoA dehydrogenase medium chain	ACADM	1.6e-04	4.3e-02
seq.5009.11	1.020 (1.011, 1.030)	moesin	MSN	1.8e-04	4.4e-02
seq.4217.49	1.020 (1.011, 1.029)	hydroxysteroid 17-beta dehydrogenase 10	HSD17B10	5.0e-05	3.3e-02
seq.19251.56	1.018 (1.010, 1.027)	serglycin	SRGN	1.8e-04	4.4e-02
seq.17345.12	1.018 (1.009, 1.027)	prostaglandin reductase 3	PTGR3	2.0e-04	4.5e-02
seq.23620.16	1.017 (1.010, 1.024)	RCSD domain containing 1	RCSD1	2.0e-05	3.3e-02
seq.9952.57	1.017 (1.010, 1.023)	transcription factor A, mitochondrial	TFAM	1.3e-05	3.3e-02
seq.2876.74	1.017 (1.009, 1.025)	DNA topoisomerase I	TOP1	1.6e-04	4.3e-02
seq.35474.11	1.016 (1.008, 1.023)	plectin	PLEC	1.2e-04	4.3e-02
seq.34923.29	1.014 (1.008, 1.020)	hydroxyacyl-thioester dehydratase type 2	HTD2	3.0e-05	3.3e-02
seq.30318.146	1.013 (1.007, 1.020)	SEC23 homolog B, COPII coat complex component	SEC23B	2.4e-04	4.7e-02
seq.19258.24	1.010 (1.005, 1.014)	glutaryl-CoA dehydrogenase	GCDH	8.2e-05	3.9e-02
seq.30423.32	1.009 (1.005, 1.013)	acyl-CoA thioesterase 9	ACOT9	2.5e-05	3.3e-02
seq.3067.67	1.007 (1.003, 1.010)	growth differentiation factor 9	GDF9	2.4e-04	4.7e-02
seq.11258.41	1.005 (1.003, 1.007)	mucosal vascular addressin cell adhesion molecule 1	MADCAM1	7.8e-05	3.9e-02
seq.7693.13	0.996 (0.994, 0.998)	TNF receptor superfamily member 10b	TNFRSF10B	2.2e-04	4.5e-02
seq.11669.39	0.995 (0.993, 0.997)	solute carrier organic anion transporter family member 5A1	SLCO5A1	4.8e-05	3.3e-02
seq.12758.47	0.994 (0.992, 0.997)	glutamate ionotropic receptor delta type subunit 2	GRID2	4.0e-05	3.3e-02
seq.8908.14	0.994 (0.992, 0.996)	potassium voltage-gated channel subfamily E regulatory subunit 5	KCNE5	1.5e-05	3.3e-02
seq.26660.95	0.994 (0.991, 0.997)	beta-secretase 1	BACE1	1.9e-04	4.4e-02
seq.14759.149	0.993 (0.989, 0.996)	cadherin 1	CDH1	2.5e-04	4.7e-02

^*Estimates are derived from a linear mixed effects regression with a random effect for participant, controlling for fire department, age, and timepoint. Reported fold change is the exponentiated beta coefficient for timepoint (binary, 0=baseline, 1=post-LA fire). Results are arranged by fold change magnitude and estimates with FDR<0.05 are shown.

In gene set enrichment analyses, we observed enrichment for 24 pathways, with the lowest p-value for purine metabolism and highest enrichment score for one carbon pool by folate (Figure 1). Generally, enriched pathways included those related to metabolism and oxidative stress (purine metabolism, pentose phosphate, glycolysis, one carbon), immune and inflammatory responses (chemokine, Fc Gamma receptor-mediated phagocytosis, B cell receptor signaling, lupus, E. coli), cellular barrier integrity and trafficking (endocytosis, tight junction, focal adhesion), and growth/cancer signaling (MAPK, VEGF, renal carcinoma, chemokine, one carbon folate). Other enriched pathways were related to neurological outcomes (neurotrophin, long-term depression).

Figure 1.

KEGG Pathways* over-enriched after LA fires in Gene Set Enrichment Analysis

*Pathways are limited to those with a minimum of 5 and a maximum of 500 genes. We used the Entrez ID linked to the associated Somamers, as per the SOMAScan annotation database, and performed analyses using the fgseaMultiLevel function, an adaptive multilevel splitting Monte Carlo approach. Results shown here are only those with FDR<0.05.

