Association between duration of smoking abstinence before non-small-cell lung cancer diagnosis and survival: a retrospective, pooled analysis of cohort studies.

BACKGROUND: The association between duration of smoking abstinence before non-small-cell lung cancer (NSCLC) diagnosis and subsequent survival can influence public health messaging delivered in lung-cancer screening. We aimed to assess whether the duration of smoking abstinence before diagnosis of NSCLC is associated with improved survival. METHODS: In this retrospective, pooled analysis of cohort studies, we used 26 cohorts participating in Clinical Outcomes Studies of the International Lung Cancer Consortium (COS-ILCCO) at 23 hospitals. 16 (62%) were from North America, six (23%) were from Europe, three (12%) were from Asia, and one (4%) was from South America. Patients enrolled were diagnosed between June 1, 1983, and Dec 31, 2019. Eligible patients had smoking data before NSCLC diagnosis, epidemiological data at diagnosis (obtained largely from patient questionnaires), and clinical information (retrieved from medical records). Kaplan-Meier curves and multivariable Cox models (ie, adjusted hazard ratios [aHRs]) were generated with individual, harmonised patient data from the consortium database. We estimated overall survival for all causes, measured in years from diagnosis date until the date of the last follow-up or death due to any cause and NSCLC-specific survival. FINDINGS: Of 42 087 patients with NSCLC in the COS-ILCCO database, 21 893 (52·0%) of whom were male and 20 194 (48·0%) of whom were female, we excluded 4474 (10·6%) with missing data. Compared with current smokers (15 036 [40·0%] of 37 613), patients with 1-3 years of smoking abstinence before NSCLC diagnosis (2890 [7·7%]) had an overall survival aHR of 0·92 (95% CI 0·87-0·97), patients with 3-5 years of smoking abstinence (1114 [3·0%]) had an overall survival aHR of 0·90 (0·83-0·97), and patients with more than 5 years of smoking abstinence (10 841 [28·8%]) had an overall survival aHR of 0·90 (0·87-0·93). Improved NSCLC-specific survival was observed in 4301 (44%) of 9727 patients who had quit cigarette smoking and was significant at abstinence durations of more than 5 years (aHR 0·87, 95% CI 0·81-0·93). Results were consistent across age, sex, histology, and disease-stage distributions. INTERPRETATION: In this large, pooled analysis of cohort studies across Asia, Europe, North America, and South America, overall survival was improved in patients with NSCLC whose duration of smoking abstinence before diagnosis was as short as 1 year. These findings suggest that quitting smoking can improve overall survival, even if NSCLC is diagnosed at a later lung-cancer screening visit. These findings also support the implementation of public health smoking cessation strategies at any time. FUNDING: The Alan B Brown Chair, The Posluns Family Fund, The Lusi Wong Fund, and the Princess Margaret Cancer Foundation.

Pregnancy pesticide exposure and child development in low- and middle-income countries: A prospective analysis of a birth cohort in rural Bangladesh and meta-analysis.

BACKGROUND: Despite considerable evidence on a negative association between pregnancy pesticide exposure and child development in high-income countries, evidence from low- and middle-income countries (LMICs) is limited. Therefore, we assessed associations between pregnancy pesticide exposure and child development in rural Bangladesh and summarised existing literature in a systematic review and meta-analysis. METHODS: We used data from 284 mother-child pairs participating in a birth cohort established in 2008. Eight urinary pesticide biomarkers were quantified in early pregnancy (mean gestational age 11.6±2.9 weeks) as an index of pesticide exposure. The Bayley Scales of Infant and Toddler Development, Third Edition were administered at 20-40 months of age. Associations between creatinine-adjusted urinary pesticide biomarker concentrations and child development scores were estimated using multivariable generalised linear models. We searched ten databases up to November 2021 to identify prospective studies on pregnancy pesticide exposure and child development conducted in LMICs. We used a random-effects model to pool similar studies, including our original analysis. The systematic review was pre-registered with PROSPERO: CRD42021292919. RESULTS: In the Bangladesh cohort, pregnancy 2-isopropyl-4-methyl-6-hydroxypyrimidine (IMPY) concentrations were inversely associated with motor development (-0.66 points [95% CI -1.23, -0.09]). Pregnancy 3,5,6-trichloro-2-pyridinol (TCPY) concentrations were inversely associated with cognitive development, but the association was small: -0.02 points (-0.04, 0.01). We observed no associations between 4-nitrophenol and 3-phenoxybenzoic acid (3-PBA) concentrations and child development. The systematic review included 13 studies from four LMICs. After pooling our results with one other study, we found consistent evidence that pregnancy 3-PBA concentrations were not associated with cognitive, language, or motor development. CONCLUSION: Evidence suggests that pregnancy exposure to some organophosphate pesticides is negatively associated with child development. Interventions to reduce in-utero pesticide exposure in LMICs may help protect child development.

