Never-smoking Women Research Articles

Gender-specific outcomes of low-dose computed tomography screening for lung cancer detection: A retrospective study in Chinese never-smoker population.

Low-dose computed tomography (LDCT) has emerged as a pivotal tool for detecting lung cancer among ever-smokers. This study aims to evaluate the gender-specific outcomes of LDCT screening within the Chinese never-smoking population. We conducted a single-center, retrospective cohort study, which analyzed LDCT screening outcomes for 42,018 asymptomatic participants. Specifically, we focused on assessing gender-specific differences in the prevalence of pulmonary nodules, and the incidence of lung cancer diagnosis among never-smokers. Among the 42,018 eligible participants, 41.50% were females and 58.50% were males. Most participants were non-smokers (77.57%), with a significantly higher proportion of non-smokers among females than males (99.33% vs. 62.14%). Pulmonary nodules were identified in 2.66% of participants, with a higher prevalence in females (2.99%) than males (2.43%) (p < 0.001). Non-smoking females had a higher incidence of positive nodules than non-smoking males (2.98% vs. 2.38%, p < 0.001). Invasive biopsies were performed in 334 individuals with nodules, confirming lung cancer in 258 cases. The majority of these cancer cases were non-smokers (212), with non-smoking females showing a higher incidence (0.85%) compared to males (0.43%) (p < 0.001). There was no significant difference in the false-positive rates between non-smoking females (0.14%) and males (0.13%). Multivariate analysis showed that never-smoking women were more likely to undergo biopsies (OR 1.65, p = 0.0016) and had a higher, though not statistically significant, probability of lung cancer diagnosis (OR 1.84, p = 0.06). This study elucidates sex-based differences within the Chinese population, revealing a higher prevalence of pulmonary nodules and lung cancers among non-smoking females. These findings offer valuable reference for both clinical practice and future research initiatives.

A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study.

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.

Abstract 7331: Establishing a single-cell eQTL dataset of lung tissues from Asian never-smokers to identify cell-type specific lung cancer susceptibility genes

Abstract Lung cancer is one of the most prevalent and deadly forms of cancer worldwide. Whilst smoking is the main determinant, genetic factors also play a crucial role as genome-wide association studies (GWAS) have identified &amp;gt;50 loci associated with lung cancer risk. Yet, for most of these loci, it is still unknown how they contribute to lung cancer risk. Expression quantitative trait loci (eQTL) studies have been powerful in linking GWAS variants to potential target genes, providing genetic mechanisms underlying common diseases such as cancers. However, the current eQTL resources lack ancestral diversity and are primarily based on bulk tissues. Emerging single-cell eQTL (sc-eQTL) approaches can detect context-specific gene regulation but are mainly of blood samples or cultured cells and still representing European populations. This limits our abilities to test GWAS variants in cancer-relevant cell types as well as in diverse populations. To generate a resource to characterize lung cancer GWAS loci, we are building a lung sc-eQTL dataset of Asian population while addressing common challenges of tissue sc-eQTL. Namely, processing fresh tissue in a population scale is logistically challenging and costly, and epithelial cells (including cell types of lung cancer origin) are vulnerable to the dissociation and freezing/thawing process. To address these issues, we incorporated sample multiplexing and cell type balancing. We collected fresh tumor-distant normal lung tissues from 131 never-smoking Korean women and dissociated them before cryopreservation. We then performed single-cell RNA sequencing (scRNA-seq) using 10x Chromium Single Cell 3’ v3.1 chemistry with multiplexing of ~6 samples/batch. To enrich for epithelial cells, we utilized flow cytometry with surface markers of four major lung cell types (epithelial: EpCAM+/CD45-, immune: EpCAM-/CD45+, endothelial and stromal: EpCAM-/CD45-) before 10X library preparation. Concurrently, we performed DNA genotyping and imputation using matched blood samples. Following scRNA-seq (~36,000 reads/cell) we performed a genotype-based sample demultiplexing using Demuxlet. By integrating Demuxlet and Scrublet, we identified ~89% of the detected cells as singlets. After applying QC to filter empty droplets and low-quality cells, we obtained 428,619 cells or 3,272 cells/patient. Cell annotation guided by Azimuth label transfer using the Human Lung Cell Atlas, identified 28 cell types including 7 of epithelial origins. We will further perform eQTL analyses for individual cell types using pseudo-bulk and LIMIX (linear mixed model) or SAIGE-qtl (poisson regression) methods followed by aggregation across the cell types. By incorporating lung cancer GWAS data, we will identify cell-type specific susceptibility genes. Our dataset will provide a unique resource for lung cancer research. Citation Format: Thong Luong, Erping Long, Jinhu Yin, Bolun Li, Ju Hye Shin, Elelta Sisay, Alexander Kane, Alyxandra Golden, Yoon Soo Chang, Nicholas Banovich, Nathaniel Rothman, Jinyoung Byun, Qing Lan, Christopher Amos, Jianxin Shi, Jin Gu Lee, Eun Young Kim, Jiyeon Choi. Establishing a single-cell eQTL dataset of lung tissues from Asian never-smokers to identify cell-type specific lung cancer susceptibility genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7331.

