publications

Firefighters have elevated rates of urinary tract cancers and other adverse health outcomes, which may be attributable to environmental occupational exposures. Untargeted metabolomics was applied to characterize this suite of environmental exposures and biological changes in response to occupational firefighting. 200 urine samples from 100 firefighters collected at baseline and two to four hours post-fire were analyzed using untargeted liquid-chromatography and high-resolution mass spectrometry. Changes in metabolite abundance after a fire were estimated with fixed effects linear regression, with false discovery rate (FDR) adjustment. Partial least squares discriminant analysis (PLS-DA) was also used, and variable important projection (VIP) scores were extracted. Systemic changes were evaluated using pathway enrichment for highly discriminating metabolites. Metabolome-wide-association-study (MWAS) identified 268 metabolites associated with firefighting activity at FDR q < 0.05. Of these, 20 were annotated with high confidence, including the amino acids taurine, proline, and betaine; the indoles kynurenic acid and indole-3-acetic acid; the known uremic toxins trimethylamine n-oxide and hippuric acid; and the hormone 7a-hydroxytestosterone. Partial least squares discriminant analysis (PLS-DA) additionally implicated choline, cortisol, and other hormones. Significant pathways included metabolism of urea cycle/amino group, alanine and aspartate, aspartate and asparagine, vitamin b3 (nicotinate and nicotinamide), and arginine and proline. Firefighters show a broad metabolic response to fires, including altered excretion of indole compounds and uremic toxins. Implicated pathways and features, particularly uremic toxins, may be important regulators of firefighter’s increased risk for urinary tract cancers.

Introduction: Firefighters face regular exposure to known and probable human carcinogens, such as polycyclic aromatic hydrocarbons (PAHs), benzene, and formaldehyde, leading to an increased risk of various cancers compared to the general population. Hispanic and black firefighters are at increased risk of additional cancers not elevated in non-Hispanic white firefighters, yet biological pathways underlying these differences are unknown. Objectives: The study objectives were to evaluate differences in the urinary metabolome between Hispanic and non-Hispanic firefighters, pre-and post-fireground exposure. Methods: To investigate the metabolic patterns, we employed a comprehensive metabolomics pipeline that leveraged liquid chromatography coupled with high-resolution mass spectrometry. We applied linear mixed effects regression to identify the differential metabolites at an FDR <0.05 among 19 Hispanic and 81 non-Hispanic firefighters. We also performed overrepresentation analysis using Mummichog to identify enriched pathways at FDR <0.05. Results Out of 175 features in HILIC(-) mode and 1847 features in RP(+) mode, we found 26 and 276 differential urinary features, respectively, when comparing Hispanic and non-Hispanic firefighters. We noted pathway enrichment in tryptophan and galactose metabolism. However, post-exposure, we did not observe differences in the metabolomic response by ethnicity despite differing fireground exposures.Conclusion: Dysregulation in the tryptophan and galactose pathway is an important contributor to cancer risks and may explain the increased cancer risk among Hispanic firefighters.

Background: Firefighters have frequent exposure to carcinogens and consequently an increased risk of cancer. Wildland-urban interface (WUI) fires, which involve both wildland and structure fires, pose special challenges to firefighters’ health. However, the extent of health risks associated with these fires remains largely underexplored. Objectives: This study aimed to identify dysregulated urine metabolites and metabolic processes among male firefighters that were associated with WUI as compared with municipal structure fire exposure. Method: High-throughput metabolomics was applied to baseline and postfire urine samples collected from male firefighters responding to WUI (N= 87 participants) or municipal structure (N= 100 participants) fires. Differential analysis was conducted by fitting linear mixed effects regression models on preprocessed ion intensity and exposure status while adjusting for demographic covariates. Differential metabolites were identified by false discovery rate (FDR)<0.05 threshold. Overrepresentation analysis and gene-set enrichment analysis were performed to identify pathways that were disturbed at p-value<0.05. Results: We conducted high resolution untargeted metabolomic analyses using urine samples from WUI and structure fires using four different modes: HILIC(-), HILIC(+), C18(-), and C18(+), and identified metabolites against an in-house library. After controlling family-wise error rate at 0.05 level, we identified 244, 297, 320, and 266 metabolites with level-1 annotation confidence from HILIC(-), HILIC(+), C18(-), and C18(+) modes, respectively. The main model identified 16, 51, 66, and 43 differential metabolites for the same respective modes, from WUI fires. For municipal structure fires, we identified 104, 191, 208, and 149 differential metabolites for the respective modes. We also reported that 7 pathways were significantly enriched after WUI fires, while 4 pathways were significantly enriched after municipal structure fires at the p-value 0.05 level. Notably, valine, leucine, and isoleucine degradation and glycine, serine, and threonine metabolism were found to be following both types of fires at p-value 0.1 level. No overlapping pathways were reported at 0.05 level. Conclusion: WUI and municipal structure fires induced numerous metabolic perturbations in firefighters that may partially explain the elevated cancer risks in firefighters.