Discussion:

Firefighters responding to the 2025 LA area urban conflagrations had significant changes in their serum proteome when comparing samples collected before and after the fires. Of the 60 serum proteins that significantly changed, many were associated with detoxification, inflammation, and oxidative stress. The top five altered proteins (based on magnitude of fold change from baseline to post-incident), included phosphogluconate dehydrogenase (PGD), adenine phosphoribosyltransferase (APRT), fructosamine 3 kinase (FN3K), pyruvate kinase L/R (PKLR), and purine nucleoside phosphorylase (PNP). Each of these five proteins fall under one of the following mechanistic categories: nucleotide synthesis and repair, oxidative stress response, or energy metabolism ^11–15.

The upregulation of these proteins is likely due in large part to the exposure to complex mixtures while WUI firefighting and urban conflagration firefighting. These exposures include, but are not limited to, polycyclic aromatic hydrocarbons, benzenes, fine and course particulate matter, heavy metals, and volatile organic compounds, which have been linked to adverse cardiovascular, respiratory, and neurological effects, and some cancers ¹⁶. Beyond these toxicants, firefighters were also likely exposed to chemicals released from structural and/or vehicle fires, such as but not limited to per- and polyfluoroalkyl substances (PFAS) and brominated and other flame retardants. While to our knowledge no PFAS-containing firefighting foams were used by the firefighters participating in this study, increased PFAS exposure has been measured through silicone wristbands with firefighter responses to structural fires, along with brominated flame retardants (BFRs) and some organophosphate esters ¹⁷.

A selection of the most over-enriched pathways (based on p-value or enrichment score), included purine metabolism and aminoacyl tRNA biosynthesis, systemic lupus erythematosus, MAPK signaling, one carbon pool by folate, and chemokine signaling. Each are briefly discussed below.

Aminoacyl tRNA biosynthesis and purine metabolism:

Pathways related to aminoacyl tRNA biosynthesis and purine metabolism increased after responding to the urban conflagrations. Aminoacyl-tRNA synthesis, a requisite step in protein synthesis that may also have other physiological functions beyond protein translation ^18–22, is likely a part of the overall adaptive response of the body to the exposure to fire smoke. Similarly, the increases in the purine metabolism pathway may reflect an increased need for energy molecules (like NAD and ATP; e.g., to combat increased oxidative stress) or a need for new DNA or RNA synthesis or repair (which requires purines as building blocks) in fire smoke-exposed individuals. Notably, increases in purine metabolism could result in higher body burden of uric acid, the primary product of purine metabolism and the cause of hyperuricemia and associated kidney injury and other diseases ^23–27. These data suggest the need for measurement of uric acid levels in exposed individuals; if they are increased then it may be helpful for these firefighters to reduce consumption of foods that are high in purine.

Lupus:

The proteins that changed in abundance post-fire were enriched in the systemic lupus erythematosus (SLE) disease pathway. SLE is a heterogeneous autoimmune disease with a range of severity and symptoms that can greatly impact quality of life. While associations between cigarette smoking, silica dust, solvents, and pesticides and SLE have been reported, many environmental triggers of this disease remain unknown ^28–30. Responders to the World Trade Center collapse with longer time at the incident or dust cloud exposure had increased incidence or risk, respectively, for developing systemic autoimmune diseases including SLE ^31,32 though evidence has been mixed ³³. In addition, particulate matter with a diameter of 2.5 micrometers or less (PM2.5) and other exposures in wildfire smoke are linked to mechanisms that lead to autoimmune disease including activation of autoreactive T-cells, oxidative stress, and dysregulation of inflammatory genes ³⁴. As previously stated, increased PFAS exposure has been measured in structural firefighters responding to fires ¹⁷. Although few studies have examined the association of PFAS with autoimmune disease, a study of alligators living in a PFAS-contaminated environment showed elevated autoimmune symptoms, including autoantibodies similar to those found in lupus ³⁵. In a previous study of structural firefighters, we observed associations between two PFAS (PFHxS and PFDA) and microRNA enriched in pathways related to lupus and rheumatoid arthritis ³⁶. Furthermore, BFR exposure has been associated with altered immune response ³⁷. Thus, it may be important to examine responders to the LA urban conflagrations for autoimmune biomarkers and symptoms in the years to come.

MAPK:

The mitogen activated protein kinase (MAPK) signaling pathway was also enriched amongst the proteins that changed from baseline to post fire. MAPK is an evolutionarily conserved signaling pathway that is an important regulator of immune function, inflammation, neurological health, and cancer risk. Prior studies of air pollution have shown that the MAPK pathway mediates health responses to particulate matter and volatile organic compounds, and that oxidative stress can induce MAPK activation, all of which are relevant for populations exposed to these products of combustion from fires ^38–41. Health effects of MAPK are diverse; MAPK regulates several aspects related to neurodegeneration and Alzheimer’s disease, specifically tau phosphorylation, neurotoxicity, neuroinflammation and synaptic dysfunction ⁴². MAPK also regulates several aspects related to cancer and can act both in a pro-oncogenic manner as well as a tumor suppressor. Finally, since MAPKs are generally activated by oxidative stress, approaches that promote antioxidant environments may help to keep the MAPK pathway in balance ⁴³.