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

BACKGROUND: Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. METHODS: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. RESULTS: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. CONCLUSIONS: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. IMPACT: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

Association between initial opioid prescription diagnosis type and subsequent chronic prescription opioid use in Rhode Island: a population-based cohort study.

OBJECTIVE: To identify initial diagnoses associated with elevated risk of chronic prescription opioid use. DESIGN: Population-based, retrospective cohort study. SETTING: State of Rhode Island. PARTICIPANTS: Rhode Island residents with an initial opioid prescription dispensed between 1 April 2019 and 31 March 2020. PRIMARY OUTCOME MEASURE: Subsequent chronic prescription opioid use, defined as receiving 60 or more days' supply of opioids in the 90 days following an initial opioid prescription. RESULTS: Among the 87 055 patients with an initial opioid prescription, 3199 (3.7%) subsequently became chronic users. Patients who become chronic users tended to receive a longer days' supply, greater quantity dispensed, but a lower morphine milligram equivalents on the initial opioid prescription. Patients prescribed an initial opioid prescription for diseases of the musculoskeletal system and connective tissue (adjusted OR (aOR): 5.9, 95% CI: 4.7 to 7.6), diseases of the nervous system (aOR: 6.3, 95% CI: 4.9 to 8.0) and neoplasms (aOR: 5.6, 95% CI: 4.2 to 7.5) had higher odds of subsequent chronic prescription opioid use, compared with a referent group that included all diagnosis types with fewer than 15 chronic opioid users, after adjusting for confounders. CONCLUSIONS: By focusing interventions and prescribing guidelines on specific types of diagnoses that carry a high risk of chronic prescription opioid use and diagnoses that would benefit equally or more from alternative management approaches, states and healthcare organisations may more efficiently decrease inappropriate opioid prescribing while improving the quality of patient care.

Deep learning classification of lung cancer histology using CT images.

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image analysis allude to the utility of radiologic data in further describing disease characteristics and for risk stratification. In this study, we propose a radiomics approach to predicting non-small cell lung cancer (NSCLC) tumor histology from non-invasive standard-of-care computed tomography (CT) data. We trained and validated convolutional neural networks (CNNs) on a dataset comprising 311 early-stage NSCLC patients receiving surgical treatment at Massachusetts General Hospital (MGH), with a focus on the two most common histological types: adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC). The CNNs were able to predict tumor histology with an AUC of 0.71(p = 0.018). We also found that using machine learning classifiers such as k-nearest neighbors (kNN) and support vector machine (SVM) on CNN-derived quantitative radiomics features yielded comparable discriminative performance, with AUC of up to 0.71 (p = 0.017). Our best performing CNN functioned as a robust probabilistic classifier in heterogeneous test sets, with qualitatively interpretable visual explanations to its predictions. Deep learning based radiomics can identify histological phenotypes in lung cancer. It has the potential to augment existing approaches and serve as a corrective aid for diagnosticians.

Metabolomic profiling for second primary lung cancer: A pilot case-control study.

