BACKGROUND:The impact of wildfire smoke (WFS) on air quality across the contiguous US has become geographically widespread. However, the effects of WFS exposure on psychometric measures of mental and physical health remain largely unknown. OBJECTIVES:To assess the associations between WFS PM2.5 and black carbon (BC) exposure and psychometric health measures. METHODS:The St. George's Respiratory Questionnaire (SGRQ) and the 36-Item Short Form Survey (SF-36) were administered to participants in the Lovelace Smokers Cohort in New Mexico to assess psychometric health measures in the past 4 weeks. WFS estimates were calculated against Albuquerque metropolitan area for 7-, 15-, 30-, and 60-d prior to questionnaire completion. The associations between exposure and health measures were assessed using linear models. RESULTS:Associations were observed for all psychometric measures with WFS PM2.5 and BC exposures estimated for 7-day prior to questionnaire completion. These associations remained for WFS exposure estimated up to 30-day prior to questionnaire completion for all SGRQ subdomains and physical health measures of SF-36, whereas associations with the mental health component were more transient and primarily evident within one week. Additionally, WFS PM2.5 exhibited stronger potency than total ambient PM2.5. Male participants, individuals with less than a college education, and those exposed to woodsmoke demonstrated stronger associations with WFS exposure. CONCLUSIONS:Exposure to WFS was associated with worse SGRQ and SF-36 scores, with notable differences in temporal patterns between mental and physical health measures. Our findings also underscore the importance of source-specific risk assessment for air pollution.

Supplementary Figure 2. Forest plot of stratified analysis for DSS.

Abstract Background: Our previous studies have linked early menopause (early-M, <45 years) with increased risks of lung-related morbidities and mortalities. However, its relationship with other cancer types and the underlying biological and causal mechanisms remains unclear. Aim: To conduct a secondary analysis evaluating the associations between early-M and blood-based epigenetic aging biomarkers, and cancer risks and mortalities using the prospective Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial. Methods: Genome-wide DNA methylation (DNAm) profiles were available from baseline blood samples in 1,517 PLCO participants who subsequently developed breast cancer or who remained cancer-free. Epigenetic age acceleration was estimated using four established DNAm clocks, HorvathAge, HannumAge, PhenoAge, and GrimAge, as well as DNAm-based telomere length. An epigenome-wide association study (EWAS) was performed followed by pathway enrichment analysis and exploratory analyses integrating immune marker data. For cancer risk and mortality analyses, we included all postmenopausal women of European ancestry with natural menopause from the full PLCO cohort with genotype and phenotype data available (n = 31,022). A polygenic risk score (PRS) for age at natural menopause was constructed using 154 genetic variants identified from the NHGRI-EBI GWAS Catalog, after quality control based on imputation quality, minor allele frequency, Hardy-Weinberg equilibrium, linkage disequilibrium, and ambiguity filtering. The associations between this PRS and cancer incidences and mortalities were modeled using Cox proportional hazards regression. Results: Phenotypic early-M was associated with higher GrimAge acceleration (0.57 years, 95%CI=0.04, 1.10) in the 1,517 PLCO participants. EWAS and pathway analyses identified CpG sites enriched in estrogen response and immune regulation pathways, consistent with immune marker profiling that revealed upregulation of immune-related proteins among women with early-M. In the full trial, genetically predicted younger age at natural menopause (per 1 SD change) was associated with lower risks of breast cancer incidence (HR=0.14, 95%CI=0,12, 0.16) and longer survival (HR=0.27, 95%CI=0.19. 0.40), and lower risk for incidence of ovarian (HR=0.07, 95%CI=0.04, 0.11) and lung (HR=0.30, 95%CI=0.17, 0.50) cancers. In contrast, a higher incidence of bladder cancer (HR=3.34, 95%CI=1.05, 10.61) was observed. No significant associations were found for colon, melanoma, or hematologic malignancies. Conclusion: Early-M is associated with accelerated biological aging and distinct immune and hormonal regulatory patterns, with the potential to contribute to heterogeneous cancer risk profiles across cancer types. Citation Format: Tiffany Y. Pei, Ting Zhai, Jinyoung Byun, Vernon S. Pankratz, Shuguang Leng. Age at menopause, epigenetic aging, and cancer risk: A secondary analysis of the PLCO Trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6258.

