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BACKGROUND: Ultrafine particles (UFP) are unregulated air pollutants abundant in aviation exhaust. Emerging evidence suggests that UFPs may impact lung health due to their high surface area-to-mass ratio and deep penetration into airways. This study aimed to assess long-term exposure to airport-related UFPs and lung cancer incidence in a multiethnic population in Los Angeles County. METHODS: Within the California Multiethnic Cohort, we examined the association between long-term exposure to airport-related UFPs and lung cancer incidence. Multivariable Cox proportional hazards regression models were used to estimate the effect of UFP exposure on lung cancer incidence. Subgroup analyses by demographics, histology and smoking status were conducted. RESULTS: Airport-related UFP exposure was not associated with lung cancer risk [per one IGR HR, 1.01; 95% confidence interval (CI), 0.97-1.05] overall and across race/ethnicity. A suggestive positive association was observed between a one IQR increase in UFP exposure and lung squamous cell carcinoma (SCC) risk (HR, 1.08; 95% CI, 1.00-1.17) with a Phet for histology = 0.05. Positive associations were observed in 5-year lag analysis for SCC (HR, 1.12; 95% CI, CI, 1.02-1.22) and large cell carcinoma risk (HR, 1.23; 95% CI, 1.01-1.49) with a Phet for histology = 0.01. CONCLUSIONS: This large prospective cohort analysis suggests a potential association between airport-related UFP exposure and specific lung histologies. The findings align with research indicating that UFPs found in aviation exhaust may induce inflammatory and oxidative injury leading to SCC. IMPACT: These results highlight the potential role of airport-related UFP exposure in the development of lung SCC.
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Aeropuertos , Neoplasias Pulmonares , Material Particulado , Humanos , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/etiología , Masculino , Femenino , Material Particulado/efectos adversos , Material Particulado/análisis , Persona de Mediana Edad , Anciano , Factores de Riesgo , Estudios de Cohortes , Contaminantes Atmosféricos/efectos adversos , Estudios Prospectivos , Exposición a Riesgos Ambientales/efectos adversos , Incidencia , Etnicidad/estadística & datos numéricos , Los Angeles/epidemiologíaRESUMEN
Importance: The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity. Objective: To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria. Design, Setting, and Participants: In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105â¯261 adults with a smoking history were included. Exposures: The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines. Outcomes: Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer). Results: Of 105â¯261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19â¯258 (18.3%) African American, 27â¯227 (25.9%) Japanese American, 21â¯383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29â¯025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%). Conclusions: The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.
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Detección Precoz del Cáncer , Neoplasias Pulmonares , Masculino , Adulto , Humanos , Persona de Mediana Edad , Femenino , Estudios de Cohortes , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/epidemiología , Etnicidad , Hispánicos o LatinosRESUMEN
In this work, we develop a novel Bayesian regression framework that can be used to complete variable selection in high dimensional settings. Unlike existing techniques, the proposed approach can leverage side information to inform about the sparsity structure of the regression coefficients. This is accomplished by replacing the usual inclusion probability in the spike and slab prior with a binary regression model which assimilates this extra source of information. To facilitate model fitting, a computationally efficient and easy to implement Markov chain Monte Carlo posterior sampling algorithm is developed via carefully chosen priors and data augmentation steps. The finite sample performance of our methodology is assessed through numerical simulations, and we further illustrate our approach by using it to identify genetic markers associated with the nicotine metabolite ratio; a key biological marker associated with nicotine dependence and smoking cessation treatment.
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Algoritmos , Teorema de Bayes , Marcadores Genéticos , Cadenas de MarkovRESUMEN
Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 µm [PM2.5], ≤10 µm [PM10], and between 2.5 and 10 µm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 µg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 µg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.
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Contaminantes Atmosféricos , Contaminación del Aire , Ozono , Masculino , Femenino , Humanos , Anciano , Material Particulado/análisis , Emisiones de Vehículos/análisis , Contaminantes Atmosféricos/análisis , Proteína C-Reactiva/análisis , Estudios de Cohortes , Benceno/análisis , Exposición a Riesgos Ambientales/análisis , Contaminación del Aire/análisis , Ozono/análisis , Dióxido de Nitrógeno/análisis , Inflamación/inducido químicamente , Inflamación/epidemiologíaRESUMEN
BACKGROUND: There is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight). RESULTS: We identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry. CONCLUSIONS: We have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use.