OBJECTIVES: Lung cancer survivors have a high risk of developing a second primary lung cancer (SPLC). While national screening guidelines have been established for initial primary lung cancer (IPLC), no consensus guidelines exist for SPLC. Furthermore, the factors that contribute to SPLC risk have not been established. This study examines the potential for using serum metabolomics to identify metabolite biomarkers that differ between SPLC cases and IPLC controls. MATERIAL AND METHODS: In this pilot case-control study, we applied an untargeted metabolomics approach based on ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) to serum samples of 82 SPLC cases and 82 frequency matched IPLC controls enrolled in the Boston Lung Cancer Study. Random forest and unconditional logistic regression models identified metabolites associated with SPLC. Candidate metabolites were integrated into a SPLC risk prediction model and the model performance was evaluated through a risk stratification approach. RESULTS: The untargeted analysis detected 1008 named and 316 unnamed metabolites among all study participants. Metabolites that were significantly associated with SPLC (False Discovery Rate q-value < 0.2) included 5-methylthioadenosine (odds ratio [OR] = 2.04, 95 % confidence interval [CI] 1.39-3.01; P = 2.8 × 10-4) and phenylacetylglutamine (OR = 2.65, 95 % CI 1.56-4.51; P = 3.2 × 10-4), each exhibiting approximately 1.5-fold increased levels among SPLC cases versus IPLC controls. In stratifying the study participants across quartiles of estimated SPLC risk, the risk prediction model identified a significantly higher proportion of SPLC cases in the fourth compared to the first quartile (68.3 % versus 39.0 %; P = 0.044). CONCLUSION: SPLC cases may have distinct metabolomic profiles compared to those in IPLC patients without SPLC. A risk stratification approach integrating metabolomics may be useful for distinguishing patients based on SPLC risk. Prospective validation studies are needed to further evaluate the potential for leveraging metabolomics in SPLC surveillance and screening.

The relationship between body-mass index and overall survival in non-small cell lung cancer by sex, smoking status, and race: A pooled analysis of 20,937 International lung Cancer consortium (ILCCO) patients.

INTRODUCTION: The relationship between Body-Mass-Index (BMI) and lung cancer prognosis is heterogeneous. We evaluated the impact of sex, smoking and race on the relationship between BMI and overall survival (OS) in non-small-cell-lung-cancer (NSCLC). METHODS: Data from 16 individual ILCCO studies were pooled to assess interactions between BMI and the following factors on OS: self-reported race, smoking status and sex, using Cox models (adjusted hazard ratios; aHR) with interaction terms and adjusted penalized smoothing spline plots in stratified analyses. RESULTS: Among 20,937 NSCLC patients with BMI values, females = 47 %; never-smokers = 14 %; White-patients = 76 %. BMI showed differential survival according to race whereby compared to normal-BMI patients, being underweight was associated with poor survival among white patients (OS, aHR = 1.66) but not among black patients (aHR = 1.06; pinteraction = 0.02). Comparing overweight/obese to normal weight patients, Black NSCLC patients who were overweight/obese also had relatively better OS (pinteraction = 0.06) when compared to White-patients. BMI was least associated with survival in Asian-patients and never-smokers. The outcomes of female ever-smokers at the extremes of BMI were associated with worse outcomes in both the underweight (pinteraction<0.001) and obese categories (pinteraction = 0.004) relative to the normal-BMI category, when compared to male ever-smokers. CONCLUSION: Underweight and obese female ever-smokers were associated with worse outcomes in White-patients. These BMI associations were not observed in Asian-patients and never-smokers. Black-patients had more favorable outcomes in the extremes of BMI when compared to White-patients. Body composition in Black-patients, and NSCLC subtypes more commonly seen in Asian-patients and never-smokers, may account for differences in these BMI-OS relationships.

Protein-altering germline mutations implicate novel genes related to lung cancer development.

Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio = 8.82, P = 1.18 × 10-15) and replication (adjusted OR = 2.93, P = 2.22 × 10-3) that is more pronounced in females (adjusted OR = 6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR = 2.61, P = 7.98 × 10-22) and replication datasets (adjusted OR = 1.55, P = 0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk.

Quantitative methods for metabolomic analyses evaluated in the Children's Health Exposure Analysis Resource (CHEAR).