Abstract Background: Wildfires are becoming more frequent and severe, reversing decades of progress in reducing fine particulate matter (PM2.5) in the United States. Although wildfire smoke (WFS) contains numerous carcinogens and toxicants, its association with cancer incidence remains unclear. Methods: We examined associations between WFS exposure and cancer incidence in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. The PLCO trial prospectively assessed cancer incidence from enrollment (1993-2001) through 2018. WFS exposure was quantified monthly at participants’ residences using near-ground WFS PM2.5, WFS black carbon (BC), and satellite-derived WFS plume-day counts from 2006 until first cancer diagnosis or last contact. Guided by evidence that three years of air-pollution exposure can influence the development of EGFR-positive lung adenocarcinoma, WFS exposure was modeled as a time-varying variable using 36-month moving averages preceding each month. Hazard ratios (HRs) were estimated using Cox proportional hazards models stratified by study center, with proportional hazards assumptions verified. Restricted cubic splines were applied to evaluate dose-response relationships. Covariates included age, sex, race and ethnicity, education, smoking history, body mass index, and trial arm. Results: Among 91,460 PLCO participants with linked WFS exposure data, we identified incident cases of 1,758 lung, 800 colorectal, 1,739 breast, 242 ovarian, 896 bladder, and 1,696 hematopoietic cancers, and 1,127 melanoma during 2006-2018. Median (range) 36-month moving-averages were 0.37 (0.0083-1.72) µg/m3 for WFS PM2.5, 0.0083 (0.00-0.21) µg/m3 for WFS BC, and 1.94 (0.097-7.18) days for monthly WFS plume-day counts. Restricted cubic splines indicated statistically significant associations (P<0.05) of WFS exposure with increased risks of lung, colorectal, breast, bladder, and hematopoietic cancers, with an approximate linear dose-response observed for most analyses. Moreover, each 1 µg/m3 increase in the 36-month moving-average of WFS PM2.5 was associated with higher risks of lung (HR=1.92; 95% CI: 1.18, 3.15), colorectal (2.31; 1.11, 4.81), breast (2.09; 1.34, 3.26), bladder (3.49; 1.66, 7.34), and hematopoietic (1.63; 1.02, 2.60) cancers. No associations were found for ovarian cancer or melanoma. Results for WFS plume-day counts were generally consistent with those for WFS PM2.5, whereas associations for WFS BC exposure were observed only for breast and bladder cancers. Conclusion: WFS exposure was associated with the risk of lung, colorectal, breast, bladder, and hematopoietic cancers. Findings need to be replicated in additional cohorts. Citation Format: Qizhen Wu, Lisa Sinclair, Vernon S. Pankratz, Qing Lan, Nathaniel Rothman, Rena Jones, Su Zhang, Shuguang Leng. Wildfire smoke and cancer risk in the United States: Evidence from the PLCO Trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6252.

Supplementary Table 1. Univariable Cox regression results for DSS.

Neuroinflammation is the brain's immune response to injury or disease and can negatively impact neurological functions, ranging from mood, cognition, learning, and memory, as well as promote neurodegenerative disease and even psychiatric conditions. Different environmental factors may trigger a neuroinflammatory response; the mechanisms of this activation may influence the pattern of activation, the immune subsets involved, and the persistence of the response. The duration of neuroinflammation may significantly outlast exposures, creating a potential unique vulnerability for rare or intermittent exposures. The neuroinflammatory response can be classified into acute, subacute, and chronic phases, with subacute neuroinflammation representing a transient state between acute and chronic inflammation. This phase, lasting from days to weeks, is denoted by metabolic disruptions, cognitive impairments, and peripheral immune activation. Environmental exposures, such as air pollution, pesticides, and heavy metals, and social factors impact oxidative stress, glial activation, and blood-brain barrier disruption, leading to neuronal injury and cognitive decline. Notably, exposures like diesel fumes and wildfire smoke have been shown to induce neuroinflammation, subsequently impacting memory and learning, and exacerbating mental health conditions such as post-traumatic stress disorder, depression, and anxiety. Triggering of reactive astrogliosis via impacts on the blood-brain barrier function may be the most common non-specific manner that environmental toxicants drive neuroinflammation, but direct outcomes from compounds that readily access the brain are also possible.