The occupation of firefighting is classified as a Group 1 carcinogen. Increased cancer risk among firefighters may be partly attributable to increased occupational exposure to a range of chemicals, including to per- and polyfluoroalkyl substances (PFAS). PFAS contain known and suspect human carcinogens. Investigating epigenetic response to PFAS exposures in firefighters may help to identify biological pathways and specific cancers, and previously unidentified health outcomes that are associated with PFAS. We therefore investigated the associations of serum PFAS levels with miRNA expression in firefighters. Blood samples collected from 303 firefighters from 6 sites across the USA were tested for 9 PFAS analytes along with miRNA expression. Linear regression was used to estimate associations between log PFAS and miRNA expression, with false discovery rate (FDR) set to 0.05 for significance, and an exploratory cutoff of FDR q<0.20. Gene set enrichment analysis (GSEA) was performed using miRTarBase’s miRWalk pathways. Age, race-ethnicity, BMI, fire department, and gender were controlled for in all models. At FDR<0.05, linear perfluorooctanesulfonic acid (n-PFOS) was inversely associated with hsa-miR-128-1-5p expression (Beta = -0.146, 95% CI -0.216, -0.076). At a relaxed FDR of 0.20, we observed inverse associations for the sum of perfluoromethylheptane sulfonate (branched) isomers (Sm-PFOS) with 5 miRNAs (hsa-let-7d-5p, hsa-let-7a-5p, hsa-miR-423-5p, hsa-let-7b-5p, has-mir-629-5p). Several pathways were enriched for multiple PFAS, including several cancers, blood diseases, autoimmune disorders, and neurological outcomes. PFAS in firefighters were found to be associated with alteration of miRNA consistent with increased risk for a range of chronic diseases.

Background: Long COVID can be debilitating due to lingering symptoms. However, there is incomplete information on the mechanistic understanding of long-COVID, and if proteomic profiles of individuals prior to development of COVID-19 can predict long-COVID status.. Objective: To investigate whether proteomic profiles of frontline workers at baseline, during convalescence for COVID-19, and/or at follow-up were associated with long COVID. Method: Frontline and essential workers in the HEROES-RECOVER cohorts were tested weekly for COVID-19 from 2020-2022. Participants with COVID-19 and those with long COVID were selected for untargeted proteomic profiling using the SOMAscan Assay at baseline, convalescence, and follow-up. We used penalized logistic regression to identify important feature proteins (SOMAmers) at each time point that were associated with long-COVID status at follow-up, at false discovery rate (FDR) q <0.05 level . We controlled for x y z. Pathway analysis was applied at each time point to identify pathways enriched among long-COVID compared to normal COVID participants, at FDR q<0.05 and, in exploratory analyses, at q <0.20. Results: Talk about sample; describe proteomics results. 116 SOMAmers were differentially expressed between workers with long COVID (n=57) and normal COVID (n=80) at FDR q < 0.05 and fold-change 1.5, including 41 at baseline, 40 at convalescence, and 35 at follow-up visit. Of these, 8 differential SOMAmers were unique to convalescence and 7 were unique to follow-up. The penalized logistic regression model identified the SOMAmers thyroglobulin and pseudouridylate synthase 7 homolog as predictive of long COVID status, at both baseline and follow-up, but not during convalescence. When comparing long COVID to normal COVID, pathway analysis revealed enrichment of alcoholism and neutrophil extracellular trap formation both at convalescence (q<0.05), and alcoholism and necroptosis at follow up (q<0.05). Conclusion: Our findings in frontline workers suggest potential new mechanisms for long COVID, possible proteins that indicate susceptibility to long COVID, and support a previously described effect on proteins in the alcoholism pathway during convalescence and followup. Further targeted studies are required to validate the ability of these proteins to predict long COVID, and the effect of long-COVID on alcohol- and necroptosis related proteins.