Polygenic Risk Score, Environmental Tobacco Smoke, and Risk of Lung Adenocarcinoma in Never-Smoking Women in Taiwan

Estimating absolute risk of lung cancer for never-smoking individuals is important to inform lung cancer screening programs. To integrate data on environmental tobacco smoke (ETS), a known lung cancer risk factor, with a polygenic risk score (PRS) that captures overall genetic susceptibility, to estimate the absolute risk of lung adenocarcinoma (LUAD) among never-smokers in Taiwan. The analyses were conducted in never-smoking women in the Taiwan Genetic Epidemiology Study of Lung Adenocarcinoma, a case-control study. Participants were recruited between September 17, 2002, and March 30, 2011. Data analysis was performed from January 17 to July 15, 2022. A PRS was derived using 25 genetic variants that achieved genome-wide significance (P < 5 × 10-8) in a recent genome-wide association study, and ETS was defined as never exposed, exposed at home or at work, and exposed at home and at work. The Individualized Coherent Absolute Risk Estimator software was used to estimate the lifetime absolute risk of LUAD in never-smoking women aged 40 years over a projected 40-year span among the controls by using the relative risk estimates for the PRS and ETS exposures, as well as age-specific lung cancer incidence rates for never-smokers in Taiwan. Likelihood ratio tests were conducted to assess an additive interaction between the PRS and ETS exposure. Data were obtained on 1024 women with LUAD (mean [SD] age, 59.6 [11.4] years, 47.9% ever exposed to ETS at home, and 19.5% ever exposed to ETS at work) and 1024 controls (mean [SD] age, 58.9 [11.0] years, 37.0% ever exposed to ETS at home, and 14.3% ever exposed to ETS at work). The overall average lifetime 40-year absolute risk of LUAD estimated using PRS alone was 2.5% (range, 0.6%-10.3%) among women never exposed to ETS. When integrating both ETS and PRS data, the estimated absolute risk was 3.7% (range, 0.6%-14.5%) for women exposed to ETS at home or work and 5.3% (range, 1.2%-12.1%) for women exposed to ETS at home and work. A super-additive interaction between ETS and the PRS (P = 6.5 × 10-4 for interaction) was identified. This study found differences in absolute risk of LUAD attributed to genetic susceptibility according to levels of ETS exposure in never-smoking women. Future studies are warranted to integrate these findings in expanded risk models for LUAD.

Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study.

The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.

An Interpretable Three-Dimensional Artificial Intelligence Model for Computer-Aided Diagnosis of Lung Nodules in Computed Tomography Images.