Supplementary Figure 1. Forest plot of multivariable Cox regression model for DSS.

Over the past three decades, the United States has experienced a notable increase in weather-related disasters, including hurricanes, floods, tornadoes, wildfires, and severe storms, posing growing challenges to healthcare preparedness and public health systems. This study analyzes Federal Emergency Management Agency (FEMA) disaster declarations from 1989 to 2019 to characterize temporal and geographic trends in weather-related events. Data after 2019 were excluded to avoid confounding effects associated with the COVID-19 pandemic, which disrupted disaster declarations, resource allocation, and healthcare system demands. Using descriptive statistics, generalized linear mixed models, and spatial clustering techniques, we identified substantial increases and nonlinear patterns in disaster declarations, with variation across hazard types and regions. These trends reflect evolving hazard exposure, regional differences, and policy-driven declaration practices. Although this study does not directly measure health outcomes or social vulnerability, the observed patterns have important implications for healthcare system capacity, workforce preparedness, and populations known to be disproportionately affected by disasters. The findings highlight the need for climate-informed training, data-driven preparedness planning, and integration of disaster trend analysis into nursing education and public health practice. Strengthening the ability of healthcare systems to anticipate and respond to evolving disaster patterns is critical for advancing resilience and promoting equitable health outcomes in the context of climate change.

Supplementary Figure 3. Assessment of the proportional-hazards assumption using Schoenfeld residuals

Over the past three decades, the United States has experienced a notable increase in weather-related disasters, including hurricanes, floods, torna-does, wildfires, and severe storms, posing growing challenges to healthcare preparedness and public health systems. This study analyzes Federal Emergency Management Agency (FEMA) disaster declarations from 1989 to 2019 to characterize temporal and geographic trends in weather-related events. Data after 2019 were excluded to avoid confounding effects asso-ciated with the COVID-19 pandemic, which disrupted disaster declara-tions, resource allocation, and healthcare system demands. Using descrip-tive statistics, generalized linear mixed models, and spatial clustering techniques, we identified substantial increases and nonlinear patterns in disaster declarations, with variation across hazard types and regions. These trends reflect evolving hazard exposure, regional differences, and policy-driven declaration practices. Although this study does not directly measure health outcomes or social vulnerability, the observed patterns have important implications for healthcare system capacity, workforce preparedness, and populations known to be disproportionately affected by disasters. The findings highlight the need for climate-informed training, data-driven preparedness planning, and integration of disaster trend analysis into nursing education and public health practice. Strengthening the ability of healthcare systems to anticipate and respond to evolving disaster patterns is critical for advancing resilience and promoting equita-ble health outcomes in the context of climate change.