With advances in technologies that facilitate metabolome-wide analyses, the incorporation of metabolomics in the pursuit of biomarkers of exposure and effect is rapidly evolving in population health studies. However, many analytic approaches are limited in their capacity to address high-dimensional metabolomics data within an epidemiologic framework, including the highly collinear nature of the metabolites and consideration of confounding variables. In this Children's Health Exposure Analysis Resource (CHEAR) network study, we showcase various analytic approaches that are established as well as novel in the field of metabolomics, including univariate single metabolite models, least absolute shrinkage and selection operator (LASSO), random forest, weighted quantile sum (WQSRS) regression, exploratory factor analysis (EFA), and latent class analysis (LCA). Here, in a Bangladeshi birth cohort (n = 199), we illustrate research questions that can be addressed by each analytic method in the assessment of associations between cord blood metabolites (1H NMR measurements) and birth anthropometric measurements (birth weight and head circumference).

Association of prenatal pesticide exposures with adverse pregnancy outcomes and stunting in rural Bangladesh.

BACKGROUND: Pesticide exposure during pregnancy is thought to adversely affect fetal growth, which in turn may impact child growth, but results have been inconsistent across studies and few have explored these effects in developing countries. OBJECTIVES: To quantify urinary concentrations of pesticide biomarkers in early pregnancy (<16 weeks' gestation), and to estimate the association of these concentrations with preterm birth, low birth weight, small for gestational age, and stunting at ~1 and 2 years of age. METHODS: Eight pesticide biomarkers were quantified in urine collected from 289 pregnant women (aged 18-40 years) participating in a birth cohort study in Bangladesh. Anthropometry measurements were conducted on the index child at birth and approximately 1 and 2 years of age. A directed acyclic graph was used to identify minimal sufficient adjustment sets. Log-binomial regression was used to estimate the relative risk (RR) with 95% confidence intervals (CI). RESULTS: 3,5,6-trichloro-2-pyridinol (TCPY), a metabolite of chlorpyrifos and chlorpyrifos methyl, and 4-nitrophenol, a metabolite of parathion and methyl parathion, were detected in nearly all women with geometric mean (95% CI) values of 3.17 (2.82-3.56) and 18.66 (17.03-20.46) µg/g creatinine, respectively. 3-phenoxybenzoic acid (3-PBA), a non-specific metabolite of several pyrethroids, and 2-isopropyl-4-methyl-6-hydroxypyrimidine (IMPY), a diazinon metabolite, were detected in 19.8% and 16.1% of women, respectively. The remaining four pesticide biomarkers were detected in <10% of women. Women in the highest quartile of 4-nitrophenol were more than 3 times more likely to deliver preterm than women in the lowest quartile: unadjusted RR (95% CI), 3.57 (1.65, 7.73). Women in the highest quartile of 4-nitrophenol were also at increased risk of having a child born small for gestational age: RR (95% CI) adjusted for household income, maternal education, and maternal total energy and meat intake, 3.81 (1.10, 13.21). Women with detectable concentrations of IMPY were at increased risk of having a child born with low birth weight compared to women with non-detectable concentrations: adjusted RR (95% CI), 2.13 (1.12, 4.08). We observed no association between any of the pesticide biomarkers and stunting at 1 or 2 years of age. DISCUSSION: Exposure to the insecticides parathion and diazinon during early pregnancy may increase the risk of adverse birth outcomes.

Body Mass Index (BMI), BMI Change, and Overall Survival in Patients With SCLC and NSCLC: A Pooled Analysis of the International Lung Cancer Consortium.