Lung cancer is typically classified into small-cell carcinoma and non-small-cell carcinoma. Non-small-cell carcinoma accounts for approximately 85% of all lung cancers. Low-dose chest computed tomography (CT) can quickly and non-invasively diagnose lung cancer. In the era of deep learning, an artificial intelligence (AI) computer-aided diagnosis system can be developed for the automatic recognition of CT images of patients, creating a new form of intelligent medical service. For many years, lung cancer has been the leading cause of cancer-related deaths in Taiwan, with smoking and air pollution increasing the likelihood of developing the disease. The incidence of lung adenocarcinoma in never-smoking women has also increased significantly in recent years, resulting in an important public health problem. Early detection of lung cancer and prompt treatment can help reduce the mortality rate of patients with lung cancer. In this study, an improved 3D interpretable hierarchical semantic convolutional neural network named HSNet was developed and validated for the automatic diagnosis of lung cancer based on a collection of lung nodule images. The interpretable AI model proposed in this study, with different training strategies and adjustment of model parameters, such as cyclic learning rate and random weight averaging, demonstrated better diagnostic performance than the previous literature, with results of a four-fold cross-validation procedure showing calcification: 0.9873 ± 0.006, margin: 0.9207 ± 0.009, subtlety: 0.9026 ± 0.014, texture: 0.9685 ± 0.006, sphericity: 0.8652 ± 0.021, and malignancy: 0.9685 ± 0.006.

Associations between Longer Leukocyte Telomere Length and Increased Lung Cancer Risk among Never Smokers in Urban China.

The complex relationship between measured leukocyte telomere length (LTL), genetically predicted LTL (gTL), and carcinogenesis is exemplified by lung cancer. We previously reported associations between longer pre-diagnostic LTL, gTL, and increased lung cancer risk among European and East Asian populations. However, we had limited statistical power to examine the associations among never smokers by gender and histology. To investigate further, we conducted nested case-control analyses on an expanded sample of never smokers from the prospective Shanghai Women's Health Studies (798 cases and 792 controls) and Shanghai Men's Health Studies (161 cases and 162 controls). We broke the case-control matching and used multivariable unconditional logistic regression models to estimate the ORs and 95% confidence intervals (CI) of incident lung cancer and adenocarcinoma (LUAD), in relation to LTL measured using quantitative PCR and gTL determined using a polygenic score. In addition, we conducted Mendelian randomization (MR) using MR-PRESSO. We found striking dose-response relationships between longer LTL and gTL, and increased lung cancer risk among never-smoking women (P trendLTL = 4×10-6; P trendgTL = 3×10-4). Similarly, among never-smoking men, longer measured LTL was associated with over triple the risk compared with those with the shortest (OR, 3.48; 95% CI, 1.85-6.57). The overall results were similar for LUAD among women and men. MR analyses supported causal associations with LUAD among women (OR1 SD gTL, 1.19; 95% CI, 1.03-1.37; P = 0.03). Longer pre-diagnostic LTL is associated with increased lung cancer risk among never smokers. Our findings firmly support the role of longer telomeres in lung carcinogenesis.

Household air pollution and epigenetic aging in Xuanwei, China

BackgroundHousehold air pollution (HAP) from indoor combustion of solid fuel is a global health burden linked to lung cancer. In Xuanwei, China, lung cancer rate for nonsmoking women is among the highest in the world and largely attributed to high levels of polycyclic aromatic hydrocarbons (PAHs) that are produced from combustion of smoky (bituminous) coal used for cooking and heating. Epigenetic age acceleration (EAA), a DNA methylation-based biomarker of aging, has been shown to be highly correlated with biological processes underlying the susceptibility of age-related diseases. We aim to assess the association between HAP exposure and EAA. MethodsWe analyzed data from 106 never-smoking women from Xuanwei, China. Information on fuel type was collected using a questionnaire, and validated exposure models were used to predict levels of 43 HAP constituents. Exposure clusters were identified using hierarchical clustering. EAA was derived for five epigenetic clocks defined as the residuals resulting from regressing each clock on chronological age. We used generalized estimating equations to test associations between exposure clusters derived from predicted levels of HAP exposure, ambient 5-methylchrysene (5-MC), a PAH previously found to be associated with risk of lung cancer, and EAA, while accounting for repeated-measurements and confounders. ResultsWe observed an increase in GrimAge EAA for clusters with 31 and 33 PAHs reflecting current (β = 0.77 y per standard deviation (SD) increase, 95 % CI:0.36,1.19) and childhood (β = 0.92 y per SD, 95 % CI:0.40,1.45) exposure, respectively. 5-MC (ng/m3-year) was found to be associated with GrimAge EAA for current (β = 0.15 y, 95 % CI:0.05,0.25) and childhood (β = 0.30 y, 95 % CI:0.13,0.47) exposure. ConclusionsOur findings suggest that exposure to PAHs from indoor smoky coal combustion, particularly 5-MC, is associated with GrimAge EAA, a biomarker of mortality.