Abstract Introduction Understanding environmental-exposure associated gene expression alterations provides insights into how they contribute to cancer risk. We previously showed that individuals exposed to diesel engine exhaust (DEE) or smoky coal exhibit gene expression changes overlapping with those of smokers, suggesting shared mechanisms of toxicity. Wood smoke, produced by incomplete combustion of biomass fuels, is classified as probably carcinogenic (Group 2A), yet studies of its gene expression effects are limited. Here, we conducted a pilot study to examine whether genes associated with smoking, DEE, and smoky coal exposure are also differentially expressed in individuals exposed to wood smoke. Methods We studied 16 never-smoking women from Guatemala in the Household Air Pollution Intervention Network trial who use wood as their primary fuel. PM2.5 exposure was measured with monitors, and urinary 1-Hydroxypyrene (1-OHP) was assessed as a biomarker of polycyclic aromatic hydrocarbons exposure. Nasal turbinate brush samples underwent bulk RNA-seq and were processed via a GTEx-based pipeline. Differential expression (DE) analysis to compare high vs. low PM2.5 and 1-OHP was conducted using limma. Gene Set Enrichment Analysis was used to evaluate whether previously reported gene signatures associated with smoking, DEE exposure, and smoky coal use, were enriched among genes up- and down-regulated for each exposure, ranked by t-statistics. Results We found that both up-regulated and down-regulated smoking-associated signatures were concordantly enriched in wood smoke exposed women with high levels of PM2.5 (p = 0.001 and p=0.04, respectively) and among women with elevated 1-OHP levels (p < 0.001 and p = 0.015, respectively). Genes down-regulated with exposure to smoky coal and DEE were also suppressed in participants with high levels of PM2.5 (p=0.005 for smoky coal signature) and 1-OHP (p<0.001 & p=0.008 for smoky coal and DEE signatures, respectively). Notably, the signatures included genes such as CYP1A1, CYP1B1, and CDH1, which are involved in activation and detoxification of carcinogens. Conclusions Wood smoke exposure in never smokers was associated with airway gene expression changes with similarities to those associated with smoking, DEE, and smoky coal, suggesting shared molecular response to combustion pollutants and pathways linked to lung cancer development. Larger studies are needed to replicate these findings and further examine biomass smoke in lung carcinogenesis. Citation Format: Batel Blechter, Lingge Yu, Wei Hu, Kaytlyn Salmons, Maggie Clarke, Dana Barr, Shuguang Leng, Gang Liu, Jennifer E. Beane-Ebel, Kyle Steenland, Nathaniel Rothman, Qing Lan. Exposure to solid fuel burning and transcriptomic changes in the nasal epithelium in never smoking women in Guatemala [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2309.

BACKGROUND:Wildfire events are increasing in frequency and intensity, and aging individuals demonstrate heightened biological susceptibility to air pollution exposures including increased risk of neurological sequelae. Declining ovarian hormones levels that occur with aging in females along with associated systemic physiological and inflammatory changes may contribute to increased cerebral vulnerability to air pollution, representing a potential but underexplored mechanism. Menopause and the menopausal transition represent a period of profound physiological change that affects cardiovascular, neurological, and immune health. METHODS:We tested whether peri-menopausal-like hormonal status amplifies hippocampal responses to acute wood smoke (WS) using an ovary-intact, 4-vinylcyclohexene diepoxide (VCD) model of moderate accelerated ovarian failure (AOF) in female C57BL/6 mice. Animals were exposed to HEPA-filtered air (FA) or WS for 4 h/day over 2 consecutive days (∼0.5 mg/m³). Exposure characterization confirmed a complex mixture of combustion products with significant levels of both trace metals and gas release during WS exposure. RESULTS:Spatial transcriptomics (10x Visium; n = 4 sections/group) with automated cell-type annotation identified astrocytes, GABAergic and glutamatergic neurons, oligodendrocytes, revealed cell type-specific transcriptional alterations following WS exposure. Distinct transcriptional patterns were observed across all identified neuronal and glial cell populations. CONCLUSION:Together, these findings define a cell-type specific transcriptomic framework describing how WS exposure and ovarian hormone decline interact to influence hippocampal responses and identify potential cellular pathways relevant to hippocampal vulnerability.

HLA typing from sequencing data is crucial for studying immune gene families, but high allele similarity challenges existing tools. We present ImmuSeeker, comprehensive software for extracting HLA genotypes, expression, and diversity at gene, one-field, and two-field allele levels, with improved Bayesian zygosity inference and graphical phylogenetic visualization. ImmuSeeker was benchmarked against nine established tools using gold-standard HLA datasets, repeated RNA sequencing (RNA-seq) and Isoform Sequencing (Iso-Seq) data, and a longitudinal patient cohort, demonstrating superior accuracy, consistency, and analytical utility. ImmuSeeker provides a scalable, robust framework for comprehensive HLA typing and immune system analyses.