INTRODUCTION: The relationships between morbid obesity, changes in body mass index (BMI) before cancer diagnosis, and lung cancer outcomes by histology (SCLC and NSCLC) have not been well studied. METHODS: Individual level data analysis was performed on 25,430 patients with NSCLC and 2787 patients with SCLC from 16 studies of the International Lung Cancer Consortium evaluating the association between various BMI variables and lung cancer overall survival, reported as adjusted hazard ratios (aHRs) from Cox proportional hazards models and adjusted penalized smoothing spline plots. RESULTS: Overall survival of NSCLC had putative U-shaped hazard ratio relationships with BMI based on spline plots: being underweight (BMI < 18.5 kg/m2; aHR = 1.56; 95% confidence interval [CI]:1.43-1.70) or morbidly overweight (BMI > 40 kg/m2; aHR = 1.09; 95% CI: 0.95-1.26) at the time of diagnosis was associated with worse stage-specific prognosis, whereas being overweight (25 kg/m2 ≤ BMI < 30 kg/m2; aHR = 0.89; 95% CI: 0.85-0.95) or obese (30 kg/m2 ≤ BMI ≤ 40 kg/m2; aHR = 0.86; 95% CI: 0.82-0.91) was associated with improved survival. Although not significant, a similar pattern was seen with SCLC. Compared with an increased or stable BMI from the period between young adulthood until date of diagnosis, a decreased BMI was associated with worse outcomes in NSCLC (aHR = 1.24; 95% CI: 1.2-1.3) and SCLC patients (aHR=1.26 (95% CI: 1.0-1.6). Decreased BMI was consistently associated with worse outcome, across clinicodemographic subsets. CONCLUSIONS: Both being underweight or morbidly obese at time of diagnosis is associated with lower stage-specific survival in independent assessments of NSCLC and SCLC patients. In addition, a decrease in BMI at lung cancer diagnosis relative to early adulthood is a consistent marker of poor survival.

Lung Cancer Risk in Never-Smokers of European Descent is Associated With Genetic Variation in the 5p15.33 TERT-CLPTM1Ll Region.

INTRODUCTION: Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer. METHODS: We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer. RESULTS: We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 × 10-16), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 × 10-16), and rs4975616 (OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 × 10-14). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate. CONCLUSIONS: We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease.

Alcohol consumption and lung cancer risk: A pooled analysis from the International Lung Cancer Consortium and the SYNERGY study.

BACKGROUND: There is inadequate evidence to determine whether there is an effect of alcohol consumption on lung cancer risk. We conducted a pooled analysis of data from the International Lung Cancer Consortium and the SYNERGY study to investigate this possible association by type of beverage with adjustment for other potential confounders. METHODS: Twenty one case-control studies and one cohort study with alcohol-intake data obtained from questionnaires were included in this pooled analysis (19,149 cases and 362,340 controls). Adjusted odds ratios (OR) or hazard ratios (HR) with corresponding 95% confidence intervals (CI) were estimated for each measure of alcohol consumption. Effect estimates were combined using random or fixed-effects models where appropriate. Associations were examined for overall lung cancer and by histological type. RESULTS: We observed an inverse association between overall risk of lung cancer and consumption of alcoholic beverages compared to non-drinkers, but the association was not monotonic. The lowest risk was observed for persons who consumed 10-19.9 g/day ethanol (OR vs. non-drinkers = 0.78; 95% CI: 0.67, 0.91), where 1 drink is approximately 12-15 g. This J-shaped association was most prominent for squamous cell carcinoma (SCC). The association with all lung cancer varied little by type of alcoholic beverage, but there were notable differences for SCC. We observed an association with beer intake (OR for ≥20 g/day vs nondrinker = 1.42; 95% CI: 1.06, 1.90). CONCLUSIONS: Whether the non-monotonic associations we observed or the positive association between beer drinking and squamous cell carcinoma reflect real effects await future analyses and insights about possible biological mechanisms.

Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk.

Genome-wide association studies (GWAS) identified the chromosome 15q25.1 locus as a leading susceptibility region for lung cancer. However, the pathogenic pathways, through which susceptibility SNPs within chromosome 15q25.1 affects lung cancer risk, have not been explored. We analyzed three cohorts with GWAS data consisting 42,901 individuals and lung expression quantitative trait loci (eQTL) data on 409 individuals to identify and validate the underlying pathways and to investigate the combined effect of genes from the identified susceptibility pathways. The KEGG neuroactive ligand receptor interaction pathway, two Reactome pathways, and 22 Gene Ontology terms were identified and replicated to be significantly associated with lung cancer risk, with P values less than 0.05 and FDR less than 0.1. Functional annotation of eQTL analysis results showed that the neuroactive ligand receptor interaction pathway and gated channel activity were involved in lung cancer risk. These pathways provide important insights for the etiology of lung cancer.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Menstrual and reproductive factors and lung cancer risk: A pooled analysis from the international lung cancer consortium.