Childhood secondhand smoke exposure and respiratory disease mortality among never-smokers: the Japan collaborative cohort study for evaluation of cancer risk.

The main source of secondhand smoke (SHS) exposure during childhood occurs at home due to close family members who smoke. This study examined the association between childhood SHS exposure and the risk of respiratory disease mortality among non-smoking adults. Data from 44233 never-smoking Japanese men and women aged 40-79years who participated in the JACC study between 1988 and 1990 were analyzed. The Cox proportional hazards model was used to calculate hazard ratios and 95% confidence intervals of respiratory disease mortality according to the number of smoking family members during childhood. Subdistribution HRs (SHRs) were calculated as a competing risk analysis. A total of 735 deaths from respiratory diseases were documented in a median follow-up of 19.2years. Living with three or more smoking family members during childhood was associated with a higher risk of respiratory disease mortality in adulthood among women; multivariable SHR compared with participants with no family member smokers during childhood was 1.60 (1.01-2.54) for participants with three or more family members who smoked during their childhood. SHS exposure from three or more family members during childhood was associated with an increased risk of respiratory disease-related mortality in adulthood.

Abstract 3009: Measured and genetically-predicted leukocyte telomere length and lung cancer risk in the prospective UK Biobank

Abstract Telomere length is a biomarker reflective of aging and genomic instability. We previously found associations between longer measured leukocyte telomere length (LTL) and increased lung cancer risk in a pooled nested case-control study with 847 cases. Additionally, we reported that longer genetically-predicted telomere length (gTL) using a polygenic risk score (PRS) with 7 single nucleotide polymorphisms (SNPs) was associated with increased lung cancer risk among never-smoking Asian women. To investigate further, we conducted prospective cohort analyses of pre-diagnostic LTL and gTL in relation to risk of overall lung cancer and its subtypes in the UK Biobank. With over triple the number of cases, we had expanded statistical power to investigate lung cancer, adenocarcinoma (LUAD), and squamous cell carcinoma (SCC) among subgroups defined by smoking status and sex in this predominantly European study population. We analyzed 371,890 participants at baseline. Over the 12.36±1.64SD year follow-up, 2829 incident lung cancer cases were diagnosed, including 1078 LUAD and 487 SCC. LTL was measured using qPCR. Using European data, we calculated a weighted PRS for gTL. The PRS was derived from 130 linkage disequilibrium pruned SNPs (r2 &amp;gt; 0.01) associated with longer LTL in the UK Biobank. Multivariable Cox regression was used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of lung cancer in relation to log-transformed continuous and quartiles (Q) of LTL and gTL separately. Associations were estimated in the overall analytic sample and among smoking-sex subgroups. We conducted Mendelian Randomization (MR) analyses using MR-PRESSO with 130 genetic instruments to assess causal associations between LTL and lung cancer among Europeans.We found a strong dose-response relationship between longer LTL and increased lung cancer risk (p-trend= 2.6E-05), with the highest quartile being statistically significant (HRQ4vs.Q1=1.27, 95%CI: 1.15-1.42). The association was apparent for LUAD (p-trend=6.6E-10; HRQ4vs.Q1=1.78, 95%CI: 1.50-2.12), but not SCC. The lung cancer associations were prominent among never-smoking women (p-trend=4.0E-05) and never-smoking men (p-trend=2.0E-03). We also found dose-response relationships between longer gTL and risk of lung cancer (p-trend=4.2E-06) and LUAD (p-trend=2.1E-08). Additionally, we found evidence for causal associations between longer LTL and risk of lung cancer (HRper 1 SD gTL=1.87, 95%CI: 1.49-2.36, p=4.0E-07) and LUAD (HRper 1 SD gTL=2.45, 95%CI: 1.69-3.57, p=6.5E-06). Longer leukocyte telomere length potentially reflects biological processes relevant to the pathogenesis of lung cancer, particularly LUAD. Citation Format: Jason Yat-Yang Wong, Batel Blechter, Aubrey K. Hubbard, Jianxin Shi, Wei Hu, Mohammad Rahman, Shahinaz Gadalla, Mitchell Machiela, Nathaniel Rothman, Qing Lan. Measured and genetically-predicted leukocyte telomere length and lung cancer risk in the prospective UK Biobank [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3009.