RATIONALE Airway macrophage black carbon load is a validated biomarker assessing total inhalation exposure of individuals to combustion particles. Its integration in epidemiological studies of air pollution and health outcomes has been limited due to its labor-intensive nature. Our group developed a first-of-its kind artificial intelligence algorithm, MacLEAP: Machine-Learning algorithm for Engulfed cArbon Particles, that automatically distinguishes macrophages from other cell types on sputum cytospin slide images and quantifies engulfed black carbon particles. The first iteration of MacLEAP demonstrated excellent performance in sputum slides stained with Papanicolaou stain, however most sputum cytospin slides are already stained with the dark purple Hema 3 stain for differential cell analysis, requiring better detection capabilities of MacLEAP for black carbon assessment. METHODS We therefore upgraded the object and segmentation detection core using Detectron2, a next-generation platform that synergizes advantages from all mainstream object detection algorithms such as Fast R-CNN, Faster R-CNN, Mask R-CNN, RetinaNet, etc. We acquired 4452 hema-3 stained sputum cytospin slide images from 115 study subjects from the SPIROMICS (SubPopulations and InteRmediate Outcome Measures in COPD Study) trial, and applied MacLEAPDetectron2 for carbon black analysis. RESULTS We report excellent detection of macrophages (R2=0.95 for total number of macrophages per person) and engulfed black carbon particles (R2=0.78 for total number of particles per person) compared to manual technician counting. Ongoing refinement of training parameters is being undertaken to further improve the performance especially in slides that are crowded with cells and/or darkly stained. CONCLUSIONS This innovative and robust MacLEAP algorithm provides a high-throughput and technician-independent solution that is also flexible and open for additional training for quantifying macrophage carbon load in sputum slides of varying quality.

BACKGROUND:Aflatoxin remains an underrecognized hepatocellular carcinoma (HCC) risk factor in the United States, where the permissible food limit (20 ppb) is fivefold higher than in Europe. METHODS:We analyzed 350 The Cancer Genome Atlas HCC cases with whole-exome sequencing, RNA sequencing, and clinical data. Aflatoxin burden was quantified by single-base substitution signature 24. HLA diversity was quantified from RNA sequencing reads using the Shannon diversity index. Multivariable Cox models estimated HRs for disease-specific survival (DSS) with aflatoxin-virus interactions, adjusting for tumor stage, age, sex, race, alcohol use, fatty liver disease, aristolochic acid signature, and HLA diversity. Linear regression evaluated the association between HLA diversity and aflatoxin burden. RESULTS:Higher aflatoxin burden was associated with poorer DSS (adjusted HR = 1.16; 95% confidence interval, 1.01-1.33). Among hepatitis C virus (HCV)-positive patients, hepatitis B virus (HBV) infection was associated with improved DSS at low aflatoxin levels; however, this association was reversed at aflatoxin levels exceeding 30 units. HCV infection was consistently associated with worse DSS across aflatoxin levels. Asian American and Black/African American patients carried higher aflatoxin burdens than Whites (P = 0.016 and 0.014). Greater HLA diversity was independently associated with lower aflatoxin burden (P < 0.001), suggesting a protective effect. CONCLUSIONS:Somatic aflatoxin exposure, both independently and synergistically with HBV/HCV infection, adversely affects HCC prognosis, whereas greater HLA diversity may mitigate the detrimental effects of aflatoxin. Aflatoxin exposure disproportionately affected Asian American and Black/African American patients (other minority groups not represented). IMPACT:Tightening US aflatoxin food limits and expanding HBV vaccination coverage in high-risk communities could reduce HCC disparities and improve patient survival.