One carbon folate:

The highest enrichment score in our KEGG pathway analysis was associated with the one carbon pool by folate pathway. One-carbon metabolism functions to transfer one-carbon units, primarily in the form of methyl groups, to support multiple physiological processes. The most notable processes include nucleotide synthesis, methylation reactions, and redox balance ^44,45. Exposures from firefighting have been linked to oxidative stress, epigenetic modifications, cancer, and other adverse health outcomes ⁴⁶. More specifically, previous studies have found increased markers of oxidative stress in response to wildland smoke exposure ^47,48. Additionally, a previous study among structural firefighters found significant changes in amino acid pathways associated with one-carbon metabolism from pre- to post-fire in urine samples ⁴⁹. Increased one-carbon folate metabolism among firefighters may be reflective of the body’s increased need for NADPH, DNA repair, and redox balance in response to smoke exposure.

Chemokine

The chemokine pathway had one of the top five enrichment scores in our pathway analysis. Chemokines are a class of cytokines involved in immune and inflammatory responses by stimulating the migration of leukocytes and other cells through binding to cell surface chemokine receptors ⁵⁰. Cigarette smoke exposure has been linked to alterations in cytokines and through this mechanism to increased lung cancer risk ⁵¹. Certain chemokines can have prognostic value, for example, CCL20 and hepatocellular carcinoma metastasis ⁵², and CCL14 and lung adenocarcinoma ⁵³. Among responders to the World Trade Center collapse, increased serum macrophage-derived chemokine (MDC) levels were associated with increased risk of airflow obstruction in subsequent years ⁵⁴. Furthermore, among incumbent firefighters compared to recruits, microRNA pathway analysis identified inflammation mediated by chemokine and cytokine signaling ⁵⁵. These data suggest the importance of future studies of anti-inflammatory treatment among firefighters after large scale events such as urban conflagrations or WUI fires.

It will be important to determine in future mechanistic studies whether the observed serum protein changes are due to direct effects from the chemicals in the fire smoke or to the various physiological changes associated with firefighting, or a combination of the two. However, since the blood samples used for proteomic analysis were collected for each participant an average of 8.6 days after their last urban conflagration firefighting event, the observed changes are less likely to reflect responses to physiological stresses such as from heat and/or high levels of exertion. For example, while sufficient exertion can acutely alter chemokines and other cytokines, the increase would be expected to return to baseline within 72 hours and in animal models heat stress induced chemokine changes are also relatively transient ^56,57, so the observed changes in firefighters are likely primarily due to the chemical exposures from the urban conflagrations.

Strengths and limitations

The strengths of the study included the ability to evaluate changes in serum proteins from before to after the fire responses, benefitting from earlier firefighter participation in aligned research within the FFCCS. The study also evaluated a large number of proteins using the SomaScan platform. To our knowledge, this is the first study that has been able to collect this kind of data on urban conflagrations. The limitations of the study include lack of serum proteomic analysis on comparison group of firefighters not responding to the LA area urban conflagrations, which we hope to be able to include in future studies. Lastly, this study lacked information on the specific chemical exposures experienced by the firefighters in this study during the urban conflagrations.

Conclusions:

Firefighter exposure to the LA area urban conflagration was associated with significant changes in the serum proteome. Altered proteins included those involved in nucleotide repair, metabolism, oxidative stress, immune and inflammatory responses, cellular barrier integrity and trafficking, and growth/cancer signaling. Specific altered pathways included purine metabolism and aminoacyl tRNA biosynthesis, systemic lupus erythematosus, MAPK signaling, one carbon pool by folate, and chemokine signaling. These findings suggest that exposed firefighters may be at increased risk of long-term adverse effects and should be monitored for persistence of the observed changes and for possible development of clinical disease.

Clinical Significance:

Firefighters responding to the 2025 Los Angeles urban conflagrations had serum protein changes associated with nucleotide repair, oxidative stress, and metabolism. Altered protein pathways included metabolism and oxidative stress, immune and inflammatory responses, cellular barrier integrity and trafficking, and growth/cancer signaling.

Learning Objectives:

• Describe how the serum proteome can be used to evaluate the effects of toxic exposures.

• Identify serum proteins and pathways significantly changed in firefighters responding to the 2025 Los Angeles area urban conflagrations

Data Availability:

Study data are not publicly available and final datasets are accessible by approved study staff.