Abstract 6056: A nested case-control study of untargeted plasma metabolomics and lung cancer risk among never-smoking women in the prospective Shanghai Women’s Health Study

Abstract Background: The etiology of lung cancer among never-smokers is unclear despite 15% of cases in men and 53% in women worldwide are not smoking-related. Metabolomics provides a snapshot of dynamic biochemical activities, including those found to be driving tumor formation and progression. This study used untargeted metabolomics with network analysis to agnostically identify network modules and independent metabolites in pre-diagnostic blood samples among never-smokers to further understand the pathogenesis of lung cancer. Methods: Within the prospective Shanghai Women’s Health Study, we conducted a nested case-control study of 395 never-smoking incident lung cancer cases and 395 never-smoking controls matched on age. We performed liquid chromatography high-resolution mass spectrometry to quantify 20,348 unique metabolic features in plasma. Because metabolic features are expected to be highly correlated and more likely to be involved in biological processes as a network of intertwined features than individually, we agnostically constructed 28 network modules using a weighted correlation network analysis approach. The associations between metabolite network modules and individual metabolites with lung cancer were assessed using conditional logistic regression models, adjusting for age, body mass index, and exposure to environmental tobacco smoke. We accounted for multiple testing using a false discovery rate (FDR) &amp;lt; 0.20. Results: We identified a network module of 122 metabolic features enriched in lysophosphatidylethanolamines that was associated with all lung cancer combined (p = 0.001, FDR = 0.028) and lung adenocarcinoma (p = 0.002, FDR = 0.056) and another network module of 440 metabolic features that was associated with lung adenocarcinoma (p = 0.014, FDR = 0.196). Metabolic features were enriched in pathways associated with cell growth and proliferation, including oxidative stress, bile acid biosynthesis, and metabolism of nucleic acids, carbohydrates, and amino acids, including 1-carbon compounds. Conclusions: Our prospective study suggests that untargeted plasma metabolomics in pre-diagnostic samples could provide new insights into the etiology of lung cancer in never-smokers. Replication and further characterization of these associations are warranted. Citation Format: Mohammad L. Rahman, Xiao-Ou Shu, Douglas Walker, Dean P. Jones, Wei Hu, Bu-tian Ji, Batel Blechter, Jason YY Wong, Qiuyin Cai, Gong Yang, Tu-Tang Gao, Wei Zheng, Nathaniel Rothman, Qing Lan. A nested case-control study of untargeted plasma metabolomics and lung cancer risk among never-smoking women in the prospective Shanghai Women’s Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6056.

Female reproductive and hormonal factors and lung cancer mortality among never-smokers: A prospective cohort study of 287 408 Chinese women.