Many clinical features of lung cancer are different in women and men. Sex steroid hormones exert effects in nonreproductive organs, such as the lungs. The association between menstrual and childbearing factors and the risk of lung cancer among women is still debated. We performed a pooled analysis of eight studies contributing to the International Lung Cancer Consortium (4,386 cases and 4,177 controls). Pooled associations between menstrual or reproductive factors and lung cancer were estimated using multivariable unconditional logistic regression. Subgroup analyses were done for menopause status, smoking habits and histology. We found no strong support for an association of age at menarche and at menopause with lung cancer, but peri/postmenopausal women were at higher risk compared to premenopausal (OR 1.47, 95% CI 1.11-1.93). Premenopausal women showed increased risks associated with parity (OR 1.74, 95% CI 1.03-2.93) and number of children (OR 2.88, 95% CI 1.21-6.93 for more than 3 children; p for trend 0.01) and decreased with breastfeeding (OR 0.54, 95% CI 0.30-0.98). In contrast, peri/postmenopausal subjects had ORs around unity for the same exposures. No major effect modification was exerted by smoking status or cancer histology. Menstrual and reproductive factors may play a role in the genesis of lung cancer, yet the mechanisms are unclear, and smoking remains the most important modifiable risk factor. More investigations in large well-designed studies are needed to confirm these findings and to clarify the underlying mechanisms of gender differences in lung cancer risk.

Exposure Enriched Case-Control (EECC) Design for the Assessment of Gene-Environment Interaction.

Genetic susceptibility and environmental exposure both play an important role in the aetiology of many diseases. Case-control studies are often the first choice to explore the joint influence of genetic and environmental factors on the risk of developing a rare disease. In practice, however, such studies may have limited power, especially when susceptibility genes are rare and exposure distributions are highly skewed. We propose a variant of the classical case-control study, the exposure enriched case-control (EECC) design, where not only cases, but also high (or low) exposed individuals are oversampled, depending on the skewness of the exposure distribution. Of course, a traditional logistic regression model is no longer valid and results in biased parameter estimation. We show that addition of a simple covariate to the regression model removes this bias and yields reliable estimates of main and interaction effects of interest. We also discuss optimal design, showing that judicious oversampling of high/low exposed individuals can boost study power considerably. We illustrate our results using data from a study involving arsenic exposure and detoxification genes in Bangladesh.

Gene copy number alterations in the azoospermia-associated AZFc region and their effect on spermatogenic impairment.

The azoospermia factor c (AZFc) region in the long arm of human Y chromosome is characterized by massive palindromes. It harbors eight multi-copy gene families that are expressed exclusively or predominantly in testis. To assess systematically the role of the AZFc region and these eight gene families in spermatogenesis, we conducted a comprehensive molecular analysis (including Y chromosome haplogrouping, AZFc deletion typing and gene copy quantification) in 654 idiopathic infertile men and 781 healthy controls in a Han Chinese population. The b2/b3 partial deletion (including both deletion-only and deletion-duplication) was consistently associated with spermatogenic impairment. In the subjects without partial AZFc deletions, a notable finding was that the frequency of DAZ and/or BPY2 copy number alterations in the infertile group was significantly higher than in the controls. Combined patterns of DAZ and/or BPY2 copy number abnormality were associated with spermatogenic impairment when compared with the pattern of all AZFc genes with common level copies. In addition, in Y chromosome haplogroup O1 (Y-hg O1), the frequency of copy number alterations of all eight gene families was significantly higher in the case group than that in the control group. Our findings indicate that the DAZ, BPY2 genes may be prominent players in spermatogenesis, and genomic rearrangements may be enriched in individuals belonging to Y-hg O1. Our findings emphasize the necessity of routine molecular analysis of AZFc structural variation during the workup of azoospermia and/or oligozoospermia, which may diminish the genetic risk of assisted reproduction.

A prospective cohort study of the association between drinking water arsenic exposure and self-reported maternal health symptoms during pregnancy in Bangladesh.