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Cotinina , Nicotina , Cotinina/metabolismo , Estudio de Asociación del Genoma Completo , Genotipo , Humanos , Nicotina/metabolismo , Fumar/genética , Fumar/metabolismoRESUMEN
BACKGROUND: In 2021, the US Preventive Services Task Force (USPSTF) revised its lung cancer screening guidelines to expand screening eligibility. We evaluated screening sensitivities and racial and ethnic disparities under the 2021 USPSTF criteria vs alternative risk-based criteria in a racially and ethnically diverse population. METHODS: In the Multiethnic Cohort, we evaluated the proportion of ever-smoking lung cancer cases eligible for screening (ie, screening sensitivity) under the 2021 USPSTF criteria and under risk-based criteria through the PLCOm2012 model (6-year risk ≥1.51%). We also calculated the screening disparity (ie, absolute sensitivity difference) for each of 4 racial or ethnic groups (African American, Japanese American, Latino, Native Hawaiian) vs White cases. RESULTS: Among 5900 lung cancer cases, 43.3% were screen eligible under the 2021 USPSTF criteria. Screening sensitivities varied by race and ethnicity, with Native Hawaiian (56.7%) and White (49.6%) cases attaining the highest sensitivities and Latino (37.3%), African American (38.4%), and Japanese American (40.0%) cases attaining the lowest. Latino cases had the greatest screening disparity vs White cases at 12.4%, followed by African American (11.2%) and Japanese American (9.6%) cases. Under risk-based screening, the overall screening sensitivity increased to 75.7%, and all racial and ethnic groups had increased sensitivities (54.5%-91.9%). Whereas the screening disparity decreased to 5.1% for African American cases, it increased to 28.6% for Latino cases and 12.8% for Japanese American cases. CONCLUSIONS: In the Multiethnic Cohort, racial and ethnic disparities decreased but persisted under the 2021 USPSTF lung cancer screening guidelines. Risk-based screening through PLCOm2012 may increase screening sensitivities and help to reduce disparities in some, but not all, racial and ethnic groups. Further optimization of risk-based screening strategies across diverse populations is needed.
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Detección Precoz del Cáncer , Neoplasias Pulmonares , Estudios de Cohortes , Etnicidad , Humanos , Neoplasias Pulmonares/diagnóstico , Tamizaje MasivoRESUMEN
Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter <2.5 µm (HR, 1.20 per 10 µg/m3; 95% CI, 1.01-1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99-1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02-1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.
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Contaminantes Atmosféricos , Contaminación del Aire , Neoplasias Pulmonares , Contaminantes Atmosféricos/efectos adversos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/efectos adversos , Contaminación del Aire/análisis , Benceno , California/epidemiología , Monóxido de Carbono , Estudios de Cohortes , Exposición a Riesgos Ambientales/efectos adversos , Humanos , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/etiología , Dióxido de Nitrógeno , Material Particulado/efectos adversos , Material Particulado/análisis , Emisiones de Vehículos/toxicidadRESUMEN
Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
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Pueblo Asiatico/genética , Población Negra/genética , Estudio de Asociación del Genoma Completo/métodos , Hispánicos o Latinos/genética , Grupos Minoritarios , Herencia Multifactorial/genética , Salud de la Mujer , Estatura/genética , Estudios de Cohortes , Femenino , Genética Médica/métodos , Equidad en Salud/tendencias , Disparidades en el Estado de Salud , Humanos , Masculino , Estados UnidosRESUMEN
BACKGROUND: The lung cancer risk of smokers varies by race/ethnicity even after adjustment for smoking. Evaluating the role of genetics in nicotine metabolism is likely important in understanding these differences, as disparities in risk may be related to differences in nicotine dose and metabolism. METHODS: We conducted a genome-wide association study in search of common genetic variants that predict nicotine and cotinine glucuronidation in a sample of 2,239 smokers (437 European Americans, 364 African Americans, 453 Latinos, 674 Japanese Americans, and 311 Native Hawaiians) in the Multiethnic Cohort Study. Urinary concentration of nicotine and its metabolites were determined. RESULTS: Among 11,892,802 variants analyzed, 1,241 were strongly associated with cotinine glucuronidation, 490 of which were also associated with nicotine glucuronidation (P < 5×10(-8)). The vast majority were within chromosomal region 4q13, near UGT2B10. Fifteen independent and globally significant SNPs explained 33.2% of the variation in cotinine glucuronidation, ranging from 55% for African Americans to 19% for Japanese Americans. The strongest single SNP association was for rs115765562 (P = 1.60 × 10(-155)). This SNP is highly correlated with a UGT2B10 splice site variant, rs116294140, which together with rs6175900 (Asp67Tyr) explains 24.3% of the variation. The top SNP for nicotine glucuronidation (rs116224959, P = 2.56 × 10(-43)) was in high LD (r(2) = 0.99) with rs115765562. CONCLUSIONS: Genetic variation in UGT2B10 contributes significantly to nicotine and cotinine glucuronidation but not to nicotine dose. IMPACT: The contribution of genetic variation to nicotine and cotinine glucuronidation varies significantly by racial/ethnic group, but is unlikely to contribute directly to lung cancer risk.