There is growing, but inconsistent evidence suggesting oestrogen may play a key role in lung cancer development, especially among never-smoking women for whom lung cancer risk factors remain largely elusive. Using the China Kadoorie Biobank, a large-scale prospective cohort with 302 510 women aged 30 to 79 years recruited from 10 regions in China during 2004 to 2008, we assessed the risk of lung cancer death among self-reported never-smoking women who were cancer-free at baseline, in relation to age at menarche, age at menopause, time since menopause, prior use of oral contraceptives (OCP), number of livebirths, breastfeeding and age at first livebirth. Women were followed up to December 31, 2016 with linkage to mortality data. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression, adjusting for key confounders including several socio-demographic, environmental and lifestyle factors. Among 287 408 never-smoking women, 814 died from lung cancer with a median follow-up of 10.3 years. Women who had used OCP within 15 years prior to baseline had a significantly higher hazard of lung cancer death compared with never-users: HR=1.85 (95% CI: 1.14-3.00) and risk increased by 6% with each additional year of use: HR=1.06 (1.01-1.10). Among parous women, the hazard of lung cancer death increased by 13% with each single livebirth: HR=1.13 (1.05-1.23); and among post-menopausal women, the risk increased by 2% with each year since menopause: HR=1.02 (1.01-1.04). These results suggest that reproductive factors which were proxies for lower endogenous oestrogen level, for example, longer duration of OCP use, could play a role in lung cancer development.

Overall and cause-specific mortality rates among men and women with high exposure to indoor air pollution from the use of smoky and smokeless coal: a cohort study in Xuanwei, China

ObjectivesNever-smoking women in Xuanwei (XW), China, have some of the highest lung cancer rates in the country. This has been attributed to the combustion of smoky coal used for indoor...

Neighborhood disadvantage and lung cancer risk in a national cohort of never smoking Black women

BackgroundCompared to women of other races who have never smoked, Black women have a higher risk of lung cancer. Whether neighborhood disadvantage, which Black women experience at higher rates than other women, is linked to never-smoking lung cancer risk remains unclear. This study investigates the association of neighborhood disadvantage and lung cancer risk in Black never-smoking women. Methods and materialsThis research utilized data from the Black Women’s Health Study, a prospective cohort of 59,000 Black women recruited from across the US in 1995 and followed by biennial questionnaires. Associations of lung cancer incidence with neighborhood-level factors (including two composite variables derived from Census Bureau data: neighborhood socioeconomic status and neighborhood concentrated disadvantage), secondhand smoke exposure, and PM2.5 were estimated using Fine-Gray subdistribution hazard models. ResultsAmong 37,650 never-smokers, 77 were diagnosed with lung cancer during follow-up from 1995 to 2018. The adjusted subdistribution hazard ratio (sHR) of lung cancer incidence with ten unit increase in neighborhood concentrated disadvantage index was 1.30 (95 % CI: 1.04, 1.63, p = 0.023). Exposure to secondhand smoke at work was associated with increased risk (sHR = 1.93, 95 % CI: 1.21, 3.10, p = 0.006), but exposure to secondhand smoke at home and PM2.5 was not. ConclusionWorse neighborhood concentrated disadvantage was associated with increased lung cancer risk in Black women who never smoked. These findings suggest that non-tobacco-related factors in disadvantaged neighborhoods may be linked to lung cancer risk in Black women and that these factors must be understood and targeted to achieve health equity.

Secondhand smoke and the risk of incident cardiovascular disease among never-smoking women

The prospective association between secondhand smoke (SHS) and the risk of incident cardiovascular disease (CVD) remains unclear. This study was the first to examine the association between SHS and risks of ischemic heart disease (IHD), stroke, and total CVD in a large cohort in Asia. The study followed 24,232 never-smoking women aged 40–59 from around Japan (Akita, Iwate, Nagano, Niigata, Ibaraki, Kochi, Nagasaki, and Okinawa prefectures). Their husbands were classified into never, former, and current smokers. After adjustment for age, body mass index, alcohol consumption, histories of hypertension and diabetes mellitus, medication use for hyperlipidemia, menopausal status, and public health center areas, the hazard ratios (HRs) of CVD according to husbands' smoking status were estimated by Cox proportional hazards models. During the 440,360 person-years follow-up, 846 women had total CVDs (103 IHDs, 744 strokes). The proportional hazard assumption was not assured during the total follow-up from 1990 to 2012, but so was then the follow-up of < and ≥ 10 person-years were examined separately. The multivariable HRs (95% confidence intervals) associated with husbands' current versus non-current smoking was 2.02 (1.19–3.45) for IHD, 1.18 (0.98–1.42) for stroke, and 1.25 (1.05–1.49) for total CVD in the follow-up of ≥10 person-years. The SHS from husbands may raise the risk of IHD among middle-aged never-smoking women.