BACKGROUND: Arsenic, a common groundwater pollutant, is associated with adverse reproductive health but few studies have examined its effect on maternal health. METHODS: A prospective cohort was recruited in Bangladesh from 2008-2011 (N = 1,458). At enrollment (<16 weeks gestational age [WGA]), arsenic was measured in personal drinking water using inductively-coupled plasma mass spectrometry. Questionnaires collected health data at enrollment, at 28 WGA, and within one month of delivery. Adjusted odds ratios (aORs) and 95% confidence intervals (95% CI) for self-reported health symptoms were estimated for each arsenic quartile using logistic regression. RESULTS: Overall, the mean concentration of arsenic was 38 µg/L (Standard deviation, 92.7 µg/L). A total of 795 women reported one or more of the following symptoms during pregnancy (cold/flu/infection, nausea/vomiting, abdominal cramping, headache, vaginal bleeding, or swollen ankles). Compared to participants exposed to the lowest quartile of arsenic (≤0.9 µg/L), the aOR for reporting any symptom during pregnancy was 0.62 (95% CI = 0.44-0.88) in the second quartile, 1.83 (95% CI = 1.25-2.69) in the third quartile, and 2.11 (95% CI = 1.42-3.13) in the fourth quartile where the mean arsenic concentration in each quartile was 1.5 µg/L, 12.0 µg/L and 144.7 µg/L, respectively. Upon examining individual symptoms, only nausea/vomiting and abdominal cramping showed consistent associations with arsenic exposure. The odds of self-reported nausea/vomiting was 0.98 (95% CI: 0.68, 1.41), 1.52 (95% CI: 1.05, 2.18), and 1.81 (95% CI: 1.26, 2.60) in the second, third and fourth quartile of arsenic relative to the lowest quartile after adjusting for age, body mass index, second-hand tobacco smoke exposure, educational status, parity, anemia, ferritin, medication usage, type of sanitation at home, and household income. A positive trend was also observed for abdominal cramping (P for trend <0.0001). A marginal negative association was observed between arsenic quartiles and odds of self-reported cold/flu/infection (P for trend = 0.08). No association was observed between arsenic and self-reported headache (P for trend = 0.19). CONCLUSION: Moderate exposure to arsenic contaminated drinking water early in pregnancy was associated with increased odds of experiencing nausea/vomiting and abdominal cramping. Preventing exposure to arsenic contaminated drinking water during pregnancy could improve maternal health.

Invasive adenocarcinoma of the lung is associated with the upper lung regions.

OBJECTIVES: We postulated that ventilation-perfusion (V/Q) relationships within the lung might influence where lung cancer occurs. To address this hypothesis we evaluated the location of lung adenocarcinoma, by both tumor lobe and superior-inferior regional distribution, and associated variables such as emphysema. MATERIALS AND METHODS: One hundred fifty-nine cases of invasive adenocarcinoma and adenocarcinoma with lepidic features were visually evaluated to identify lobar or regional tumor location. Regions were determined by automated division of the lungs into three equal volumes: (upper region, middle region, or lower region). Automated densitometry was used to measure radiographic emphysema. RESULTS: The majority of invasive adenocarcinomas occurred in the upper lobes (69%), with 94% of upper lobe adenocarcinomas occurring in the upper region of the lung. The distribution of adenocarcinoma, when classified as upper or lower lobe, was not different between invasive adenocarcinoma and adenocarcinoma with lepidic features (formerly bronchioloalveolar cell carcinoma, P = 0.08). Regional distribution of tumor was significantly different between invasive adenocarcinoma and adenocarcinoma with lepidic features (P = 0.001). Logistic regression analysis with the outcome of invasive adenocarcinoma histology was used to adjust for confounders. Tumor region continued to be a significant predictor (OR 8.5, P = 0.008, compared to lower region), whereas lobar location of tumor was not (P = 0.09). In stratified analysis, smoking was not associated with region of invasive adenocarcinoma occurrence (P = 0.089). There was no difference in total emphysema scores between invasive adenocarcinoma cases occurring in each of the three regions (P = 0.155). There was also no difference in the distribution of region of adenocarcinoma occurrence between quartiles of emphysema (P = 0.217). CONCLUSION: Invasive adenocarcinoma of the lung is highly associated with the upper lung regions. This association is not related to smoking, history of COPD, or total emphysema. The regional distribution of invasive adenocarcinoma may be due to V/Q relationships or other local factors.