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Etnicidad/genética , Estudio de Asociación del Genoma Completo/métodos , Glucurónidos/metabolismo , Nicotina/metabolismo , Fumar/genética , Anciano , Femenino , Variación Genética , Genotipo , Humanos , Masculino , Persona de Mediana Edad , Fenotipo , Polimorfismo de Nucleótido Simple , Control de CalidadRESUMEN
Nicotine metabolism influences smoking behavior and differences in metabolism probably contribute to ethnic variability in lung cancer risk. We report here on the proportion of nicotine metabolism by cytochrome P450 2A6-catalyzed C-oxidation, UDP-glucuronosyl transferase 2B10 (UGT2B10)-catalyzed N-glucuronidation and flavin monooxygenase 3-catalyzed N-oxidation in five ethnic/racial groups and the role of UGT2B10 genotype on the metabolic patterns observed. Nicotine and its metabolites were quantified in urine from African American (AA, n = 364), Native Hawaiian (NH, n = 311), White (n = 437), Latino (LA, n = 453) and Japanese American (JA, n = 674) smokers. Total nicotine equivalents, the sum of nicotine and six metabolites, and nicotine metabolism phenotypes were calculated. The relationship of UGT2B10 genotype to nicotine metabolic pathways was determined for each group; geometric means were computed and adjusted for age, sex, creatinine, and body mass index. Nicotine metabolism patterns were unique across the groups, C-oxidation was lowest in JA and NH (P < 0.0001), and N-glucuronidation lowest in AA (P < 0.0001). There was no difference in C-oxidation among Whites and AA and LA. Nicotine and cotinine glucuronide ratios were 2- and 3-fold lower in AA compared with Whites. Two UGT variants, a missense mutation (Asp67Tyr, rs61750900) and a splice variant (rs116294140) accounted for 33% of the variation in glucuronidation. In AA, the splice variant accounted for the majority of the reduced nicotine glucuronidation. UGT2B10 variant allele carriers had increased levels of C-oxidation (P = 0.0099). Our data indicate that the relative importance of nicotine metabolic pathways varies by ethnicity, and all pathways should be considered when characterizing the role of nicotine metabolism on smoking behavior and cancer risk.
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Glucuronatos/genética , Glucuronosiltransferasa/genética , Neoplasias/genética , Nicotina/análogos & derivados , Nicotina/metabolismo , Fumar/genética , Adolescente , Adulto , Etnicidad/genética , Femenino , Genotipo , Glucuronosiltransferasa/farmacocinética , Hepatocitos/metabolismo , Humanos , Masculino , Microsomas Hepáticos/efectos de los fármacos , Microsomas Hepáticos/metabolismo , Persona de Mediana Edad , Neoplasias/metabolismo , Neoplasias/patología , Nicotina/genética , Factores de RiesgoRESUMEN
Tobacco smoking is the most important and well-established bladder cancer risk factor and a rich source of chemical carcinogens and reactive oxygen species that can induce damage to DNA in urothelial cells. Therefore, common variation in DNA repair genes might modify bladder cancer risk. In this study, we present results from meta-analyses and pooled analyses conducted as part of the International Consortium of Bladder Cancer. We included data on 10 single nucleotide polymorphisms corresponding to seven DNA repair genes from 13 studies. Pooled analyses and meta-analyses included 5,282 cases and 5,954 controls of non-Latino white origin. We found evidence for weak but consistent associations with ERCC2 D312N [rs1799793; per-allele odds ratio (OR), 1.10; 95% confidence interval (95% CI), 1.01-1.19; P = 0.021], NBN E185Q (rs1805794; per-allele OR, 1.09; 95% CI, 1.01-1.18; P = 0.028), and XPC A499V (rs2228000; per-allele OR, 1.10; 95% CI, 1.00-1.21; P = 0.044). The association with NBN E185Q was limited to ever smokers (interaction P = 0.002) and was strongest for the highest levels of smoking dose and smoking duration. Overall, our study provides the strongest evidence to date for a role of common variants in DNA repair genes in bladder carcinogenesis.