Abstract 2254: Risk models for lung cancer in never-smoking women in Shanghai with implications for screening

Abstract Background: The majority of female lung cancer cases in Asia are never-smokers with distinct risk factor profiles. Given the high burden of disease in this population, there is an increasing need to improve the understanding of lung cancer. Current risk models for lung cancer focus on active smokers and individuals of European ancestry. Therefore, we developed statistical models by integrating genetic and environmental risk factors to estimate absolute and population attribute risk of lung cancer among never-smoking women in Asia. Methods: We built absolute risk models for lung cancer among never-smoking women using data from 71,300 women (760 incident cases) in the Shanghai Women’s Health Study (SWHS), a population-based prospective cohort study. Relative risks were estimated using a multivariable Cox regression model with questionnaire-based risk factors. To account for missing genetic data for some subjects, we simulated genotypes for 10 common single nucleotide polymorphisms (SNP) using information on minor allele frequencies (MAF) and odds ratio estimates from previous genome-wide association studies (GWAS), conditional on family history of lung cancer. We used the iCARE tool to build two models for predicting lifetime (40 years) and 6-year absolute risk of lung cancer using age-specific lung cancer incidence rates, age-specific competing mortality rates, and risk factor distribution with: 1) questionnaire-based risk factors only and 2) questionnaire and genetic data. We then used the full absolute risk model to estimate the population attributable risk (PAR) due to modifiable risk factors, namely coal use and exposure to environmental tobacco smoke (ETS). Results: The questionnaire-based only model included family history of lung cancer, coal use, exposure to ETS, and body mass index (BMI). The full model also included data on 10 lung cancer related SNPs from our previous GWAS and had a wider spread in distribution of absolute lifetime risk (median=2.41%; range=0.43-12.36) compared to the questionnaire-based only model (median=2.72%; range=1.93-4.87). We used the full model to estimate the PAR and found that 1.74% and 6.33% of lung cancer cases could be prevented if never-smoking women in Shanghai did not use coal and were not exposed to ETS, respectively. Furthermore, we found that the full model estimated that 2.5% of the study population had a 6-year absolute risk of lung cancer higher than 1.51%, which is the suggested risk threshold for screening by existing risk models. Conclusion: We built risk models for never-smoking Asian women and estimated the contribution of coal use and ETS to the burden of lung cancer in Shanghai. This initial work shows promise for expanding and validating risk models in this population with potential translational implications, such as providing insight to identifying high risk individuals that may be eligible for lung cancer screening and primary prevention efforts. Citation Format: Batel Blechter, Parichoy Pal Choudhury, Xiao-ou Shu, Wei Zheng, Qiuyin Cai, Gong Yang, Jason Y.Y. Wong, Bu-Tian Ji, Wei Hu, Anne Rositch, Nilanjan Chatterjee, Nathaniel Rothman, Qing Lan. Risk models for lung cancer in never-smoking women in Shanghai with implications for screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2254.

Airway inflammation in adolescents and elderly women: Chronic air pollution exposure and polygenic susceptibility