Hearing loss in newborns is a prevalent issue that can hinder the growth of language skills and cognitive development. Given that hearing loss often co-occurs with other adverse birth outcomes and the recognized role of metals in causing such outcomes, it is conceivable that metals may also serve as a risk factor of hearing loss. This study examined the associations between maternal residential exposure to thirteen PM2.5-bound metals and failure in Newborn Hearing Screening (NHS) in offspring in New Mexico from 2008 to 2017 to ascertain possible implications of these environmental exposures. This retrospective cohort study included 141,406 births (7670 births in disease group and 133,736 births in non-diseased group) in New Mexico during 2008-2017. Thirteen PM2.5-bound metals released from the U.S. Environmental Protection Agency (EPA) Toxic Release Inventory (TRI) facilities were investigated potentially as risk factors. The RSEI model estimated maternal residential exposure to PM2.5-bound metals during pregnancy, and spatial log-binomial regressions, adjusted for confounders, calculated adjusted relative risks (aRRs) for the association with NHS failure. Findings indicated that maternal residential exposure to PM2.5-bound metals - including antimony, barium, beryllium, chromium, cobalt, manganese, mercury, vanadium, and zinc - during pregnancy were positively associated with NHS failure in offspring, showing aRRs ranging from 1.07 to 2.18. A significant trend was observed when exposures were categorized as zero, low, medium, and high of these metals. Our findings indicate that maternal exposure to these PM2.5-bound metals may adversely affect newborn hearing, underscoring air pollution as a modifiable risk factor for improving hearing health outcomes.

Background:Numerous studies have assessed the risk of SARS-CoV-2 exposure and infection among health care workers during the pandemic. However, far fewer studies have investigated the impact of SARS-CoV-2 on essential workers in other sectors. Moreover, guidance for maintaining a safely operating workplace in sectors outside of health care remains limited. Workplace surveillance has been recommended by the Centers for Disease Control and Prevention, but few studies have examined the feasibility or effectiveness of this approach. Objective:The objective of this study was to investigate the feasibility and effectiveness of using frequent point-of-care molecular workplace surveillance as an intervention strategy to prevent the spread of SARS-CoV-2 at essential rural workplaces (mining sites) where physical distancing, remote work, and flexible schedules are not possible. Methods:In this nonrandomized controlled clinical trial conducted from February 2021, to March 2022, 169 miners in New Mexico (intervention cohort) and 61 miners in Wyoming (control cohort) were enrolled. Investigators performed point-of-care rapid antigen testing on midnasal swabs (NSs) self-collected by intervention miners. Our first outcome was the intervention acceptance rate in the intervention cohort. Our second outcome was the rate of cumulative postbaseline seropositivity to SARS-CoV-2 nucleocapsid protein, which was analyzed in the intervention cohort and compared to the control cohort between baseline and 12 months. The diagnostic accuracy of detecting SARS-CoV-2 using rapid antigen testing on NSs was compared to laboratory-based reverse transcriptase polymerase chain reaction (RT-PCR) on nasopharyngeal swabs (NPSs) in a subset of 68 samples. Results:Our intervention had a mean acceptance rate of 96.4% (11,413/11,842). The intervention miners exhibited a lower cumulative postbaseline incident seropositivity at 12 months compared to control miners (14/97, 14% vs 17/45, 38%; P=.002). Analysis of SARS-CoV-2 antigen detection in self-administered NSs revealed 100% sensitivity and specificity compared to laboratory-based RT-PCR testing on NPSs. Conclusions:Our findings establish frequent point-of-care molecular workplace COVID-19 surveillance as a feasible option for keeping essential rural workplaces open and preventing SARS-CoV-2 spread. These findings extend beyond this study, providing valuable insights for designing interventions to maintain employees' safety at other essential workplaces during an infectious disease outbreak.