Background and aimThe fractional exhaled nitric oxide (FeNO) concentration in the exhaled breath is a biomarker for eosinophilic airway inflammation. We explored the interplay between chronic air pollution exposure and polygenic susceptibility to airway inflammation at different critical age stages. MethodsAdolescents (15 yr) enrolled in the GINIplus/LISA birth cohorts (n = 2434) and 220 elderly women (75 yr on average) enrolled in the SALIA cohort with FeNO measurements available were investigated. Environmental main effects of the mean of ESCAPE land-use regression air pollutant concentrations within a time window of 15 years and main effects of the polygenic risk scores (PRS) using internal weights from elastic net regression of genome-wide derived single nucleotide polymorphisms were investigated. Furthermore, we examined gene-environment interaction (GxE) effects on natural log-transformed FeNO levels by adjusted linear regression models. ResultsWhile we observed no significant environmental and polygenic main effects on airway inflammation in either age group, we found robust harmful effects of chronic nitrogen dioxide (NO2) exposure in the GxE models for elderly women (16.2 % increase in FeNO, p-value = 0.027). Stratified analyses found GxE effects between the PRS and chronic NO2 exposure in never-smoker elderly women and in adolescents without any inflammatory respiratory conditions. ConclusionsFeNO measurement is a useful biomarker to detect higher risk of NO2-induced eosinophilic airway inflammation in the elderly. There was limited evidence for GxE effects on airway inflammation in adolescents or the elderly. Further GxE studies in subpopulations should be conducted to investigate the assumption that susceptibility to airway inflammation differs between age stages.

Charting a Path Towards Asian American Cancer Health Equity: A Way Forward.

On July 29, 2021, the US Food and Drug Administration’s Oncology Center of Excellence convened Conversations on Cancer. This Conversation, the first ever by the US Food and Drug Administration, focused on Asian Americans and served as the platform for this Commentary. Panelists elaborated on topics ranging from heterogeneity in Asian American demographics to racism through a path to health equity and supplemented this Commentary with literature citations. Asian Americans are the fastest-growing US race group, yet data aggregation obscures distinctions and cancer disparities within the more than 24 million Asians living in the United States with harmful impacts on communities and patients, as illustrated by breast cancer survivor Susan Shinagawa’s patient-to-advocate journey. Bigotry against Asian Americans has been pervasive since the 19th century, but especially during the COVID-19 pandemic. Asian Americans are unique as the first US population to experience cancer as the leading cause of death. Asian Americans are disproportionately affected by cancers because of infectious origins and have the highest rates of lung cancer among never-smoking women. The infinitesimal proportion of the National Institutes of Health’s budget compared with experiencing the highest percentage increases of any US racial population more than 3 decades highlights the dearth of focused research among Asian Americans. Recognizing the heterogeneity of Asian Americans and that disaggregated data are critical for accurately characterizing distinct ethnic groups, focusing on the impact of racism and COVID-19 on cancer disparities, and focusing and prioritizing funding resources are necessary steps forward for achieving health equity for Asian Americans.

Endogenous sex hormones, aromatase activity and lung cancer risk in postmenopausal never-smoking women.

Although reproductive factors have been repeatedly associated with lung cancer risk, no study to date has directly evaluated the relationship with endogenous sex hormones nor with aromatase activity in postmenopausal never-smoking women. A case-control study of 397 incident lung cancer cases and their individually matched controls, nested within the Shanghai Women's Health Study, was conducted among postmenopausal women who were lifetime never smokers. Prediagnostic concentrations of sex hormones was quantitated using LC-MS/MS assays in plasma. The product-substrate molar ratio of estrone to androstenedione was used as an index of aromatase activity (IAA). Multivariable conditional logistic regression models were used to calculate odds ratios (ORs) for lung cancer. Baseline concentrations of estradiol, free testosterone and IAA were inversely associated with subsequent risk of lung cancer in multivariable-adjusted models. When further adjusted for body mass index, the inverse association with estradiol was attenuated and no longer statistically significant, but the association with free testosterone and IAA remained. In analyses confined to participants having never used menopausal hormone therapy in 376 case-control pairs, the inverse association with free testosterone and IAA was slightly strengthened. OR for the highest vs the lowest quartile of free testosterone was 0.55 (95% CI=0.34-0.90; Ptrend =.03), and the corresponding OR for IAA was 0.57 (95% CI=0.34-0.96; Ptrend =.04). Our study, for the first time, suggests that higher levels of circulating free testosterone and estimated aromatase activity may be associated with lower lung cancer risk in postmenopausal never-smoking women.

JIM Reading List.

JIM Reading List.