Rationale: Wildfire frequency and intensity increased globally due to the impacts of climate change. Evidence concerning health impacts after episodic exposure to wildfire smoke is limited. Methods: Using the Lovelace Smokers Cohort (LSC), we evaluated whether wildfire smoke exposure was associated with psychometric measures of physical and mental health and whether the associations observed were modified by individual factors.The St. George's Respiratory Questionnaire (SGRQ) and the 36-Item Short Form Survey (SF-36) were administered to assess respiratory-specific and general health-related quality of life in 4 weeks prior to questionnaire filling, respectively. Exposure to wildfire smoke was quantified using satellite-derived smoke plume imagery in combination of near ground estimates of PM2.5 and black carbon concentrations. Results: The Albuquerque metropolitan area in New Mexico, the catchment area of the LSC was frequently affected by wildfire smoke during non-winter seasons that predominantly originated from the fires in Apache and Gila National Forest around the Arizona and New Mexico borders. We identified a total of 381 smoke days from 2006 to 2016 when Albuquerque overlapped with smoke plumes. The contribution of smoke to ambient PM2.5 levels was estimated to be an average of 2.31 µg/m3 during these days which is equivalent to 57% of the average ambient PM2.5 levels during non-smoke days. Among subjects (n=747) who filled SGRQ and SF-36 health survey between 2006 and 2016, wildfire smoke exposure was associated with worse psychometric measures, with mental health more likely to be affected by recent (1-2 weeks) wildfire smoke exposure, while physical health affected by wildfire smoke exposure estimated for up to 4-8 weeks. Specifically, per 1 µg/m3 increase (90th to 95th percentile) in smoke PM2.5 in 7-, 15-, and 30-day prior to questionnaire filling is associated with an increase of 4 or more points in activity and symptom scores of SGRQ, an effects size exceeding clinical significance. Additionally, the associations were stronger among males, individuals with lower education, those with chronic mucous hypersecretion, and participants with prior residential woodsmoke exposure. Conclusions: This study suggests that episodic exposure to wildfire smoke is associated with worse SGRQ and SF-36 scores, with distinct timing differences between the impacts on mental and physical health. Additionally, individuals with lower education levels, chronic mucus hypersecretion, or prior woodsmoke exposure appear to be more vulnerable to the effects of wildfire smoke. Further research is needed to validate these findings and to explore the biological mechanisms underlying these associations.

BACKGROUND: We previously identified a sputum 12-gene methylation panel that predicts lung aging and risk for lung cancer. RESEARCH QUESTION: Can the sputum methylation panel be used as a readout to derive a dietary pattern beneficial for lung health? Is this dietary pattern associated with various subjective and objective lung health phenotypes? Does this relationship vary among people who currently smoke vs previously smoked? STUDY DESIGN AND METHODS: Using the Lovelace Smoker Cohort (LSC), we employed the least absolute shrinkage and selection operator regularized Poisson regression to define a dietary pattern for sputum. Associations of the dietary pattern with objective and subjective lung health measurements were examined using generalized linear and Cox models in the LSC and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening trial. RESULTS: The Dietary Pattern for Healthy Lung (DiPHeaL) includes low consumption of processed meat, and high consumption of dark green vegetables, tea, alcohol, and fruit juice. In the LSC, a higher DiPHeaL score (1 SD) was associated with better FEV1 (by 96.1 mL/s), FEV1/FVC ratio (by 1.83%), and respiratory quality of life (by 4.9 for activity score), and decreased cardiopulmonary mortality (by 47%) in participants who previously smoked (all P values < .05), but not in participants who currently smoke. Moreover, effect sizes of the DiPHeaL score on respiratory quality of life measures were greater among participants who previously smoked with airway obstruction compared with those without. Associations with cardiovascular and respiratory mortality were replicated in PLCO participants who previously smoked. A higher DiPHeaL score was also associated with lower lung cancer incidence in participants who previously smoked, as well as reduced COPD incidence and lung cancer mortality regardless of smoking status in the PLCO. INTERPRETATION: We defined a novel dietary pattern for lung epigenetic aging, which linked to lung health measurements. Participants who previously smoked, especially those with airway obstruction, may benefit the most from nutritional modification.